From 3dfe998ae9d2c70cbbd3a2c93d9d17a2145d980d Mon Sep 17 00:00:00 2001 From: Sergey Cherkashin <4erkashin@list.ru> Date: Fri, 9 Nov 2018 18:51:36 +0300 Subject: [PATCH 1/5] Move python test on testgres and add stress test --- .travis.yml | 1 + Makefile | 2 +- README.md | 11 +- run_tests.sh | 7 +- tests/pg_qs_test_runner.py | 69 +- tests/prepare_stress.sh | 19 + tests/query_tpcds.sql | 4866 ++++++++++++++++++++++++++++++++++++ tests/test_cases.py | 508 ++-- 8 files changed, 5182 insertions(+), 301 deletions(-) create mode 100755 tests/prepare_stress.sh create mode 100644 tests/query_tpcds.sql diff --git a/.travis.yml b/.travis.yml index dc651bd..3708b14 100644 --- a/.travis.yml +++ b/.travis.yml @@ -24,6 +24,7 @@ env: - PG_VERSION=10 - PG_VERSION=9.6 LEVEL=hardcore - PG_VERSION=9.6 + - PG_VERSION=10 LEVEL=stress matrix: allow_failures: diff --git a/Makefile b/Makefile index 08d24ac..6458a14 100644 --- a/Makefile +++ b/Makefile @@ -9,7 +9,7 @@ DATA_built = $(EXTENSION)--$(EXTVERSION).sql PGFILEDESC = "pg_query_state - facility to track progress of plan execution" EXTRA_CLEAN = ./isolation_output $(EXTENSION)--$(EXTVERSION).sql \ - Dockerfile ./tests/*.pyc + Dockerfile ./tests/*.pyc ./tmp_stress ifdef USE_PGXS PG_CONFIG = pg_config diff --git a/README.md b/README.md index 34ecdb0..ea16884 100644 --- a/README.md +++ b/README.md @@ -34,18 +34,15 @@ Done! ## Tests Tests using parallel sessions using python 2.7 script: ``` + export PG_CONFIG=/path/to/pg_config python tests/pg_qs_test_runner.py [OPTION]... ``` *prerequisite packages*: -* `psycopg2` version 2.6 or later +* `testgres` version 1.8.2 or later * `PyYAML` version 3.11 or later - + *options*: -* *- -host* --- postgres server host, default value is *localhost* -* *- -port* --- postgres server port, default value is *5432* -* *- -database* --- database name, default value is *postgres* -* *- -user* --- user name, default value is *postgres* -* *- -password* --- user's password, default value is empty +* *--stress* --- run stress test using tpc-ds benchmark ## Function pg\_query\_state ```plpgsql diff --git a/run_tests.sh b/run_tests.sh index bb7b75c..0053aee 100755 --- a/run_tests.sh +++ b/run_tests.sh @@ -8,6 +8,7 @@ # * scan-build # * hardcore # * nightmare +# * stress # set -ux @@ -146,7 +147,11 @@ set +x -e virtualenv /tmp/env && source /tmp/env/bin/activate && pip install PyYAML && pip install psycopg2 set -e #exit virtualenv with error code -python tests/pg_qs_test_runner.py --port $PGPORT +if [ "$LEVEL" = "stress" ]; then + python tests/pg_qs_test_runner.py --stress +else + python tests/pg_qs_test_runner.py +fi deactivate set -x diff --git a/tests/pg_qs_test_runner.py b/tests/pg_qs_test_runner.py index 716719e..dc68dc4 100644 --- a/tests/pg_qs_test_runner.py +++ b/tests/pg_qs_test_runner.py @@ -5,17 +5,11 @@ ''' import argparse -import psycopg2 import sys from test_cases import * - -class PasswordPromptAction(argparse.Action): - def __call__(self, parser, args, values, option_string=None): - password = getpass.getpass() - setattr(args, self.dest, password) +import testgres class SetupException(Exception): pass -class TeardownException(Exception): pass setup_cmd = [ 'drop extension if exists pg_query_state cascade', @@ -25,17 +19,11 @@ class TeardownException(Exception): pass 'create table foo(c1 integer, c2 text)', 'create table bar(c1 integer, c2 boolean)', 'insert into foo select i, md5(random()::text) from generate_series(1, 1000000) as i', - 'insert into bar select i, i%2=1 from generate_series(1, 500000) as i', + 'insert into bar select i, i%%2=1 from generate_series(1, 500000) as i', 'analyze foo', 'analyze bar', ] -teardown_cmd = [ - 'drop table foo cascade', - 'drop table bar cascade', - 'drop extension pg_query_state cascade', - ] - tests = [ test_deadlock, test_simple_query, @@ -50,36 +38,26 @@ class TeardownException(Exception): pass test_insert_on_conflict, ] -def setup(con): +def setup(node): ''' Creates pg_query_state extension, creates tables for tests, fills it with data ''' print 'setting up...' + conn = testgres.connection.NodeConnection(node) try: - cur = con.cursor() for cmd in setup_cmd: - cur.execute(cmd) - con.commit() - cur.close() + conn.execute(cmd) + conn.commit() + conn.close() except Exception, e: raise SetupException('Setup failed: %s' % e) print 'done!' -def teardown(con): - ''' Drops table and extension ''' - print 'tearing down...' - try: - cur = con.cursor() - for cmd in teardown_cmd: - cur.execute(cmd) - con.commit() - cur.close() - except Exception, e: - raise TeardownException('Teardown failed: %s' % e) - print 'done!' - -def main(config): +def main(args): ''' Main test function ''' - con = psycopg2.connect(**config) - setup(con) + node = testgres.get_new_node() + node.init() + node.append_conf("shared_preload_libraries='pg_query_state'\n") + node.start() + setup(node) for i, test in enumerate(tests): if test.__doc__: @@ -87,18 +65,21 @@ def main(config): else: descr = 'test case %d' % (i+1) print ("%s..." % descr),; sys.stdout.flush() - test(config) + test(node) print 'ok!' - teardown(con) - con.close() + if args.stress: + print 'Start stress test' + stress_test(node) + print 'Start stress finished successfully' + print 'stop' + + node.stop() + node.cleanup() if __name__ == '__main__': parser = argparse.ArgumentParser(description='Query state of running backends tests') - parser.add_argument('--host', default='localhost', help='postgres server host') - parser.add_argument('--port', type=int, default=5432, help='postgres server port') - parser.add_argument('--user', dest='user', default='postgres', help='user name') - parser.add_argument('--database', dest='database', default='postgres', help='database name') - parser.add_argument('--password', dest='password', nargs=0, action=PasswordPromptAction, default='') + parser.add_argument('--stress', help='run stress test using tpc-ds benchmark', + action="store_true") args = parser.parse_args() - main(args.__dict__) + main(args) diff --git a/tests/prepare_stress.sh b/tests/prepare_stress.sh new file mode 100755 index 0000000..12dbf60 --- /dev/null +++ b/tests/prepare_stress.sh @@ -0,0 +1,19 @@ +#!/bin/sh +mkdir -p tmp_stress +cd tmp_stress +rm -rf ./* +git clone https://github.com/gregrahn/tpcds-kit.git +cd tpcds-kit/tools +make -s + +#Generate data +./dsdgen -FORCE -VERBOSE +mkdir tables -p +#Prepare data +for i in `ls *.dat`; do + echo "Prepare file " $i + sed 's/|$//' $i > tables/$i +done +#Generate queries +./dsqgen -DIRECTORY ../query_templates -INPUT ../query_templates/templates.lst \ + -VERBOSE Y -QUALIFY Y -DIALECT netezza diff --git a/tests/query_tpcds.sql b/tests/query_tpcds.sql new file mode 100644 index 0000000..d619abe --- /dev/null +++ b/tests/query_tpcds.sql @@ -0,0 +1,4866 @@ +-- start query 1 in stream 0 using template query1.tpl +with customer_total_return as +(select sr_customer_sk as ctr_customer_sk +,sr_store_sk as ctr_store_sk +,sum(SR_FEE) as ctr_total_return +from store_returns +,date_dim +where sr_returned_date_sk = d_date_sk +and d_year =2000 +group by sr_customer_sk +,sr_store_sk) + select c_customer_id +from customer_total_return ctr1 +,store +,customer +where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2 +from customer_total_return ctr2 +where ctr1.ctr_store_sk = ctr2.ctr_store_sk) +and s_store_sk = ctr1.ctr_store_sk +and s_state = 'TN' +and ctr1.ctr_customer_sk = c_customer_sk +order by c_customer_id +limit 100; + +-- end query 1 in stream 0 using template query1.tpl +-- start query 2 in stream 0 using template query2.tpl +with wscs as + (select sold_date_sk + ,sales_price + from (select ws_sold_date_sk sold_date_sk + ,ws_ext_sales_price sales_price + from web_sales + union all + select cs_sold_date_sk sold_date_sk + ,cs_ext_sales_price sales_price + from catalog_sales) as sdsp), + wswscs as + (select d_week_seq, + sum(case when (d_day_name='Sunday') then sales_price else null end) sun_sales, + sum(case when (d_day_name='Monday') then sales_price else null end) mon_sales, + sum(case when (d_day_name='Tuesday') then sales_price else null end) tue_sales, + sum(case when (d_day_name='Wednesday') then sales_price else null end) wed_sales, + sum(case when (d_day_name='Thursday') then sales_price else null end) thu_sales, + sum(case when (d_day_name='Friday') then sales_price else null end) fri_sales, + sum(case when (d_day_name='Saturday') then sales_price else null end) sat_sales + from wscs + ,date_dim + where d_date_sk = sold_date_sk + group by d_week_seq) + select d_week_seq1 + ,round(sun_sales1/sun_sales2,2) + ,round(mon_sales1/mon_sales2,2) + ,round(tue_sales1/tue_sales2,2) + ,round(wed_sales1/wed_sales2,2) + ,round(thu_sales1/thu_sales2,2) + ,round(fri_sales1/fri_sales2,2) + ,round(sat_sales1/sat_sales2,2) + from + (select wswscs.d_week_seq d_week_seq1 + ,sun_sales sun_sales1 + ,mon_sales mon_sales1 + ,tue_sales tue_sales1 + ,wed_sales wed_sales1 + ,thu_sales thu_sales1 + ,fri_sales fri_sales1 + ,sat_sales sat_sales1 + from wswscs,date_dim + where date_dim.d_week_seq = wswscs.d_week_seq and + d_year = 1998) y, + (select wswscs.d_week_seq d_week_seq2 + ,sun_sales sun_sales2 + ,mon_sales mon_sales2 + ,tue_sales tue_sales2 + ,wed_sales wed_sales2 + ,thu_sales thu_sales2 + ,fri_sales fri_sales2 + ,sat_sales sat_sales2 + from wswscs + ,date_dim + where date_dim.d_week_seq = wswscs.d_week_seq and + d_year = 1998+1) z + where d_week_seq1=d_week_seq2-53 + order by d_week_seq1; + +-- end query 2 in stream 0 using template query2.tpl +-- start query 3 in stream 0 using template query3.tpl +select dt.d_year + ,item.i_brand_id brand_id + ,item.i_brand brand + ,sum(ss_sales_price) sum_agg + from date_dim dt + ,store_sales + ,item + where dt.d_date_sk = store_sales.ss_sold_date_sk + and store_sales.ss_item_sk = item.i_item_sk + and item.i_manufact_id = 816 + and dt.d_moy=11 + group by dt.d_year + ,item.i_brand + ,item.i_brand_id + order by dt.d_year + ,sum_agg desc + ,brand_id + limit 100; + +-- end query 3 in stream 0 using template query3.tpl +-- start query 4 in stream 0 using template query4.tpl +with year_total as ( + select c_customer_id customer_id + ,c_first_name customer_first_name + ,c_last_name customer_last_name + ,c_preferred_cust_flag customer_preferred_cust_flag + ,c_birth_country customer_birth_country + ,c_login customer_login + ,c_email_address customer_email_address + ,d_year dyear + ,sum(((ss_ext_list_price-ss_ext_wholesale_cost-ss_ext_discount_amt)+ss_ext_sales_price)/2) year_total + ,'s' sale_type + from customer + ,store_sales + ,date_dim + where c_customer_sk = ss_customer_sk + and ss_sold_date_sk = d_date_sk + group by c_customer_id + ,c_first_name + ,c_last_name + ,c_preferred_cust_flag + ,c_birth_country + ,c_login + ,c_email_address + ,d_year + union all + select c_customer_id customer_id + ,c_first_name customer_first_name + ,c_last_name customer_last_name + ,c_preferred_cust_flag customer_preferred_cust_flag + ,c_birth_country customer_birth_country + ,c_login customer_login + ,c_email_address customer_email_address + ,d_year dyear + ,sum((((cs_ext_list_price-cs_ext_wholesale_cost-cs_ext_discount_amt)+cs_ext_sales_price)/2) ) year_total + ,'c' sale_type + from customer + ,catalog_sales + ,date_dim + where c_customer_sk = cs_bill_customer_sk + and cs_sold_date_sk = d_date_sk + group by c_customer_id + ,c_first_name + ,c_last_name + ,c_preferred_cust_flag + ,c_birth_country + ,c_login + ,c_email_address + ,d_year +union all + select c_customer_id customer_id + ,c_first_name customer_first_name + ,c_last_name customer_last_name + ,c_preferred_cust_flag customer_preferred_cust_flag + ,c_birth_country customer_birth_country + ,c_login customer_login + ,c_email_address customer_email_address + ,d_year dyear + ,sum((((ws_ext_list_price-ws_ext_wholesale_cost-ws_ext_discount_amt)+ws_ext_sales_price)/2) ) year_total + ,'w' sale_type + from customer + ,web_sales + ,date_dim + where c_customer_sk = ws_bill_customer_sk + and ws_sold_date_sk = d_date_sk + group by c_customer_id + ,c_first_name + ,c_last_name + ,c_preferred_cust_flag + ,c_birth_country + ,c_login + ,c_email_address + ,d_year + ) + select + t_s_secyear.customer_id + ,t_s_secyear.customer_first_name + ,t_s_secyear.customer_last_name + ,t_s_secyear.customer_birth_country + from year_total t_s_firstyear + ,year_total t_s_secyear + ,year_total t_c_firstyear + ,year_total t_c_secyear + ,year_total t_w_firstyear + ,year_total t_w_secyear + where t_s_secyear.customer_id = t_s_firstyear.customer_id + and t_s_firstyear.customer_id = t_c_secyear.customer_id + and t_s_firstyear.customer_id = t_c_firstyear.customer_id + and t_s_firstyear.customer_id = t_w_firstyear.customer_id + and t_s_firstyear.customer_id = t_w_secyear.customer_id + and t_s_firstyear.sale_type = 's' + and t_c_firstyear.sale_type = 'c' + and t_w_firstyear.sale_type = 'w' + and t_s_secyear.sale_type = 's' + and t_c_secyear.sale_type = 'c' + and t_w_secyear.sale_type = 'w' + and t_s_firstyear.dyear = 1999 + and t_s_secyear.dyear = 1999+1 + and t_c_firstyear.dyear = 1999 + and t_c_secyear.dyear = 1999+1 + and t_w_firstyear.dyear = 1999 + and t_w_secyear.dyear = 1999+1 + and t_s_firstyear.year_total > 0 + and t_c_firstyear.year_total > 0 + and t_w_firstyear.year_total > 0 + and case when t_c_firstyear.year_total > 0 then t_c_secyear.year_total / t_c_firstyear.year_total else null end + > case when t_s_firstyear.year_total > 0 then t_s_secyear.year_total / t_s_firstyear.year_total else null end + and case when t_c_firstyear.year_total > 0 then t_c_secyear.year_total / t_c_firstyear.year_total else null end + > case when t_w_firstyear.year_total > 0 then t_w_secyear.year_total / t_w_firstyear.year_total else null end + order by t_s_secyear.customer_id + ,t_s_secyear.customer_first_name + ,t_s_secyear.customer_last_name + ,t_s_secyear.customer_birth_country +limit 100; + +-- end query 4 in stream 0 using template query4.tpl +-- start query 5 in stream 0 using template query5.tpl +with ssr as + (select s_store_id, + sum(sales_price) as sales, + sum(profit) as profit, + sum(return_amt) as returns, + sum(net_loss) as profit_loss + from + ( select ss_store_sk as store_sk, + ss_sold_date_sk as date_sk, + ss_ext_sales_price as sales_price, + ss_net_profit as profit, + cast(0 as decimal(7,2)) as return_amt, + cast(0 as decimal(7,2)) as net_loss + from store_sales + union all + select sr_store_sk as store_sk, + sr_returned_date_sk as date_sk, + cast(0 as decimal(7,2)) as sales_price, + cast(0 as decimal(7,2)) as profit, + sr_return_amt as return_amt, + sr_net_loss as net_loss + from store_returns + ) salesreturns, + date_dim, + store + where date_sk = d_date_sk + and d_date between cast('2000-08-19' as date) + and (cast('2000-08-19' as date) + 14 days) + and store_sk = s_store_sk + group by s_store_id) + , + csr as + (select cp_catalog_page_id, + sum(sales_price) as sales, + sum(profit) as profit, + sum(return_amt) as returns, + sum(net_loss) as profit_loss + from + ( select cs_catalog_page_sk as page_sk, + cs_sold_date_sk as date_sk, + cs_ext_sales_price as sales_price, + cs_net_profit as profit, + cast(0 as decimal(7,2)) as return_amt, + cast(0 as decimal(7,2)) as net_loss + from catalog_sales + union all + select cr_catalog_page_sk as page_sk, + cr_returned_date_sk as date_sk, + cast(0 as decimal(7,2)) as sales_price, + cast(0 as decimal(7,2)) as profit, + cr_return_amount as return_amt, + cr_net_loss as net_loss + from catalog_returns + ) salesreturns, + date_dim, + catalog_page + where date_sk = d_date_sk + and d_date between cast('2000-08-19' as date) + and (cast('2000-08-19' as date) + 14 days) + and page_sk = cp_catalog_page_sk + group by cp_catalog_page_id) + , + wsr as + (select web_site_id, + sum(sales_price) as sales, + sum(profit) as profit, + sum(return_amt) as returns, + sum(net_loss) as profit_loss + from + ( select ws_web_site_sk as wsr_web_site_sk, + ws_sold_date_sk as date_sk, + ws_ext_sales_price as sales_price, + ws_net_profit as profit, + cast(0 as decimal(7,2)) as return_amt, + cast(0 as decimal(7,2)) as net_loss + from web_sales + union all + select ws_web_site_sk as wsr_web_site_sk, + wr_returned_date_sk as date_sk, + cast(0 as decimal(7,2)) as sales_price, + cast(0 as decimal(7,2)) as profit, + wr_return_amt as return_amt, + wr_net_loss as net_loss + from web_returns left outer join web_sales on + ( wr_item_sk = ws_item_sk + and wr_order_number = ws_order_number) + ) salesreturns, + date_dim, + web_site + where date_sk = d_date_sk + and d_date between cast('2000-08-19' as date) + and (cast('2000-08-19' as date) + 14 days) + and wsr_web_site_sk = web_site_sk + group by web_site_id) + select channel + , id + , sum(sales) as sales + , sum(returns) as returns + , sum(profit) as profit + from + (select 'store channel' as channel + , 'store' || s_store_id as id + , sales + , returns + , (profit - profit_loss) as profit + from ssr + union all + select 'catalog channel' as channel + , 'catalog_page' || cp_catalog_page_id as id + , sales + , returns + , (profit - profit_loss) as profit + from csr + union all + select 'web channel' as channel + , 'web_site' || web_site_id as id + , sales + , returns + , (profit - profit_loss) as profit + from wsr + ) x + group by rollup (channel, id) + order by channel + ,id + limit 100; + +-- end query 5 in stream 0 using template query5.tpl +-- start query 6 in stream 0 using template query6.tpl +select a.ca_state state, count(*) cnt + from customer_address a + ,customer c + ,store_sales s + ,date_dim d + ,item i + where a.ca_address_sk = c.c_current_addr_sk + and c.c_customer_sk = s.ss_customer_sk + and s.ss_sold_date_sk = d.d_date_sk + and s.ss_item_sk = i.i_item_sk + and d.d_month_seq = + (select distinct (d_month_seq) + from date_dim + where d_year = 2002 + and d_moy = 3 ) + and i.i_current_price > 1.2 * + (select avg(j.i_current_price) + from item j + where j.i_category = i.i_category) + group by a.ca_state + having count(*) >= 10 + order by cnt, a.ca_state + limit 100; + +-- end query 6 in stream 0 using template query6.tpl +-- start query 7 in stream 0 using template query7.tpl +select i_item_id, + avg(ss_quantity) agg1, + avg(ss_list_price) agg2, + avg(ss_coupon_amt) agg3, + avg(ss_sales_price) agg4 + from store_sales, customer_demographics, date_dim, item, promotion + where ss_sold_date_sk = d_date_sk and + ss_item_sk = i_item_sk and + ss_cdemo_sk = cd_demo_sk and + ss_promo_sk = p_promo_sk and + cd_gender = 'F' and + cd_marital_status = 'W' and + cd_education_status = 'College' and + (p_channel_email = 'N' or p_channel_event = 'N') and + d_year = 2001 + group by i_item_id + order by i_item_id + limit 100; + +-- end query 7 in stream 0 using template query7.tpl +-- start query 8 in stream 0 using template query8.tpl +select s_store_name + ,sum(ss_net_profit) + from store_sales + ,date_dim + ,store, + (select ca_zip + from ( + SELECT substr(ca_zip,1,5) ca_zip + FROM customer_address + WHERE substr(ca_zip,1,5) IN ( + '47602','16704','35863','28577','83910','36201', + '58412','48162','28055','41419','80332', + '38607','77817','24891','16226','18410', + '21231','59345','13918','51089','20317', + '17167','54585','67881','78366','47770', + '18360','51717','73108','14440','21800', + '89338','45859','65501','34948','25973', + '73219','25333','17291','10374','18829', + '60736','82620','41351','52094','19326', + '25214','54207','40936','21814','79077', + '25178','75742','77454','30621','89193', + '27369','41232','48567','83041','71948', + '37119','68341','14073','16891','62878', + '49130','19833','24286','27700','40979', + '50412','81504','94835','84844','71954', + '39503','57649','18434','24987','12350', + '86379','27413','44529','98569','16515', + '27287','24255','21094','16005','56436', + '91110','68293','56455','54558','10298', + '83647','32754','27052','51766','19444', + '13869','45645','94791','57631','20712', + '37788','41807','46507','21727','71836', + '81070','50632','88086','63991','20244', + '31655','51782','29818','63792','68605', + '94898','36430','57025','20601','82080', + '33869','22728','35834','29086','92645', + '98584','98072','11652','78093','57553', + '43830','71144','53565','18700','90209', + '71256','38353','54364','28571','96560', + '57839','56355','50679','45266','84680', + '34306','34972','48530','30106','15371', + '92380','84247','92292','68852','13338', + '34594','82602','70073','98069','85066', + '47289','11686','98862','26217','47529', + '63294','51793','35926','24227','14196', + '24594','32489','99060','49472','43432', + '49211','14312','88137','47369','56877', + '20534','81755','15794','12318','21060', + '73134','41255','63073','81003','73873', + '66057','51184','51195','45676','92696', + '70450','90669','98338','25264','38919', + '59226','58581','60298','17895','19489', + '52301','80846','95464','68770','51634', + '19988','18367','18421','11618','67975', + '25494','41352','95430','15734','62585', + '97173','33773','10425','75675','53535', + '17879','41967','12197','67998','79658', + '59130','72592','14851','43933','68101', + '50636','25717','71286','24660','58058', + '72991','95042','15543','33122','69280', + '11912','59386','27642','65177','17672', + '33467','64592','36335','54010','18767', + '63193','42361','49254','33113','33159', + '36479','59080','11855','81963','31016', + '49140','29392','41836','32958','53163', + '13844','73146','23952','65148','93498', + '14530','46131','58454','13376','13378', + '83986','12320','17193','59852','46081', + '98533','52389','13086','68843','31013', + '13261','60560','13443','45533','83583', + '11489','58218','19753','22911','25115', + '86709','27156','32669','13123','51933', + '39214','41331','66943','14155','69998', + '49101','70070','35076','14242','73021', + '59494','15782','29752','37914','74686', + '83086','34473','15751','81084','49230', + '91894','60624','17819','28810','63180', + '56224','39459','55233','75752','43639', + '55349','86057','62361','50788','31830', + '58062','18218','85761','60083','45484', + '21204','90229','70041','41162','35390', + '16364','39500','68908','26689','52868', + '81335','40146','11340','61527','61794', + '71997','30415','59004','29450','58117', + '69952','33562','83833','27385','61860', + '96435','48333','23065','32961','84919', + '61997','99132','22815','56600','68730', + '48017','95694','32919','88217','27116', + '28239','58032','18884','16791','21343', + '97462','18569','75660','15475') + intersect + select ca_zip + from (SELECT substr(ca_zip,1,5) ca_zip,count(*) cnt + FROM customer_address, customer + WHERE ca_address_sk = c_current_addr_sk and + c_preferred_cust_flag='Y' + group by ca_zip + having count(*) > 10)A1)A2) V1 + where ss_store_sk = s_store_sk + and ss_sold_date_sk = d_date_sk + and d_qoy = 2 and d_year = 1998 + and (substr(s_zip,1,2) = substr(V1.ca_zip,1,2)) + group by s_store_name + order by s_store_name + limit 100; + +-- end query 8 in stream 0 using template query8.tpl +-- start query 9 in stream 0 using template query9.tpl +select case when (select count(*) + from store_sales + where ss_quantity between 1 and 20) > 1071 + then (select avg(ss_ext_tax) + from store_sales + where ss_quantity between 1 and 20) + else (select avg(ss_net_paid_inc_tax) + from store_sales + where ss_quantity between 1 and 20) end bucket1 , + case when (select count(*) + from store_sales + where ss_quantity between 21 and 40) > 39161 + then (select avg(ss_ext_tax) + from store_sales + where ss_quantity between 21 and 40) + else (select avg(ss_net_paid_inc_tax) + from store_sales + where ss_quantity between 21 and 40) end bucket2, + case when (select count(*) + from store_sales + where ss_quantity between 41 and 60) > 29434 + then (select avg(ss_ext_tax) + from store_sales + where ss_quantity between 41 and 60) + else (select avg(ss_net_paid_inc_tax) + from store_sales + where ss_quantity between 41 and 60) end bucket3, + case when (select count(*) + from store_sales + where ss_quantity between 61 and 80) > 6568 + then (select avg(ss_ext_tax) + from store_sales + where ss_quantity between 61 and 80) + else (select avg(ss_net_paid_inc_tax) + from store_sales + where ss_quantity between 61 and 80) end bucket4, + case when (select count(*) + from store_sales + where ss_quantity between 81 and 100) > 21216 + then (select avg(ss_ext_tax) + from store_sales + where ss_quantity between 81 and 100) + else (select avg(ss_net_paid_inc_tax) + from store_sales + where ss_quantity between 81 and 100) end bucket5 +from reason +where r_reason_sk = 1 +; + +-- end query 9 in stream 0 using template query9.tpl +-- start query 10 in stream 0 using template query10.tpl +select + cd_gender, + cd_marital_status, + cd_education_status, + count(*) cnt1, + cd_purchase_estimate, + count(*) cnt2, + cd_credit_rating, + count(*) cnt3, + cd_dep_count, + count(*) cnt4, + cd_dep_employed_count, + count(*) cnt5, + cd_dep_college_count, + count(*) cnt6 + from + customer c,customer_address ca,customer_demographics + where + c.c_current_addr_sk = ca.ca_address_sk and + ca_county in ('Fairfield County','Campbell County','Washtenaw County','Escambia County','Cleburne County') and + cd_demo_sk = c.c_current_cdemo_sk and + exists (select * + from store_sales,date_dim + where c.c_customer_sk = ss_customer_sk and + ss_sold_date_sk = d_date_sk and + d_year = 2001 and + d_moy between 3 and 3+3) and + (exists (select * + from web_sales,date_dim + where c.c_customer_sk = ws_bill_customer_sk and + ws_sold_date_sk = d_date_sk and + d_year = 2001 and + d_moy between 3 ANd 3+3) or + exists (select * + from catalog_sales,date_dim + where c.c_customer_sk = cs_ship_customer_sk and + cs_sold_date_sk = d_date_sk and + d_year = 2001 and + d_moy between 3 and 3+3)) + group by cd_gender, + cd_marital_status, + cd_education_status, + cd_purchase_estimate, + cd_credit_rating, + cd_dep_count, + cd_dep_employed_count, + cd_dep_college_count + order by cd_gender, + cd_marital_status, + cd_education_status, + cd_purchase_estimate, + cd_credit_rating, + cd_dep_count, + cd_dep_employed_count, + cd_dep_college_count +limit 100; + +-- end query 10 in stream 0 using template query10.tpl +-- start query 11 in stream 0 using template query11.tpl +with year_total as ( + select c_customer_id customer_id + ,c_first_name customer_first_name + ,c_last_name customer_last_name + ,c_preferred_cust_flag customer_preferred_cust_flag + ,c_birth_country customer_birth_country + ,c_login customer_login + ,c_email_address customer_email_address + ,d_year dyear + ,sum(ss_ext_list_price-ss_ext_discount_amt) year_total + ,'s' sale_type + from customer + ,store_sales + ,date_dim + where c_customer_sk = ss_customer_sk + and ss_sold_date_sk = d_date_sk + group by c_customer_id + ,c_first_name + ,c_last_name + ,c_preferred_cust_flag + ,c_birth_country + ,c_login + ,c_email_address + ,d_year + union all + select c_customer_id customer_id + ,c_first_name customer_first_name + ,c_last_name customer_last_name + ,c_preferred_cust_flag customer_preferred_cust_flag + ,c_birth_country customer_birth_country + ,c_login customer_login + ,c_email_address customer_email_address + ,d_year dyear + ,sum(ws_ext_list_price-ws_ext_discount_amt) year_total + ,'w' sale_type + from customer + ,web_sales + ,date_dim + where c_customer_sk = ws_bill_customer_sk + and ws_sold_date_sk = d_date_sk + group by c_customer_id + ,c_first_name + ,c_last_name + ,c_preferred_cust_flag + ,c_birth_country + ,c_login + ,c_email_address + ,d_year + ) + select + t_s_secyear.customer_id + ,t_s_secyear.customer_first_name + ,t_s_secyear.customer_last_name + ,t_s_secyear.customer_email_address + from year_total t_s_firstyear + ,year_total t_s_secyear + ,year_total t_w_firstyear + ,year_total t_w_secyear + where t_s_secyear.customer_id = t_s_firstyear.customer_id + and t_s_firstyear.customer_id = t_w_secyear.customer_id + and t_s_firstyear.customer_id = t_w_firstyear.customer_id + and t_s_firstyear.sale_type = 's' + and t_w_firstyear.sale_type = 'w' + and t_s_secyear.sale_type = 's' + and t_w_secyear.sale_type = 'w' + and t_s_firstyear.dyear = 1998 + and t_s_secyear.dyear = 1998+1 + and t_w_firstyear.dyear = 1998 + and t_w_secyear.dyear = 1998+1 + and t_s_firstyear.year_total > 0 + and t_w_firstyear.year_total > 0 + and case when t_w_firstyear.year_total > 0 then t_w_secyear.year_total / t_w_firstyear.year_total else 0.0 end + > case when t_s_firstyear.year_total > 0 then t_s_secyear.year_total / t_s_firstyear.year_total else 0.0 end + order by t_s_secyear.customer_id + ,t_s_secyear.customer_first_name + ,t_s_secyear.customer_last_name + ,t_s_secyear.customer_email_address +limit 100; + +-- end query 11 in stream 0 using template query11.tpl +-- start query 12 in stream 0 using template query12.tpl +select i_item_id + ,i_item_desc + ,i_category + ,i_class + ,i_current_price + ,sum(ws_ext_sales_price) as itemrevenue + ,sum(ws_ext_sales_price)*100/sum(sum(ws_ext_sales_price)) over + (partition by i_class) as revenueratio +from + web_sales + ,item + ,date_dim +where + ws_item_sk = i_item_sk + and i_category in ('Men', 'Books', 'Electronics') + and ws_sold_date_sk = d_date_sk + and d_date between cast('2001-06-15' as date) + and (cast('2001-06-15' as date) + 30 days) +group by + i_item_id + ,i_item_desc + ,i_category + ,i_class + ,i_current_price +order by + i_category + ,i_class + ,i_item_id + ,i_item_desc + ,revenueratio +limit 100; + +-- end query 12 in stream 0 using template query12.tpl +-- start query 13 in stream 0 using template query13.tpl +select avg(ss_quantity) + ,avg(ss_ext_sales_price) + ,avg(ss_ext_wholesale_cost) + ,sum(ss_ext_wholesale_cost) + from store_sales + ,store + ,customer_demographics + ,household_demographics + ,customer_address + ,date_dim + where s_store_sk = ss_store_sk + and ss_sold_date_sk = d_date_sk and d_year = 2001 + and((ss_hdemo_sk=hd_demo_sk + and cd_demo_sk = ss_cdemo_sk + and cd_marital_status = 'M' + and cd_education_status = 'College' + and ss_sales_price between 100.00 and 150.00 + and hd_dep_count = 3 + )or + (ss_hdemo_sk=hd_demo_sk + and cd_demo_sk = ss_cdemo_sk + and cd_marital_status = 'D' + and cd_education_status = 'Primary' + and ss_sales_price between 50.00 and 100.00 + and hd_dep_count = 1 + ) or + (ss_hdemo_sk=hd_demo_sk + and cd_demo_sk = ss_cdemo_sk + and cd_marital_status = 'W' + and cd_education_status = '2 yr Degree' + and ss_sales_price between 150.00 and 200.00 + and hd_dep_count = 1 + )) + and((ss_addr_sk = ca_address_sk + and ca_country = 'United States' + and ca_state in ('IL', 'TN', 'TX') + and ss_net_profit between 100 and 200 + ) or + (ss_addr_sk = ca_address_sk + and ca_country = 'United States' + and ca_state in ('WY', 'OH', 'ID') + and ss_net_profit between 150 and 300 + ) or + (ss_addr_sk = ca_address_sk + and ca_country = 'United States' + and ca_state in ('MS', 'SC', 'IA') + and ss_net_profit between 50 and 250 + )) +; + +-- end query 13 in stream 0 using template query13.tpl +-- start query 14 in stream 0 using template query14.tpl +with cross_items as + (select i_item_sk ss_item_sk + from item, + (select iss.i_brand_id brand_id + ,iss.i_class_id class_id + ,iss.i_category_id category_id + from store_sales + ,item iss + ,date_dim d1 + where ss_item_sk = iss.i_item_sk + and ss_sold_date_sk = d1.d_date_sk + and d1.d_year between 1999 AND 1999 + 2 + intersect + select ics.i_brand_id + ,ics.i_class_id + ,ics.i_category_id + from catalog_sales + ,item ics + ,date_dim d2 + where cs_item_sk = ics.i_item_sk + and cs_sold_date_sk = d2.d_date_sk + and d2.d_year between 1999 AND 1999 + 2 + intersect + select iws.i_brand_id + ,iws.i_class_id + ,iws.i_category_id + from web_sales + ,item iws + ,date_dim d3 + where ws_item_sk = iws.i_item_sk + and ws_sold_date_sk = d3.d_date_sk + and d3.d_year between 1999 AND 1999 + 2) + where i_brand_id = brand_id + and i_class_id = class_id + and i_category_id = category_id +), + avg_sales as + (select avg(quantity*list_price) average_sales + from (select ss_quantity quantity + ,ss_list_price list_price + from store_sales + ,date_dim + where ss_sold_date_sk = d_date_sk + and d_year between 1999 and 1999 + 2 + union all + select cs_quantity quantity + ,cs_list_price list_price + from catalog_sales + ,date_dim + where cs_sold_date_sk = d_date_sk + and d_year between 1999 and 1999 + 2 + union all + select ws_quantity quantity + ,ws_list_price list_price + from web_sales + ,date_dim + where ws_sold_date_sk = d_date_sk + and d_year between 1999 and 1999 + 2) x) + select channel, i_brand_id,i_class_id,i_category_id,sum(sales), sum(number_sales) + from( + select 'store' channel, i_brand_id,i_class_id + ,i_category_id,sum(ss_quantity*ss_list_price) sales + , count(*) number_sales + from store_sales + ,item + ,date_dim + where ss_item_sk in (select ss_item_sk from cross_items) + and ss_item_sk = i_item_sk + and ss_sold_date_sk = d_date_sk + and d_year = 1999+2 + and d_moy = 11 + group by i_brand_id,i_class_id,i_category_id + having sum(ss_quantity*ss_list_price) > (select average_sales from avg_sales) + union all + select 'catalog' channel, i_brand_id,i_class_id,i_category_id, sum(cs_quantity*cs_list_price) sales, count(*) number_sales + from catalog_sales + ,item + ,date_dim + where cs_item_sk in (select ss_item_sk from cross_items) + and cs_item_sk = i_item_sk + and cs_sold_date_sk = d_date_sk + and d_year = 1999+2 + and d_moy = 11 + group by i_brand_id,i_class_id,i_category_id + having sum(cs_quantity*cs_list_price) > (select average_sales from avg_sales) + union all + select 'web' channel, i_brand_id,i_class_id,i_category_id, sum(ws_quantity*ws_list_price) sales , count(*) number_sales + from web_sales + ,item + ,date_dim + where ws_item_sk in (select ss_item_sk from cross_items) + and ws_item_sk = i_item_sk + and ws_sold_date_sk = d_date_sk + and d_year = 1999+2 + and d_moy = 11 + group by i_brand_id,i_class_id,i_category_id + having sum(ws_quantity*ws_list_price) > (select average_sales from avg_sales) + ) y + group by rollup (channel, i_brand_id,i_class_id,i_category_id) + order by channel,i_brand_id,i_class_id,i_category_id + limit 100; +with cross_items as + (select i_item_sk ss_item_sk + from item, + (select iss.i_brand_id brand_id + ,iss.i_class_id class_id + ,iss.i_category_id category_id + from store_sales + ,item iss + ,date_dim d1 + where ss_item_sk = iss.i_item_sk + and ss_sold_date_sk = d1.d_date_sk + and d1.d_year between 1999 AND 1999 + 2 + intersect + select ics.i_brand_id + ,ics.i_class_id + ,ics.i_category_id + from catalog_sales + ,item ics + ,date_dim d2 + where cs_item_sk = ics.i_item_sk + and cs_sold_date_sk = d2.d_date_sk + and d2.d_year between 1999 AND 1999 + 2 + intersect + select iws.i_brand_id + ,iws.i_class_id + ,iws.i_category_id + from web_sales + ,item iws + ,date_dim d3 + where ws_item_sk = iws.i_item_sk + and ws_sold_date_sk = d3.d_date_sk + and d3.d_year between 1999 AND 1999 + 2) x + where i_brand_id = brand_id + and i_class_id = class_id + and i_category_id = category_id +), + avg_sales as +(select avg(quantity*list_price) average_sales + from (select ss_quantity quantity + ,ss_list_price list_price + from store_sales + ,date_dim + where ss_sold_date_sk = d_date_sk + and d_year between 1999 and 1999 + 2 + union all + select cs_quantity quantity + ,cs_list_price list_price + from catalog_sales + ,date_dim + where cs_sold_date_sk = d_date_sk + and d_year between 1999 and 1999 + 2 + union all + select ws_quantity quantity + ,ws_list_price list_price + from web_sales + ,date_dim + where ws_sold_date_sk = d_date_sk + and d_year between 1999 and 1999 + 2) x) + select this_year.channel ty_channel + ,this_year.i_brand_id ty_brand + ,this_year.i_class_id ty_class + ,this_year.i_category_id ty_category + ,this_year.sales ty_sales + ,this_year.number_sales ty_number_sales + ,last_year.channel ly_channel + ,last_year.i_brand_id ly_brand + ,last_year.i_class_id ly_class + ,last_year.i_category_id ly_category + ,last_year.sales ly_sales + ,last_year.number_sales ly_number_sales + from + (select 'store' channel, i_brand_id,i_class_id,i_category_id + ,sum(ss_quantity*ss_list_price) sales, count(*) number_sales + from store_sales + ,item + ,date_dim + where ss_item_sk in (select ss_item_sk from cross_items) + and ss_item_sk = i_item_sk + and ss_sold_date_sk = d_date_sk + and d_week_seq = (select d_week_seq + from date_dim + where d_year = 1999 + 1 + and d_moy = 12 + and d_dom = 3) + group by i_brand_id,i_class_id,i_category_id + having sum(ss_quantity*ss_list_price) > (select average_sales from avg_sales)) this_year, + (select 'store' channel, i_brand_id,i_class_id + ,i_category_id, sum(ss_quantity*ss_list_price) sales, count(*) number_sales + from store_sales + ,item + ,date_dim + where ss_item_sk in (select ss_item_sk from cross_items) + and ss_item_sk = i_item_sk + and ss_sold_date_sk = d_date_sk + and d_week_seq = (select d_week_seq + from date_dim + where d_year = 1999 + and d_moy = 12 + and d_dom = 3) + group by i_brand_id,i_class_id,i_category_id + having sum(ss_quantity*ss_list_price) > (select average_sales from avg_sales)) last_year + where this_year.i_brand_id= last_year.i_brand_id + and this_year.i_class_id = last_year.i_class_id + and this_year.i_category_id = last_year.i_category_id + order by this_year.channel, this_year.i_brand_id, this_year.i_class_id, this_year.i_category_id + limit 100; + +-- end query 14 in stream 0 using template query14.tpl +-- start query 15 in stream 0 using template query15.tpl +select ca_zip + ,sum(cs_sales_price) + from catalog_sales + ,customer + ,customer_address + ,date_dim + where cs_bill_customer_sk = c_customer_sk + and c_current_addr_sk = ca_address_sk + and ( substr(ca_zip,1,5) in ('85669', '86197','88274','83405','86475', + '85392', '85460', '80348', '81792') + or ca_state in ('CA','WA','GA') + or cs_sales_price > 500) + and cs_sold_date_sk = d_date_sk + and d_qoy = 2 and d_year = 2001 + group by ca_zip + order by ca_zip + limit 100; + +-- end query 15 in stream 0 using template query15.tpl +-- start query 16 in stream 0 using template query16.tpl +select + count(distinct cs_order_number) as "order count" + ,sum(cs_ext_ship_cost) as "total shipping cost" + ,sum(cs_net_profit) as "total net profit" +from + catalog_sales cs1 + ,date_dim + ,customer_address + ,call_center +where + d_date between '2002-4-01' and + (cast('2002-4-01' as date) + 60 days) +and cs1.cs_ship_date_sk = d_date_sk +and cs1.cs_ship_addr_sk = ca_address_sk +and ca_state = 'PA' +and cs1.cs_call_center_sk = cc_call_center_sk +and cc_county in ('Williamson County','Williamson County','Williamson County','Williamson County', + 'Williamson County' +) +and exists (select * + from catalog_sales cs2 + where cs1.cs_order_number = cs2.cs_order_number + and cs1.cs_warehouse_sk <> cs2.cs_warehouse_sk) +and not exists(select * + from catalog_returns cr1 + where cs1.cs_order_number = cr1.cr_order_number) +order by count(distinct cs_order_number) +limit 100; + +-- end query 16 in stream 0 using template query16.tpl +-- start query 17 in stream 0 using template query17.tpl +select i_item_id + ,i_item_desc + ,s_state + ,count(ss_quantity) as store_sales_quantitycount + ,avg(ss_quantity) as store_sales_quantityave + ,stddev_samp(ss_quantity) as store_sales_quantitystdev + ,stddev_samp(ss_quantity)/avg(ss_quantity) as store_sales_quantitycov + ,count(sr_return_quantity) as store_returns_quantitycount + ,avg(sr_return_quantity) as store_returns_quantityave + ,stddev_samp(sr_return_quantity) as store_returns_quantitystdev + ,stddev_samp(sr_return_quantity)/avg(sr_return_quantity) as store_returns_quantitycov + ,count(cs_quantity) as catalog_sales_quantitycount ,avg(cs_quantity) as catalog_sales_quantityave + ,stddev_samp(cs_quantity) as catalog_sales_quantitystdev + ,stddev_samp(cs_quantity)/avg(cs_quantity) as catalog_sales_quantitycov + from store_sales + ,store_returns + ,catalog_sales + ,date_dim d1 + ,date_dim d2 + ,date_dim d3 + ,store + ,item + where d1.d_quarter_name = '2001Q1' + and d1.d_date_sk = ss_sold_date_sk + and i_item_sk = ss_item_sk + and s_store_sk = ss_store_sk + and ss_customer_sk = sr_customer_sk + and ss_item_sk = sr_item_sk + and ss_ticket_number = sr_ticket_number + and sr_returned_date_sk = d2.d_date_sk + and d2.d_quarter_name in ('2001Q1','2001Q2','2001Q3') + and sr_customer_sk = cs_bill_customer_sk + and sr_item_sk = cs_item_sk + and cs_sold_date_sk = d3.d_date_sk + and d3.d_quarter_name in ('2001Q1','2001Q2','2001Q3') + group by i_item_id + ,i_item_desc + ,s_state + order by i_item_id + ,i_item_desc + ,s_state +limit 100; + +-- end query 17 in stream 0 using template query17.tpl +-- start query 18 in stream 0 using template query18.tpl +select i_item_id, + ca_country, + ca_state, + ca_county, + avg( cast(cs_quantity as decimal(12,2))) agg1, + avg( cast(cs_list_price as decimal(12,2))) agg2, + avg( cast(cs_coupon_amt as decimal(12,2))) agg3, + avg( cast(cs_sales_price as decimal(12,2))) agg4, + avg( cast(cs_net_profit as decimal(12,2))) agg5, + avg( cast(c_birth_year as decimal(12,2))) agg6, + avg( cast(cd1.cd_dep_count as decimal(12,2))) agg7 + from catalog_sales, customer_demographics cd1, + customer_demographics cd2, customer, customer_address, date_dim, item + where cs_sold_date_sk = d_date_sk and + cs_item_sk = i_item_sk and + cs_bill_cdemo_sk = cd1.cd_demo_sk and + cs_bill_customer_sk = c_customer_sk and + cd1.cd_gender = 'F' and + cd1.cd_education_status = 'Primary' and + c_current_cdemo_sk = cd2.cd_demo_sk and + c_current_addr_sk = ca_address_sk and + c_birth_month in (1,3,7,11,10,4) and + d_year = 2001 and + ca_state in ('AL','MO','TN' + ,'GA','MT','IN','CA') + group by rollup (i_item_id, ca_country, ca_state, ca_county) + order by ca_country, + ca_state, + ca_county, + i_item_id + limit 100; + +-- end query 18 in stream 0 using template query18.tpl +-- start query 19 in stream 0 using template query19.tpl +select i_brand_id brand_id, i_brand brand, i_manufact_id, i_manufact, + sum(ss_ext_sales_price) ext_price + from date_dim, store_sales, item,customer,customer_address,store + where d_date_sk = ss_sold_date_sk + and ss_item_sk = i_item_sk + and i_manager_id=14 + and d_moy=11 + and d_year=2002 + and ss_customer_sk = c_customer_sk + and c_current_addr_sk = ca_address_sk + and substr(ca_zip,1,5) <> substr(s_zip,1,5) + and ss_store_sk = s_store_sk + group by i_brand + ,i_brand_id + ,i_manufact_id + ,i_manufact + order by ext_price desc + ,i_brand + ,i_brand_id + ,i_manufact_id + ,i_manufact +limit 100 ; + +-- end query 19 in stream 0 using template query19.tpl +-- start query 20 in stream 0 using template query20.tpl +select i_item_id + ,i_item_desc + ,i_category + ,i_class + ,i_current_price + ,sum(cs_ext_sales_price) as itemrevenue + ,sum(cs_ext_sales_price)*100/sum(sum(cs_ext_sales_price)) over + (partition by i_class) as revenueratio + from catalog_sales + ,item + ,date_dim + where cs_item_sk = i_item_sk + and i_category in ('Books', 'Music', 'Sports') + and cs_sold_date_sk = d_date_sk + and d_date between cast('2002-06-18' as date) + and (cast('2002-06-18' as date) + 30 days) + group by i_item_id + ,i_item_desc + ,i_category + ,i_class + ,i_current_price + order by i_category + ,i_class + ,i_item_id + ,i_item_desc + ,revenueratio +limit 100; + +-- end query 20 in stream 0 using template query20.tpl +-- start query 21 in stream 0 using template query21.tpl +select * + from(select w_warehouse_name + ,i_item_id + ,sum(case when (cast(d_date as date) < cast ('1999-06-22' as date)) + then inv_quantity_on_hand + else 0 end) as inv_before + ,sum(case when (cast(d_date as date) >= cast ('1999-06-22' as date)) + then inv_quantity_on_hand + else 0 end) as inv_after + from inventory + ,warehouse + ,item + ,date_dim + where i_current_price between 0.99 and 1.49 + and i_item_sk = inv_item_sk + and inv_warehouse_sk = w_warehouse_sk + and inv_date_sk = d_date_sk + and d_date between (cast ('1999-06-22' as date) - 30 days) + and (cast ('1999-06-22' as date) + 30 days) + group by w_warehouse_name, i_item_id) x + where (case when inv_before > 0 + then inv_after / inv_before + else null + end) between 2.0/3.0 and 3.0/2.0 + order by w_warehouse_name + ,i_item_id + limit 100; + +-- end query 21 in stream 0 using template query21.tpl +-- start query 22 in stream 0 using template query22.tpl +select i_product_name + ,i_brand + ,i_class + ,i_category + ,avg(inv_quantity_on_hand) qoh + from inventory + ,date_dim + ,item + where inv_date_sk=d_date_sk + and inv_item_sk=i_item_sk + and d_month_seq between 1200 and 1200 + 11 + group by rollup(i_product_name + ,i_brand + ,i_class + ,i_category) +order by qoh, i_product_name, i_brand, i_class, i_category +limit 100; + +-- end query 22 in stream 0 using template query22.tpl +-- start query 23 in stream 0 using template query23.tpl +with frequent_ss_items as + (select substr(i_item_desc,1,30) itemdesc,i_item_sk item_sk,d_date solddate,count(*) cnt + from store_sales + ,date_dim + ,item + where ss_sold_date_sk = d_date_sk + and ss_item_sk = i_item_sk + and d_year in (2000,2000+1,2000+2,2000+3) + group by substr(i_item_desc,1,30),i_item_sk,d_date + having count(*) >4), + max_store_sales as + (select max(csales) tpcds_cmax + from (select c_customer_sk,sum(ss_quantity*ss_sales_price) csales + from store_sales + ,customer + ,date_dim + where ss_customer_sk = c_customer_sk + and ss_sold_date_sk = d_date_sk + and d_year in (2000,2000+1,2000+2,2000+3) + group by c_customer_sk)), + best_ss_customer as + (select c_customer_sk,sum(ss_quantity*ss_sales_price) ssales + from store_sales + ,customer + where ss_customer_sk = c_customer_sk + group by c_customer_sk + having sum(ss_quantity*ss_sales_price) > (95/100.0) * (select + * +from + max_store_sales)) + select sum(sales) + from (select cs_quantity*cs_list_price sales + from catalog_sales + ,date_dim + where d_year = 2000 + and d_moy = 7 + and cs_sold_date_sk = d_date_sk + and cs_item_sk in (select item_sk from frequent_ss_items) + and cs_bill_customer_sk in (select c_customer_sk from best_ss_customer) + union all + select ws_quantity*ws_list_price sales + from web_sales + ,date_dim + where d_year = 2000 + and d_moy = 7 + and ws_sold_date_sk = d_date_sk + and ws_item_sk in (select item_sk from frequent_ss_items) + and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer)) + limit 100; +with frequent_ss_items as + (select substr(i_item_desc,1,30) itemdesc,i_item_sk item_sk,d_date solddate,count(*) cnt + from store_sales + ,date_dim + ,item + where ss_sold_date_sk = d_date_sk + and ss_item_sk = i_item_sk + and d_year in (2000,2000 + 1,2000 + 2,2000 + 3) + group by substr(i_item_desc,1,30),i_item_sk,d_date + having count(*) >4), + max_store_sales as + (select max(csales) tpcds_cmax + from (select c_customer_sk,sum(ss_quantity*ss_sales_price) csales + from store_sales + ,customer + ,date_dim + where ss_customer_sk = c_customer_sk + and ss_sold_date_sk = d_date_sk + and d_year in (2000,2000+1,2000+2,2000+3) + group by c_customer_sk)), + best_ss_customer as + (select c_customer_sk,sum(ss_quantity*ss_sales_price) ssales + from store_sales + ,customer + where ss_customer_sk = c_customer_sk + group by c_customer_sk + having sum(ss_quantity*ss_sales_price) > (95/100.0) * (select + * + from max_store_sales)) + select c_last_name,c_first_name,sales + from (select c_last_name,c_first_name,sum(cs_quantity*cs_list_price) sales + from catalog_sales + ,customer + ,date_dim + where d_year = 2000 + and d_moy = 7 + and cs_sold_date_sk = d_date_sk + and cs_item_sk in (select item_sk from frequent_ss_items) + and cs_bill_customer_sk in (select c_customer_sk from best_ss_customer) + and cs_bill_customer_sk = c_customer_sk + group by c_last_name,c_first_name + union all + select c_last_name,c_first_name,sum(ws_quantity*ws_list_price) sales + from web_sales + ,customer + ,date_dim + where d_year = 2000 + and d_moy = 7 + and ws_sold_date_sk = d_date_sk + and ws_item_sk in (select item_sk from frequent_ss_items) + and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer) + and ws_bill_customer_sk = c_customer_sk + group by c_last_name,c_first_name) + order by c_last_name,c_first_name,sales + limit 100; + +-- end query 23 in stream 0 using template query23.tpl +-- start query 24 in stream 0 using template query24.tpl +with ssales as +(select c_last_name + ,c_first_name + ,s_store_name + ,ca_state + ,s_state + ,i_color + ,i_current_price + ,i_manager_id + ,i_units + ,i_size + ,sum(ss_net_paid) netpaid +from store_sales + ,store_returns + ,store + ,item + ,customer + ,customer_address +where ss_ticket_number = sr_ticket_number + and ss_item_sk = sr_item_sk + and ss_customer_sk = c_customer_sk + and ss_item_sk = i_item_sk + and ss_store_sk = s_store_sk + and c_current_addr_sk = ca_address_sk + and c_birth_country <> upper(ca_country) + and s_zip = ca_zip +and s_market_id=5 +group by c_last_name + ,c_first_name + ,s_store_name + ,ca_state + ,s_state + ,i_color + ,i_current_price + ,i_manager_id + ,i_units + ,i_size) +select c_last_name + ,c_first_name + ,s_store_name + ,sum(netpaid) paid +from ssales +where i_color = 'aquamarine' +group by c_last_name + ,c_first_name + ,s_store_name +having sum(netpaid) > (select 0.05*avg(netpaid) + from ssales) +order by c_last_name + ,c_first_name + ,s_store_name +; +with ssales as +(select c_last_name + ,c_first_name + ,s_store_name + ,ca_state + ,s_state + ,i_color + ,i_current_price + ,i_manager_id + ,i_units + ,i_size + ,sum(ss_net_paid) netpaid +from store_sales + ,store_returns + ,store + ,item + ,customer + ,customer_address +where ss_ticket_number = sr_ticket_number + and ss_item_sk = sr_item_sk + and ss_customer_sk = c_customer_sk + and ss_item_sk = i_item_sk + and ss_store_sk = s_store_sk + and c_current_addr_sk = ca_address_sk + and c_birth_country <> upper(ca_country) + and s_zip = ca_zip + and s_market_id = 5 +group by c_last_name + ,c_first_name + ,s_store_name + ,ca_state + ,s_state + ,i_color + ,i_current_price + ,i_manager_id + ,i_units + ,i_size) +select c_last_name + ,c_first_name + ,s_store_name + ,sum(netpaid) paid +from ssales +where i_color = 'seashell' +group by c_last_name + ,c_first_name + ,s_store_name +having sum(netpaid) > (select 0.05*avg(netpaid) + from ssales) +order by c_last_name + ,c_first_name + ,s_store_name +; + +-- end query 24 in stream 0 using template query24.tpl +-- start query 25 in stream 0 using template query25.tpl +select + i_item_id + ,i_item_desc + ,s_store_id + ,s_store_name + ,max(ss_net_profit) as store_sales_profit + ,max(sr_net_loss) as store_returns_loss + ,max(cs_net_profit) as catalog_sales_profit + from + store_sales + ,store_returns + ,catalog_sales + ,date_dim d1 + ,date_dim d2 + ,date_dim d3 + ,store + ,item + where + d1.d_moy = 4 + and d1.d_year = 1999 + and d1.d_date_sk = ss_sold_date_sk + and i_item_sk = ss_item_sk + and s_store_sk = ss_store_sk + and ss_customer_sk = sr_customer_sk + and ss_item_sk = sr_item_sk + and ss_ticket_number = sr_ticket_number + and sr_returned_date_sk = d2.d_date_sk + and d2.d_moy between 4 and 10 + and d2.d_year = 1999 + and sr_customer_sk = cs_bill_customer_sk + and sr_item_sk = cs_item_sk + and cs_sold_date_sk = d3.d_date_sk + and d3.d_moy between 4 and 10 + and d3.d_year = 1999 + group by + i_item_id + ,i_item_desc + ,s_store_id + ,s_store_name + order by + i_item_id + ,i_item_desc + ,s_store_id + ,s_store_name + limit 100; + +-- end query 25 in stream 0 using template query25.tpl +-- start query 26 in stream 0 using template query26.tpl +select i_item_id, + avg(cs_quantity) agg1, + avg(cs_list_price) agg2, + avg(cs_coupon_amt) agg3, + avg(cs_sales_price) agg4 + from catalog_sales, customer_demographics, date_dim, item, promotion + where cs_sold_date_sk = d_date_sk and + cs_item_sk = i_item_sk and + cs_bill_cdemo_sk = cd_demo_sk and + cs_promo_sk = p_promo_sk and + cd_gender = 'M' and + cd_marital_status = 'W' and + cd_education_status = 'Unknown' and + (p_channel_email = 'N' or p_channel_event = 'N') and + d_year = 2002 + group by i_item_id + order by i_item_id + limit 100; + +-- end query 26 in stream 0 using template query26.tpl +-- start query 27 in stream 0 using template query27.tpl +select i_item_id, + s_state, grouping(s_state) g_state, + avg(ss_quantity) agg1, + avg(ss_list_price) agg2, + avg(ss_coupon_amt) agg3, + avg(ss_sales_price) agg4 + from store_sales, customer_demographics, date_dim, store, item + where ss_sold_date_sk = d_date_sk and + ss_item_sk = i_item_sk and + ss_store_sk = s_store_sk and + ss_cdemo_sk = cd_demo_sk and + cd_gender = 'M' and + cd_marital_status = 'W' and + cd_education_status = 'Secondary' and + d_year = 1999 and + s_state in ('TN','TN', 'TN', 'TN', 'TN', 'TN') + group by rollup (i_item_id, s_state) + order by i_item_id + ,s_state + limit 100; + +-- end query 27 in stream 0 using template query27.tpl +-- start query 28 in stream 0 using template query28.tpl +select * +from (select avg(ss_list_price) B1_LP + ,count(ss_list_price) B1_CNT + ,count(distinct ss_list_price) B1_CNTD + from store_sales + where ss_quantity between 0 and 5 + and (ss_list_price between 107 and 107+10 + or ss_coupon_amt between 1319 and 1319+1000 + or ss_wholesale_cost between 60 and 60+20)) B1, + (select avg(ss_list_price) B2_LP + ,count(ss_list_price) B2_CNT + ,count(distinct ss_list_price) B2_CNTD + from store_sales + where ss_quantity between 6 and 10 + and (ss_list_price between 23 and 23+10 + or ss_coupon_amt between 825 and 825+1000 + or ss_wholesale_cost between 43 and 43+20)) B2, + (select avg(ss_list_price) B3_LP + ,count(ss_list_price) B3_CNT + ,count(distinct ss_list_price) B3_CNTD + from store_sales + where ss_quantity between 11 and 15 + and (ss_list_price between 74 and 74+10 + or ss_coupon_amt between 4381 and 4381+1000 + or ss_wholesale_cost between 57 and 57+20)) B3, + (select avg(ss_list_price) B4_LP + ,count(ss_list_price) B4_CNT + ,count(distinct ss_list_price) B4_CNTD + from store_sales + where ss_quantity between 16 and 20 + and (ss_list_price between 89 and 89+10 + or ss_coupon_amt between 3117 and 3117+1000 + or ss_wholesale_cost between 68 and 68+20)) B4, + (select avg(ss_list_price) B5_LP + ,count(ss_list_price) B5_CNT + ,count(distinct ss_list_price) B5_CNTD + from store_sales + where ss_quantity between 21 and 25 + and (ss_list_price between 58 and 58+10 + or ss_coupon_amt between 9402 and 9402+1000 + or ss_wholesale_cost between 38 and 38+20)) B5, + (select avg(ss_list_price) B6_LP + ,count(ss_list_price) B6_CNT + ,count(distinct ss_list_price) B6_CNTD + from store_sales + where ss_quantity between 26 and 30 + and (ss_list_price between 64 and 64+10 + or ss_coupon_amt between 5792 and 5792+1000 + or ss_wholesale_cost between 73 and 73+20)) B6 +limit 100; + +-- end query 28 in stream 0 using template query28.tpl +-- start query 29 in stream 0 using template query29.tpl +select + i_item_id + ,i_item_desc + ,s_store_id + ,s_store_name + ,max(ss_quantity) as store_sales_quantity + ,max(sr_return_quantity) as store_returns_quantity + ,max(cs_quantity) as catalog_sales_quantity + from + store_sales + ,store_returns + ,catalog_sales + ,date_dim d1 + ,date_dim d2 + ,date_dim d3 + ,store + ,item + where + d1.d_moy = 4 + and d1.d_year = 1998 + and d1.d_date_sk = ss_sold_date_sk + and i_item_sk = ss_item_sk + and s_store_sk = ss_store_sk + and ss_customer_sk = sr_customer_sk + and ss_item_sk = sr_item_sk + and ss_ticket_number = sr_ticket_number + and sr_returned_date_sk = d2.d_date_sk + and d2.d_moy between 4 and 4 + 3 + and d2.d_year = 1998 + and sr_customer_sk = cs_bill_customer_sk + and sr_item_sk = cs_item_sk + and cs_sold_date_sk = d3.d_date_sk + and d3.d_year in (1998,1998+1,1998+2) + group by + i_item_id + ,i_item_desc + ,s_store_id + ,s_store_name + order by + i_item_id + ,i_item_desc + ,s_store_id + ,s_store_name + limit 100; + +-- end query 29 in stream 0 using template query29.tpl +-- start query 30 in stream 0 using template query30.tpl +with customer_total_return as + (select wr_returning_customer_sk as ctr_customer_sk + ,ca_state as ctr_state, + sum(wr_return_amt) as ctr_total_return + from web_returns + ,date_dim + ,customer_address + where wr_returned_date_sk = d_date_sk + and d_year =2000 + and wr_returning_addr_sk = ca_address_sk + group by wr_returning_customer_sk + ,ca_state) + select c_customer_id,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag + ,c_birth_day,c_birth_month,c_birth_year,c_birth_country,c_login,c_email_address + ,c_last_review_date_sk,ctr_total_return + from customer_total_return ctr1 + ,customer_address + ,customer + where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2 + from customer_total_return ctr2 + where ctr1.ctr_state = ctr2.ctr_state) + and ca_address_sk = c_current_addr_sk + and ca_state = 'AR' + and ctr1.ctr_customer_sk = c_customer_sk + order by c_customer_id,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag + ,c_birth_day,c_birth_month,c_birth_year,c_birth_country,c_login,c_email_address + ,c_last_review_date_sk,ctr_total_return +limit 100; + +-- end query 30 in stream 0 using template query30.tpl +-- start query 31 in stream 0 using template query31.tpl +with ss as + (select ca_county,d_qoy, d_year,sum(ss_ext_sales_price) as store_sales + from store_sales,date_dim,customer_address + where ss_sold_date_sk = d_date_sk + and ss_addr_sk=ca_address_sk + group by ca_county,d_qoy, d_year), + ws as + (select ca_county,d_qoy, d_year,sum(ws_ext_sales_price) as web_sales + from web_sales,date_dim,customer_address + where ws_sold_date_sk = d_date_sk + and ws_bill_addr_sk=ca_address_sk + group by ca_county,d_qoy, d_year) + select + ss1.ca_county + ,ss1.d_year + ,ws2.web_sales/ws1.web_sales web_q1_q2_increase + ,ss2.store_sales/ss1.store_sales store_q1_q2_increase + ,ws3.web_sales/ws2.web_sales web_q2_q3_increase + ,ss3.store_sales/ss2.store_sales store_q2_q3_increase + from + ss ss1 + ,ss ss2 + ,ss ss3 + ,ws ws1 + ,ws ws2 + ,ws ws3 + where + ss1.d_qoy = 1 + and ss1.d_year = 1999 + and ss1.ca_county = ss2.ca_county + and ss2.d_qoy = 2 + and ss2.d_year = 1999 + and ss2.ca_county = ss3.ca_county + and ss3.d_qoy = 3 + and ss3.d_year = 1999 + and ss1.ca_county = ws1.ca_county + and ws1.d_qoy = 1 + and ws1.d_year = 1999 + and ws1.ca_county = ws2.ca_county + and ws2.d_qoy = 2 + and ws2.d_year = 1999 + and ws1.ca_county = ws3.ca_county + and ws3.d_qoy = 3 + and ws3.d_year =1999 + and case when ws1.web_sales > 0 then ws2.web_sales/ws1.web_sales else null end + > case when ss1.store_sales > 0 then ss2.store_sales/ss1.store_sales else null end + and case when ws2.web_sales > 0 then ws3.web_sales/ws2.web_sales else null end + > case when ss2.store_sales > 0 then ss3.store_sales/ss2.store_sales else null end + order by store_q2_q3_increase; + +-- end query 31 in stream 0 using template query31.tpl +-- start query 32 in stream 0 using template query32.tpl +select sum(cs_ext_discount_amt) as "excess discount amount" +from + catalog_sales + ,item + ,date_dim +where +i_manufact_id = 722 +and i_item_sk = cs_item_sk +and d_date between '2001-03-09' and + (cast('2001-03-09' as date) + 90 days) +and d_date_sk = cs_sold_date_sk +and cs_ext_discount_amt + > ( + select + 1.3 * avg(cs_ext_discount_amt) + from + catalog_sales + ,date_dim + where + cs_item_sk = i_item_sk + and d_date between '2001-03-09' and + (cast('2001-03-09' as date) + 90 days) + and d_date_sk = cs_sold_date_sk + ) +limit 100; + +-- end query 32 in stream 0 using template query32.tpl +-- start query 33 in stream 0 using template query33.tpl +with ss as ( + select + i_manufact_id,sum(ss_ext_sales_price) total_sales + from + store_sales, + date_dim, + customer_address, + item + where + i_manufact_id in (select + i_manufact_id +from + item +where i_category in ('Books')) + and ss_item_sk = i_item_sk + and ss_sold_date_sk = d_date_sk + and d_year = 2001 + and d_moy = 3 + and ss_addr_sk = ca_address_sk + and ca_gmt_offset = -5 + group by i_manufact_id), + cs as ( + select + i_manufact_id,sum(cs_ext_sales_price) total_sales + from + catalog_sales, + date_dim, + customer_address, + item + where + i_manufact_id in (select + i_manufact_id +from + item +where i_category in ('Books')) + and cs_item_sk = i_item_sk + and cs_sold_date_sk = d_date_sk + and d_year = 2001 + and d_moy = 3 + and cs_bill_addr_sk = ca_address_sk + and ca_gmt_offset = -5 + group by i_manufact_id), + ws as ( + select + i_manufact_id,sum(ws_ext_sales_price) total_sales + from + web_sales, + date_dim, + customer_address, + item + where + i_manufact_id in (select + i_manufact_id +from + item +where i_category in ('Books')) + and ws_item_sk = i_item_sk + and ws_sold_date_sk = d_date_sk + and d_year = 2001 + and d_moy = 3 + and ws_bill_addr_sk = ca_address_sk + and ca_gmt_offset = -5 + group by i_manufact_id) + select i_manufact_id ,sum(total_sales) total_sales + from (select * from ss + union all + select * from cs + union all + select * from ws) tmp1 + group by i_manufact_id + order by total_sales +limit 100; + +-- end query 33 in stream 0 using template query33.tpl +-- start query 34 in stream 0 using template query34.tpl +select c_last_name + ,c_first_name + ,c_salutation + ,c_preferred_cust_flag + ,ss_ticket_number + ,cnt from + (select ss_ticket_number + ,ss_customer_sk + ,count(*) cnt + from store_sales,date_dim,store,household_demographics + where store_sales.ss_sold_date_sk = date_dim.d_date_sk + and store_sales.ss_store_sk = store.s_store_sk + and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk + and (date_dim.d_dom between 1 and 3 or date_dim.d_dom between 25 and 28) + and (household_demographics.hd_buy_potential = '1001-5000' or + household_demographics.hd_buy_potential = '0-500') + and household_demographics.hd_vehicle_count > 0 + and (case when household_demographics.hd_vehicle_count > 0 + then household_demographics.hd_dep_count/ household_demographics.hd_vehicle_count + else null + end) > 1.2 + and date_dim.d_year in (2000,2000+1,2000+2) + and store.s_county in ('Williamson County','Williamson County','Williamson County','Williamson County', + 'Williamson County','Williamson County','Williamson County','Williamson County') + group by ss_ticket_number,ss_customer_sk) dn,customer + where ss_customer_sk = c_customer_sk + and cnt between 15 and 20 + order by c_last_name,c_first_name,c_salutation,c_preferred_cust_flag desc, ss_ticket_number; + +-- end query 34 in stream 0 using template query34.tpl +-- start query 35 in stream 0 using template query35.tpl +select + ca_state, + cd_gender, + cd_marital_status, + cd_dep_count, + count(*) cnt1, + avg(cd_dep_count), + stddev_samp(cd_dep_count), + sum(cd_dep_count), + cd_dep_employed_count, + count(*) cnt2, + avg(cd_dep_employed_count), + stddev_samp(cd_dep_employed_count), + sum(cd_dep_employed_count), + cd_dep_college_count, + count(*) cnt3, + avg(cd_dep_college_count), + stddev_samp(cd_dep_college_count), + sum(cd_dep_college_count) + from + customer c,customer_address ca,customer_demographics + where + c.c_current_addr_sk = ca.ca_address_sk and + cd_demo_sk = c.c_current_cdemo_sk and + exists (select * + from store_sales,date_dim + where c.c_customer_sk = ss_customer_sk and + ss_sold_date_sk = d_date_sk and + d_year = 1999 and + d_qoy < 4) and + (exists (select * + from web_sales,date_dim + where c.c_customer_sk = ws_bill_customer_sk and + ws_sold_date_sk = d_date_sk and + d_year = 1999 and + d_qoy < 4) or + exists (select * + from catalog_sales,date_dim + where c.c_customer_sk = cs_ship_customer_sk and + cs_sold_date_sk = d_date_sk and + d_year = 1999 and + d_qoy < 4)) + group by ca_state, + cd_gender, + cd_marital_status, + cd_dep_count, + cd_dep_employed_count, + cd_dep_college_count + order by ca_state, + cd_gender, + cd_marital_status, + cd_dep_count, + cd_dep_employed_count, + cd_dep_college_count + limit 100; + +-- end query 35 in stream 0 using template query35.tpl +-- start query 36 in stream 0 using template query36.tpl +select + sum(ss_net_profit)/sum(ss_ext_sales_price) as gross_margin + ,i_category + ,i_class + ,grouping(i_category)+grouping(i_class) as lochierarchy + ,rank() over ( + partition by grouping(i_category)+grouping(i_class), + case when grouping(i_class) = 0 then i_category end + order by sum(ss_net_profit)/sum(ss_ext_sales_price) asc) as rank_within_parent + from + store_sales + ,date_dim d1 + ,item + ,store + where + d1.d_year = 2000 + and d1.d_date_sk = ss_sold_date_sk + and i_item_sk = ss_item_sk + and s_store_sk = ss_store_sk + and s_state in ('TN','TN','TN','TN', + 'TN','TN','TN','TN') + group by rollup(i_category,i_class) + order by + lochierarchy desc + ,case when lochierarchy = 0 then i_category end + ,rank_within_parent + limit 100; + +-- end query 36 in stream 0 using template query36.tpl +-- start query 37 in stream 0 using template query37.tpl +select i_item_id + ,i_item_desc + ,i_current_price + from item, inventory, date_dim, catalog_sales + where i_current_price between 29 and 29 + 30 + and inv_item_sk = i_item_sk + and d_date_sk=inv_date_sk + and d_date between cast('2002-03-29' as date) and (cast('2002-03-29' as date) + 60 days) + and i_manufact_id in (705,742,777,944) + and inv_quantity_on_hand between 100 and 500 + and cs_item_sk = i_item_sk + group by i_item_id,i_item_desc,i_current_price + order by i_item_id + limit 100; + +-- end query 37 in stream 0 using template query37.tpl +-- start query 38 in stream 0 using template query38.tpl +select count(*) from ( + select distinct c_last_name, c_first_name, d_date + from store_sales, date_dim, customer + where store_sales.ss_sold_date_sk = date_dim.d_date_sk + and store_sales.ss_customer_sk = customer.c_customer_sk + and d_month_seq between 1189 and 1189 + 11 + intersect + select distinct c_last_name, c_first_name, d_date + from catalog_sales, date_dim, customer + where catalog_sales.cs_sold_date_sk = date_dim.d_date_sk + and catalog_sales.cs_bill_customer_sk = customer.c_customer_sk + and d_month_seq between 1189 and 1189 + 11 + intersect + select distinct c_last_name, c_first_name, d_date + from web_sales, date_dim, customer + where web_sales.ws_sold_date_sk = date_dim.d_date_sk + and web_sales.ws_bill_customer_sk = customer.c_customer_sk + and d_month_seq between 1189 and 1189 + 11 +) hot_cust +limit 100; + +-- end query 38 in stream 0 using template query38.tpl +-- start query 39 in stream 0 using template query39.tpl +with inv as +(select w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy + ,stdev,mean, case mean when 0 then null else stdev/mean end cov + from(select w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy + ,stddev_samp(inv_quantity_on_hand) stdev,avg(inv_quantity_on_hand) mean + from inventory + ,item + ,warehouse + ,date_dim + where inv_item_sk = i_item_sk + and inv_warehouse_sk = w_warehouse_sk + and inv_date_sk = d_date_sk + and d_year =2000 + group by w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy) foo + where case mean when 0 then 0 else stdev/mean end > 1) +select inv1.w_warehouse_sk,inv1.i_item_sk,inv1.d_moy,inv1.mean, inv1.cov + ,inv2.w_warehouse_sk,inv2.i_item_sk,inv2.d_moy,inv2.mean, inv2.cov +from inv inv1,inv inv2 +where inv1.i_item_sk = inv2.i_item_sk + and inv1.w_warehouse_sk = inv2.w_warehouse_sk + and inv1.d_moy=1 + and inv2.d_moy=1+1 +order by inv1.w_warehouse_sk,inv1.i_item_sk,inv1.d_moy,inv1.mean,inv1.cov + ,inv2.d_moy,inv2.mean, inv2.cov +; +with inv as +(select w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy + ,stdev,mean, case mean when 0 then null else stdev/mean end cov + from(select w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy + ,stddev_samp(inv_quantity_on_hand) stdev,avg(inv_quantity_on_hand) mean + from inventory + ,item + ,warehouse + ,date_dim + where inv_item_sk = i_item_sk + and inv_warehouse_sk = w_warehouse_sk + and inv_date_sk = d_date_sk + and d_year =2000 + group by w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy) foo + where case mean when 0 then 0 else stdev/mean end > 1) +select inv1.w_warehouse_sk,inv1.i_item_sk,inv1.d_moy,inv1.mean, inv1.cov + ,inv2.w_warehouse_sk,inv2.i_item_sk,inv2.d_moy,inv2.mean, inv2.cov +from inv inv1,inv inv2 +where inv1.i_item_sk = inv2.i_item_sk + and inv1.w_warehouse_sk = inv2.w_warehouse_sk + and inv1.d_moy=1 + and inv2.d_moy=1+1 + and inv1.cov > 1.5 +order by inv1.w_warehouse_sk,inv1.i_item_sk,inv1.d_moy,inv1.mean,inv1.cov + ,inv2.d_moy,inv2.mean, inv2.cov +; + +-- end query 39 in stream 0 using template query39.tpl +-- start query 40 in stream 0 using template query40.tpl +select + w_state + ,i_item_id + ,sum(case when (cast(d_date as date) < cast ('2001-05-02' as date)) + then cs_sales_price - coalesce(cr_refunded_cash,0) else 0 end) as sales_before + ,sum(case when (cast(d_date as date) >= cast ('2001-05-02' as date)) + then cs_sales_price - coalesce(cr_refunded_cash,0) else 0 end) as sales_after + from + catalog_sales left outer join catalog_returns on + (cs_order_number = cr_order_number + and cs_item_sk = cr_item_sk) + ,warehouse + ,item + ,date_dim + where + i_current_price between 0.99 and 1.49 + and i_item_sk = cs_item_sk + and cs_warehouse_sk = w_warehouse_sk + and cs_sold_date_sk = d_date_sk + and d_date between (cast ('2001-05-02' as date) - 30 days) + and (cast ('2001-05-02' as date) + 30 days) + group by + w_state,i_item_id + order by w_state,i_item_id +limit 100; + +-- end query 40 in stream 0 using template query40.tpl +-- start query 41 in stream 0 using template query41.tpl +select distinct(i_product_name) + from item i1 + where i_manufact_id between 704 and 704+40 + and (select count(*) as item_cnt + from item + where (i_manufact = i1.i_manufact and + ((i_category = 'Women' and + (i_color = 'forest' or i_color = 'lime') and + (i_units = 'Pallet' or i_units = 'Pound') and + (i_size = 'economy' or i_size = 'small') + ) or + (i_category = 'Women' and + (i_color = 'navy' or i_color = 'slate') and + (i_units = 'Gross' or i_units = 'Bunch') and + (i_size = 'extra large' or i_size = 'petite') + ) or + (i_category = 'Men' and + (i_color = 'powder' or i_color = 'sky') and + (i_units = 'Dozen' or i_units = 'Lb') and + (i_size = 'N/A' or i_size = 'large') + ) or + (i_category = 'Men' and + (i_color = 'maroon' or i_color = 'smoke') and + (i_units = 'Ounce' or i_units = 'Case') and + (i_size = 'economy' or i_size = 'small') + ))) or + (i_manufact = i1.i_manufact and + ((i_category = 'Women' and + (i_color = 'dark' or i_color = 'aquamarine') and + (i_units = 'Ton' or i_units = 'Tbl') and + (i_size = 'economy' or i_size = 'small') + ) or + (i_category = 'Women' and + (i_color = 'frosted' or i_color = 'plum') and + (i_units = 'Dram' or i_units = 'Box') and + (i_size = 'extra large' or i_size = 'petite') + ) or + (i_category = 'Men' and + (i_color = 'papaya' or i_color = 'peach') and + (i_units = 'Bundle' or i_units = 'Carton') and + (i_size = 'N/A' or i_size = 'large') + ) or + (i_category = 'Men' and + (i_color = 'firebrick' or i_color = 'sienna') and + (i_units = 'Cup' or i_units = 'Each') and + (i_size = 'economy' or i_size = 'small') + )))) > 0 + order by i_product_name + limit 100; + +-- end query 41 in stream 0 using template query41.tpl +-- start query 42 in stream 0 using template query42.tpl +select dt.d_year + ,item.i_category_id + ,item.i_category + ,sum(ss_ext_sales_price) + from date_dim dt + ,store_sales + ,item + where dt.d_date_sk = store_sales.ss_sold_date_sk + and store_sales.ss_item_sk = item.i_item_sk + and item.i_manager_id = 1 + and dt.d_moy=11 + and dt.d_year=1998 + group by dt.d_year + ,item.i_category_id + ,item.i_category + order by sum(ss_ext_sales_price) desc,dt.d_year + ,item.i_category_id + ,item.i_category +limit 100 ; + +-- end query 42 in stream 0 using template query42.tpl +-- start query 43 in stream 0 using template query43.tpl +select s_store_name, s_store_id, + sum(case when (d_day_name='Sunday') then ss_sales_price else null end) sun_sales, + sum(case when (d_day_name='Monday') then ss_sales_price else null end) mon_sales, + sum(case when (d_day_name='Tuesday') then ss_sales_price else null end) tue_sales, + sum(case when (d_day_name='Wednesday') then ss_sales_price else null end) wed_sales, + sum(case when (d_day_name='Thursday') then ss_sales_price else null end) thu_sales, + sum(case when (d_day_name='Friday') then ss_sales_price else null end) fri_sales, + sum(case when (d_day_name='Saturday') then ss_sales_price else null end) sat_sales + from date_dim, store_sales, store + where d_date_sk = ss_sold_date_sk and + s_store_sk = ss_store_sk and + s_gmt_offset = -5 and + d_year = 2000 + group by s_store_name, s_store_id + order by s_store_name, s_store_id,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales + limit 100; + +-- end query 43 in stream 0 using template query43.tpl +-- start query 44 in stream 0 using template query44.tpl +select asceding.rnk, i1.i_product_name best_performing, i2.i_product_name worst_performing +from(select * + from (select item_sk,rank() over (order by rank_col asc) rnk + from (select ss_item_sk item_sk,avg(ss_net_profit) rank_col + from store_sales ss1 + where ss_store_sk = 4 + group by ss_item_sk + having avg(ss_net_profit) > 0.9*(select avg(ss_net_profit) rank_col + from store_sales + where ss_store_sk = 4 + and ss_hdemo_sk is null + group by ss_store_sk))V1)V11 + where rnk < 11) asceding, + (select * + from (select item_sk,rank() over (order by rank_col desc) rnk + from (select ss_item_sk item_sk,avg(ss_net_profit) rank_col + from store_sales ss1 + where ss_store_sk = 4 + group by ss_item_sk + having avg(ss_net_profit) > 0.9*(select avg(ss_net_profit) rank_col + from store_sales + where ss_store_sk = 4 + and ss_hdemo_sk is null + group by ss_store_sk))V2)V21 + where rnk < 11) descending, +item i1, +item i2 +where asceding.rnk = descending.rnk + and i1.i_item_sk=asceding.item_sk + and i2.i_item_sk=descending.item_sk +order by asceding.rnk +limit 100; + +-- end query 44 in stream 0 using template query44.tpl +-- start query 45 in stream 0 using template query45.tpl +select ca_zip, ca_city, sum(ws_sales_price) + from web_sales, customer, customer_address, date_dim, item + where ws_bill_customer_sk = c_customer_sk + and c_current_addr_sk = ca_address_sk + and ws_item_sk = i_item_sk + and ( substr(ca_zip,1,5) in ('85669', '86197','88274','83405','86475', '85392', '85460', '80348', '81792') + or + i_item_id in (select i_item_id + from item + where i_item_sk in (2, 3, 5, 7, 11, 13, 17, 19, 23, 29) + ) + ) + and ws_sold_date_sk = d_date_sk + and d_qoy = 1 and d_year = 2000 + group by ca_zip, ca_city + order by ca_zip, ca_city + limit 100; + +-- end query 45 in stream 0 using template query45.tpl +-- start query 46 in stream 0 using template query46.tpl +select c_last_name + ,c_first_name + ,ca_city + ,bought_city + ,ss_ticket_number + ,amt,profit + from + (select ss_ticket_number + ,ss_customer_sk + ,ca_city bought_city + ,sum(ss_coupon_amt) amt + ,sum(ss_net_profit) profit + from store_sales,date_dim,store,household_demographics,customer_address + where store_sales.ss_sold_date_sk = date_dim.d_date_sk + and store_sales.ss_store_sk = store.s_store_sk + and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk + and store_sales.ss_addr_sk = customer_address.ca_address_sk + and (household_demographics.hd_dep_count = 8 or + household_demographics.hd_vehicle_count= 0) + and date_dim.d_dow in (6,0) + and date_dim.d_year in (2000,2000+1,2000+2) + and store.s_city in ('Midway','Fairview','Fairview','Midway','Fairview') + group by ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city) dn,customer,customer_address current_addr + where ss_customer_sk = c_customer_sk + and customer.c_current_addr_sk = current_addr.ca_address_sk + and current_addr.ca_city <> bought_city + order by c_last_name + ,c_first_name + ,ca_city + ,bought_city + ,ss_ticket_number + limit 100; + +-- end query 46 in stream 0 using template query46.tpl +-- start query 47 in stream 0 using template query47.tpl +with v1 as( + select i_category, i_brand, + s_store_name, s_company_name, + d_year, d_moy, + sum(ss_sales_price) sum_sales, + avg(sum(ss_sales_price)) over + (partition by i_category, i_brand, + s_store_name, s_company_name, d_year) + avg_monthly_sales, + rank() over + (partition by i_category, i_brand, + s_store_name, s_company_name + order by d_year, d_moy) rn + from item, store_sales, date_dim, store + where ss_item_sk = i_item_sk and + ss_sold_date_sk = d_date_sk and + ss_store_sk = s_store_sk and + ( + d_year = 2000 or + ( d_year = 2000-1 and d_moy =12) or + ( d_year = 2000+1 and d_moy =1) + ) + group by i_category, i_brand, + s_store_name, s_company_name, + d_year, d_moy), + v2 as( + select v1.s_store_name, v1.s_company_name + ,v1.d_year + ,v1.avg_monthly_sales + ,v1.sum_sales, v1_lag.sum_sales psum, v1_lead.sum_sales nsum + from v1, v1 v1_lag, v1 v1_lead + where v1.i_category = v1_lag.i_category and + v1.i_category = v1_lead.i_category and + v1.i_brand = v1_lag.i_brand and + v1.i_brand = v1_lead.i_brand and + v1.s_store_name = v1_lag.s_store_name and + v1.s_store_name = v1_lead.s_store_name and + v1.s_company_name = v1_lag.s_company_name and + v1.s_company_name = v1_lead.s_company_name and + v1.rn = v1_lag.rn + 1 and + v1.rn = v1_lead.rn - 1) + select * + from v2 + where d_year = 2000 and + avg_monthly_sales > 0 and + case when avg_monthly_sales > 0 then abs(sum_sales - avg_monthly_sales) / avg_monthly_sales else null end > 0.1 + order by sum_sales - avg_monthly_sales, nsum + limit 100; + +-- end query 47 in stream 0 using template query47.tpl +-- start query 48 in stream 0 using template query48.tpl +select sum (ss_quantity) + from store_sales, store, customer_demographics, customer_address, date_dim + where s_store_sk = ss_store_sk + and ss_sold_date_sk = d_date_sk and d_year = 2001 + and + ( + ( + cd_demo_sk = ss_cdemo_sk + and + cd_marital_status = 'S' + and + cd_education_status = 'Secondary' + and + ss_sales_price between 100.00 and 150.00 + ) + or + ( + cd_demo_sk = ss_cdemo_sk + and + cd_marital_status = 'M' + and + cd_education_status = '2 yr Degree' + and + ss_sales_price between 50.00 and 100.00 + ) + or + ( + cd_demo_sk = ss_cdemo_sk + and + cd_marital_status = 'D' + and + cd_education_status = 'Advanced Degree' + and + ss_sales_price between 150.00 and 200.00 + ) + ) + and + ( + ( + ss_addr_sk = ca_address_sk + and + ca_country = 'United States' + and + ca_state in ('ND', 'NY', 'SD') + and ss_net_profit between 0 and 2000 + ) + or + (ss_addr_sk = ca_address_sk + and + ca_country = 'United States' + and + ca_state in ('MD', 'GA', 'KS') + and ss_net_profit between 150 and 3000 + ) + or + (ss_addr_sk = ca_address_sk + and + ca_country = 'United States' + and + ca_state in ('CO', 'MN', 'NC') + and ss_net_profit between 50 and 25000 + ) + ) +; + +-- end query 48 in stream 0 using template query48.tpl +-- start query 49 in stream 0 using template query49.tpl +select channel, item, return_ratio, return_rank, currency_rank from + (select + 'web' as channel + ,web.item + ,web.return_ratio + ,web.return_rank + ,web.currency_rank + from ( + select + item + ,return_ratio + ,currency_ratio + ,rank() over (order by return_ratio) as return_rank + ,rank() over (order by currency_ratio) as currency_rank + from + ( select ws.ws_item_sk as item + ,(cast(sum(coalesce(wr.wr_return_quantity,0)) as decimal(15,4))/ + cast(sum(coalesce(ws.ws_quantity,0)) as decimal(15,4) )) as return_ratio + ,(cast(sum(coalesce(wr.wr_return_amt,0)) as decimal(15,4))/ + cast(sum(coalesce(ws.ws_net_paid,0)) as decimal(15,4) )) as currency_ratio + from + web_sales ws left outer join web_returns wr + on (ws.ws_order_number = wr.wr_order_number and + ws.ws_item_sk = wr.wr_item_sk) + ,date_dim + where + wr.wr_return_amt > 10000 + and ws.ws_net_profit > 1 + and ws.ws_net_paid > 0 + and ws.ws_quantity > 0 + and ws_sold_date_sk = d_date_sk + and d_year = 1998 + and d_moy = 11 + group by ws.ws_item_sk + ) in_web + ) web + where + ( + web.return_rank <= 10 + or + web.currency_rank <= 10 + ) + union + select + 'catalog' as channel + ,catalog.item + ,catalog.return_ratio + ,catalog.return_rank + ,catalog.currency_rank + from ( + select + item + ,return_ratio + ,currency_ratio + ,rank() over (order by return_ratio) as return_rank + ,rank() over (order by currency_ratio) as currency_rank + from + ( select + cs.cs_item_sk as item + ,(cast(sum(coalesce(cr.cr_return_quantity,0)) as decimal(15,4))/ + cast(sum(coalesce(cs.cs_quantity,0)) as decimal(15,4) )) as return_ratio + ,(cast(sum(coalesce(cr.cr_return_amount,0)) as decimal(15,4))/ + cast(sum(coalesce(cs.cs_net_paid,0)) as decimal(15,4) )) as currency_ratio + from + catalog_sales cs left outer join catalog_returns cr + on (cs.cs_order_number = cr.cr_order_number and + cs.cs_item_sk = cr.cr_item_sk) + ,date_dim + where + cr.cr_return_amount > 10000 + and cs.cs_net_profit > 1 + and cs.cs_net_paid > 0 + and cs.cs_quantity > 0 + and cs_sold_date_sk = d_date_sk + and d_year = 1998 + and d_moy = 11 + group by cs.cs_item_sk + ) in_cat + ) catalog + where + ( + catalog.return_rank <= 10 + or + catalog.currency_rank <=10 + ) + union + select + 'store' as channel + ,store.item + ,store.return_ratio + ,store.return_rank + ,store.currency_rank + from ( + select + item + ,return_ratio + ,currency_ratio + ,rank() over (order by return_ratio) as return_rank + ,rank() over (order by currency_ratio) as currency_rank + from + ( select sts.ss_item_sk as item + ,(cast(sum(coalesce(sr.sr_return_quantity,0)) as decimal(15,4))/cast(sum(coalesce(sts.ss_quantity,0)) as decimal(15,4) )) as return_ratio + ,(cast(sum(coalesce(sr.sr_return_amt,0)) as decimal(15,4))/cast(sum(coalesce(sts.ss_net_paid,0)) as decimal(15,4) )) as currency_ratio + from + store_sales sts left outer join store_returns sr + on (sts.ss_ticket_number = sr.sr_ticket_number and sts.ss_item_sk = sr.sr_item_sk) + ,date_dim + where + sr.sr_return_amt > 10000 + and sts.ss_net_profit > 1 + and sts.ss_net_paid > 0 + and sts.ss_quantity > 0 + and ss_sold_date_sk = d_date_sk + and d_year = 1998 + and d_moy = 11 + group by sts.ss_item_sk + ) in_store + ) store + where ( + store.return_rank <= 10 + or + store.currency_rank <= 10 + ) + ) + order by 1,4,5,2 + limit 100; + +-- end query 49 in stream 0 using template query49.tpl +-- start query 50 in stream 0 using template query50.tpl +select + s_store_name + ,s_company_id + ,s_street_number + ,s_street_name + ,s_street_type + ,s_suite_number + ,s_city + ,s_county + ,s_state + ,s_zip + ,sum(case when (sr_returned_date_sk - ss_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days" + ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 30) and + (sr_returned_date_sk - ss_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days" + ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 60) and + (sr_returned_date_sk - ss_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days" + ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 90) and + (sr_returned_date_sk - ss_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days" + ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 120) then 1 else 0 end) as ">120 days" +from + store_sales + ,store_returns + ,store + ,date_dim d1 + ,date_dim d2 +where + d2.d_year = 2001 +and d2.d_moy = 8 +and ss_ticket_number = sr_ticket_number +and ss_item_sk = sr_item_sk +and ss_sold_date_sk = d1.d_date_sk +and sr_returned_date_sk = d2.d_date_sk +and ss_customer_sk = sr_customer_sk +and ss_store_sk = s_store_sk +group by + s_store_name + ,s_company_id + ,s_street_number + ,s_street_name + ,s_street_type + ,s_suite_number + ,s_city + ,s_county + ,s_state + ,s_zip +order by s_store_name + ,s_company_id + ,s_street_number + ,s_street_name + ,s_street_type + ,s_suite_number + ,s_city + ,s_county + ,s_state + ,s_zip +limit 100; + +-- end query 50 in stream 0 using template query50.tpl +-- start query 51 in stream 0 using template query51.tpl +WITH web_v1 as ( +select + ws_item_sk item_sk, d_date, + sum(sum(ws_sales_price)) + over (partition by ws_item_sk order by d_date rows between unbounded preceding and current row) cume_sales +from web_sales + ,date_dim +where ws_sold_date_sk=d_date_sk + and d_month_seq between 1212 and 1212+11 + and ws_item_sk is not NULL +group by ws_item_sk, d_date), +store_v1 as ( +select + ss_item_sk item_sk, d_date, + sum(sum(ss_sales_price)) + over (partition by ss_item_sk order by d_date rows between unbounded preceding and current row) cume_sales +from store_sales + ,date_dim +where ss_sold_date_sk=d_date_sk + and d_month_seq between 1212 and 1212+11 + and ss_item_sk is not NULL +group by ss_item_sk, d_date) + select * +from (select item_sk + ,d_date + ,web_sales + ,store_sales + ,max(web_sales) + over (partition by item_sk order by d_date rows between unbounded preceding and current row) web_cumulative + ,max(store_sales) + over (partition by item_sk order by d_date rows between unbounded preceding and current row) store_cumulative + from (select case when web.item_sk is not null then web.item_sk else store.item_sk end item_sk + ,case when web.d_date is not null then web.d_date else store.d_date end d_date + ,web.cume_sales web_sales + ,store.cume_sales store_sales + from web_v1 web full outer join store_v1 store on (web.item_sk = store.item_sk + and web.d_date = store.d_date) + )x )y +where web_cumulative > store_cumulative +order by item_sk + ,d_date +limit 100; + +-- end query 51 in stream 0 using template query51.tpl +-- start query 52 in stream 0 using template query52.tpl +select dt.d_year + ,item.i_brand_id brand_id + ,item.i_brand brand + ,sum(ss_ext_sales_price) ext_price + from date_dim dt + ,store_sales + ,item + where dt.d_date_sk = store_sales.ss_sold_date_sk + and store_sales.ss_item_sk = item.i_item_sk + and item.i_manager_id = 1 + and dt.d_moy=12 + and dt.d_year=2000 + group by dt.d_year + ,item.i_brand + ,item.i_brand_id + order by dt.d_year + ,ext_price desc + ,brand_id +limit 100 ; + +-- end query 52 in stream 0 using template query52.tpl +-- start query 53 in stream 0 using template query53.tpl +select * from +(select i_manufact_id, +sum(ss_sales_price) sum_sales, +avg(sum(ss_sales_price)) over (partition by i_manufact_id) avg_quarterly_sales +from item, store_sales, date_dim, store +where ss_item_sk = i_item_sk and +ss_sold_date_sk = d_date_sk and +ss_store_sk = s_store_sk and +d_month_seq in (1186,1186+1,1186+2,1186+3,1186+4,1186+5,1186+6,1186+7,1186+8,1186+9,1186+10,1186+11) and +((i_category in ('Books','Children','Electronics') and +i_class in ('personal','portable','reference','self-help') and +i_brand in ('scholaramalgamalg #14','scholaramalgamalg #7', + 'exportiunivamalg #9','scholaramalgamalg #9')) +or(i_category in ('Women','Music','Men') and +i_class in ('accessories','classical','fragrances','pants') and +i_brand in ('amalgimporto #1','edu packscholar #1','exportiimporto #1', + 'importoamalg #1'))) +group by i_manufact_id, d_qoy ) tmp1 +where case when avg_quarterly_sales > 0 + then abs (sum_sales - avg_quarterly_sales)/ avg_quarterly_sales + else null end > 0.1 +order by avg_quarterly_sales, + sum_sales, + i_manufact_id +limit 100; + +-- end query 53 in stream 0 using template query53.tpl +-- start query 54 in stream 0 using template query54.tpl +with my_customers as ( + select distinct c_customer_sk + , c_current_addr_sk + from + ( select cs_sold_date_sk sold_date_sk, + cs_bill_customer_sk customer_sk, + cs_item_sk item_sk + from catalog_sales + union all + select ws_sold_date_sk sold_date_sk, + ws_bill_customer_sk customer_sk, + ws_item_sk item_sk + from web_sales + ) cs_or_ws_sales, + item, + date_dim, + customer + where sold_date_sk = d_date_sk + and item_sk = i_item_sk + and i_category = 'Music' + and i_class = 'country' + and c_customer_sk = cs_or_ws_sales.customer_sk + and d_moy = 1 + and d_year = 1999 + ) + , my_revenue as ( + select c_customer_sk, + sum(ss_ext_sales_price) as revenue + from my_customers, + store_sales, + customer_address, + store, + date_dim + where c_current_addr_sk = ca_address_sk + and ca_county = s_county + and ca_state = s_state + and ss_sold_date_sk = d_date_sk + and c_customer_sk = ss_customer_sk + and d_month_seq between (select distinct d_month_seq+1 + from date_dim where d_year = 1999 and d_moy = 1) + and (select distinct d_month_seq+3 + from date_dim where d_year = 1999 and d_moy = 1) + group by c_customer_sk + ) + , segments as + (select cast((revenue/50) as int) as segment + from my_revenue + ) + select segment, count(*) as num_customers, segment*50 as segment_base + from segments + group by segment + order by segment, num_customers + limit 100; + +-- end query 54 in stream 0 using template query54.tpl +-- start query 55 in stream 0 using template query55.tpl +select i_brand_id brand_id, i_brand brand, + sum(ss_ext_sales_price) ext_price + from date_dim, store_sales, item + where d_date_sk = ss_sold_date_sk + and ss_item_sk = i_item_sk + and i_manager_id=52 + and d_moy=11 + and d_year=2000 + group by i_brand, i_brand_id + order by ext_price desc, i_brand_id +limit 100 ; + +-- end query 55 in stream 0 using template query55.tpl +-- start query 56 in stream 0 using template query56.tpl +with ss as ( + select i_item_id,sum(ss_ext_sales_price) total_sales + from + store_sales, + date_dim, + customer_address, + item + where i_item_id in (select + i_item_id +from item +where i_color in ('powder','orchid','pink')) + and ss_item_sk = i_item_sk + and ss_sold_date_sk = d_date_sk + and d_year = 2000 + and d_moy = 3 + and ss_addr_sk = ca_address_sk + and ca_gmt_offset = -6 + group by i_item_id), + cs as ( + select i_item_id,sum(cs_ext_sales_price) total_sales + from + catalog_sales, + date_dim, + customer_address, + item + where + i_item_id in (select + i_item_id +from item +where i_color in ('powder','orchid','pink')) + and cs_item_sk = i_item_sk + and cs_sold_date_sk = d_date_sk + and d_year = 2000 + and d_moy = 3 + and cs_bill_addr_sk = ca_address_sk + and ca_gmt_offset = -6 + group by i_item_id), + ws as ( + select i_item_id,sum(ws_ext_sales_price) total_sales + from + web_sales, + date_dim, + customer_address, + item + where + i_item_id in (select + i_item_id +from item +where i_color in ('powder','orchid','pink')) + and ws_item_sk = i_item_sk + and ws_sold_date_sk = d_date_sk + and d_year = 2000 + and d_moy = 3 + and ws_bill_addr_sk = ca_address_sk + and ca_gmt_offset = -6 + group by i_item_id) + select i_item_id ,sum(total_sales) total_sales + from (select * from ss + union all + select * from cs + union all + select * from ws) tmp1 + group by i_item_id + order by total_sales, + i_item_id + limit 100; + +-- end query 56 in stream 0 using template query56.tpl +-- start query 57 in stream 0 using template query57.tpl +with v1 as( + select i_category, i_brand, + cc_name, + d_year, d_moy, + sum(cs_sales_price) sum_sales, + avg(sum(cs_sales_price)) over + (partition by i_category, i_brand, + cc_name, d_year) + avg_monthly_sales, + rank() over + (partition by i_category, i_brand, + cc_name + order by d_year, d_moy) rn + from item, catalog_sales, date_dim, call_center + where cs_item_sk = i_item_sk and + cs_sold_date_sk = d_date_sk and + cc_call_center_sk= cs_call_center_sk and + ( + d_year = 2001 or + ( d_year = 2001-1 and d_moy =12) or + ( d_year = 2001+1 and d_moy =1) + ) + group by i_category, i_brand, + cc_name , d_year, d_moy), + v2 as( + select v1.i_category, v1.i_brand, v1.cc_name + ,v1.d_year + ,v1.avg_monthly_sales + ,v1.sum_sales, v1_lag.sum_sales psum, v1_lead.sum_sales nsum + from v1, v1 v1_lag, v1 v1_lead + where v1.i_category = v1_lag.i_category and + v1.i_category = v1_lead.i_category and + v1.i_brand = v1_lag.i_brand and + v1.i_brand = v1_lead.i_brand and + v1. cc_name = v1_lag. cc_name and + v1. cc_name = v1_lead. cc_name and + v1.rn = v1_lag.rn + 1 and + v1.rn = v1_lead.rn - 1) + select * + from v2 + where d_year = 2001 and + avg_monthly_sales > 0 and + case when avg_monthly_sales > 0 then abs(sum_sales - avg_monthly_sales) / avg_monthly_sales else null end > 0.1 + order by sum_sales - avg_monthly_sales, avg_monthly_sales + limit 100; + +-- end query 57 in stream 0 using template query57.tpl +-- start query 58 in stream 0 using template query58.tpl +with ss_items as + (select i_item_id item_id + ,sum(ss_ext_sales_price) ss_item_rev + from store_sales + ,item + ,date_dim + where ss_item_sk = i_item_sk + and d_date in (select d_date + from date_dim + where d_week_seq = (select d_week_seq + from date_dim + where d_date = '2001-06-16')) + and ss_sold_date_sk = d_date_sk + group by i_item_id), + cs_items as + (select i_item_id item_id + ,sum(cs_ext_sales_price) cs_item_rev + from catalog_sales + ,item + ,date_dim + where cs_item_sk = i_item_sk + and d_date in (select d_date + from date_dim + where d_week_seq = (select d_week_seq + from date_dim + where d_date = '2001-06-16')) + and cs_sold_date_sk = d_date_sk + group by i_item_id), + ws_items as + (select i_item_id item_id + ,sum(ws_ext_sales_price) ws_item_rev + from web_sales + ,item + ,date_dim + where ws_item_sk = i_item_sk + and d_date in (select d_date + from date_dim + where d_week_seq =(select d_week_seq + from date_dim + where d_date = '2001-06-16')) + and ws_sold_date_sk = d_date_sk + group by i_item_id) + select ss_items.item_id + ,ss_item_rev + ,ss_item_rev/((ss_item_rev+cs_item_rev+ws_item_rev)/3) * 100 ss_dev + ,cs_item_rev + ,cs_item_rev/((ss_item_rev+cs_item_rev+ws_item_rev)/3) * 100 cs_dev + ,ws_item_rev + ,ws_item_rev/((ss_item_rev+cs_item_rev+ws_item_rev)/3) * 100 ws_dev + ,(ss_item_rev+cs_item_rev+ws_item_rev)/3 average + from ss_items,cs_items,ws_items + where ss_items.item_id=cs_items.item_id + and ss_items.item_id=ws_items.item_id + and ss_item_rev between 0.9 * cs_item_rev and 1.1 * cs_item_rev + and ss_item_rev between 0.9 * ws_item_rev and 1.1 * ws_item_rev + and cs_item_rev between 0.9 * ss_item_rev and 1.1 * ss_item_rev + and cs_item_rev between 0.9 * ws_item_rev and 1.1 * ws_item_rev + and ws_item_rev between 0.9 * ss_item_rev and 1.1 * ss_item_rev + and ws_item_rev between 0.9 * cs_item_rev and 1.1 * cs_item_rev + order by item_id + ,ss_item_rev + limit 100; + +-- end query 58 in stream 0 using template query58.tpl +-- start query 59 in stream 0 using template query59.tpl +with wss as + (select d_week_seq, + ss_store_sk, + sum(case when (d_day_name='Sunday') then ss_sales_price else null end) sun_sales, + sum(case when (d_day_name='Monday') then ss_sales_price else null end) mon_sales, + sum(case when (d_day_name='Tuesday') then ss_sales_price else null end) tue_sales, + sum(case when (d_day_name='Wednesday') then ss_sales_price else null end) wed_sales, + sum(case when (d_day_name='Thursday') then ss_sales_price else null end) thu_sales, + sum(case when (d_day_name='Friday') then ss_sales_price else null end) fri_sales, + sum(case when (d_day_name='Saturday') then ss_sales_price else null end) sat_sales + from store_sales,date_dim + where d_date_sk = ss_sold_date_sk + group by d_week_seq,ss_store_sk + ) + select s_store_name1,s_store_id1,d_week_seq1 + ,sun_sales1/sun_sales2,mon_sales1/mon_sales2 + ,tue_sales1/tue_sales2,wed_sales1/wed_sales2,thu_sales1/thu_sales2 + ,fri_sales1/fri_sales2,sat_sales1/sat_sales2 + from + (select s_store_name s_store_name1,wss.d_week_seq d_week_seq1 + ,s_store_id s_store_id1,sun_sales sun_sales1 + ,mon_sales mon_sales1,tue_sales tue_sales1 + ,wed_sales wed_sales1,thu_sales thu_sales1 + ,fri_sales fri_sales1,sat_sales sat_sales1 + from wss,store,date_dim d + where d.d_week_seq = wss.d_week_seq and + ss_store_sk = s_store_sk and + d_month_seq between 1195 and 1195 + 11) y, + (select s_store_name s_store_name2,wss.d_week_seq d_week_seq2 + ,s_store_id s_store_id2,sun_sales sun_sales2 + ,mon_sales mon_sales2,tue_sales tue_sales2 + ,wed_sales wed_sales2,thu_sales thu_sales2 + ,fri_sales fri_sales2,sat_sales sat_sales2 + from wss,store,date_dim d + where d.d_week_seq = wss.d_week_seq and + ss_store_sk = s_store_sk and + d_month_seq between 1195+ 12 and 1195 + 23) x + where s_store_id1=s_store_id2 + and d_week_seq1=d_week_seq2-52 + order by s_store_name1,s_store_id1,d_week_seq1 +limit 100; + +-- end query 59 in stream 0 using template query59.tpl +-- start query 60 in stream 0 using template query60.tpl +with ss as ( + select + i_item_id,sum(ss_ext_sales_price) total_sales + from + store_sales, + date_dim, + customer_address, + item + where + i_item_id in (select + i_item_id +from + item +where i_category in ('Jewelry')) + and ss_item_sk = i_item_sk + and ss_sold_date_sk = d_date_sk + and d_year = 2000 + and d_moy = 10 + and ss_addr_sk = ca_address_sk + and ca_gmt_offset = -5 + group by i_item_id), + cs as ( + select + i_item_id,sum(cs_ext_sales_price) total_sales + from + catalog_sales, + date_dim, + customer_address, + item + where + i_item_id in (select + i_item_id +from + item +where i_category in ('Jewelry')) + and cs_item_sk = i_item_sk + and cs_sold_date_sk = d_date_sk + and d_year = 2000 + and d_moy = 10 + and cs_bill_addr_sk = ca_address_sk + and ca_gmt_offset = -5 + group by i_item_id), + ws as ( + select + i_item_id,sum(ws_ext_sales_price) total_sales + from + web_sales, + date_dim, + customer_address, + item + where + i_item_id in (select + i_item_id +from + item +where i_category in ('Jewelry')) + and ws_item_sk = i_item_sk + and ws_sold_date_sk = d_date_sk + and d_year = 2000 + and d_moy = 10 + and ws_bill_addr_sk = ca_address_sk + and ca_gmt_offset = -5 + group by i_item_id) + select + i_item_id +,sum(total_sales) total_sales + from (select * from ss + union all + select * from cs + union all + select * from ws) tmp1 + group by i_item_id + order by i_item_id + ,total_sales + limit 100; + +-- end query 60 in stream 0 using template query60.tpl +-- start query 61 in stream 0 using template query61.tpl +select promotions,total,cast(promotions as decimal(15,4))/cast(total as decimal(15,4))*100 +from + (select sum(ss_ext_sales_price) promotions + from store_sales + ,store + ,promotion + ,date_dim + ,customer + ,customer_address + ,item + where ss_sold_date_sk = d_date_sk + and ss_store_sk = s_store_sk + and ss_promo_sk = p_promo_sk + and ss_customer_sk= c_customer_sk + and ca_address_sk = c_current_addr_sk + and ss_item_sk = i_item_sk + and ca_gmt_offset = -7 + and i_category = 'Home' + and (p_channel_dmail = 'Y' or p_channel_email = 'Y' or p_channel_tv = 'Y') + and s_gmt_offset = -7 + and d_year = 2000 + and d_moy = 12) promotional_sales, + (select sum(ss_ext_sales_price) total + from store_sales + ,store + ,date_dim + ,customer + ,customer_address + ,item + where ss_sold_date_sk = d_date_sk + and ss_store_sk = s_store_sk + and ss_customer_sk= c_customer_sk + and ca_address_sk = c_current_addr_sk + and ss_item_sk = i_item_sk + and ca_gmt_offset = -7 + and i_category = 'Home' + and s_gmt_offset = -7 + and d_year = 2000 + and d_moy = 12) all_sales +order by promotions, total +limit 100; + +-- end query 61 in stream 0 using template query61.tpl +-- start query 62 in stream 0 using template query62.tpl +select + substr(w_warehouse_name,1,20) + ,sm_type + ,web_name + ,sum(case when (ws_ship_date_sk - ws_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days" + ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 30) and + (ws_ship_date_sk - ws_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days" + ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 60) and + (ws_ship_date_sk - ws_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days" + ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 90) and + (ws_ship_date_sk - ws_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days" + ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 120) then 1 else 0 end) as ">120 days" +from + web_sales + ,warehouse + ,ship_mode + ,web_site + ,date_dim +where + d_month_seq between 1223 and 1223 + 11 +and ws_ship_date_sk = d_date_sk +and ws_warehouse_sk = w_warehouse_sk +and ws_ship_mode_sk = sm_ship_mode_sk +and ws_web_site_sk = web_site_sk +group by + substr(w_warehouse_name,1,20) + ,sm_type + ,web_name +order by substr(w_warehouse_name,1,20) + ,sm_type + ,web_name +limit 100; + +-- end query 62 in stream 0 using template query62.tpl +-- start query 63 in stream 0 using template query63.tpl +select * +from (select i_manager_id + ,sum(ss_sales_price) sum_sales + ,avg(sum(ss_sales_price)) over (partition by i_manager_id) avg_monthly_sales + from item + ,store_sales + ,date_dim + ,store + where ss_item_sk = i_item_sk + and ss_sold_date_sk = d_date_sk + and ss_store_sk = s_store_sk + and d_month_seq in (1222,1222+1,1222+2,1222+3,1222+4,1222+5,1222+6,1222+7,1222+8,1222+9,1222+10,1222+11) + and (( i_category in ('Books','Children','Electronics') + and i_class in ('personal','portable','reference','self-help') + and i_brand in ('scholaramalgamalg #14','scholaramalgamalg #7', + 'exportiunivamalg #9','scholaramalgamalg #9')) + or( i_category in ('Women','Music','Men') + and i_class in ('accessories','classical','fragrances','pants') + and i_brand in ('amalgimporto #1','edu packscholar #1','exportiimporto #1', + 'importoamalg #1'))) +group by i_manager_id, d_moy) tmp1 +where case when avg_monthly_sales > 0 then abs (sum_sales - avg_monthly_sales) / avg_monthly_sales else null end > 0.1 +order by i_manager_id + ,avg_monthly_sales + ,sum_sales +limit 100; + +-- end query 63 in stream 0 using template query63.tpl +-- start query 64 in stream 0 using template query64.tpl +with cs_ui as + (select cs_item_sk + ,sum(cs_ext_list_price) as sale,sum(cr_refunded_cash+cr_reversed_charge+cr_store_credit) as refund + from catalog_sales + ,catalog_returns + where cs_item_sk = cr_item_sk + and cs_order_number = cr_order_number + group by cs_item_sk + having sum(cs_ext_list_price)>2*sum(cr_refunded_cash+cr_reversed_charge+cr_store_credit)), +cross_sales as + (select i_product_name product_name + ,i_item_sk item_sk + ,s_store_name store_name + ,s_zip store_zip + ,ad1.ca_street_number b_street_number + ,ad1.ca_street_name b_street_name + ,ad1.ca_city b_city + ,ad1.ca_zip b_zip + ,ad2.ca_street_number c_street_number + ,ad2.ca_street_name c_street_name + ,ad2.ca_city c_city + ,ad2.ca_zip c_zip + ,d1.d_year as syear + ,d2.d_year as fsyear + ,d3.d_year s2year + ,count(*) cnt + ,sum(ss_wholesale_cost) s1 + ,sum(ss_list_price) s2 + ,sum(ss_coupon_amt) s3 + FROM store_sales + ,store_returns + ,cs_ui + ,date_dim d1 + ,date_dim d2 + ,date_dim d3 + ,store + ,customer + ,customer_demographics cd1 + ,customer_demographics cd2 + ,promotion + ,household_demographics hd1 + ,household_demographics hd2 + ,customer_address ad1 + ,customer_address ad2 + ,income_band ib1 + ,income_band ib2 + ,item + WHERE ss_store_sk = s_store_sk AND + ss_sold_date_sk = d1.d_date_sk AND + ss_customer_sk = c_customer_sk AND + ss_cdemo_sk= cd1.cd_demo_sk AND + ss_hdemo_sk = hd1.hd_demo_sk AND + ss_addr_sk = ad1.ca_address_sk and + ss_item_sk = i_item_sk and + ss_item_sk = sr_item_sk and + ss_ticket_number = sr_ticket_number and + ss_item_sk = cs_ui.cs_item_sk and + c_current_cdemo_sk = cd2.cd_demo_sk AND + c_current_hdemo_sk = hd2.hd_demo_sk AND + c_current_addr_sk = ad2.ca_address_sk and + c_first_sales_date_sk = d2.d_date_sk and + c_first_shipto_date_sk = d3.d_date_sk and + ss_promo_sk = p_promo_sk and + hd1.hd_income_band_sk = ib1.ib_income_band_sk and + hd2.hd_income_band_sk = ib2.ib_income_band_sk and + cd1.cd_marital_status <> cd2.cd_marital_status and + i_color in ('orange','lace','lawn','misty','blush','pink') and + i_current_price between 48 and 48 + 10 and + i_current_price between 48 + 1 and 48 + 15 +group by i_product_name + ,i_item_sk + ,s_store_name + ,s_zip + ,ad1.ca_street_number + ,ad1.ca_street_name + ,ad1.ca_city + ,ad1.ca_zip + ,ad2.ca_street_number + ,ad2.ca_street_name + ,ad2.ca_city + ,ad2.ca_zip + ,d1.d_year + ,d2.d_year + ,d3.d_year +) +select cs1.product_name + ,cs1.store_name + ,cs1.store_zip + ,cs1.b_street_number + ,cs1.b_street_name + ,cs1.b_city + ,cs1.b_zip + ,cs1.c_street_number + ,cs1.c_street_name + ,cs1.c_city + ,cs1.c_zip + ,cs1.syear + ,cs1.cnt + ,cs1.s1 as s11 + ,cs1.s2 as s21 + ,cs1.s3 as s31 + ,cs2.s1 as s12 + ,cs2.s2 as s22 + ,cs2.s3 as s32 + ,cs2.syear + ,cs2.cnt +from cross_sales cs1,cross_sales cs2 +where cs1.item_sk=cs2.item_sk and + cs1.syear = 1999 and + cs2.syear = 1999 + 1 and + cs2.cnt <= cs1.cnt and + cs1.store_name = cs2.store_name and + cs1.store_zip = cs2.store_zip +order by cs1.product_name + ,cs1.store_name + ,cs2.cnt + ,cs1.s1 + ,cs2.s1; + +-- end query 64 in stream 0 using template query64.tpl +-- start query 65 in stream 0 using template query65.tpl +select + s_store_name, + i_item_desc, + sc.revenue, + i_current_price, + i_wholesale_cost, + i_brand + from store, item, + (select ss_store_sk, avg(revenue) as ave + from + (select ss_store_sk, ss_item_sk, + sum(ss_sales_price) as revenue + from store_sales, date_dim + where ss_sold_date_sk = d_date_sk and d_month_seq between 1176 and 1176+11 + group by ss_store_sk, ss_item_sk) sa + group by ss_store_sk) sb, + (select ss_store_sk, ss_item_sk, sum(ss_sales_price) as revenue + from store_sales, date_dim + where ss_sold_date_sk = d_date_sk and d_month_seq between 1176 and 1176+11 + group by ss_store_sk, ss_item_sk) sc + where sb.ss_store_sk = sc.ss_store_sk and + sc.revenue <= 0.1 * sb.ave and + s_store_sk = sc.ss_store_sk and + i_item_sk = sc.ss_item_sk + order by s_store_name, i_item_desc +limit 100; + +-- end query 65 in stream 0 using template query65.tpl +-- start query 66 in stream 0 using template query66.tpl +select + w_warehouse_name + ,w_warehouse_sq_ft + ,w_city + ,w_county + ,w_state + ,w_country + ,ship_carriers + ,year + ,sum(jan_sales) as jan_sales + ,sum(feb_sales) as feb_sales + ,sum(mar_sales) as mar_sales + ,sum(apr_sales) as apr_sales + ,sum(may_sales) as may_sales + ,sum(jun_sales) as jun_sales + ,sum(jul_sales) as jul_sales + ,sum(aug_sales) as aug_sales + ,sum(sep_sales) as sep_sales + ,sum(oct_sales) as oct_sales + ,sum(nov_sales) as nov_sales + ,sum(dec_sales) as dec_sales + ,sum(jan_sales/w_warehouse_sq_ft) as jan_sales_per_sq_foot + ,sum(feb_sales/w_warehouse_sq_ft) as feb_sales_per_sq_foot + ,sum(mar_sales/w_warehouse_sq_ft) as mar_sales_per_sq_foot + ,sum(apr_sales/w_warehouse_sq_ft) as apr_sales_per_sq_foot + ,sum(may_sales/w_warehouse_sq_ft) as may_sales_per_sq_foot + ,sum(jun_sales/w_warehouse_sq_ft) as jun_sales_per_sq_foot + ,sum(jul_sales/w_warehouse_sq_ft) as jul_sales_per_sq_foot + ,sum(aug_sales/w_warehouse_sq_ft) as aug_sales_per_sq_foot + ,sum(sep_sales/w_warehouse_sq_ft) as sep_sales_per_sq_foot + ,sum(oct_sales/w_warehouse_sq_ft) as oct_sales_per_sq_foot + ,sum(nov_sales/w_warehouse_sq_ft) as nov_sales_per_sq_foot + ,sum(dec_sales/w_warehouse_sq_ft) as dec_sales_per_sq_foot + ,sum(jan_net) as jan_net + ,sum(feb_net) as feb_net + ,sum(mar_net) as mar_net + ,sum(apr_net) as apr_net + ,sum(may_net) as may_net + ,sum(jun_net) as jun_net + ,sum(jul_net) as jul_net + ,sum(aug_net) as aug_net + ,sum(sep_net) as sep_net + ,sum(oct_net) as oct_net + ,sum(nov_net) as nov_net + ,sum(dec_net) as dec_net + from ( + select + w_warehouse_name + ,w_warehouse_sq_ft + ,w_city + ,w_county + ,w_state + ,w_country + ,'ORIENTAL' || ',' || 'BOXBUNDLES' as ship_carriers + ,d_year as year + ,sum(case when d_moy = 1 + then ws_ext_sales_price* ws_quantity else 0 end) as jan_sales + ,sum(case when d_moy = 2 + then ws_ext_sales_price* ws_quantity else 0 end) as feb_sales + ,sum(case when d_moy = 3 + then ws_ext_sales_price* ws_quantity else 0 end) as mar_sales + ,sum(case when d_moy = 4 + then ws_ext_sales_price* ws_quantity else 0 end) as apr_sales + ,sum(case when d_moy = 5 + then ws_ext_sales_price* ws_quantity else 0 end) as may_sales + ,sum(case when d_moy = 6 + then ws_ext_sales_price* ws_quantity else 0 end) as jun_sales + ,sum(case when d_moy = 7 + then ws_ext_sales_price* ws_quantity else 0 end) as jul_sales + ,sum(case when d_moy = 8 + then ws_ext_sales_price* ws_quantity else 0 end) as aug_sales + ,sum(case when d_moy = 9 + then ws_ext_sales_price* ws_quantity else 0 end) as sep_sales + ,sum(case when d_moy = 10 + then ws_ext_sales_price* ws_quantity else 0 end) as oct_sales + ,sum(case when d_moy = 11 + then ws_ext_sales_price* ws_quantity else 0 end) as nov_sales + ,sum(case when d_moy = 12 + then ws_ext_sales_price* ws_quantity else 0 end) as dec_sales + ,sum(case when d_moy = 1 + then ws_net_paid_inc_ship * ws_quantity else 0 end) as jan_net + ,sum(case when d_moy = 2 + then ws_net_paid_inc_ship * ws_quantity else 0 end) as feb_net + ,sum(case when d_moy = 3 + then ws_net_paid_inc_ship * ws_quantity else 0 end) as mar_net + ,sum(case when d_moy = 4 + then ws_net_paid_inc_ship * ws_quantity else 0 end) as apr_net + ,sum(case when d_moy = 5 + then ws_net_paid_inc_ship * ws_quantity else 0 end) as may_net + ,sum(case when d_moy = 6 + then ws_net_paid_inc_ship * ws_quantity else 0 end) as jun_net + ,sum(case when d_moy = 7 + then ws_net_paid_inc_ship * ws_quantity else 0 end) as jul_net + ,sum(case when d_moy = 8 + then ws_net_paid_inc_ship * ws_quantity else 0 end) as aug_net + ,sum(case when d_moy = 9 + then ws_net_paid_inc_ship * ws_quantity else 0 end) as sep_net + ,sum(case when d_moy = 10 + then ws_net_paid_inc_ship * ws_quantity else 0 end) as oct_net + ,sum(case when d_moy = 11 + then ws_net_paid_inc_ship * ws_quantity else 0 end) as nov_net + ,sum(case when d_moy = 12 + then ws_net_paid_inc_ship * ws_quantity else 0 end) as dec_net + from + web_sales + ,warehouse + ,date_dim + ,time_dim + ,ship_mode + where + ws_warehouse_sk = w_warehouse_sk + and ws_sold_date_sk = d_date_sk + and ws_sold_time_sk = t_time_sk + and ws_ship_mode_sk = sm_ship_mode_sk + and d_year = 2001 + and t_time between 42970 and 42970+28800 + and sm_carrier in ('ORIENTAL','BOXBUNDLES') + group by + w_warehouse_name + ,w_warehouse_sq_ft + ,w_city + ,w_county + ,w_state + ,w_country + ,d_year + union all + select + w_warehouse_name + ,w_warehouse_sq_ft + ,w_city + ,w_county + ,w_state + ,w_country + ,'ORIENTAL' || ',' || 'BOXBUNDLES' as ship_carriers + ,d_year as year + ,sum(case when d_moy = 1 + then cs_ext_list_price* cs_quantity else 0 end) as jan_sales + ,sum(case when d_moy = 2 + then cs_ext_list_price* cs_quantity else 0 end) as feb_sales + ,sum(case when d_moy = 3 + then cs_ext_list_price* cs_quantity else 0 end) as mar_sales + ,sum(case when d_moy = 4 + then cs_ext_list_price* cs_quantity else 0 end) as apr_sales + ,sum(case when d_moy = 5 + then cs_ext_list_price* cs_quantity else 0 end) as may_sales + ,sum(case when d_moy = 6 + then cs_ext_list_price* cs_quantity else 0 end) as jun_sales + ,sum(case when d_moy = 7 + then cs_ext_list_price* cs_quantity else 0 end) as jul_sales + ,sum(case when d_moy = 8 + then cs_ext_list_price* cs_quantity else 0 end) as aug_sales + ,sum(case when d_moy = 9 + then cs_ext_list_price* cs_quantity else 0 end) as sep_sales + ,sum(case when d_moy = 10 + then cs_ext_list_price* cs_quantity else 0 end) as oct_sales + ,sum(case when d_moy = 11 + then cs_ext_list_price* cs_quantity else 0 end) as nov_sales + ,sum(case when d_moy = 12 + then cs_ext_list_price* cs_quantity else 0 end) as dec_sales + ,sum(case when d_moy = 1 + then cs_net_paid * cs_quantity else 0 end) as jan_net + ,sum(case when d_moy = 2 + then cs_net_paid * cs_quantity else 0 end) as feb_net + ,sum(case when d_moy = 3 + then cs_net_paid * cs_quantity else 0 end) as mar_net + ,sum(case when d_moy = 4 + then cs_net_paid * cs_quantity else 0 end) as apr_net + ,sum(case when d_moy = 5 + then cs_net_paid * cs_quantity else 0 end) as may_net + ,sum(case when d_moy = 6 + then cs_net_paid * cs_quantity else 0 end) as jun_net + ,sum(case when d_moy = 7 + then cs_net_paid * cs_quantity else 0 end) as jul_net + ,sum(case when d_moy = 8 + then cs_net_paid * cs_quantity else 0 end) as aug_net + ,sum(case when d_moy = 9 + then cs_net_paid * cs_quantity else 0 end) as sep_net + ,sum(case when d_moy = 10 + then cs_net_paid * cs_quantity else 0 end) as oct_net + ,sum(case when d_moy = 11 + then cs_net_paid * cs_quantity else 0 end) as nov_net + ,sum(case when d_moy = 12 + then cs_net_paid * cs_quantity else 0 end) as dec_net + from + catalog_sales + ,warehouse + ,date_dim + ,time_dim + ,ship_mode + where + cs_warehouse_sk = w_warehouse_sk + and cs_sold_date_sk = d_date_sk + and cs_sold_time_sk = t_time_sk + and cs_ship_mode_sk = sm_ship_mode_sk + and d_year = 2001 + and t_time between 42970 AND 42970+28800 + and sm_carrier in ('ORIENTAL','BOXBUNDLES') + group by + w_warehouse_name + ,w_warehouse_sq_ft + ,w_city + ,w_county + ,w_state + ,w_country + ,d_year + ) x + group by + w_warehouse_name + ,w_warehouse_sq_ft + ,w_city + ,w_county + ,w_state + ,w_country + ,ship_carriers + ,year + order by w_warehouse_name + limit 100; + +-- end query 66 in stream 0 using template query66.tpl +-- start query 67 in stream 0 using template query67.tpl +select * +from (select i_category + ,i_class + ,i_brand + ,i_product_name + ,d_year + ,d_qoy + ,d_moy + ,s_store_id + ,sumsales + ,rank() over (partition by i_category order by sumsales desc) rk + from (select i_category + ,i_class + ,i_brand + ,i_product_name + ,d_year + ,d_qoy + ,d_moy + ,s_store_id + ,sum(coalesce(ss_sales_price*ss_quantity,0)) sumsales + from store_sales + ,date_dim + ,store + ,item + where ss_sold_date_sk=d_date_sk + and ss_item_sk=i_item_sk + and ss_store_sk = s_store_sk + and d_month_seq between 1217 and 1217+11 + group by rollup(i_category, i_class, i_brand, i_product_name, d_year, d_qoy, d_moy,s_store_id))dw1) dw2 +where rk <= 100 +order by i_category + ,i_class + ,i_brand + ,i_product_name + ,d_year + ,d_qoy + ,d_moy + ,s_store_id + ,sumsales + ,rk +limit 100; + +-- end query 67 in stream 0 using template query67.tpl +-- start query 68 in stream 0 using template query68.tpl +select c_last_name + ,c_first_name + ,ca_city + ,bought_city + ,ss_ticket_number + ,extended_price + ,extended_tax + ,list_price + from (select ss_ticket_number + ,ss_customer_sk + ,ca_city bought_city + ,sum(ss_ext_sales_price) extended_price + ,sum(ss_ext_list_price) list_price + ,sum(ss_ext_tax) extended_tax + from store_sales + ,date_dim + ,store + ,household_demographics + ,customer_address + where store_sales.ss_sold_date_sk = date_dim.d_date_sk + and store_sales.ss_store_sk = store.s_store_sk + and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk + and store_sales.ss_addr_sk = customer_address.ca_address_sk + and date_dim.d_dom between 1 and 2 + and (household_demographics.hd_dep_count = 3 or + household_demographics.hd_vehicle_count= 4) + and date_dim.d_year in (1998,1998+1,1998+2) + and store.s_city in ('Fairview','Midway') + group by ss_ticket_number + ,ss_customer_sk + ,ss_addr_sk,ca_city) dn + ,customer + ,customer_address current_addr + where ss_customer_sk = c_customer_sk + and customer.c_current_addr_sk = current_addr.ca_address_sk + and current_addr.ca_city <> bought_city + order by c_last_name + ,ss_ticket_number + limit 100; + +-- end query 68 in stream 0 using template query68.tpl +-- start query 69 in stream 0 using template query69.tpl +select + cd_gender, + cd_marital_status, + cd_education_status, + count(*) cnt1, + cd_purchase_estimate, + count(*) cnt2, + cd_credit_rating, + count(*) cnt3 + from + customer c,customer_address ca,customer_demographics + where + c.c_current_addr_sk = ca.ca_address_sk and + ca_state in ('IL','TX','ME') and + cd_demo_sk = c.c_current_cdemo_sk and + exists (select * + from store_sales,date_dim + where c.c_customer_sk = ss_customer_sk and + ss_sold_date_sk = d_date_sk and + d_year = 2002 and + d_moy between 1 and 1+2) and + (not exists (select * + from web_sales,date_dim + where c.c_customer_sk = ws_bill_customer_sk and + ws_sold_date_sk = d_date_sk and + d_year = 2002 and + d_moy between 1 and 1+2) and + not exists (select * + from catalog_sales,date_dim + where c.c_customer_sk = cs_ship_customer_sk and + cs_sold_date_sk = d_date_sk and + d_year = 2002 and + d_moy between 1 and 1+2)) + group by cd_gender, + cd_marital_status, + cd_education_status, + cd_purchase_estimate, + cd_credit_rating + order by cd_gender, + cd_marital_status, + cd_education_status, + cd_purchase_estimate, + cd_credit_rating + limit 100; + +-- end query 69 in stream 0 using template query69.tpl +-- start query 70 in stream 0 using template query70.tpl +select + sum(ss_net_profit) as total_sum + ,s_state + ,s_county + ,grouping(s_state)+grouping(s_county) as lochierarchy + ,rank() over ( + partition by grouping(s_state)+grouping(s_county), + case when grouping(s_county) = 0 then s_state end + order by sum(ss_net_profit) desc) as rank_within_parent + from + store_sales + ,date_dim d1 + ,store + where + d1.d_month_seq between 1220 and 1220+11 + and d1.d_date_sk = ss_sold_date_sk + and s_store_sk = ss_store_sk + and s_state in + ( select s_state + from (select s_state as s_state, + rank() over ( partition by s_state order by sum(ss_net_profit) desc) as ranking + from store_sales, store, date_dim + where d_month_seq between 1220 and 1220+11 + and d_date_sk = ss_sold_date_sk + and s_store_sk = ss_store_sk + group by s_state + ) tmp1 + where ranking <= 5 + ) + group by rollup(s_state,s_county) + order by + lochierarchy desc + ,case when lochierarchy = 0 then s_state end + ,rank_within_parent + limit 100; + +-- end query 70 in stream 0 using template query70.tpl +-- start query 71 in stream 0 using template query71.tpl +select i_brand_id brand_id, i_brand brand,t_hour,t_minute, + sum(ext_price) ext_price + from item, (select ws_ext_sales_price as ext_price, + ws_sold_date_sk as sold_date_sk, + ws_item_sk as sold_item_sk, + ws_sold_time_sk as time_sk + from web_sales,date_dim + where d_date_sk = ws_sold_date_sk + and d_moy=12 + and d_year=2002 + union all + select cs_ext_sales_price as ext_price, + cs_sold_date_sk as sold_date_sk, + cs_item_sk as sold_item_sk, + cs_sold_time_sk as time_sk + from catalog_sales,date_dim + where d_date_sk = cs_sold_date_sk + and d_moy=12 + and d_year=2002 + union all + select ss_ext_sales_price as ext_price, + ss_sold_date_sk as sold_date_sk, + ss_item_sk as sold_item_sk, + ss_sold_time_sk as time_sk + from store_sales,date_dim + where d_date_sk = ss_sold_date_sk + and d_moy=12 + and d_year=2002 + ) tmp,time_dim + where + sold_item_sk = i_item_sk + and i_manager_id=1 + and time_sk = t_time_sk + and (t_meal_time = 'breakfast' or t_meal_time = 'dinner') + group by i_brand, i_brand_id,t_hour,t_minute + order by ext_price desc, i_brand_id + ; + +-- end query 71 in stream 0 using template query71.tpl +-- start query 72 in stream 0 using template query72.tpl +select i_item_desc + ,w_warehouse_name + ,d1.d_week_seq + ,sum(case when p_promo_sk is null then 1 else 0 end) no_promo + ,sum(case when p_promo_sk is not null then 1 else 0 end) promo + ,count(*) total_cnt +from catalog_sales +join inventory on (cs_item_sk = inv_item_sk) +join warehouse on (w_warehouse_sk=inv_warehouse_sk) +join item on (i_item_sk = cs_item_sk) +join customer_demographics on (cs_bill_cdemo_sk = cd_demo_sk) +join household_demographics on (cs_bill_hdemo_sk = hd_demo_sk) +join date_dim d1 on (cs_sold_date_sk = d1.d_date_sk) +join date_dim d2 on (inv_date_sk = d2.d_date_sk) +join date_dim d3 on (cs_ship_date_sk = d3.d_date_sk) +left outer join promotion on (cs_promo_sk=p_promo_sk) +left outer join catalog_returns on (cr_item_sk = cs_item_sk and cr_order_number = cs_order_number) +where d1.d_week_seq = d2.d_week_seq + and inv_quantity_on_hand < cs_quantity + and d3.d_date > d1.d_date + 5 + and hd_buy_potential = '1001-5000' + and d1.d_year = 1998 + and cd_marital_status = 'S' +group by i_item_desc,w_warehouse_name,d1.d_week_seq +order by total_cnt desc, i_item_desc, w_warehouse_name, d_week_seq +limit 100; + +-- end query 72 in stream 0 using template query72.tpl +-- start query 73 in stream 0 using template query73.tpl +select c_last_name + ,c_first_name + ,c_salutation + ,c_preferred_cust_flag + ,ss_ticket_number + ,cnt from + (select ss_ticket_number + ,ss_customer_sk + ,count(*) cnt + from store_sales,date_dim,store,household_demographics + where store_sales.ss_sold_date_sk = date_dim.d_date_sk + and store_sales.ss_store_sk = store.s_store_sk + and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk + and date_dim.d_dom between 1 and 2 + and (household_demographics.hd_buy_potential = '1001-5000' or + household_demographics.hd_buy_potential = '5001-10000') + and household_demographics.hd_vehicle_count > 0 + and case when household_demographics.hd_vehicle_count > 0 then + household_demographics.hd_dep_count/ household_demographics.hd_vehicle_count else null end > 1 + and date_dim.d_year in (2000,2000+1,2000+2) + and store.s_county in ('Williamson County','Williamson County','Williamson County','Williamson County') + group by ss_ticket_number,ss_customer_sk) dj,customer + where ss_customer_sk = c_customer_sk + and cnt between 1 and 5 + order by cnt desc, c_last_name asc; + +-- end query 73 in stream 0 using template query73.tpl +-- start query 74 in stream 0 using template query74.tpl +with year_total as ( + select c_customer_id customer_id + ,c_first_name customer_first_name + ,c_last_name customer_last_name + ,d_year as year + ,max(ss_net_paid) year_total + ,'s' sale_type + from customer + ,store_sales + ,date_dim + where c_customer_sk = ss_customer_sk + and ss_sold_date_sk = d_date_sk + and d_year in (1999,1999+1) + group by c_customer_id + ,c_first_name + ,c_last_name + ,d_year + union all + select c_customer_id customer_id + ,c_first_name customer_first_name + ,c_last_name customer_last_name + ,d_year as year + ,max(ws_net_paid) year_total + ,'w' sale_type + from customer + ,web_sales + ,date_dim + where c_customer_sk = ws_bill_customer_sk + and ws_sold_date_sk = d_date_sk + and d_year in (1999,1999+1) + group by c_customer_id + ,c_first_name + ,c_last_name + ,d_year + ) + select + t_s_secyear.customer_id, t_s_secyear.customer_first_name, t_s_secyear.customer_last_name + from year_total t_s_firstyear + ,year_total t_s_secyear + ,year_total t_w_firstyear + ,year_total t_w_secyear + where t_s_secyear.customer_id = t_s_firstyear.customer_id + and t_s_firstyear.customer_id = t_w_secyear.customer_id + and t_s_firstyear.customer_id = t_w_firstyear.customer_id + and t_s_firstyear.sale_type = 's' + and t_w_firstyear.sale_type = 'w' + and t_s_secyear.sale_type = 's' + and t_w_secyear.sale_type = 'w' + and t_s_firstyear.year = 1999 + and t_s_secyear.year = 1999+1 + and t_w_firstyear.year = 1999 + and t_w_secyear.year = 1999+1 + and t_s_firstyear.year_total > 0 + and t_w_firstyear.year_total > 0 + and case when t_w_firstyear.year_total > 0 then t_w_secyear.year_total / t_w_firstyear.year_total else null end + > case when t_s_firstyear.year_total > 0 then t_s_secyear.year_total / t_s_firstyear.year_total else null end + order by 1,3,2 +limit 100; + +-- end query 74 in stream 0 using template query74.tpl +-- start query 75 in stream 0 using template query75.tpl +WITH all_sales AS ( + SELECT d_year + ,i_brand_id + ,i_class_id + ,i_category_id + ,i_manufact_id + ,SUM(sales_cnt) AS sales_cnt + ,SUM(sales_amt) AS sales_amt + FROM (SELECT d_year + ,i_brand_id + ,i_class_id + ,i_category_id + ,i_manufact_id + ,cs_quantity - COALESCE(cr_return_quantity,0) AS sales_cnt + ,cs_ext_sales_price - COALESCE(cr_return_amount,0.0) AS sales_amt + FROM catalog_sales JOIN item ON i_item_sk=cs_item_sk + JOIN date_dim ON d_date_sk=cs_sold_date_sk + LEFT JOIN catalog_returns ON (cs_order_number=cr_order_number + AND cs_item_sk=cr_item_sk) + WHERE i_category='Sports' + UNION + SELECT d_year + ,i_brand_id + ,i_class_id + ,i_category_id + ,i_manufact_id + ,ss_quantity - COALESCE(sr_return_quantity,0) AS sales_cnt + ,ss_ext_sales_price - COALESCE(sr_return_amt,0.0) AS sales_amt + FROM store_sales JOIN item ON i_item_sk=ss_item_sk + JOIN date_dim ON d_date_sk=ss_sold_date_sk + LEFT JOIN store_returns ON (ss_ticket_number=sr_ticket_number + AND ss_item_sk=sr_item_sk) + WHERE i_category='Sports' + UNION + SELECT d_year + ,i_brand_id + ,i_class_id + ,i_category_id + ,i_manufact_id + ,ws_quantity - COALESCE(wr_return_quantity,0) AS sales_cnt + ,ws_ext_sales_price - COALESCE(wr_return_amt,0.0) AS sales_amt + FROM web_sales JOIN item ON i_item_sk=ws_item_sk + JOIN date_dim ON d_date_sk=ws_sold_date_sk + LEFT JOIN web_returns ON (ws_order_number=wr_order_number + AND ws_item_sk=wr_item_sk) + WHERE i_category='Sports') sales_detail + GROUP BY d_year, i_brand_id, i_class_id, i_category_id, i_manufact_id) + SELECT prev_yr.d_year AS prev_year + ,curr_yr.d_year AS year + ,curr_yr.i_brand_id + ,curr_yr.i_class_id + ,curr_yr.i_category_id + ,curr_yr.i_manufact_id + ,prev_yr.sales_cnt AS prev_yr_cnt + ,curr_yr.sales_cnt AS curr_yr_cnt + ,curr_yr.sales_cnt-prev_yr.sales_cnt AS sales_cnt_diff + ,curr_yr.sales_amt-prev_yr.sales_amt AS sales_amt_diff + FROM all_sales curr_yr, all_sales prev_yr + WHERE curr_yr.i_brand_id=prev_yr.i_brand_id + AND curr_yr.i_class_id=prev_yr.i_class_id + AND curr_yr.i_category_id=prev_yr.i_category_id + AND curr_yr.i_manufact_id=prev_yr.i_manufact_id + AND curr_yr.d_year=2002 + AND prev_yr.d_year=2002-1 + AND CAST(curr_yr.sales_cnt AS DECIMAL(17,2))/CAST(prev_yr.sales_cnt AS DECIMAL(17,2))<0.9 + ORDER BY sales_cnt_diff,sales_amt_diff + limit 100; + +-- end query 75 in stream 0 using template query75.tpl +-- start query 76 in stream 0 using template query76.tpl +select channel, col_name, d_year, d_qoy, i_category, COUNT(*) sales_cnt, SUM(ext_sales_price) sales_amt FROM ( + SELECT 'store' as channel, 'ss_customer_sk' col_name, d_year, d_qoy, i_category, ss_ext_sales_price ext_sales_price + FROM store_sales, item, date_dim + WHERE ss_customer_sk IS NULL + AND ss_sold_date_sk=d_date_sk + AND ss_item_sk=i_item_sk + UNION ALL + SELECT 'web' as channel, 'ws_promo_sk' col_name, d_year, d_qoy, i_category, ws_ext_sales_price ext_sales_price + FROM web_sales, item, date_dim + WHERE ws_promo_sk IS NULL + AND ws_sold_date_sk=d_date_sk + AND ws_item_sk=i_item_sk + UNION ALL + SELECT 'catalog' as channel, 'cs_bill_customer_sk' col_name, d_year, d_qoy, i_category, cs_ext_sales_price ext_sales_price + FROM catalog_sales, item, date_dim + WHERE cs_bill_customer_sk IS NULL + AND cs_sold_date_sk=d_date_sk + AND cs_item_sk=i_item_sk) foo +GROUP BY channel, col_name, d_year, d_qoy, i_category +ORDER BY channel, col_name, d_year, d_qoy, i_category +limit 100; + +-- end query 76 in stream 0 using template query76.tpl +-- start query 77 in stream 0 using template query77.tpl +with ss as + (select s_store_sk, + sum(ss_ext_sales_price) as sales, + sum(ss_net_profit) as profit + from store_sales, + date_dim, + store + where ss_sold_date_sk = d_date_sk + and d_date between cast('2000-08-10' as date) + and (cast('2000-08-10' as date) + 30 days) + and ss_store_sk = s_store_sk + group by s_store_sk) + , + sr as + (select s_store_sk, + sum(sr_return_amt) as returns, + sum(sr_net_loss) as profit_loss + from store_returns, + date_dim, + store + where sr_returned_date_sk = d_date_sk + and d_date between cast('2000-08-10' as date) + and (cast('2000-08-10' as date) + 30 days) + and sr_store_sk = s_store_sk + group by s_store_sk), + cs as + (select cs_call_center_sk, + sum(cs_ext_sales_price) as sales, + sum(cs_net_profit) as profit + from catalog_sales, + date_dim + where cs_sold_date_sk = d_date_sk + and d_date between cast('2000-08-10' as date) + and (cast('2000-08-10' as date) + 30 days) + group by cs_call_center_sk + ), + cr as + (select cr_call_center_sk, + sum(cr_return_amount) as returns, + sum(cr_net_loss) as profit_loss + from catalog_returns, + date_dim + where cr_returned_date_sk = d_date_sk + and d_date between cast('2000-08-10' as date) + and (cast('2000-08-10' as date) + 30 days) + group by cr_call_center_sk + ), + ws as + ( select wp_web_page_sk, + sum(ws_ext_sales_price) as sales, + sum(ws_net_profit) as profit + from web_sales, + date_dim, + web_page + where ws_sold_date_sk = d_date_sk + and d_date between cast('2000-08-10' as date) + and (cast('2000-08-10' as date) + 30 days) + and ws_web_page_sk = wp_web_page_sk + group by wp_web_page_sk), + wr as + (select wp_web_page_sk, + sum(wr_return_amt) as returns, + sum(wr_net_loss) as profit_loss + from web_returns, + date_dim, + web_page + where wr_returned_date_sk = d_date_sk + and d_date between cast('2000-08-10' as date) + and (cast('2000-08-10' as date) + 30 days) + and wr_web_page_sk = wp_web_page_sk + group by wp_web_page_sk) + select channel + , id + , sum(sales) as sales + , sum(returns) as returns + , sum(profit) as profit + from + (select 'store channel' as channel + , ss.s_store_sk as id + , sales + , coalesce(returns, 0) as returns + , (profit - coalesce(profit_loss,0)) as profit + from ss left join sr + on ss.s_store_sk = sr.s_store_sk + union all + select 'catalog channel' as channel + , cs_call_center_sk as id + , sales + , returns + , (profit - profit_loss) as profit + from cs + , cr + union all + select 'web channel' as channel + , ws.wp_web_page_sk as id + , sales + , coalesce(returns, 0) returns + , (profit - coalesce(profit_loss,0)) as profit + from ws left join wr + on ws.wp_web_page_sk = wr.wp_web_page_sk + ) x + group by rollup (channel, id) + order by channel + ,id + limit 100; + +-- end query 77 in stream 0 using template query77.tpl +-- start query 78 in stream 0 using template query78.tpl +with ws as + (select d_year AS ws_sold_year, ws_item_sk, + ws_bill_customer_sk ws_customer_sk, + sum(ws_quantity) ws_qty, + sum(ws_wholesale_cost) ws_wc, + sum(ws_sales_price) ws_sp + from web_sales + left join web_returns on wr_order_number=ws_order_number and ws_item_sk=wr_item_sk + join date_dim on ws_sold_date_sk = d_date_sk + where wr_order_number is null + group by d_year, ws_item_sk, ws_bill_customer_sk + ), +cs as + (select d_year AS cs_sold_year, cs_item_sk, + cs_bill_customer_sk cs_customer_sk, + sum(cs_quantity) cs_qty, + sum(cs_wholesale_cost) cs_wc, + sum(cs_sales_price) cs_sp + from catalog_sales + left join catalog_returns on cr_order_number=cs_order_number and cs_item_sk=cr_item_sk + join date_dim on cs_sold_date_sk = d_date_sk + where cr_order_number is null + group by d_year, cs_item_sk, cs_bill_customer_sk + ), +ss as + (select d_year AS ss_sold_year, ss_item_sk, + ss_customer_sk, + sum(ss_quantity) ss_qty, + sum(ss_wholesale_cost) ss_wc, + sum(ss_sales_price) ss_sp + from store_sales + left join store_returns on sr_ticket_number=ss_ticket_number and ss_item_sk=sr_item_sk + join date_dim on ss_sold_date_sk = d_date_sk + where sr_ticket_number is null + group by d_year, ss_item_sk, ss_customer_sk + ) + select +ss_customer_sk, +round(ss_qty/(coalesce(ws_qty,0)+coalesce(cs_qty,0)),2) ratio, +ss_qty store_qty, ss_wc store_wholesale_cost, ss_sp store_sales_price, +coalesce(ws_qty,0)+coalesce(cs_qty,0) other_chan_qty, +coalesce(ws_wc,0)+coalesce(cs_wc,0) other_chan_wholesale_cost, +coalesce(ws_sp,0)+coalesce(cs_sp,0) other_chan_sales_price +from ss +left join ws on (ws_sold_year=ss_sold_year and ws_item_sk=ss_item_sk and ws_customer_sk=ss_customer_sk) +left join cs on (cs_sold_year=ss_sold_year and cs_item_sk=ss_item_sk and cs_customer_sk=ss_customer_sk) +where (coalesce(ws_qty,0)>0 or coalesce(cs_qty, 0)>0) and ss_sold_year=1998 +order by + ss_customer_sk, + ss_qty desc, ss_wc desc, ss_sp desc, + other_chan_qty, + other_chan_wholesale_cost, + other_chan_sales_price, + ratio +limit 100; + +-- end query 78 in stream 0 using template query78.tpl +-- start query 79 in stream 0 using template query79.tpl +select + c_last_name,c_first_name,substr(s_city,1,30),ss_ticket_number,amt,profit + from + (select ss_ticket_number + ,ss_customer_sk + ,store.s_city + ,sum(ss_coupon_amt) amt + ,sum(ss_net_profit) profit + from store_sales,date_dim,store,household_demographics + where store_sales.ss_sold_date_sk = date_dim.d_date_sk + and store_sales.ss_store_sk = store.s_store_sk + and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk + and (household_demographics.hd_dep_count = 7 or household_demographics.hd_vehicle_count > -1) + and date_dim.d_dow = 1 + and date_dim.d_year in (2000,2000+1,2000+2) + and store.s_number_employees between 200 and 295 + group by ss_ticket_number,ss_customer_sk,ss_addr_sk,store.s_city) ms,customer + where ss_customer_sk = c_customer_sk + order by c_last_name,c_first_name,substr(s_city,1,30), profit +limit 100; + +-- end query 79 in stream 0 using template query79.tpl +-- start query 80 in stream 0 using template query80.tpl +with ssr as + (select s_store_id as store_id, + sum(ss_ext_sales_price) as sales, + sum(coalesce(sr_return_amt, 0)) as returns, + sum(ss_net_profit - coalesce(sr_net_loss, 0)) as profit + from store_sales left outer join store_returns on + (ss_item_sk = sr_item_sk and ss_ticket_number = sr_ticket_number), + date_dim, + store, + item, + promotion + where ss_sold_date_sk = d_date_sk + and d_date between cast('2002-08-14' as date) + and (cast('2002-08-14' as date) + 30 days) + and ss_store_sk = s_store_sk + and ss_item_sk = i_item_sk + and i_current_price > 50 + and ss_promo_sk = p_promo_sk + and p_channel_tv = 'N' + group by s_store_id) + , + csr as + (select cp_catalog_page_id as catalog_page_id, + sum(cs_ext_sales_price) as sales, + sum(coalesce(cr_return_amount, 0)) as returns, + sum(cs_net_profit - coalesce(cr_net_loss, 0)) as profit + from catalog_sales left outer join catalog_returns on + (cs_item_sk = cr_item_sk and cs_order_number = cr_order_number), + date_dim, + catalog_page, + item, + promotion + where cs_sold_date_sk = d_date_sk + and d_date between cast('2002-08-14' as date) + and (cast('2002-08-14' as date) + 30 days) + and cs_catalog_page_sk = cp_catalog_page_sk + and cs_item_sk = i_item_sk + and i_current_price > 50 + and cs_promo_sk = p_promo_sk + and p_channel_tv = 'N' +group by cp_catalog_page_id) + , + wsr as + (select web_site_id, + sum(ws_ext_sales_price) as sales, + sum(coalesce(wr_return_amt, 0)) as returns, + sum(ws_net_profit - coalesce(wr_net_loss, 0)) as profit + from web_sales left outer join web_returns on + (ws_item_sk = wr_item_sk and ws_order_number = wr_order_number), + date_dim, + web_site, + item, + promotion + where ws_sold_date_sk = d_date_sk + and d_date between cast('2002-08-14' as date) + and (cast('2002-08-14' as date) + 30 days) + and ws_web_site_sk = web_site_sk + and ws_item_sk = i_item_sk + and i_current_price > 50 + and ws_promo_sk = p_promo_sk + and p_channel_tv = 'N' +group by web_site_id) + select channel + , id + , sum(sales) as sales + , sum(returns) as returns + , sum(profit) as profit + from + (select 'store channel' as channel + , 'store' || store_id as id + , sales + , returns + , profit + from ssr + union all + select 'catalog channel' as channel + , 'catalog_page' || catalog_page_id as id + , sales + , returns + , profit + from csr + union all + select 'web channel' as channel + , 'web_site' || web_site_id as id + , sales + , returns + , profit + from wsr + ) x + group by rollup (channel, id) + order by channel + ,id + limit 100; + +-- end query 80 in stream 0 using template query80.tpl +-- start query 81 in stream 0 using template query81.tpl +with customer_total_return as + (select cr_returning_customer_sk as ctr_customer_sk + ,ca_state as ctr_state, + sum(cr_return_amt_inc_tax) as ctr_total_return + from catalog_returns + ,date_dim + ,customer_address + where cr_returned_date_sk = d_date_sk + and d_year =2001 + and cr_returning_addr_sk = ca_address_sk + group by cr_returning_customer_sk + ,ca_state ) + select c_customer_id,c_salutation,c_first_name,c_last_name,ca_street_number,ca_street_name + ,ca_street_type,ca_suite_number,ca_city,ca_county,ca_state,ca_zip,ca_country,ca_gmt_offset + ,ca_location_type,ctr_total_return + from customer_total_return ctr1 + ,customer_address + ,customer + where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2 + from customer_total_return ctr2 + where ctr1.ctr_state = ctr2.ctr_state) + and ca_address_sk = c_current_addr_sk + and ca_state = 'TN' + and ctr1.ctr_customer_sk = c_customer_sk + order by c_customer_id,c_salutation,c_first_name,c_last_name,ca_street_number,ca_street_name + ,ca_street_type,ca_suite_number,ca_city,ca_county,ca_state,ca_zip,ca_country,ca_gmt_offset + ,ca_location_type,ctr_total_return + limit 100; + +-- end query 81 in stream 0 using template query81.tpl +-- start query 82 in stream 0 using template query82.tpl +select i_item_id + ,i_item_desc + ,i_current_price + from item, inventory, date_dim, store_sales + where i_current_price between 58 and 58+30 + and inv_item_sk = i_item_sk + and d_date_sk=inv_date_sk + and d_date between cast('2001-01-13' as date) and (cast('2001-01-13' as date) + 60 days) + and i_manufact_id in (259,559,580,485) + and inv_quantity_on_hand between 100 and 500 + and ss_item_sk = i_item_sk + group by i_item_id,i_item_desc,i_current_price + order by i_item_id + limit 100; + +-- end query 82 in stream 0 using template query82.tpl +-- start query 83 in stream 0 using template query83.tpl +with sr_items as + (select i_item_id item_id, + sum(sr_return_quantity) sr_item_qty + from store_returns, + item, + date_dim + where sr_item_sk = i_item_sk + and d_date in + (select d_date + from date_dim + where d_week_seq in + (select d_week_seq + from date_dim + where d_date in ('2001-07-13','2001-09-10','2001-11-16'))) + and sr_returned_date_sk = d_date_sk + group by i_item_id), + cr_items as + (select i_item_id item_id, + sum(cr_return_quantity) cr_item_qty + from catalog_returns, + item, + date_dim + where cr_item_sk = i_item_sk + and d_date in + (select d_date + from date_dim + where d_week_seq in + (select d_week_seq + from date_dim + where d_date in ('2001-07-13','2001-09-10','2001-11-16'))) + and cr_returned_date_sk = d_date_sk + group by i_item_id), + wr_items as + (select i_item_id item_id, + sum(wr_return_quantity) wr_item_qty + from web_returns, + item, + date_dim + where wr_item_sk = i_item_sk + and d_date in + (select d_date + from date_dim + where d_week_seq in + (select d_week_seq + from date_dim + where d_date in ('2001-07-13','2001-09-10','2001-11-16'))) + and wr_returned_date_sk = d_date_sk + group by i_item_id) + select sr_items.item_id + ,sr_item_qty + ,sr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 sr_dev + ,cr_item_qty + ,cr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 cr_dev + ,wr_item_qty + ,wr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 wr_dev + ,(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 average + from sr_items + ,cr_items + ,wr_items + where sr_items.item_id=cr_items.item_id + and sr_items.item_id=wr_items.item_id + order by sr_items.item_id + ,sr_item_qty + limit 100; + +-- end query 83 in stream 0 using template query83.tpl +-- start query 84 in stream 0 using template query84.tpl +select c_customer_id as customer_id + , coalesce(c_last_name,'') || ', ' || coalesce(c_first_name,'') as customername + from customer + ,customer_address + ,customer_demographics + ,household_demographics + ,income_band + ,store_returns + where ca_city = 'Woodland' + and c_current_addr_sk = ca_address_sk + and ib_lower_bound >= 60306 + and ib_upper_bound <= 60306 + 50000 + and ib_income_band_sk = hd_income_band_sk + and cd_demo_sk = c_current_cdemo_sk + and hd_demo_sk = c_current_hdemo_sk + and sr_cdemo_sk = cd_demo_sk + order by c_customer_id + limit 100; + +-- end query 84 in stream 0 using template query84.tpl +-- start query 85 in stream 0 using template query85.tpl +select substr(r_reason_desc,1,20) + ,avg(ws_quantity) + ,avg(wr_refunded_cash) + ,avg(wr_fee) + from web_sales, web_returns, web_page, customer_demographics cd1, + customer_demographics cd2, customer_address, date_dim, reason + where ws_web_page_sk = wp_web_page_sk + and ws_item_sk = wr_item_sk + and ws_order_number = wr_order_number + and ws_sold_date_sk = d_date_sk and d_year = 1998 + and cd1.cd_demo_sk = wr_refunded_cdemo_sk + and cd2.cd_demo_sk = wr_returning_cdemo_sk + and ca_address_sk = wr_refunded_addr_sk + and r_reason_sk = wr_reason_sk + and + ( + ( + cd1.cd_marital_status = 'D' + and + cd1.cd_marital_status = cd2.cd_marital_status + and + cd1.cd_education_status = 'Primary' + and + cd1.cd_education_status = cd2.cd_education_status + and + ws_sales_price between 100.00 and 150.00 + ) + or + ( + cd1.cd_marital_status = 'S' + and + cd1.cd_marital_status = cd2.cd_marital_status + and + cd1.cd_education_status = 'College' + and + cd1.cd_education_status = cd2.cd_education_status + and + ws_sales_price between 50.00 and 100.00 + ) + or + ( + cd1.cd_marital_status = 'U' + and + cd1.cd_marital_status = cd2.cd_marital_status + and + cd1.cd_education_status = 'Advanced Degree' + and + cd1.cd_education_status = cd2.cd_education_status + and + ws_sales_price between 150.00 and 200.00 + ) + ) + and + ( + ( + ca_country = 'United States' + and + ca_state in ('NC', 'TX', 'IA') + and ws_net_profit between 100 and 200 + ) + or + ( + ca_country = 'United States' + and + ca_state in ('WI', 'WV', 'GA') + and ws_net_profit between 150 and 300 + ) + or + ( + ca_country = 'United States' + and + ca_state in ('OK', 'VA', 'KY') + and ws_net_profit between 50 and 250 + ) + ) +group by r_reason_desc +order by substr(r_reason_desc,1,20) + ,avg(ws_quantity) + ,avg(wr_refunded_cash) + ,avg(wr_fee) +limit 100; + +-- end query 85 in stream 0 using template query85.tpl +-- start query 86 in stream 0 using template query86.tpl +select + sum(ws_net_paid) as total_sum + ,i_category + ,i_class + ,grouping(i_category)+grouping(i_class) as lochierarchy + ,rank() over ( + partition by grouping(i_category)+grouping(i_class), + case when grouping(i_class) = 0 then i_category end + order by sum(ws_net_paid) desc) as rank_within_parent + from + web_sales + ,date_dim d1 + ,item + where + d1.d_month_seq between 1186 and 1186+11 + and d1.d_date_sk = ws_sold_date_sk + and i_item_sk = ws_item_sk + group by rollup(i_category,i_class) + order by + lochierarchy desc, + case when lochierarchy = 0 then i_category end, + rank_within_parent + limit 100; + +-- end query 86 in stream 0 using template query86.tpl +-- start query 87 in stream 0 using template query87.tpl +select count(*) +from ((select distinct c_last_name, c_first_name, d_date + from store_sales, date_dim, customer + where store_sales.ss_sold_date_sk = date_dim.d_date_sk + and store_sales.ss_customer_sk = customer.c_customer_sk + and d_month_seq between 1202 and 1202+11) + except + (select distinct c_last_name, c_first_name, d_date + from catalog_sales, date_dim, customer + where catalog_sales.cs_sold_date_sk = date_dim.d_date_sk + and catalog_sales.cs_bill_customer_sk = customer.c_customer_sk + and d_month_seq between 1202 and 1202+11) + except + (select distinct c_last_name, c_first_name, d_date + from web_sales, date_dim, customer + where web_sales.ws_sold_date_sk = date_dim.d_date_sk + and web_sales.ws_bill_customer_sk = customer.c_customer_sk + and d_month_seq between 1202 and 1202+11) +) cool_cust +; + +-- end query 87 in stream 0 using template query87.tpl +-- start query 88 in stream 0 using template query88.tpl +select * +from + (select count(*) h8_30_to_9 + from store_sales, household_demographics , time_dim, store + where ss_sold_time_sk = time_dim.t_time_sk + and ss_hdemo_sk = household_demographics.hd_demo_sk + and ss_store_sk = s_store_sk + and time_dim.t_hour = 8 + and time_dim.t_minute >= 30 + and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or + (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or + (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2)) + and store.s_store_name = 'ese') s1, + (select count(*) h9_to_9_30 + from store_sales, household_demographics , time_dim, store + where ss_sold_time_sk = time_dim.t_time_sk + and ss_hdemo_sk = household_demographics.hd_demo_sk + and ss_store_sk = s_store_sk + and time_dim.t_hour = 9 + and time_dim.t_minute < 30 + and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or + (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or + (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2)) + and store.s_store_name = 'ese') s2, + (select count(*) h9_30_to_10 + from store_sales, household_demographics , time_dim, store + where ss_sold_time_sk = time_dim.t_time_sk + and ss_hdemo_sk = household_demographics.hd_demo_sk + and ss_store_sk = s_store_sk + and time_dim.t_hour = 9 + and time_dim.t_minute >= 30 + and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or + (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or + (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2)) + and store.s_store_name = 'ese') s3, + (select count(*) h10_to_10_30 + from store_sales, household_demographics , time_dim, store + where ss_sold_time_sk = time_dim.t_time_sk + and ss_hdemo_sk = household_demographics.hd_demo_sk + and ss_store_sk = s_store_sk + and time_dim.t_hour = 10 + and time_dim.t_minute < 30 + and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or + (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or + (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2)) + and store.s_store_name = 'ese') s4, + (select count(*) h10_30_to_11 + from store_sales, household_demographics , time_dim, store + where ss_sold_time_sk = time_dim.t_time_sk + and ss_hdemo_sk = household_demographics.hd_demo_sk + and ss_store_sk = s_store_sk + and time_dim.t_hour = 10 + and time_dim.t_minute >= 30 + and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or + (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or + (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2)) + and store.s_store_name = 'ese') s5, + (select count(*) h11_to_11_30 + from store_sales, household_demographics , time_dim, store + where ss_sold_time_sk = time_dim.t_time_sk + and ss_hdemo_sk = household_demographics.hd_demo_sk + and ss_store_sk = s_store_sk + and time_dim.t_hour = 11 + and time_dim.t_minute < 30 + and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or + (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or + (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2)) + and store.s_store_name = 'ese') s6, + (select count(*) h11_30_to_12 + from store_sales, household_demographics , time_dim, store + where ss_sold_time_sk = time_dim.t_time_sk + and ss_hdemo_sk = household_demographics.hd_demo_sk + and ss_store_sk = s_store_sk + and time_dim.t_hour = 11 + and time_dim.t_minute >= 30 + and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or + (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or + (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2)) + and store.s_store_name = 'ese') s7, + (select count(*) h12_to_12_30 + from store_sales, household_demographics , time_dim, store + where ss_sold_time_sk = time_dim.t_time_sk + and ss_hdemo_sk = household_demographics.hd_demo_sk + and ss_store_sk = s_store_sk + and time_dim.t_hour = 12 + and time_dim.t_minute < 30 + and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or + (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or + (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2)) + and store.s_store_name = 'ese') s8 +; + +-- end query 88 in stream 0 using template query88.tpl +-- start query 89 in stream 0 using template query89.tpl +select * +from( +select i_category, i_class, i_brand, + s_store_name, s_company_name, + d_moy, + sum(ss_sales_price) sum_sales, + avg(sum(ss_sales_price)) over + (partition by i_category, i_brand, s_store_name, s_company_name) + avg_monthly_sales +from item, store_sales, date_dim, store +where ss_item_sk = i_item_sk and + ss_sold_date_sk = d_date_sk and + ss_store_sk = s_store_sk and + d_year in (2001) and + ((i_category in ('Books','Children','Electronics') and + i_class in ('history','school-uniforms','audio') + ) + or (i_category in ('Men','Sports','Shoes') and + i_class in ('pants','tennis','womens') + )) +group by i_category, i_class, i_brand, + s_store_name, s_company_name, d_moy) tmp1 +where case when (avg_monthly_sales <> 0) then (abs(sum_sales - avg_monthly_sales) / avg_monthly_sales) else null end > 0.1 +order by sum_sales - avg_monthly_sales, s_store_name +limit 100; + +-- end query 89 in stream 0 using template query89.tpl +-- start query 90 in stream 0 using template query90.tpl +select cast(amc as decimal(15,4))/cast(pmc as decimal(15,4)) am_pm_ratio + from ( select count(*) amc + from web_sales, household_demographics , time_dim, web_page + where ws_sold_time_sk = time_dim.t_time_sk + and ws_ship_hdemo_sk = household_demographics.hd_demo_sk + and ws_web_page_sk = web_page.wp_web_page_sk + and time_dim.t_hour between 12 and 12+1 + and household_demographics.hd_dep_count = 6 + and web_page.wp_char_count between 5000 and 5200) at, + ( select count(*) pmc + from web_sales, household_demographics , time_dim, web_page + where ws_sold_time_sk = time_dim.t_time_sk + and ws_ship_hdemo_sk = household_demographics.hd_demo_sk + and ws_web_page_sk = web_page.wp_web_page_sk + and time_dim.t_hour between 14 and 14+1 + and household_demographics.hd_dep_count = 6 + and web_page.wp_char_count between 5000 and 5200) pt + order by am_pm_ratio + limit 100; + +-- end query 90 in stream 0 using template query90.tpl +-- start query 91 in stream 0 using template query91.tpl +select + cc_call_center_id Call_Center, + cc_name Call_Center_Name, + cc_manager Manager, + sum(cr_net_loss) Returns_Loss +from + call_center, + catalog_returns, + date_dim, + customer, + customer_address, + customer_demographics, + household_demographics +where + cr_call_center_sk = cc_call_center_sk +and cr_returned_date_sk = d_date_sk +and cr_returning_customer_sk= c_customer_sk +and cd_demo_sk = c_current_cdemo_sk +and hd_demo_sk = c_current_hdemo_sk +and ca_address_sk = c_current_addr_sk +and d_year = 2000 +and d_moy = 12 +and ( (cd_marital_status = 'M' and cd_education_status = 'Unknown') + or(cd_marital_status = 'W' and cd_education_status = 'Advanced Degree')) +and hd_buy_potential like 'Unknown%' +and ca_gmt_offset = -7 +group by cc_call_center_id,cc_name,cc_manager,cd_marital_status,cd_education_status +order by sum(cr_net_loss) desc; + +-- end query 91 in stream 0 using template query91.tpl +-- start query 92 in stream 0 using template query92.tpl +select + sum(ws_ext_discount_amt) as "Excess Discount Amount" +from + web_sales + ,item + ,date_dim +where +i_manufact_id = 714 +and i_item_sk = ws_item_sk +and d_date between '2000-02-01' and + (cast('2000-02-01' as date) + 90 days) +and d_date_sk = ws_sold_date_sk +and ws_ext_discount_amt + > ( + SELECT + 1.3 * avg(ws_ext_discount_amt) + FROM + web_sales + ,date_dim + WHERE + ws_item_sk = i_item_sk + and d_date between '2000-02-01' and + (cast('2000-02-01' as date) + 90 days) + and d_date_sk = ws_sold_date_sk + ) +order by sum(ws_ext_discount_amt) +limit 100; + +-- end query 92 in stream 0 using template query92.tpl +-- start query 93 in stream 0 using template query93.tpl +select ss_customer_sk + ,sum(act_sales) sumsales + from (select ss_item_sk + ,ss_ticket_number + ,ss_customer_sk + ,case when sr_return_quantity is not null then (ss_quantity-sr_return_quantity)*ss_sales_price + else (ss_quantity*ss_sales_price) end act_sales + from store_sales left outer join store_returns on (sr_item_sk = ss_item_sk + and sr_ticket_number = ss_ticket_number) + ,reason + where sr_reason_sk = r_reason_sk + and r_reason_desc = 'reason 58') t + group by ss_customer_sk + order by sumsales, ss_customer_sk +limit 100; + +-- end query 93 in stream 0 using template query93.tpl +-- start query 94 in stream 0 using template query94.tpl +select + count(distinct ws_order_number) as "order count" + ,sum(ws_ext_ship_cost) as "total shipping cost" + ,sum(ws_net_profit) as "total net profit" +from + web_sales ws1 + ,date_dim + ,customer_address + ,web_site +where + d_date between '2002-5-01' and + (cast('2002-5-01' as date) + 60 days) +and ws1.ws_ship_date_sk = d_date_sk +and ws1.ws_ship_addr_sk = ca_address_sk +and ca_state = 'OK' +and ws1.ws_web_site_sk = web_site_sk +and web_company_name = 'pri' +and exists (select * + from web_sales ws2 + where ws1.ws_order_number = ws2.ws_order_number + and ws1.ws_warehouse_sk <> ws2.ws_warehouse_sk) +and not exists(select * + from web_returns wr1 + where ws1.ws_order_number = wr1.wr_order_number) +order by count(distinct ws_order_number) +limit 100; + +-- end query 94 in stream 0 using template query94.tpl +-- start query 95 in stream 0 using template query95.tpl +with ws_wh as +(select ws1.ws_order_number,ws1.ws_warehouse_sk wh1,ws2.ws_warehouse_sk wh2 + from web_sales ws1,web_sales ws2 + where ws1.ws_order_number = ws2.ws_order_number + and ws1.ws_warehouse_sk <> ws2.ws_warehouse_sk) + select + count(distinct ws_order_number) as "order count" + ,sum(ws_ext_ship_cost) as "total shipping cost" + ,sum(ws_net_profit) as "total net profit" +from + web_sales ws1 + ,date_dim + ,customer_address + ,web_site +where + d_date between '2001-4-01' and + (cast('2001-4-01' as date) + 60 days) +and ws1.ws_ship_date_sk = d_date_sk +and ws1.ws_ship_addr_sk = ca_address_sk +and ca_state = 'VA' +and ws1.ws_web_site_sk = web_site_sk +and web_company_name = 'pri' +and ws1.ws_order_number in (select ws_order_number + from ws_wh) +and ws1.ws_order_number in (select wr_order_number + from web_returns,ws_wh + where wr_order_number = ws_wh.ws_order_number) +order by count(distinct ws_order_number) +limit 100; + +-- end query 95 in stream 0 using template query95.tpl +-- start query 96 in stream 0 using template query96.tpl +select count(*) +from store_sales + ,household_demographics + ,time_dim, store +where ss_sold_time_sk = time_dim.t_time_sk + and ss_hdemo_sk = household_demographics.hd_demo_sk + and ss_store_sk = s_store_sk + and time_dim.t_hour = 8 + and time_dim.t_minute >= 30 + and household_demographics.hd_dep_count = 0 + and store.s_store_name = 'ese' +order by count(*) +limit 100; + +-- end query 96 in stream 0 using template query96.tpl +-- start query 97 in stream 0 using template query97.tpl +with ssci as ( +select ss_customer_sk customer_sk + ,ss_item_sk item_sk +from store_sales,date_dim +where ss_sold_date_sk = d_date_sk + and d_month_seq between 1199 and 1199 + 11 +group by ss_customer_sk + ,ss_item_sk), +csci as( + select cs_bill_customer_sk customer_sk + ,cs_item_sk item_sk +from catalog_sales,date_dim +where cs_sold_date_sk = d_date_sk + and d_month_seq between 1199 and 1199 + 11 +group by cs_bill_customer_sk + ,cs_item_sk) + select sum(case when ssci.customer_sk is not null and csci.customer_sk is null then 1 else 0 end) store_only + ,sum(case when ssci.customer_sk is null and csci.customer_sk is not null then 1 else 0 end) catalog_only + ,sum(case when ssci.customer_sk is not null and csci.customer_sk is not null then 1 else 0 end) store_and_catalog +from ssci full outer join csci on (ssci.customer_sk=csci.customer_sk + and ssci.item_sk = csci.item_sk) +limit 100; + +-- end query 97 in stream 0 using template query97.tpl +-- start query 98 in stream 0 using template query98.tpl +select i_item_id + ,i_item_desc + ,i_category + ,i_class + ,i_current_price + ,sum(ss_ext_sales_price) as itemrevenue + ,sum(ss_ext_sales_price)*100/sum(sum(ss_ext_sales_price)) over + (partition by i_class) as revenueratio +from + store_sales + ,item + ,date_dim +where + ss_item_sk = i_item_sk + and i_category in ('Men', 'Sports', 'Jewelry') + and ss_sold_date_sk = d_date_sk + and d_date between cast('1999-02-05' as date) + and (cast('1999-02-05' as date) + 30 days) +group by + i_item_id + ,i_item_desc + ,i_category + ,i_class + ,i_current_price +order by + i_category + ,i_class + ,i_item_id + ,i_item_desc + ,revenueratio; + +-- end query 98 in stream 0 using template query98.tpl +-- start query 99 in stream 0 using template query99.tpl +select + substr(w_warehouse_name,1,20) + ,sm_type + ,cc_name + ,sum(case when (cs_ship_date_sk - cs_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days" + ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 30) and + (cs_ship_date_sk - cs_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days" + ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 60) and + (cs_ship_date_sk - cs_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days" + ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 90) and + (cs_ship_date_sk - cs_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days" + ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 120) then 1 else 0 end) as ">120 days" +from + catalog_sales + ,warehouse + ,ship_mode + ,call_center + ,date_dim +where + d_month_seq between 1194 and 1194 + 11 +and cs_ship_date_sk = d_date_sk +and cs_warehouse_sk = w_warehouse_sk +and cs_ship_mode_sk = sm_ship_mode_sk +and cs_call_center_sk = cc_call_center_sk +group by + substr(w_warehouse_name,1,20) + ,sm_type + ,cc_name +order by substr(w_warehouse_name,1,20) + ,sm_type + ,cc_name +limit 100; + +-- end query 99 in stream 0 using template query99.tpl diff --git a/tests/test_cases.py b/tests/test_cases.py index 175dbd1..5c82bb4 100644 --- a/tests/test_cases.py +++ b/tests/test_cases.py @@ -1,48 +1,119 @@ +import testgres import json -import psycopg2 -import psycopg2.extensions import re -import select import time import xml.etree.ElementTree as ET import yaml from time import sleep - -def wait(conn): - """wait for some event on connection to postgres""" - while 1: - state = conn.poll() - if state == psycopg2.extensions.POLL_OK: - break - elif state == psycopg2.extensions.POLL_WRITE: - select.select([], [conn.fileno()], []) - elif state == psycopg2.extensions.POLL_READ: - select.select([conn.fileno()], [], []) +from multiprocessing import Process, Queue, Condition +import subprocess +import os + +class AsyncQueryExecutor(): + """ Run query in separate process """ + process = Process() + def __init__(self, node): + self.node = node + self.conn = testgres.connection.NodeConnection(node) + self.cursor = self.conn.cursor + self.backend_pid = self.conn.pid + self.res_q = Queue() + self.condition = Condition() + self.result = [] + + def run_internal(self, conn, query, multiple, res_q, condition): + condition.acquire() + commands = [] + if multiple: + commands = query.split(';') + for i, cmd in enumerate(query.split(';')): + if (len(cmd.strip()) == 0): + del commands[i] else: - raise psycopg2.OperationalError("poll() returned %s" % state) - -def n_async_connect(config, n=1): - """establish n asynchronious connections to the postgres with specified config""" + commands.append(query) + + conn.begin() + condition.notify() + condition.release() + for cmd in commands: + try: + res = conn.execute(cmd) + res_q.put(res) + conn.commit() + except Exception, e: + print 'Unable to execute query: "', cmd ,'"' + print 'Reason: %s' %e + conn.rollback() + continue + return - aconfig = config.copy() - aconfig['async'] = True + def run(self, query, multiple = False): + """Run async query""" + self.process = Process(target=self.run_internal, + args=(self.conn, query, multiple, self.res_q, self.condition)) + self.process.start() + self.condition.acquire() + self.condition.wait() + + def wait(self): + self.result = self.res_q.get() + if self.process.is_alive(): + self.process.join() + + def terminate(self): + if self.process.is_alive(): + self.node.psql("SELECT pg_cancel_backend(%d)" % self.backend_pid) + self.process.terminate() + + def close(self): + self.terminate() + self.conn.close() + +def pqs_args(pid, verbose=False, costs=False, timing=False, + buffers=False, triggers=False, format='text'): + s = "%d, %s, %s, %s, %s, %s, '%s'" % (pid, verbose, costs, timing, buffers, + triggers, format) + return s + +def set_guc(conn, param, value): + conn.execute('set %s to %s' % (param, value)) + conn.commit() + +def query_state(node, query, args={}, gucs={}, num_workers=0, expected_len=1, delay = 0): + """ + Get intermediate state of 'query' on connection 'async_conn' after number of 'steps' + of node executions from start of query + """ result = [] - for _ in xrange(n): - conn = psycopg2.connect(**aconfig) - wait(conn) - result.append(conn) - return result + aq = AsyncQueryExecutor(node) + conn = testgres.connection.NodeConnection(node) -def n_close(conns): - """close connections to postgres""" + gucs.update({'enable_mergejoin' : 'off'}) + gucs.update({'max_parallel_workers_per_gather' : num_workers}) + for param, value in gucs.items(): + set_guc(aq.conn, param, value) - for conn in conns: - conn.close() + aq.run(query) + sleep(delay) + # extract current state of query progress + while len(result) < expected_len and aq.process.is_alive(): + result = conn.execute(r"""SELECT pid, + frame_number, + query_text, + plan, + leader_pid + FROM pg_query_state(%s);""" % + pqs_args(aq.backend_pid, **args)) + aq.wait() + aq.close() + conn.close() + assert result[0][0] == aq.backend_pid and result[0][1] == 0 \ + and result[0][2] == query and result[0][4] == None -notices = [] + return result -def debug_output(qs, qs_len, pid, query, expected): +def debug_output(qs, qs_len, pid, query, expected, expected2 = None): something_happened = False if (qs_len and len(qs) != qs_len ): print "len(qs): ", len(qs), ", expected: ", qs_len @@ -57,10 +128,15 @@ def debug_output(qs, qs_len, pid, query, expected): print "qs[0][2]:\n", qs[0][2] print "Expected:\n", query something_happened = True - if (not (re.match(expected, qs[0][3]))): + if (expected and not (re.match(expected, qs[0][3]))): print "qs[0][3]:\n", qs[0][3] print "Expected:\n", expected something_happened = True + if (qs_len == 2 and expected2 and + not (re.match(expected2, qs[1][3]))): + print "qs[1][3]:\n", qs[1][3] + print "Expected:\n", expected + something_happened = True if (qs[0][4] != None): print "qs[0][4]: ", qs[0][4], "Expected: None" something_happened = True @@ -75,90 +151,31 @@ def debug_output(qs, qs_len, pid, query, expected): if (something_happened): print "If test have not crashed, then it's OK" -def notices_warning(): - if (len(notices) > 0): - print("") - print("WARNING:") - print(notices) - -def pg_query_state(config, pid, verbose=False, costs=False, timing=False, \ - buffers=False, triggers=False, format='text'): - """ - Get query state from backend with specified pid and optional parameters. - Save any warning, info, notice and log data in global variable 'notices' - """ - - global notices - - conn = psycopg2.connect(**config) - curs = conn.cursor() - result = [] - while not result: - curs.callproc('pg_query_state', (pid, verbose, costs, timing, buffers, triggers, format)) - result = curs.fetchall() - notices = conn.notices[:] - conn.close() - return result - -def test_deadlock(config): +def test_deadlock(node): """test when two backends try to extract state of each other""" - acon1, acon2 = n_async_connect(config, 2) - acurs1 = acon1.cursor() - acurs2 = acon2.cursor() - - while True: - acurs1.callproc('pg_query_state', (acon2.get_backend_pid(),)) - acurs2.callproc('pg_query_state', (acon1.get_backend_pid(),)) + async_query1 = AsyncQueryExecutor(node) + async_query2 = AsyncQueryExecutor(node) - # listen acon1, acon2 with timeout = 10 sec to determine deadlock - r, w, x = select.select([acon1.fileno(), acon2.fileno()], [], [], 10) - assert (r or w or x), "Deadlock is happened under cross reading of query states" - - wait(acon1) - wait(acon2) + for try_n in range(10): + async_query1.run("select pg_query_state(%d)" % async_query2.backend_pid) + async_query2.run("select pg_query_state(%d)" % async_query1.backend_pid) + async_query1.wait() + async_query2.wait() # exit from loop if one backend could read state of execution 'pg_query_state' # from other backend - if acurs1.fetchone() or acurs2.fetchone(): + if async_query1.result or async_query1.result: break + expected = "Deadlock is happened under cross reading of query states" + assert re.match(expected, async_query1.result) or (re.search(expected, async_query2.result)) - n_close((acon1, acon2)) - -def query_state(config, async_conn, query, args={}, num_workers=0): - """ - Get intermediate state of 'query' on connection 'async_conn' after number of 'steps' - of node executions from start of query - """ - - acurs = async_conn.cursor() - conn = psycopg2.connect(**config) - curs = conn.cursor() - - set_guc(async_conn, 'enable_mergejoin', 'off') - set_guc(async_conn, 'max_parallel_workers_per_gather', num_workers) - acurs.execute(query) + async_query1.close() + async_query2.close() - # extract current state of query progress - pg_qs_args = { - 'config': config, - 'pid': async_conn.get_backend_pid() - } - for k, v in args.iteritems(): - pg_qs_args[k] = v - result = pg_query_state(**pg_qs_args) - wait(async_conn) - - set_guc(async_conn, 'pg_query_state.executor_trace', 'off') - set_guc(async_conn, 'enable_mergejoin', 'on') - - conn.close() - return result - -def test_simple_query(config): +def test_simple_query(node): """test statistics of simple query""" - acon, = n_async_connect(config) query = 'select count(*) from foo join bar on foo.c1=bar.c1' expected = r"""Aggregate \(Current loop: actual rows=\d+, loop number=1\) -> Hash Join \(Current loop: actual rows=\d+, loop number=1\) @@ -168,49 +185,51 @@ def test_simple_query(config): Buckets: \d+ Batches: \d+ Memory Usage: \d+kB -> Seq Scan on bar \(Current loop: actual rows=\d+, loop number=1\)""" - qs = query_state(config, acon, query) - debug_output(qs, 1, acon.get_backend_pid(), query, expected) - notices_warning() - #assert len(qs) == 1 #Skip this check while output of test can be different - assert qs[0][0] == acon.get_backend_pid() and qs[0][1] == 0 \ - and qs[0][2] == query and re.match(expected, qs[0][3]) and qs[0][4] == None - - n_close((acon,)) + qs = query_state(node, query) + debug_output(qs, 1, None, query, expected) + assert re.match(expected, qs[0][3]) -def test_concurrent_access(config): +def test_concurrent_access(node): """test when two backends compete with each other to extract state from third running backend""" - acon1, acon2, acon3 = n_async_connect(config, 3) - acurs1, acurs2, acurs3 = acon1.cursor(), acon2.cursor(), acon3.cursor() + acon1 = AsyncQueryExecutor(node) + acon2 = AsyncQueryExecutor(node) + acon3 = AsyncQueryExecutor(node) + query = 'select count(*) from foo join bar on foo.c1=bar.c1' - set_guc(acon3, 'max_parallel_workers_per_gather', 0) - acurs3.execute(query) - time.sleep(0.1) - acurs1.callproc('pg_query_state', (acon3.get_backend_pid(),)) - acurs2.callproc('pg_query_state', (acon3.get_backend_pid(),)) - wait(acon1) - wait(acon2) - wait(acon3) - - qs1, qs2 = acurs1.fetchall(), acurs2.fetchall() - assert len(qs1) == len(qs2) == 1 \ - and qs1[0][0] == qs2[0][0] == acon3.get_backend_pid() \ - and qs1[0][1] == qs2[0][1] == 0 \ - and qs1[0][2] == qs2[0][2] == query \ - and len(qs1[0][3]) > 0 and len(qs2[0][3]) > 0 \ - and qs1[0][4] == qs2[0][4] == None - #assert len(notices) == 0 - notices_warning() - - n_close((acon1, acon2, acon3)) - -def test_nested_call(config): + set_guc(acon3.conn, 'max_parallel_workers_per_gather', 0) + acon3.run(query) + + psq_query = r"""SELECT pid, + frame_number, + query_text, + plan, + leader_pid + FROM pg_query_state(%s);""" % pqs_args(acon3.backend_pid) + + while len(acon1.result) < 1 and acon3.process.is_alive(): + acon1.run(psq_query) + acon2.run(psq_query) + acon1.wait() + acon2.wait() + acon3.terminate() + + qs1 = acon1.result + qs2 = acon2.result + + assert acon3.backend_pid == qs1[0][0] + assert acon3.backend_pid == qs2[0][0] + + acon1.close() + acon2.close() + acon3.close() + +def test_nested_call(node): """test statistics under calling function""" - acon, = n_async_connect(config) - util_conn = psycopg2.connect(**config) - util_curs = util_conn.cursor() + conn = testgres.connection.NodeConnection(node) + create_function = """ create or replace function n_join_foo_bar() returns integer as $$ begin @@ -231,29 +250,25 @@ def test_nested_call(config): Buckets: \d+ Batches: \d+ Memory Usage: \d+kB -> Seq Scan on bar \(Current loop: actual rows=\d+, loop number=1\)""" - util_curs.execute(create_function) - util_conn.commit() + conn.execute(create_function) + conn.commit() - qs = query_state(config, acon, call_function) + qs = query_state(node, call_function, expected_len = 2) + debug_output(qs, 2, None, call_function, None, expected_nested) assert len(qs) == 2 \ - and qs[0][0] == qs[1][0] == acon.get_backend_pid() \ and qs[0][1] == 0 and qs[1][1] == 1 \ and qs[0][2] == call_function and qs[0][3] == expected \ and qs[1][2] == nested_query and re.match(expected_nested, qs[1][3]) \ and qs[0][4] == qs[1][4] == None - assert len(notices) == 0 - util_curs.execute(drop_function) - - util_conn.close() - n_close((acon,)) + conn.execute(drop_function) + conn.commit() + conn.close() -def test_insert_on_conflict(config): +def test_insert_on_conflict(node): """test statistics on conflicting tuples under INSERT ON CONFLICT query""" - acon, = n_async_connect(config) - util_conn = psycopg2.connect(**config) - util_curs = util_conn.cursor() + util_conn = testgres.connection.NodeConnection(node) add_field_uniqueness = 'alter table foo add constraint unique_c1 unique(c1)' drop_field_uniqueness = 'alter table foo drop constraint unique_c1' query = 'insert into foo select i, md5(random()::text) from generate_series(1, 30000) as i on conflict do nothing' @@ -263,36 +278,21 @@ def test_insert_on_conflict(config): Conflicting Tuples: \d+ -> Function Scan on generate_series i \(Current loop: actual rows=\d+, loop number=\d+\)""" - util_curs.execute(add_field_uniqueness) + util_conn.execute(add_field_uniqueness) util_conn.commit() - qs = query_state(config, acon, query) - - debug_output(qs, 1, acon.get_backend_pid(), query, expected) - notices_warning() - #assert len(qs) == 1 \ - assert qs[0][0] == acon.get_backend_pid() and qs[0][1] == 0 \ - and qs[0][2] == query and re.match(expected, qs[0][3]) \ - and qs[0][4] == None - assert len(notices) == 0 - - util_curs.execute(drop_field_uniqueness) + qs = query_state(node, query) + debug_output(qs, 1, None, query, expected) + assert re.match(expected, qs[0][3]) + util_conn.execute(drop_field_uniqueness) util_conn.close() - n_close((acon,)) -def set_guc(async_conn, param, value): - acurs = async_conn.cursor() - acurs.execute('set %s to %s' % (param, value)) - wait(async_conn) - -def test_trigger(config): +def test_trigger(node): """test trigger statistics""" - acon, = n_async_connect(config) - acurs = acon.cursor() - util_conn = psycopg2.connect(**config) - util_curs = util_conn.cursor() + util_conn = testgres.connection.NodeConnection(node) + create_trigger_function = """ create or replace function unique_c1_in_foo() returns trigger as $$ begin @@ -312,35 +312,23 @@ def test_trigger(config): -> Function Scan on generate_series i \(Current loop: actual rows=\d+, loop number=1\)""" trigger_suffix = r"""Trigger unique_foo_c1: calls=\d+""" - util_curs.execute(create_trigger_function) - util_curs.execute(create_trigger) + util_conn.execute(create_trigger_function) + util_conn.execute(create_trigger) util_conn.commit() - qs = query_state(config, acon, query, {'triggers': True}) - debug_output(qs, None, acon.get_backend_pid(), query, expected_upper) - notices_warning() - assert qs[0][0] == acon.get_backend_pid() and qs[0][1] == 0 \ - and qs[0][2] == query and re.match(expected_upper, qs[0][3]) \ - and qs[0][4] == None - assert len(notices) == 0 - - qs = query_state(config, acon, query, {'triggers': False}) - debug_output(qs, None, acon.get_backend_pid(), query, expected_upper) - notices_warning() - assert qs[0][0] == acon.get_backend_pid() and qs[0][1] == 0 \ - and qs[0][2] == query and re.match(expected_upper, qs[0][3]) \ - and qs[0][4] == None - assert len(notices) == 0 - - util_curs.execute(drop_temps) + qs = query_state(node, query, {'triggers': True}, delay = 1) + debug_output(qs, 2, None, query, expected_upper+'\n'+ trigger_suffix) + assert re.match(expected_upper+'\n'+ trigger_suffix, qs[0][3]) + qs = query_state(node, query, {'triggers': False}) + debug_output(qs, 1, None, query, expected_upper) + assert re.match(expected_upper, qs[0][3]) + util_conn.execute(drop_temps) util_conn.close() - n_close((acon,)) -def test_costs(config): +def test_costs(node): """test plan costs""" - acon, = n_async_connect(config) query = 'select count(*) from foo join bar on foo.c1=bar.c1' expected = r"""Aggregate \(cost=\d+.\d+..\d+.\d+ rows=\d+ width=8\) \(Current loop: actual rows=0, loop number=1\) -> Hash Join \(cost=\d+.\d+..\d+.\d+ rows=\d+ width=0\) \(Current loop: actual rows=0, loop number=1\) @@ -350,18 +338,14 @@ def test_costs(config): Buckets: \d+ Batches: \d+ Memory Usage: \d+kB -> Seq Scan on bar \(cost=0.00..\d+.\d+ rows=\d+ width=4\) \(Current loop: actual rows=\d+, loop number=1\)""" - qs = query_state(config, acon, query, {'costs': True}) + qs = query_state(node, query, {'costs': True}) debug_output(qs, 1, None, query, expected) - notices_warning() - assert len(qs) == 1 and re.match(expected, qs[0][3]) - assert len(notices) == 0 - - n_close((acon,)) + assert len(qs) == 1 + assert re.match(expected, qs[0][3]) def test_buffers(config): """test buffer statistics""" - acon, = n_async_connect(config) query = 'select count(*) from foo join bar on foo.c1=bar.c1' expected = r"""Aggregate \(Current loop: actual rows=0, loop number=1\) -> Hash Join \(Current loop: actual rows=0, loop number=1\) @@ -373,38 +357,27 @@ def test_buffers(config): -> Seq Scan on bar \(Current loop: actual rows=\d+, loop number=1\) Buffers: .*""" - set_guc(acon, 'pg_query_state.enable_buffers', 'on') - - qs = query_state(config, acon, query, {'buffers': True}) + qs = query_state(config, query, {'buffers': True}, + gucs = {'pg_query_state.enable_buffers' : 'on'}) debug_output(qs, 1, None, query, expected) - notices_warning() assert len(qs) == 1 and re.match(expected, qs[0][3]) - assert len(notices) == 0 - - n_close((acon,)) -def test_timing(config): +def test_timing(node): """test timing statistics""" - acon, = n_async_connect(config) query = 'select count(*) from foo join bar on foo.c1=bar.c1' expected = r"""Aggregate \(Current loop: running time=\d+.\d+ actual rows=0, loop number=1\) -> Hash Join \(Current loop: running time=\d+.\d+ actual rows=0, loop number=1\) Hash Cond: \(foo.c1 = bar.c1\) - -> Seq Scan on foo \(Current loop: actual time=\d+.\d+..\d+.\d+ rows=1, loop number=1\) - -> Hash \(Current loop: running time=\d+.\d+ actual rows=0, loop number=1\) - Buckets: \d+ Batches: \d+ Memory Usage: \d+kB - -> Seq Scan on bar \(Current loop: actual time=\d+.\d+..\d+.\d+ rows=\d+, loop number=1\)""" - - set_guc(acon, 'pg_query_state.enable_timing', 'on') + -> Seq Scan on foo \(Current loop: (actual|running) time=\d+.\d+(..\d+.\d+)? (actual )?rows=\d+, loop number=1\) + -> Hash \(Current loop: running time=\d+.\d+ actual rows=0, loop number=1\)( + Buckets: \d+ Batches: \d+ Memory Usage: \d+kB)? + -> Seq Scan on bar \(Current loop: (actual|running) time=\d+.\d+(..\d+.\d+)* (actual )*rows=\d+, loop number=1\)""" - qs = query_state(config, acon, query, {'timing': True}) + qs = query_state(node, query, {'timing': True}, + gucs={'pg_query_state.enable_timing' : 'on'}) debug_output(qs, 1, None, query, expected) - notices_warning() assert len(qs) == 1 and re.match(expected, qs[0][3]) - assert len(notices) == 0 - - n_close((acon,)) def check_plan(plan): assert plan.has_key('Current loop') @@ -429,7 +402,6 @@ def check_xml(root): def test_formats(config): """test all formats of pg_query_state output""" - acon, = n_async_connect(config) query = 'select count(*) from foo join bar on foo.c1=bar.c1' expected = r"""Aggregate \(Current loop: actual rows=0, loop number=1\) -> Hash Join \(Current loop: actual rows=0, loop number=1\) @@ -439,61 +411,101 @@ def test_formats(config): Buckets: \d+ Batches: \d+ Memory Usage: \d+kB -> Seq Scan on bar \(Current loop: actual rows=\d+, loop number=1\)""" - qs = query_state(config, acon, query, {'format': 'text'}) + qs = query_state(config, query, {'format': 'text'}) debug_output(qs, 1, None, query, expected) - notices_warning() assert len(qs) == 1 and re.match(expected, qs[0][3]) - assert len(notices) == 0 - qs = query_state(config, acon, query, {'format': 'json'}) + qs = query_state(config, query, {'format': 'json'}) try: js_obj = json.loads(qs[0][3]) except ValueError: assert False, 'Invalid json format' assert len(qs) == 1 - assert len(notices) == 0 check_plan(js_obj['Plan']) - qs = query_state(config, acon, query, {'format': 'xml'}) + qs = query_state(config, query, {'format': 'xml'}) assert len(qs) == 1 - assert len(notices) == 0 try: xml_root = ET.fromstring(qs[0][3]) except: assert False, 'Invalid xml format' check_xml(xml_root) - qs = query_state(config, acon, query, {'format': 'yaml'}) + qs = query_state(config, query, {'format': 'yaml'}) try: yaml_doc = yaml.load(qs[0][3]) except: assert False, 'Invalid yaml format' assert len(qs) == 1 - assert len(notices) == 0 check_plan(yaml_doc['Plan']) - n_close((acon,)) - -def test_timing_buffers_conflicts(config): +def test_timing_buffers_conflicts(node): """test when caller requests timing and buffers but counterpart turned off its""" - acon, = n_async_connect(config) query = 'select count(*) from foo join bar on foo.c1=bar.c1' timing_pattern = '(?:running time=\d+.\d+)|(?:actual time=\d+.\d+..\d+.\d+)' buffers_pattern = 'Buffers:' - qs = query_state(config, acon, query, {'timing': True, 'buffers': False}) + qs = query_state(node, query, {'timing': True, 'buffers': False}) assert len(qs) == 1 and not re.search(timing_pattern, qs[0][3]) - assert notices == ['WARNING: timing statistics disabled\n'] + # Here you can add a check of notices in the case when the + # testgres will be able to receive them + #assert 'WARNING: timing statistics disabled\n' in notices - qs = query_state(config, acon, query, {'timing': False, 'buffers': True}) + qs = query_state(node, query, {'timing': False, 'buffers': True}) assert len(qs) == 1 and not re.search(buffers_pattern, qs[0][3]) - assert notices == ['WARNING: buffers statistics disabled\n'] + #assert 'WARNING: buffers statistics disabled\n' in notices - qs = query_state(config, acon, query, {'timing': True, 'buffers': True}) + qs = query_state(node, query, {'timing': True, 'buffers': True}) assert len(qs) == 1 and not re.search(timing_pattern, qs[0][3]) \ and not re.search(buffers_pattern, qs[0][3]) - assert len(notices) == 2 and 'WARNING: timing statistics disabled\n' in notices \ - and 'WARNING: buffers statistics disabled\n' in notices + #assert len(notices) == 2 and 'WARNING: timing statistics disabled\n' in notices \ + # and 'WARNING: buffers statistics disabled\n' in notices - n_close((acon,)) + +class DataLoadException(Exception): pass +class StressTestException(Exception): pass + +def load_tpcds_data(node): + print 'Load tpcds...' + subprocess.call(['./tests/prepare_stress.sh']) + tables = open('tmp_stress/tpcds-kit/tools/tpcds.sql', 'r') + tables_sql = tables.read() + try: + # Create tables + node.psql(filename="tmp_stress/tpcds-kit/tools/tpcds.sql") + # Copy table data from files + for table_datafile in os.listdir('tmp_stress/tpcds-kit/tools/'): + if table_datafile.endswith(".dat"): + table_name = os.path.splitext(os.path.basename(table_datafile))[0] + copy_cmd = "\\copy %s FROM 'tmp_stress/tpcds-kit/tools/tables/%s' CSV DELIMITER '|'" % (table_name, table_datafile) + print "Load table ", table_name + node.safe_psql("TRUNCATE %s" % table_name) + node.safe_psql(copy_cmd) + except Exception, e: + raise DataLoadException('Load failed: %s' % e) + print 'done!' + +def stress_test(node): + """stress test""" + load_tpcds_data(node) + + # execute query in separate thread + async_psql = AsyncQueryExecutor(node) + sql = open("tests/query_tpcds.sql",'r').read() + aq = AsyncQueryExecutor(node) + aq.run(sql, True) + + conn = testgres.connection.NodeConnection(node) + while aq.process.is_alive(): + try: + conn.execute('SELECT * FROM pg_query_state(%d)' % aq.backend_pid) + except Exception, e: + async_psql_ex = AsyncQueryExecutor(node) + async_psql_ex.run('SELECT state, query FROM pg_stat_activity where pid = %d;' % aq.backend_pid) + async_psql_ex.wait() + print 'pg_query_state FAILED' + print 'state of backend:' + print async_psql_ex.result + raise StressTestException('Unable to get query state: %s' % e) + aq.close() From ee24bd4cbe907d59c7ae2d116943d43d6ad88c37 Mon Sep 17 00:00:00 2001 From: Sergey Cherkashin <4erkashin@list.ru> Date: Sat, 10 Nov 2018 20:05:55 +0300 Subject: [PATCH 2/5] Fix regexps in python tests. Fix testing by Travis CI. --- Dockerfile.tmpl | 2 +- run_tests.sh | 5 ++-- tests/test_cases.py | 62 ++++++++++++++++++++++----------------------- 3 files changed, 35 insertions(+), 34 deletions(-) diff --git a/Dockerfile.tmpl b/Dockerfile.tmpl index 43d3691..0aab86f 100644 --- a/Dockerfile.tmpl +++ b/Dockerfile.tmpl @@ -4,7 +4,7 @@ FROM postgres:${PG_VERSION}-alpine RUN apk add --no-cache \ openssl curl \ perl perl-ipc-run \ - make musl-dev gcc bison flex coreutils \ + make musl-dev gcc bison flex coreutils linux-headers git\ zlib-dev libedit-dev \ clang clang-analyzer \ python2 python2-dev py2-virtualenv; diff --git a/run_tests.sh b/run_tests.sh index 0053aee..3a94cea 100755 --- a/run_tests.sh +++ b/run_tests.sh @@ -144,8 +144,9 @@ if [ -f regression.diffs ]; then cat regression.diffs; fi # run python tests set +x -e -virtualenv /tmp/env && source /tmp/env/bin/activate && -pip install PyYAML && pip install psycopg2 +virtualenv /tmp/env && source /tmp/env/bin/activate +pip install PyYAML +pip install testgres set -e #exit virtualenv with error code if [ "$LEVEL" = "stress" ]; then python tests/pg_qs_test_runner.py --stress diff --git a/tests/test_cases.py b/tests/test_cases.py index 5c82bb4..d111fa6 100644 --- a/tests/test_cases.py +++ b/tests/test_cases.py @@ -53,7 +53,7 @@ def run(self, query, multiple = False): args=(self.conn, query, multiple, self.res_q, self.condition)) self.process.start() self.condition.acquire() - self.condition.wait() + self.condition.wait(5) def wait(self): self.result = self.res_q.get() @@ -135,7 +135,7 @@ def debug_output(qs, qs_len, pid, query, expected, expected2 = None): if (qs_len == 2 and expected2 and not (re.match(expected2, qs[1][3]))): print "qs[1][3]:\n", qs[1][3] - print "Expected:\n", expected + print "Expected:\n", expected2 something_happened = True if (qs[0][4] != None): print "qs[0][4]: ", qs[0][4], "Expected: None" @@ -181,8 +181,8 @@ def test_simple_query(node): -> Hash Join \(Current loop: actual rows=\d+, loop number=1\) Hash Cond: \(foo.c1 = bar.c1\) -> Seq Scan on foo \(Current loop: actual rows=\d+, loop number=1\) - -> Hash \(Current loop: actual rows=\d+, loop number=1\) - Buckets: \d+ Batches: \d+ Memory Usage: \d+kB + -> Hash \(Current loop: actual rows=\d+, loop number=1\)( + Buckets: \d+ Batches: \d+ Memory Usage: \d+kB)? -> Seq Scan on bar \(Current loop: actual rows=\d+, loop number=1\)""" qs = query_state(node, query) @@ -242,12 +242,12 @@ def test_nested_call(node): expected = 'Function Scan on n_join_foo_bar (Current loop: actual rows=0, loop number=1)' expected_nested = r"""Result \(Current loop: actual rows=0, loop number=1\) InitPlan 1 \(returns \$0\) - -> Aggregate \(Current loop: actual rows=0, loop number=1\) - -> Hash Join \(Current loop: actual rows=0, loop number=1\) + -> Aggregate \(Current loop: actual rows=\d+, loop number=1\) + -> Hash Join \(Current loop: actual rows=\d+, loop number=1\) Hash Cond: \(foo.c1 = bar.c1\) - -> Seq Scan on foo \(Current loop: actual rows=1, loop number=1\) - -> Hash \(Current loop: actual rows=0, loop number=1\) - Buckets: \d+ Batches: \d+ Memory Usage: \d+kB + -> Seq Scan on foo \(Current loop: actual rows=\d+, loop number=1\) + -> Hash \(Current loop: actual rows=\d+, loop number=1\)( + Buckets: \d+ Batches: \d+ Memory Usage: \d+kB)? -> Seq Scan on bar \(Current loop: actual rows=\d+, loop number=1\)""" conn.execute(create_function) @@ -282,7 +282,7 @@ def test_insert_on_conflict(node): util_conn.commit() qs = query_state(node, query) - debug_output(qs, 1, None, query, expected) + debug_output(qs, None, None, query, expected) assert re.match(expected, qs[0][3]) util_conn.execute(drop_field_uniqueness) @@ -317,10 +317,10 @@ def test_trigger(node): util_conn.commit() qs = query_state(node, query, {'triggers': True}, delay = 1) - debug_output(qs, 2, None, query, expected_upper+'\n'+ trigger_suffix) + debug_output(qs, None, None, query, expected_upper+'\n'+ trigger_suffix) assert re.match(expected_upper+'\n'+ trigger_suffix, qs[0][3]) qs = query_state(node, query, {'triggers': False}) - debug_output(qs, 1, None, query, expected_upper) + debug_output(qs, None, None, query, expected_upper) assert re.match(expected_upper, qs[0][3]) util_conn.execute(drop_temps) @@ -331,11 +331,11 @@ def test_costs(node): query = 'select count(*) from foo join bar on foo.c1=bar.c1' expected = r"""Aggregate \(cost=\d+.\d+..\d+.\d+ rows=\d+ width=8\) \(Current loop: actual rows=0, loop number=1\) - -> Hash Join \(cost=\d+.\d+..\d+.\d+ rows=\d+ width=0\) \(Current loop: actual rows=0, loop number=1\) + -> Hash Join \(cost=\d+.\d+..\d+.\d+ rows=\d+ width=0\) \(Current loop: actual rows=\d+, loop number=1\) Hash Cond: \(foo.c1 = bar.c1\) - -> Seq Scan on foo \(cost=0.00..\d+.\d+ rows=\d+ width=4\) \(Current loop: actual rows=1, loop number=1\) - -> Hash \(cost=\d+.\d+..\d+.\d+ rows=\d+ width=4\) \(Current loop: actual rows=0, loop number=1\) - Buckets: \d+ Batches: \d+ Memory Usage: \d+kB + -> Seq Scan on foo \(cost=0.00..\d+.\d+ rows=\d+ width=4\) \(Current loop: actual rows=\d+, loop number=1\) + -> Hash \(cost=\d+.\d+..\d+.\d+ rows=\d+ width=4\) \(Current loop: actual rows=\d+, loop number=1\)( + Buckets: \d+ Batches: \d+ Memory Usage: \d+kB)? -> Seq Scan on bar \(cost=0.00..\d+.\d+ rows=\d+ width=4\) \(Current loop: actual rows=\d+, loop number=1\)""" qs = query_state(node, query, {'costs': True}) @@ -348,14 +348,14 @@ def test_buffers(config): query = 'select count(*) from foo join bar on foo.c1=bar.c1' expected = r"""Aggregate \(Current loop: actual rows=0, loop number=1\) - -> Hash Join \(Current loop: actual rows=0, loop number=1\) + -> Hash Join \(Current loop: actual rows=\d+, loop number=1\) Hash Cond: \(foo.c1 = bar.c1\) - -> Seq Scan on foo \(Current loop: actual rows=1, loop number=1\) - Buffers: [^\n]* - -> Hash \(Current loop: actual rows=0, loop number=1\) - Buckets: \d+ Batches: \d+ Memory Usage: \d+kB - -> Seq Scan on bar \(Current loop: actual rows=\d+, loop number=1\) - Buffers: .*""" + -> Seq Scan on foo \(Current loop: actual rows=\d+, loop number=1\)( + Buffers: [^\n]*)? + -> Hash \(Current loop: actual rows=\d+, loop number=1\)( + Buckets: \d+ Batches: \d+ Memory Usage: \d+kB)? + -> Seq Scan on bar \(Current loop: actual rows=\d+, loop number=1\)( + Buffers: .*)?""" qs = query_state(config, query, {'buffers': True}, gucs = {'pg_query_state.enable_buffers' : 'on'}) @@ -367,10 +367,10 @@ def test_timing(node): query = 'select count(*) from foo join bar on foo.c1=bar.c1' expected = r"""Aggregate \(Current loop: running time=\d+.\d+ actual rows=0, loop number=1\) - -> Hash Join \(Current loop: running time=\d+.\d+ actual rows=0, loop number=1\) + -> Hash Join \(Current loop: running time=\d+.\d+ actual rows=\d+, loop number=1\) Hash Cond: \(foo.c1 = bar.c1\) -> Seq Scan on foo \(Current loop: (actual|running) time=\d+.\d+(..\d+.\d+)? (actual )?rows=\d+, loop number=1\) - -> Hash \(Current loop: running time=\d+.\d+ actual rows=0, loop number=1\)( + -> Hash \(Current loop: running time=\d+.\d+ actual rows=\d+, loop number=1\)( Buckets: \d+ Batches: \d+ Memory Usage: \d+kB)? -> Seq Scan on bar \(Current loop: (actual|running) time=\d+.\d+(..\d+.\d+)* (actual )*rows=\d+, loop number=1\)""" @@ -403,12 +403,12 @@ def test_formats(config): """test all formats of pg_query_state output""" query = 'select count(*) from foo join bar on foo.c1=bar.c1' - expected = r"""Aggregate \(Current loop: actual rows=0, loop number=1\) - -> Hash Join \(Current loop: actual rows=0, loop number=1\) + expected = r"""Aggregate \(Current loop: actual rows=\d+, loop number=1\) + -> Hash Join \(Current loop: actual rows=\d+, loop number=1\) Hash Cond: \(foo.c1 = bar.c1\) - -> Seq Scan on foo \(Current loop: actual rows=1, loop number=1\) - -> Hash \(Current loop: actual rows=0, loop number=1\) - Buckets: \d+ Batches: \d+ Memory Usage: \d+kB + -> Seq Scan on foo \(Current loop: actual rows=\d, loop number=1\) + -> Hash \(Current loop: actual rows=\d+, loop number=1\)( + Buckets: \d+ Batches: \d+ Memory Usage: \d+kB)? -> Seq Scan on bar \(Current loop: actual rows=\d+, loop number=1\)""" qs = query_state(config, query, {'format': 'text'}) @@ -489,7 +489,7 @@ def load_tpcds_data(node): def stress_test(node): """stress test""" load_tpcds_data(node) - + print 'Test running...' # execute query in separate thread async_psql = AsyncQueryExecutor(node) sql = open("tests/query_tpcds.sql",'r').read() From 320c84878c53f0c4527cd8b1b0f13020cab49571 Mon Sep 17 00:00:00 2001 From: Sergey Cherkashin <4erkashin@list.ru> Date: Wed, 14 Nov 2018 01:21:51 +0300 Subject: [PATCH 3/5] Improve stress test --- run_tests.sh | 2 + tests/query_tpcds.sql | 87 +++++++++++++++++---------------- tests/test_cases.py | 109 +++++++++++++++++++++++++----------------- 3 files changed, 113 insertions(+), 85 deletions(-) diff --git a/run_tests.sh b/run_tests.sh index 3a94cea..edfb7f7 100755 --- a/run_tests.sh +++ b/run_tests.sh @@ -146,7 +146,9 @@ if [ -f regression.diffs ]; then cat regression.diffs; fi set +x -e virtualenv /tmp/env && source /tmp/env/bin/activate pip install PyYAML +pip install psycopg2 pip install testgres +pip install progressbar2 set -e #exit virtualenv with error code if [ "$LEVEL" = "stress" ]; then python tests/pg_qs_test_runner.py --stress diff --git a/tests/query_tpcds.sql b/tests/query_tpcds.sql index d619abe..70e799e 100644 --- a/tests/query_tpcds.sql +++ b/tests/query_tpcds.sql @@ -248,7 +248,7 @@ with ssr as store where date_sk = d_date_sk and d_date between cast('2000-08-19' as date) - and (cast('2000-08-19' as date) + 14 days) + and (cast('2000-08-19' as date) + interval '14 days') and store_sk = s_store_sk group by s_store_id) , @@ -279,7 +279,7 @@ with ssr as catalog_page where date_sk = d_date_sk and d_date between cast('2000-08-19' as date) - and (cast('2000-08-19' as date) + 14 days) + and (cast('2000-08-19' as date) + interval '14 days') and page_sk = cp_catalog_page_sk group by cp_catalog_page_id) , @@ -312,7 +312,7 @@ with ssr as web_site where date_sk = d_date_sk and d_date between cast('2000-08-19' as date) - and (cast('2000-08-19' as date) + 14 days) + and (cast('2000-08-19' as date) + interval '14 days') and wsr_web_site_sk = web_site_sk group by web_site_id) select channel @@ -712,7 +712,7 @@ where and i_category in ('Men', 'Books', 'Electronics') and ws_sold_date_sk = d_date_sk and d_date between cast('2001-06-15' as date) - and (cast('2001-06-15' as date) + 30 days) + and (cast('2001-06-15' as date) + interval '30 days') group by i_item_id ,i_item_desc @@ -812,7 +812,7 @@ with cross_items as ,date_dim d3 where ws_item_sk = iws.i_item_sk and ws_sold_date_sk = d3.d_date_sk - and d3.d_year between 1999 AND 1999 + 2) + and d3.d_year between 1999 AND 1999 + 2) as sub where i_brand_id = brand_id and i_class_id = class_id and i_category_id = category_id @@ -838,7 +838,7 @@ with cross_items as from web_sales ,date_dim where ws_sold_date_sk = d_date_sk - and d_year between 1999 and 1999 + 2) x) + and d_year between 1999 and 1999 + 2) as x) select channel, i_brand_id,i_class_id,i_category_id,sum(sales), sum(number_sales) from( select 'store' channel, i_brand_id,i_class_id @@ -882,6 +882,7 @@ with cross_items as group by rollup (channel, i_brand_id,i_class_id,i_category_id) order by channel,i_brand_id,i_class_id,i_category_id limit 100; + with cross_items as (select i_item_sk ss_item_sk from item, @@ -913,7 +914,7 @@ with cross_items as ,date_dim d3 where ws_item_sk = iws.i_item_sk and ws_sold_date_sk = d3.d_date_sk - and d3.d_year between 1999 AND 1999 + 2) x + and d3.d_year between 1999 AND 1999 + 2) as x where i_brand_id = brand_id and i_class_id = class_id and i_category_id = category_id @@ -939,7 +940,7 @@ with cross_items as from web_sales ,date_dim where ws_sold_date_sk = d_date_sk - and d_year between 1999 and 1999 + 2) x) + and d_year between 1999 and 1999 + 2) as x) select this_year.channel ty_channel ,this_year.i_brand_id ty_brand ,this_year.i_class_id ty_class @@ -1022,7 +1023,7 @@ from ,call_center where d_date between '2002-4-01' and - (cast('2002-4-01' as date) + 60 days) + (cast('2002-4-01' as date) + interval '60 days') and cs1.cs_ship_date_sk = d_date_sk and cs1.cs_ship_addr_sk = ca_address_sk and ca_state = 'PA' @@ -1161,7 +1162,7 @@ select i_item_id and i_category in ('Books', 'Music', 'Sports') and cs_sold_date_sk = d_date_sk and d_date between cast('2002-06-18' as date) - and (cast('2002-06-18' as date) + 30 days) + and (cast('2002-06-18' as date) + interval '30 days') group by i_item_id ,i_item_desc ,i_category @@ -1193,8 +1194,8 @@ select * and i_item_sk = inv_item_sk and inv_warehouse_sk = w_warehouse_sk and inv_date_sk = d_date_sk - and d_date between (cast ('1999-06-22' as date) - 30 days) - and (cast ('1999-06-22' as date) + 30 days) + and d_date between (cast ('1999-06-22' as date) - interval '30 days') + and (cast ('1999-06-22' as date) + interval '30 days') group by w_warehouse_name, i_item_id) x where (case when inv_before > 0 then inv_after / inv_before @@ -1238,14 +1239,15 @@ with frequent_ss_items as having count(*) >4), max_store_sales as (select max(csales) tpcds_cmax - from (select c_customer_sk,sum(ss_quantity*ss_sales_price) csales + from (select c_customer_sk,sum(ss_quantity*ss_sales_price) as csales from store_sales ,customer ,date_dim where ss_customer_sk = c_customer_sk and ss_sold_date_sk = d_date_sk and d_year in (2000,2000+1,2000+2,2000+3) - group by c_customer_sk)), + group by c_customer_sk) as scsales + ), best_ss_customer as (select c_customer_sk,sum(ss_quantity*ss_sales_price) ssales from store_sales @@ -1273,8 +1275,9 @@ from and d_moy = 7 and ws_sold_date_sk = d_date_sk and ws_item_sk in (select item_sk from frequent_ss_items) - and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer)) + and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer)) as foo limit 100; + with frequent_ss_items as (select substr(i_item_desc,1,30) itemdesc,i_item_sk item_sk,d_date solddate,count(*) cnt from store_sales @@ -1294,7 +1297,7 @@ with frequent_ss_items as where ss_customer_sk = c_customer_sk and ss_sold_date_sk = d_date_sk and d_year in (2000,2000+1,2000+2,2000+3) - group by c_customer_sk)), + group by c_customer_sk) as scsales), best_ss_customer as (select c_customer_sk,sum(ss_quantity*ss_sales_price) ssales from store_sales @@ -1327,7 +1330,7 @@ with frequent_ss_items as and ws_item_sk in (select item_sk from frequent_ss_items) and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer) and ws_bill_customer_sk = c_customer_sk - group by c_last_name,c_first_name) + group by c_last_name,c_first_name) as sub order by c_last_name,c_first_name,sales limit 100; @@ -1724,7 +1727,7 @@ where i_manufact_id = 722 and i_item_sk = cs_item_sk and d_date between '2001-03-09' and - (cast('2001-03-09' as date) + 90 days) + (cast('2001-03-09' as date) + interval '90 days') and d_date_sk = cs_sold_date_sk and cs_ext_discount_amt > ( @@ -1736,7 +1739,7 @@ and cs_ext_discount_amt where cs_item_sk = i_item_sk and d_date between '2001-03-09' and - (cast('2001-03-09' as date) + 90 days) + (cast('2001-03-09' as date) + interval '90 days') and d_date_sk = cs_sold_date_sk ) limit 100; @@ -1944,7 +1947,7 @@ select i_item_id where i_current_price between 29 and 29 + 30 and inv_item_sk = i_item_sk and d_date_sk=inv_date_sk - and d_date between cast('2002-03-29' as date) and (cast('2002-03-29' as date) + 60 days) + and d_date between cast('2002-03-29' as date) and (cast('2002-03-29' as date) + interval '60 days') and i_manufact_id in (705,742,777,944) and inv_quantity_on_hand between 100 and 500 and cs_item_sk = i_item_sk @@ -2050,8 +2053,8 @@ select and i_item_sk = cs_item_sk and cs_warehouse_sk = w_warehouse_sk and cs_sold_date_sk = d_date_sk - and d_date between (cast ('2001-05-02' as date) - 30 days) - and (cast ('2001-05-02' as date) + 30 days) + and d_date between (cast ('2001-05-02' as date) - interval '30 days') + and (cast ('2001-05-02' as date) + interval '30 days') group by w_state,i_item_id order by w_state,i_item_id @@ -2395,7 +2398,7 @@ select channel, item, return_ratio, return_rank, currency_rank from and d_moy = 11 group by ws.ws_item_sk ) in_web - ) web + ) as web where ( web.return_rank <= 10 @@ -2438,7 +2441,7 @@ select channel, item, return_ratio, return_rank, currency_rank from and d_moy = 11 group by cs.cs_item_sk ) in_cat - ) catalog + ) as catalog where ( catalog.return_rank <= 10 @@ -2477,13 +2480,13 @@ select channel, item, return_ratio, return_rank, currency_rank from and d_moy = 11 group by sts.ss_item_sk ) in_store - ) store + ) as store where ( store.return_rank <= 10 or store.currency_rank <= 10 ) - ) + )as tab order by 1,4,5,2 limit 100; @@ -3927,7 +3930,7 @@ with ss as store where ss_sold_date_sk = d_date_sk and d_date between cast('2000-08-10' as date) - and (cast('2000-08-10' as date) + 30 days) + and (cast('2000-08-10' as date) + interval '30 days') and ss_store_sk = s_store_sk group by s_store_sk) , @@ -3940,7 +3943,7 @@ with ss as store where sr_returned_date_sk = d_date_sk and d_date between cast('2000-08-10' as date) - and (cast('2000-08-10' as date) + 30 days) + and (cast('2000-08-10' as date) + interval '30 days') and sr_store_sk = s_store_sk group by s_store_sk), cs as @@ -3951,7 +3954,7 @@ with ss as date_dim where cs_sold_date_sk = d_date_sk and d_date between cast('2000-08-10' as date) - and (cast('2000-08-10' as date) + 30 days) + and (cast('2000-08-10' as date) + interval '30 days') group by cs_call_center_sk ), cr as @@ -3962,7 +3965,7 @@ with ss as date_dim where cr_returned_date_sk = d_date_sk and d_date between cast('2000-08-10' as date) - and (cast('2000-08-10' as date) + 30 days) + and (cast('2000-08-10' as date) + interval '30 days') group by cr_call_center_sk ), ws as @@ -3974,7 +3977,7 @@ with ss as web_page where ws_sold_date_sk = d_date_sk and d_date between cast('2000-08-10' as date) - and (cast('2000-08-10' as date) + 30 days) + and (cast('2000-08-10' as date) + interval '30 days') and ws_web_page_sk = wp_web_page_sk group by wp_web_page_sk), wr as @@ -3986,7 +3989,7 @@ with ss as web_page where wr_returned_date_sk = d_date_sk and d_date between cast('2000-08-10' as date) - and (cast('2000-08-10' as date) + 30 days) + and (cast('2000-08-10' as date) + interval '30 days') and wr_web_page_sk = wp_web_page_sk group by wp_web_page_sk) select channel @@ -4014,7 +4017,7 @@ with ss as select 'web channel' as channel , ws.wp_web_page_sk as id , sales - , coalesce(returns, 0) returns + , coalesce(returns, 0) as returns , (profit - coalesce(profit_loss,0)) as profit from ws left join wr on ws.wp_web_page_sk = wr.wp_web_page_sk @@ -4120,7 +4123,7 @@ with ssr as promotion where ss_sold_date_sk = d_date_sk and d_date between cast('2002-08-14' as date) - and (cast('2002-08-14' as date) + 30 days) + and (cast('2002-08-14' as date) + interval '30 days') and ss_store_sk = s_store_sk and ss_item_sk = i_item_sk and i_current_price > 50 @@ -4141,7 +4144,7 @@ with ssr as promotion where cs_sold_date_sk = d_date_sk and d_date between cast('2002-08-14' as date) - and (cast('2002-08-14' as date) + 30 days) + and (cast('2002-08-14' as date) + interval '30 days') and cs_catalog_page_sk = cp_catalog_page_sk and cs_item_sk = i_item_sk and i_current_price > 50 @@ -4162,7 +4165,7 @@ group by cp_catalog_page_id) promotion where ws_sold_date_sk = d_date_sk and d_date between cast('2002-08-14' as date) - and (cast('2002-08-14' as date) + 30 days) + and (cast('2002-08-14' as date) + interval '30 days') and ws_web_site_sk = web_site_sk and ws_item_sk = i_item_sk and i_current_price > 50 @@ -4241,7 +4244,7 @@ select i_item_id where i_current_price between 58 and 58+30 and inv_item_sk = i_item_sk and d_date_sk=inv_date_sk - and d_date between cast('2001-01-13' as date) and (cast('2001-01-13' as date) + 60 days) + and d_date between cast('2001-01-13' as date) and (cast('2001-01-13' as date) + interval '60 days') and i_manufact_id in (259,559,580,485) and inv_quantity_on_hand between 100 and 500 and ss_item_sk = i_item_sk @@ -4657,7 +4660,7 @@ where i_manufact_id = 714 and i_item_sk = ws_item_sk and d_date between '2000-02-01' and - (cast('2000-02-01' as date) + 90 days) + (cast('2000-02-01' as date) + interval '90 days') and d_date_sk = ws_sold_date_sk and ws_ext_discount_amt > ( @@ -4669,7 +4672,7 @@ and ws_ext_discount_amt WHERE ws_item_sk = i_item_sk and d_date between '2000-02-01' and - (cast('2000-02-01' as date) + 90 days) + (cast('2000-02-01' as date) + interval '90 days') and d_date_sk = ws_sold_date_sk ) order by sum(ws_ext_discount_amt) @@ -4706,7 +4709,7 @@ from ,web_site where d_date between '2002-5-01' and - (cast('2002-5-01' as date) + 60 days) + (cast('2002-5-01' as date) + interval '60 days') and ws1.ws_ship_date_sk = d_date_sk and ws1.ws_ship_addr_sk = ca_address_sk and ca_state = 'OK' @@ -4740,7 +4743,7 @@ from ,web_site where d_date between '2001-4-01' and - (cast('2001-4-01' as date) + 60 days) + (cast('2001-4-01' as date) + interval '60 days') and ws1.ws_ship_date_sk = d_date_sk and ws1.ws_ship_addr_sk = ca_address_sk and ca_state = 'VA' @@ -4814,7 +4817,7 @@ where and i_category in ('Men', 'Sports', 'Jewelry') and ss_sold_date_sk = d_date_sk and d_date between cast('1999-02-05' as date) - and (cast('1999-02-05' as date) + 30 days) + and (cast('1999-02-05' as date) + interval '60 days') group by i_item_id ,i_item_desc diff --git a/tests/test_cases.py b/tests/test_cases.py index d111fa6..a6ebba8 100644 --- a/tests/test_cases.py +++ b/tests/test_cases.py @@ -1,4 +1,5 @@ import testgres +import psycopg2.extensions import json import re import time @@ -8,6 +9,9 @@ from multiprocessing import Process, Queue, Condition import subprocess import os +import progressbar + +class SQLExecuteException(Exception): pass class AsyncQueryExecutor(): """ Run query in separate process """ @@ -21,36 +25,45 @@ def __init__(self, node): self.condition = Condition() self.result = [] - def run_internal(self, conn, query, multiple, res_q, condition): + def run_internal(self, conn, query, res_q, condition): condition.acquire() - commands = [] - if multiple: - commands = query.split(';') - for i, cmd in enumerate(query.split(';')): - if (len(cmd.strip()) == 0): - del commands[i] - else: - commands.append(query) - conn.begin() condition.notify() condition.release() - for cmd in commands: - try: - res = conn.execute(cmd) - res_q.put(res) - conn.commit() - except Exception, e: - print 'Unable to execute query: "', cmd ,'"' - print 'Reason: %s' %e - conn.rollback() - continue + try: + res = conn.execute(query) + res_q.put(res) + conn.commit() + except Exception, e: + conn.rollback() + print 'Unable to execute query: "', query ,'"' + raise SQLExecuteException( + 'Unable to execute query: "%s"\nReason: %s' %(query, e)) return + def run_stress(self, conn, query, condition): + condition.acquire() + condition.notify() + condition.release() + i = 1 + try: + conn.begin() + conn.execute(query) + conn.commit() + except psycopg2.extensions.QueryCanceledError: + pass + except Exception, e: + print "Unable to execute: %s" %query + print "Reason: %s" %e + def run(self, query, multiple = False): """Run async query""" - self.process = Process(target=self.run_internal, - args=(self.conn, query, multiple, self.res_q, self.condition)) + if multiple: + self.process = Process(target=self.run_stress, + args=(self.conn, query, self.condition)) + else: + self.process = Process(target=self.run_internal, + args=(self.conn, query, self.res_q, self.condition)) self.process.start() self.condition.acquire() self.condition.wait(5) @@ -61,13 +74,15 @@ def wait(self): self.process.join() def terminate(self): - if self.process.is_alive(): + if self.node.pid: self.node.psql("SELECT pg_cancel_backend(%d)" % self.backend_pid) + if self.process.is_alive(): self.process.terminate() def close(self): self.terminate() - self.conn.close() + if self.node.pid: + self.conn.close() def pqs_args(pid, verbose=False, costs=False, timing=False, buffers=False, triggers=False, format='text'): @@ -469,8 +484,6 @@ class StressTestException(Exception): pass def load_tpcds_data(node): print 'Load tpcds...' subprocess.call(['./tests/prepare_stress.sh']) - tables = open('tmp_stress/tpcds-kit/tools/tpcds.sql', 'r') - tables_sql = tables.read() try: # Create tables node.psql(filename="tmp_stress/tpcds-kit/tools/tpcds.sql") @@ -491,21 +504,31 @@ def stress_test(node): load_tpcds_data(node) print 'Test running...' # execute query in separate thread - async_psql = AsyncQueryExecutor(node) - sql = open("tests/query_tpcds.sql",'r').read() - aq = AsyncQueryExecutor(node) - aq.run(sql, True) - - conn = testgres.connection.NodeConnection(node) - while aq.process.is_alive(): + with open("tests/query_tpcds.sql",'r') as f: + sql = f.read() + commands = sql.split(';') + for i, cmd in enumerate(sql.split(';')): + if (len(cmd.strip()) == 0): + del commands[i] + + timeout_list = [] + bar = progressbar.ProgressBar(max_value=len(commands)) + for i, cmd in enumerate(commands): + bar.update(i+1) try: - conn.execute('SELECT * FROM pg_query_state(%d)' % aq.backend_pid) - except Exception, e: - async_psql_ex = AsyncQueryExecutor(node) - async_psql_ex.run('SELECT state, query FROM pg_stat_activity where pid = %d;' % aq.backend_pid) - async_psql_ex.wait() - print 'pg_query_state FAILED' - print 'state of backend:' - print async_psql_ex.result - raise StressTestException('Unable to get query state: %s' % e) - aq.close() + conn = testgres.connection.NodeConnection(node) + aq = AsyncQueryExecutor(node) + # set query timeout to 10 sec + set_guc(aq.conn, 'statement_timeout', 10000) + set_guc(conn, 'statement_timeout', 10000) + aq.run(cmd, True) + while aq.process.is_alive() and node.pid: + conn.execute('SELECT * FROM pg_query_state(%d)' % aq.backend_pid) + #TODO: Put here testgres exception when supported + except psycopg2.extensions.QueryCanceledError: + timeout_list.append(i) + finally: + aq.close() + conn.close() + if len(timeout_list) > 0: + print 'It was pg_query_state timeouts(10s) on queries: ', timeout_list From fa6ce2d8604e43beaad06f230763e15c209c7c14 Mon Sep 17 00:00:00 2001 From: Sergey Cherkashin <4erkashin@list.ru> Date: Wed, 14 Nov 2018 19:29:24 +0300 Subject: [PATCH 4/5] Fix sql queries in stress test --- tests/query_tpcds.sql | 876 +++++++++++++++++++++--------------------- tests/test_cases.py | 7 +- 2 files changed, 443 insertions(+), 440 deletions(-) diff --git a/tests/query_tpcds.sql b/tests/query_tpcds.sql index 70e799e..e82fca1 100644 --- a/tests/query_tpcds.sql +++ b/tests/query_tpcds.sql @@ -29,12 +29,12 @@ with wscs as ,sales_price from (select ws_sold_date_sk sold_date_sk ,ws_ext_sales_price sales_price - from web_sales + from web_sales union all select cs_sold_date_sk sold_date_sk ,cs_ext_sales_price sales_price from catalog_sales) as sdsp), - wswscs as + wswscs as (select d_week_seq, sum(case when (d_day_name='Sunday') then sales_price else null end) sun_sales, sum(case when (d_day_name='Monday') then sales_price else null end) mon_sales, @@ -64,7 +64,7 @@ with wscs as ,thu_sales thu_sales1 ,fri_sales fri_sales1 ,sat_sales sat_sales1 - from wswscs,date_dim + from wswscs,date_dim where date_dim.d_week_seq = wswscs.d_week_seq and d_year = 1998) y, (select wswscs.d_week_seq d_week_seq2 @@ -76,7 +76,7 @@ with wscs as ,fri_sales fri_sales2 ,sat_sales sat_sales2 from wswscs - ,date_dim + ,date_dim where date_dim.d_week_seq = wswscs.d_week_seq and d_year = 1998+1) z where d_week_seq1=d_week_seq2-53 @@ -84,11 +84,11 @@ with wscs as -- end query 2 in stream 0 using template query2.tpl -- start query 3 in stream 0 using template query3.tpl -select dt.d_year - ,item.i_brand_id brand_id +select dt.d_year + ,item.i_brand_id brand_id ,item.i_brand brand ,sum(ss_sales_price) sum_agg - from date_dim dt + from date_dim dt ,store_sales ,item where dt.d_date_sk = store_sales.ss_sold_date_sk @@ -178,7 +178,7 @@ union all ,c_email_address ,d_year ) - select + select t_s_secyear.customer_id ,t_s_secyear.customer_first_name ,t_s_secyear.customer_last_name @@ -247,7 +247,7 @@ with ssr as date_dim, store where date_sk = d_date_sk - and d_date between cast('2000-08-19' as date) + and d_date between cast('2000-08-19' as date) and (cast('2000-08-19' as date) + interval '14 days') and store_sk = s_store_sk group by s_store_id) @@ -320,7 +320,7 @@ with ssr as , sum(sales) as sales , sum(returns) as returns , sum(profit) as profit - from + from (select 'store channel' as channel , 'store' || s_store_id as id , sales @@ -359,37 +359,37 @@ select a.ca_state state, count(*) cnt and c.c_customer_sk = s.ss_customer_sk and s.ss_sold_date_sk = d.d_date_sk and s.ss_item_sk = i.i_item_sk - and d.d_month_seq = + and d.d_month_seq = (select distinct (d_month_seq) from date_dim where d_year = 2002 and d_moy = 3 ) - and i.i_current_price > 1.2 * - (select avg(j.i_current_price) - from item j + and i.i_current_price > 1.2 * + (select avg(j.i_current_price) + from item j where j.i_category = i.i_category) group by a.ca_state having count(*) >= 10 - order by cnt, a.ca_state + order by cnt, a.ca_state limit 100; -- end query 6 in stream 0 using template query6.tpl -- start query 7 in stream 0 using template query7.tpl -select i_item_id, +select i_item_id, avg(ss_quantity) agg1, avg(ss_list_price) agg2, avg(ss_coupon_amt) agg3, - avg(ss_sales_price) agg4 + avg(ss_sales_price) agg4 from store_sales, customer_demographics, date_dim, item, promotion where ss_sold_date_sk = d_date_sk and ss_item_sk = i_item_sk and ss_cdemo_sk = cd_demo_sk and ss_promo_sk = p_promo_sk and - cd_gender = 'F' and + cd_gender = 'F' and cd_marital_status = 'W' and cd_education_status = 'College' and (p_channel_email = 'N' or p_channel_event = 'N') and - d_year = 2001 + d_year = 2001 group by i_item_id order by i_item_id limit 100; @@ -504,12 +504,12 @@ select s_store_name -- end query 8 in stream 0 using template query8.tpl -- start query 9 in stream 0 using template query9.tpl -select case when (select count(*) - from store_sales +select case when (select count(*) + from store_sales where ss_quantity between 1 and 20) > 1071 - then (select avg(ss_ext_tax) - from store_sales - where ss_quantity between 1 and 20) + then (select avg(ss_ext_tax) + from store_sales + where ss_quantity between 1 and 20) else (select avg(ss_net_paid_inc_tax) from store_sales where ss_quantity between 1 and 20) end bucket1 , @@ -518,7 +518,7 @@ select case when (select count(*) where ss_quantity between 21 and 40) > 39161 then (select avg(ss_ext_tax) from store_sales - where ss_quantity between 21 and 40) + where ss_quantity between 21 and 40) else (select avg(ss_net_paid_inc_tax) from store_sales where ss_quantity between 21 and 40) end bucket2, @@ -555,7 +555,7 @@ where r_reason_sk = 1 -- end query 9 in stream 0 using template query9.tpl -- start query 10 in stream 0 using template query10.tpl -select +select cd_gender, cd_marital_status, cd_education_status, @@ -575,7 +575,7 @@ select where c.c_current_addr_sk = ca.ca_address_sk and ca_county in ('Fairfield County','Campbell County','Washtenaw County','Escambia County','Cleburne County') and - cd_demo_sk = c.c_current_cdemo_sk and + cd_demo_sk = c.c_current_cdemo_sk and exists (select * from store_sales,date_dim where c.c_customer_sk = ss_customer_sk and @@ -587,8 +587,8 @@ select where c.c_customer_sk = ws_bill_customer_sk and ws_sold_date_sk = d_date_sk and d_year = 2001 and - d_moy between 3 ANd 3+3) or - exists (select * + d_moy between 3 ANd 3+3) or + exists (select * from catalog_sales,date_dim where c.c_customer_sk = cs_ship_customer_sk and cs_sold_date_sk = d_date_sk and @@ -633,11 +633,11 @@ with year_total as ( group by c_customer_id ,c_first_name ,c_last_name - ,c_preferred_cust_flag + ,c_preferred_cust_flag ,c_birth_country ,c_login ,c_email_address - ,d_year + ,d_year union all select c_customer_id customer_id ,c_first_name customer_first_name @@ -657,13 +657,13 @@ with year_total as ( group by c_customer_id ,c_first_name ,c_last_name - ,c_preferred_cust_flag + ,c_preferred_cust_flag ,c_birth_country ,c_login ,c_email_address ,d_year ) - select + select t_s_secyear.customer_id ,t_s_secyear.customer_first_name ,t_s_secyear.customer_last_name @@ -696,30 +696,30 @@ limit 100; -- end query 11 in stream 0 using template query11.tpl -- start query 12 in stream 0 using template query12.tpl select i_item_id - ,i_item_desc - ,i_category - ,i_class + ,i_item_desc + ,i_category + ,i_class ,i_current_price - ,sum(ws_ext_sales_price) as itemrevenue + ,sum(ws_ext_sales_price) as itemrevenue ,sum(ws_ext_sales_price)*100/sum(sum(ws_ext_sales_price)) over (partition by i_class) as revenueratio -from +from web_sales - ,item + ,item ,date_dim -where - ws_item_sk = i_item_sk +where + ws_item_sk = i_item_sk and i_category in ('Men', 'Books', 'Electronics') and ws_sold_date_sk = d_date_sk - and d_date between cast('2001-06-15' as date) + and d_date between cast('2001-06-15' as date) and (cast('2001-06-15' as date) + interval '30 days') -group by +group by i_item_id - ,i_item_desc + ,i_item_desc ,i_category ,i_class ,i_current_price -order by +order by i_category ,i_class ,i_item_id @@ -746,36 +746,36 @@ select avg(ss_quantity) and cd_marital_status = 'M' and cd_education_status = 'College' and ss_sales_price between 100.00 and 150.00 - and hd_dep_count = 3 + and hd_dep_count = 3 )or (ss_hdemo_sk=hd_demo_sk and cd_demo_sk = ss_cdemo_sk and cd_marital_status = 'D' and cd_education_status = 'Primary' - and ss_sales_price between 50.00 and 100.00 + and ss_sales_price between 50.00 and 100.00 and hd_dep_count = 1 - ) or + ) or (ss_hdemo_sk=hd_demo_sk and cd_demo_sk = ss_cdemo_sk and cd_marital_status = 'W' and cd_education_status = '2 yr Degree' - and ss_sales_price between 150.00 and 200.00 - and hd_dep_count = 1 + and ss_sales_price between 150.00 and 200.00 + and hd_dep_count = 1 )) and((ss_addr_sk = ca_address_sk and ca_country = 'United States' and ca_state in ('IL', 'TN', 'TX') - and ss_net_profit between 100 and 200 + and ss_net_profit between 100 and 200 ) or (ss_addr_sk = ca_address_sk and ca_country = 'United States' and ca_state in ('WY', 'OH', 'ID') - and ss_net_profit between 150 and 300 + and ss_net_profit between 150 and 300 ) or (ss_addr_sk = ca_address_sk and ca_country = 'United States' and ca_state in ('MS', 'SC', 'IA') - and ss_net_profit between 50 and 250 + and ss_net_profit between 50 and 250 )) ; @@ -793,7 +793,7 @@ with cross_items as where ss_item_sk = iss.i_item_sk and ss_sold_date_sk = d1.d_date_sk and d1.d_year between 1999 AND 1999 + 2 - intersect + intersect select ics.i_brand_id ,ics.i_class_id ,ics.i_category_id @@ -825,13 +825,13 @@ with cross_items as ,date_dim where ss_sold_date_sk = d_date_sk and d_year between 1999 and 1999 + 2 - union all - select cs_quantity quantity + union all + select cs_quantity quantity ,cs_list_price list_price from catalog_sales ,date_dim where cs_sold_date_sk = d_date_sk - and d_year between 1999 and 1999 + 2 + and d_year between 1999 and 1999 + 2 union all select ws_quantity quantity ,ws_list_price list_price @@ -850,7 +850,7 @@ with cross_items as where ss_item_sk in (select ss_item_sk from cross_items) and ss_item_sk = i_item_sk and ss_sold_date_sk = d_date_sk - and d_year = 1999+2 + and d_year = 1999+2 and d_moy = 11 group by i_brand_id,i_class_id,i_category_id having sum(ss_quantity*ss_list_price) > (select average_sales from avg_sales) @@ -862,7 +862,7 @@ with cross_items as where cs_item_sk in (select ss_item_sk from cross_items) and cs_item_sk = i_item_sk and cs_sold_date_sk = d_date_sk - and d_year = 1999+2 + and d_year = 1999+2 and d_moy = 11 group by i_brand_id,i_class_id,i_category_id having sum(cs_quantity*cs_list_price) > (select average_sales from avg_sales) @@ -952,11 +952,11 @@ with cross_items as ,last_year.i_class_id ly_class ,last_year.i_category_id ly_category ,last_year.sales ly_sales - ,last_year.number_sales ly_number_sales + ,last_year.number_sales ly_number_sales from (select 'store' channel, i_brand_id,i_class_id,i_category_id ,sum(ss_quantity*ss_list_price) sales, count(*) number_sales - from store_sales + from store_sales ,item ,date_dim where ss_item_sk in (select ss_item_sk from cross_items) @@ -999,7 +999,7 @@ select ca_zip ,customer_address ,date_dim where cs_bill_customer_sk = c_customer_sk - and c_current_addr_sk = ca_address_sk + and c_current_addr_sk = ca_address_sk and ( substr(ca_zip,1,5) in ('85669', '86197','88274','83405','86475', '85392', '85460', '80348', '81792') or ca_state in ('CA','WA','GA') @@ -1012,7 +1012,7 @@ select ca_zip -- end query 15 in stream 0 using template query15.tpl -- start query 16 in stream 0 using template query16.tpl -select +select count(distinct cs_order_number) as "order count" ,sum(cs_ext_ship_cost) as "total shipping cost" ,sum(cs_net_profit) as "total net profit" @@ -1022,7 +1022,7 @@ from ,customer_address ,call_center where - d_date between '2002-4-01' and + d_date between '2002-4-01' and (cast('2002-4-01' as date) + interval '60 days') and cs1.cs_ship_date_sk = d_date_sk and cs1.cs_ship_addr_sk = ca_address_sk @@ -1090,7 +1090,7 @@ limit 100; -- start query 18 in stream 0 using template query18.tpl select i_item_id, ca_country, - ca_state, + ca_state, ca_county, avg( cast(cs_quantity as decimal(12,2))) agg1, avg( cast(cs_list_price as decimal(12,2))) agg2, @@ -1099,13 +1099,13 @@ select i_item_id, avg( cast(cs_net_profit as decimal(12,2))) agg5, avg( cast(c_birth_year as decimal(12,2))) agg6, avg( cast(cd1.cd_dep_count as decimal(12,2))) agg7 - from catalog_sales, customer_demographics cd1, + from catalog_sales, customer_demographics cd1, customer_demographics cd2, customer, customer_address, date_dim, item where cs_sold_date_sk = d_date_sk and cs_item_sk = i_item_sk and cs_bill_cdemo_sk = cd1.cd_demo_sk and cs_bill_customer_sk = c_customer_sk and - cd1.cd_gender = 'F' and + cd1.cd_gender = 'F' and cd1.cd_education_status = 'Primary' and c_current_cdemo_sk = cd2.cd_demo_sk and c_current_addr_sk = ca_address_sk and @@ -1115,7 +1115,7 @@ select i_item_id, ,'GA','MT','IN','CA') group by rollup (i_item_id, ca_country, ca_state, ca_county) order by ca_country, - ca_state, + ca_state, ca_county, i_item_id limit 100; @@ -1130,10 +1130,10 @@ select i_brand_id brand_id, i_brand brand, i_manufact_id, i_manufact, and i_manager_id=14 and d_moy=11 and d_year=2002 - and ss_customer_sk = c_customer_sk + and ss_customer_sk = c_customer_sk and c_current_addr_sk = ca_address_sk - and substr(ca_zip,1,5) <> substr(s_zip,1,5) - and ss_store_sk = s_store_sk + and substr(ca_zip,1,5) <> substr(s_zip,1,5) + and ss_store_sk = s_store_sk group by i_brand ,i_brand_id ,i_manufact_id @@ -1148,23 +1148,23 @@ limit 100 ; -- end query 19 in stream 0 using template query19.tpl -- start query 20 in stream 0 using template query20.tpl select i_item_id - ,i_item_desc - ,i_category - ,i_class + ,i_item_desc + ,i_category + ,i_class ,i_current_price - ,sum(cs_ext_sales_price) as itemrevenue + ,sum(cs_ext_sales_price) as itemrevenue ,sum(cs_ext_sales_price)*100/sum(sum(cs_ext_sales_price)) over (partition by i_class) as revenueratio from catalog_sales - ,item + ,item ,date_dim - where cs_item_sk = i_item_sk + where cs_item_sk = i_item_sk and i_category in ('Books', 'Music', 'Sports') and cs_sold_date_sk = d_date_sk - and d_date between cast('2002-06-18' as date) + and d_date between cast('2002-06-18' as date) and (cast('2002-06-18' as date) + interval '30 days') group by i_item_id - ,i_item_desc + ,i_item_desc ,i_category ,i_class ,i_current_price @@ -1181,10 +1181,10 @@ select * from(select w_warehouse_name ,i_item_id ,sum(case when (cast(d_date as date) < cast ('1999-06-22' as date)) - then inv_quantity_on_hand + then inv_quantity_on_hand else 0 end) as inv_before ,sum(case when (cast(d_date as date) >= cast ('1999-06-22' as date)) - then inv_quantity_on_hand + then inv_quantity_on_hand else 0 end) as inv_after from inventory ,warehouse @@ -1197,8 +1197,8 @@ select * and d_date between (cast ('1999-06-22' as date) - interval '30 days') and (cast ('1999-06-22' as date) + interval '30 days') group by w_warehouse_name, i_item_id) x - where (case when inv_before > 0 - then inv_after / inv_before + where (case when inv_before > 0 + then inv_after / inv_before else null end) between 2.0/3.0 and 3.0/2.0 order by w_warehouse_name @@ -1227,25 +1227,25 @@ limit 100; -- end query 22 in stream 0 using template query22.tpl -- start query 23 in stream 0 using template query23.tpl -with frequent_ss_items as +with frequent_ss_items as (select substr(i_item_desc,1,30) itemdesc,i_item_sk item_sk,d_date solddate,count(*) cnt from store_sales - ,date_dim + ,date_dim ,item where ss_sold_date_sk = d_date_sk - and ss_item_sk = i_item_sk + and ss_item_sk = i_item_sk and d_year in (2000,2000+1,2000+2,2000+3) group by substr(i_item_desc,1,30),i_item_sk,d_date having count(*) >4), max_store_sales as - (select max(csales) tpcds_cmax + (select max(csales) tpcds_cmax from (select c_customer_sk,sum(ss_quantity*ss_sales_price) as csales from store_sales ,customer - ,date_dim + ,date_dim where ss_customer_sk = c_customer_sk and ss_sold_date_sk = d_date_sk - and d_year in (2000,2000+1,2000+2,2000+3) + and d_year in (2000,2000+1,2000+2,2000+3) group by c_customer_sk) as scsales ), best_ss_customer as @@ -1261,21 +1261,21 @@ from select sum(sales) from (select cs_quantity*cs_list_price sales from catalog_sales - ,date_dim - where d_year = 2000 - and d_moy = 7 - and cs_sold_date_sk = d_date_sk + ,date_dim + where d_year = 2000 + and d_moy = 7 + and cs_sold_date_sk = d_date_sk and cs_item_sk in (select item_sk from frequent_ss_items) and cs_bill_customer_sk in (select c_customer_sk from best_ss_customer) union all select ws_quantity*ws_list_price sales - from web_sales - ,date_dim - where d_year = 2000 - and d_moy = 7 - and ws_sold_date_sk = d_date_sk + from web_sales + ,date_dim + where d_year = 2000 + and d_moy = 7 + and ws_sold_date_sk = d_date_sk and ws_item_sk in (select item_sk from frequent_ss_items) - and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer)) as foo + and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer)) as foo limit 100; with frequent_ss_items as @@ -1293,7 +1293,7 @@ with frequent_ss_items as from (select c_customer_sk,sum(ss_quantity*ss_sales_price) csales from store_sales ,customer - ,date_dim + ,date_dim where ss_customer_sk = c_customer_sk and ss_sold_date_sk = d_date_sk and d_year in (2000,2000+1,2000+2,2000+3) @@ -1311,26 +1311,26 @@ with frequent_ss_items as from (select c_last_name,c_first_name,sum(cs_quantity*cs_list_price) sales from catalog_sales ,customer - ,date_dim - where d_year = 2000 - and d_moy = 7 - and cs_sold_date_sk = d_date_sk + ,date_dim + where d_year = 2000 + and d_moy = 7 + and cs_sold_date_sk = d_date_sk and cs_item_sk in (select item_sk from frequent_ss_items) and cs_bill_customer_sk in (select c_customer_sk from best_ss_customer) - and cs_bill_customer_sk = c_customer_sk + and cs_bill_customer_sk = c_customer_sk group by c_last_name,c_first_name union all select c_last_name,c_first_name,sum(ws_quantity*ws_list_price) sales from web_sales ,customer - ,date_dim - where d_year = 2000 - and d_moy = 7 - and ws_sold_date_sk = d_date_sk + ,date_dim + where d_year = 2000 + and d_moy = 7 + and ws_sold_date_sk = d_date_sk and ws_item_sk in (select item_sk from frequent_ss_items) and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer) and ws_bill_customer_sk = c_customer_sk - group by c_last_name,c_first_name) as sub + group by c_last_name,c_first_name) as sub order by c_last_name,c_first_name,sales limit 100; @@ -1443,7 +1443,7 @@ order by c_last_name -- end query 24 in stream 0 using template query24.tpl -- start query 25 in stream 0 using template query25.tpl -select +select i_item_id ,i_item_desc ,s_store_id @@ -1475,7 +1475,7 @@ select and sr_customer_sk = cs_bill_customer_sk and sr_item_sk = cs_item_sk and cs_sold_date_sk = d3.d_date_sk - and d3.d_moy between 4 and 10 + and d3.d_moy between 4 and 10 and d3.d_year = 1999 group by i_item_id @@ -1491,21 +1491,21 @@ select -- end query 25 in stream 0 using template query25.tpl -- start query 26 in stream 0 using template query26.tpl -select i_item_id, +select i_item_id, avg(cs_quantity) agg1, avg(cs_list_price) agg2, avg(cs_coupon_amt) agg3, - avg(cs_sales_price) agg4 + avg(cs_sales_price) agg4 from catalog_sales, customer_demographics, date_dim, item, promotion where cs_sold_date_sk = d_date_sk and cs_item_sk = i_item_sk and cs_bill_cdemo_sk = cd_demo_sk and cs_promo_sk = p_promo_sk and - cd_gender = 'M' and + cd_gender = 'M' and cd_marital_status = 'W' and cd_education_status = 'Unknown' and (p_channel_email = 'N' or p_channel_event = 'N') and - d_year = 2002 + d_year = 2002 group by i_item_id order by i_item_id limit 100; @@ -1541,7 +1541,7 @@ from (select avg(ss_list_price) B1_LP ,count(distinct ss_list_price) B1_CNTD from store_sales where ss_quantity between 0 and 5 - and (ss_list_price between 107 and 107+10 + and (ss_list_price between 107 and 107+10 or ss_coupon_amt between 1319 and 1319+1000 or ss_wholesale_cost between 60 and 60+20)) B1, (select avg(ss_list_price) B2_LP @@ -1588,7 +1588,7 @@ limit 100; -- end query 28 in stream 0 using template query28.tpl -- start query 29 in stream 0 using template query29.tpl -select +select i_item_id ,i_item_desc ,s_store_id @@ -1606,7 +1606,7 @@ select ,store ,item where - d1.d_moy = 4 + d1.d_moy = 4 and d1.d_year = 1998 and d1.d_date_sk = ss_sold_date_sk and i_item_sk = ss_item_sk @@ -1615,11 +1615,11 @@ select and ss_item_sk = sr_item_sk and ss_ticket_number = sr_ticket_number and sr_returned_date_sk = d2.d_date_sk - and d2.d_moy between 4 and 4 + 3 + and d2.d_moy between 4 and 4 + 3 and d2.d_year = 1998 and sr_customer_sk = cs_bill_customer_sk and sr_item_sk = cs_item_sk - and cs_sold_date_sk = d3.d_date_sk + and cs_sold_date_sk = d3.d_date_sk and d3.d_year in (1998,1998+1,1998+2) group by i_item_id @@ -1627,7 +1627,7 @@ select ,s_store_id ,s_store_name order by - i_item_id + i_item_id ,i_item_desc ,s_store_id ,s_store_name @@ -1637,14 +1637,14 @@ select -- start query 30 in stream 0 using template query30.tpl with customer_total_return as (select wr_returning_customer_sk as ctr_customer_sk - ,ca_state as ctr_state, + ,ca_state as ctr_state, sum(wr_return_amt) as ctr_total_return from web_returns ,date_dim ,customer_address - where wr_returned_date_sk = d_date_sk + where wr_returned_date_sk = d_date_sk and d_year =2000 - and wr_returning_addr_sk = ca_address_sk + and wr_returning_addr_sk = ca_address_sk group by wr_returning_customer_sk ,ca_state) select c_customer_id,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag @@ -1654,7 +1654,7 @@ with customer_total_return as ,customer_address ,customer where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2 - from customer_total_return ctr2 + from customer_total_return ctr2 where ctr1.ctr_state = ctr2.ctr_state) and ca_address_sk = c_current_addr_sk and ca_state = 'AR' @@ -1678,7 +1678,7 @@ with ss as where ws_sold_date_sk = d_date_sk and ws_bill_addr_sk=ca_address_sk group by ca_county,d_qoy, d_year) - select + select ss1.ca_county ,ss1.d_year ,ws2.web_sales/ws1.web_sales web_q1_q2_increase @@ -1710,7 +1710,7 @@ with ss as and ws1.ca_county = ws3.ca_county and ws3.d_qoy = 3 and ws3.d_year =1999 - and case when ws1.web_sales > 0 then ws2.web_sales/ws1.web_sales else null end + and case when ws1.web_sales > 0 then ws2.web_sales/ws1.web_sales else null end > case when ss1.store_sales > 0 then ss2.store_sales/ss1.store_sales else null end and case when ws2.web_sales > 0 then ws3.web_sales/ws2.web_sales else null end > case when ss2.store_sales > 0 then ss3.store_sales/ss2.store_sales else null end @@ -1718,30 +1718,30 @@ with ss as -- end query 31 in stream 0 using template query31.tpl -- start query 32 in stream 0 using template query32.tpl -select sum(cs_ext_discount_amt) as "excess discount amount" -from - catalog_sales - ,item +select sum(cs_ext_discount_amt) as "excess discount amount" +from + catalog_sales + ,item ,date_dim where i_manufact_id = 722 -and i_item_sk = cs_item_sk -and d_date between '2001-03-09' and +and i_item_sk = cs_item_sk +and d_date between '2001-03-09' and (cast('2001-03-09' as date) + interval '90 days') -and d_date_sk = cs_sold_date_sk -and cs_ext_discount_amt - > ( - select - 1.3 * avg(cs_ext_discount_amt) - from - catalog_sales +and d_date_sk = cs_sold_date_sk +and cs_ext_discount_amt + > ( + select + 1.3 * avg(cs_ext_discount_amt) + from + catalog_sales ,date_dim - where - cs_item_sk = i_item_sk + where + cs_item_sk = i_item_sk and d_date between '2001-03-09' and (cast('2001-03-09' as date) + interval '90 days') - and d_date_sk = cs_sold_date_sk - ) + and d_date_sk = cs_sold_date_sk + ) limit 100; -- end query 32 in stream 0 using template query32.tpl @@ -1765,7 +1765,7 @@ where i_category in ('Books')) and d_year = 2001 and d_moy = 3 and ss_addr_sk = ca_address_sk - and ca_gmt_offset = -5 + and ca_gmt_offset = -5 group by i_manufact_id), cs as ( select @@ -1786,7 +1786,7 @@ where i_category in ('Books')) and d_year = 2001 and d_moy = 3 and cs_bill_addr_sk = ca_address_sk - and ca_gmt_offset = -5 + and ca_gmt_offset = -5 group by i_manufact_id), ws as ( select @@ -1810,9 +1810,9 @@ where i_category in ('Books')) and ca_gmt_offset = -5 group by i_manufact_id) select i_manufact_id ,sum(total_sales) total_sales - from (select * from ss + from (select * from ss union all - select * from cs + select * from cs union all select * from ws) tmp1 group by i_manufact_id @@ -1832,15 +1832,15 @@ select c_last_name ,count(*) cnt from store_sales,date_dim,store,household_demographics where store_sales.ss_sold_date_sk = date_dim.d_date_sk - and store_sales.ss_store_sk = store.s_store_sk + and store_sales.ss_store_sk = store.s_store_sk and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk and (date_dim.d_dom between 1 and 3 or date_dim.d_dom between 25 and 28) and (household_demographics.hd_buy_potential = '1001-5000' or household_demographics.hd_buy_potential = '0-500') and household_demographics.hd_vehicle_count > 0 - and (case when household_demographics.hd_vehicle_count > 0 - then household_demographics.hd_dep_count/ household_demographics.hd_vehicle_count - else null + and (case when household_demographics.hd_vehicle_count > 0 + then household_demographics.hd_dep_count/ household_demographics.hd_vehicle_count + else null end) > 1.2 and date_dim.d_year in (2000,2000+1,2000+2) and store.s_county in ('Williamson County','Williamson County','Williamson County','Williamson County', @@ -1852,7 +1852,7 @@ select c_last_name -- end query 34 in stream 0 using template query34.tpl -- start query 35 in stream 0 using template query35.tpl -select +select ca_state, cd_gender, cd_marital_status, @@ -1875,7 +1875,7 @@ select customer c,customer_address ca,customer_demographics where c.c_current_addr_sk = ca.ca_address_sk and - cd_demo_sk = c.c_current_cdemo_sk and + cd_demo_sk = c.c_current_cdemo_sk and exists (select * from store_sales,date_dim where c.c_customer_sk = ss_customer_sk and @@ -1887,8 +1887,8 @@ select where c.c_customer_sk = ws_bill_customer_sk and ws_sold_date_sk = d_date_sk and d_year = 1999 and - d_qoy < 4) or - exists (select * + d_qoy < 4) or + exists (select * from catalog_sales,date_dim where c.c_customer_sk = cs_ship_customer_sk and cs_sold_date_sk = d_date_sk and @@ -1910,14 +1910,16 @@ select -- end query 35 in stream 0 using template query35.tpl -- start query 36 in stream 0 using template query36.tpl -select +select * +from +(select sum(ss_net_profit)/sum(ss_ext_sales_price) as gross_margin ,i_category ,i_class ,grouping(i_category)+grouping(i_class) as lochierarchy ,rank() over ( partition by grouping(i_category)+grouping(i_class), - case when grouping(i_class) = 0 then i_category end + case when grouping(i_class) = 0 then i_category end order by sum(ss_net_profit)/sum(ss_ext_sales_price) asc) as rank_within_parent from store_sales @@ -1925,13 +1927,13 @@ select ,item ,store where - d1.d_year = 2000 + d1.d_year = 2000 and d1.d_date_sk = ss_sold_date_sk - and i_item_sk = ss_item_sk + and i_item_sk = ss_item_sk and s_store_sk = ss_store_sk and s_state in ('TN','TN','TN','TN', 'TN','TN','TN','TN') - group by rollup(i_category,i_class) + group by rollup(i_category,i_class)) as sub order by lochierarchy desc ,case when lochierarchy = 0 then i_category end @@ -2034,27 +2036,27 @@ order by inv1.w_warehouse_sk,inv1.i_item_sk,inv1.d_moy,inv1.mean,inv1.cov -- end query 39 in stream 0 using template query39.tpl -- start query 40 in stream 0 using template query40.tpl -select +select w_state ,i_item_id - ,sum(case when (cast(d_date as date) < cast ('2001-05-02' as date)) + ,sum(case when (cast(d_date as date) < cast ('2001-05-02' as date)) then cs_sales_price - coalesce(cr_refunded_cash,0) else 0 end) as sales_before - ,sum(case when (cast(d_date as date) >= cast ('2001-05-02' as date)) + ,sum(case when (cast(d_date as date) >= cast ('2001-05-02' as date)) then cs_sales_price - coalesce(cr_refunded_cash,0) else 0 end) as sales_after from catalog_sales left outer join catalog_returns on - (cs_order_number = cr_order_number + (cs_order_number = cr_order_number and cs_item_sk = cr_item_sk) - ,warehouse + ,warehouse ,item ,date_dim where i_current_price between 0.99 and 1.49 and i_item_sk = cs_item_sk - and cs_warehouse_sk = w_warehouse_sk + and cs_warehouse_sk = w_warehouse_sk and cs_sold_date_sk = d_date_sk and d_date between (cast ('2001-05-02' as date) - interval '30 days') - and (cast ('2001-05-02' as date) + interval '30 days') + and (cast ('2001-05-02' as date) + interval '30 days') group by w_state,i_item_id order by w_state,i_item_id @@ -2064,12 +2066,12 @@ limit 100; -- start query 41 in stream 0 using template query41.tpl select distinct(i_product_name) from item i1 - where i_manufact_id between 704 and 704+40 + where i_manufact_id between 704 and 704+40 and (select count(*) as item_cnt from item where (i_manufact = i1.i_manufact and - ((i_category = 'Women' and - (i_color = 'forest' or i_color = 'lime') and + ((i_category = 'Women' and + (i_color = 'forest' or i_color = 'lime') and (i_units = 'Pallet' or i_units = 'Pound') and (i_size = 'economy' or i_size = 'small') ) or @@ -2089,8 +2091,8 @@ select distinct(i_product_name) (i_size = 'economy' or i_size = 'small') ))) or (i_manufact = i1.i_manufact and - ((i_category = 'Women' and - (i_color = 'dark' or i_color = 'aquamarine') and + ((i_category = 'Women' and + (i_color = 'dark' or i_color = 'aquamarine') and (i_units = 'Ton' or i_units = 'Tbl') and (i_size = 'economy' or i_size = 'small') ) or @@ -2123,7 +2125,7 @@ select dt.d_year ,item where dt.d_date_sk = store_sales.ss_sold_date_sk and store_sales.ss_item_sk = item.i_item_sk - and item.i_manager_id = 1 + and item.i_manager_id = 1 and dt.d_moy=11 and dt.d_year=1998 group by dt.d_year @@ -2148,7 +2150,7 @@ select s_store_name, s_store_id, where d_date_sk = ss_sold_date_sk and s_store_sk = ss_store_sk and s_gmt_offset = -5 and - d_year = 2000 + d_year = 2000 group by s_store_name, s_store_id order by s_store_name, s_store_id,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales limit 100; @@ -2158,7 +2160,7 @@ select s_store_name, s_store_id, select asceding.rnk, i1.i_product_name best_performing, i2.i_product_name worst_performing from(select * from (select item_sk,rank() over (order by rank_col asc) rnk - from (select ss_item_sk item_sk,avg(ss_net_profit) rank_col + from (select ss_item_sk item_sk,avg(ss_net_profit) rank_col from store_sales ss1 where ss_store_sk = 4 group by ss_item_sk @@ -2182,7 +2184,7 @@ from(select * where rnk < 11) descending, item i1, item i2 -where asceding.rnk = descending.rnk +where asceding.rnk = descending.rnk and i1.i_item_sk=asceding.item_sk and i2.i_item_sk=descending.item_sk order by asceding.rnk @@ -2193,10 +2195,10 @@ limit 100; select ca_zip, ca_city, sum(ws_sales_price) from web_sales, customer, customer_address, date_dim, item where ws_bill_customer_sk = c_customer_sk - and c_current_addr_sk = ca_address_sk - and ws_item_sk = i_item_sk + and c_current_addr_sk = ca_address_sk + and ws_item_sk = i_item_sk and ( substr(ca_zip,1,5) in ('85669', '86197','88274','83405','86475', '85392', '85460', '80348', '81792') - or + or i_item_id in (select i_item_id from item where i_item_sk in (2, 3, 5, 7, 11, 13, 17, 19, 23, 29) @@ -2215,23 +2217,23 @@ select c_last_name ,ca_city ,bought_city ,ss_ticket_number - ,amt,profit + ,amt,profit from (select ss_ticket_number ,ss_customer_sk ,ca_city bought_city ,sum(ss_coupon_amt) amt ,sum(ss_net_profit) profit - from store_sales,date_dim,store,household_demographics,customer_address + from store_sales,date_dim,store,household_demographics,customer_address where store_sales.ss_sold_date_sk = date_dim.d_date_sk - and store_sales.ss_store_sk = store.s_store_sk + and store_sales.ss_store_sk = store.s_store_sk and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk and store_sales.ss_addr_sk = customer_address.ca_address_sk and (household_demographics.hd_dep_count = 8 or household_demographics.hd_vehicle_count= 0) and date_dim.d_dow in (6,0) - and date_dim.d_year in (2000,2000+1,2000+2) - and store.s_city in ('Midway','Fairview','Fairview','Midway','Fairview') + and date_dim.d_year in (2000,2000+1,2000+2) + and store.s_city in ('Midway','Fairview','Fairview','Midway','Fairview') group by ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city) dn,customer,customer_address current_addr where ss_customer_sk = c_customer_sk and customer.c_current_addr_sk = current_addr.ca_address_sk @@ -2288,7 +2290,7 @@ with v1 as( v1.rn = v1_lead.rn - 1) select * from v2 - where d_year = 2000 and + where d_year = 2000 and avg_monthly_sales > 0 and case when avg_monthly_sales > 0 then abs(sum_sales - avg_monthly_sales) / avg_monthly_sales else null end > 0.1 order by sum_sales - avg_monthly_sales, nsum @@ -2300,36 +2302,36 @@ select sum (ss_quantity) from store_sales, store, customer_demographics, customer_address, date_dim where s_store_sk = ss_store_sk and ss_sold_date_sk = d_date_sk and d_year = 2001 - and + and ( ( cd_demo_sk = ss_cdemo_sk - and + and cd_marital_status = 'S' - and + and cd_education_status = 'Secondary' - and - ss_sales_price between 100.00 and 150.00 + and + ss_sales_price between 100.00 and 150.00 ) or ( cd_demo_sk = ss_cdemo_sk - and + and cd_marital_status = 'M' - and + and cd_education_status = '2 yr Degree' - and - ss_sales_price between 50.00 and 100.00 + and + ss_sales_price between 50.00 and 100.00 ) - or + or ( cd_demo_sk = ss_cdemo_sk - and + and cd_marital_status = 'D' - and + and cd_education_status = 'Advanced Degree' - and - ss_sales_price between 150.00 and 200.00 + and + ss_sales_price between 150.00 and 200.00 ) ) and @@ -2340,7 +2342,7 @@ select sum (ss_quantity) ca_country = 'United States' and ca_state in ('ND', 'NY', 'SD') - and ss_net_profit between 0 and 2000 + and ss_net_profit between 0 and 2000 ) or (ss_addr_sk = ca_address_sk @@ -2348,7 +2350,7 @@ select sum (ss_quantity) ca_country = 'United States' and ca_state in ('MD', 'GA', 'KS') - and ss_net_profit between 150 and 3000 + and ss_net_profit between 150 and 3000 ) or (ss_addr_sk = ca_address_sk @@ -2356,7 +2358,7 @@ select sum (ss_quantity) ca_country = 'United States' and ca_state in ('CO', 'MN', 'NC') - and ss_net_profit between 50 and 25000 + and ss_net_profit between 50 and 25000 ) ) ; @@ -2371,7 +2373,7 @@ select channel, item, return_ratio, return_rank, currency_rank from ,web.return_rank ,web.currency_rank from ( - select + select item ,return_ratio ,currency_ratio @@ -2383,13 +2385,13 @@ select channel, item, return_ratio, return_rank, currency_rank from cast(sum(coalesce(ws.ws_quantity,0)) as decimal(15,4) )) as return_ratio ,(cast(sum(coalesce(wr.wr_return_amt,0)) as decimal(15,4))/ cast(sum(coalesce(ws.ws_net_paid,0)) as decimal(15,4) )) as currency_ratio - from - web_sales ws left outer join web_returns wr - on (ws.ws_order_number = wr.wr_order_number and + from + web_sales ws left outer join web_returns wr + on (ws.ws_order_number = wr.wr_order_number and ws.ws_item_sk = wr.wr_item_sk) ,date_dim - where - wr.wr_return_amt > 10000 + where + wr.wr_return_amt > 10000 and ws.ws_net_profit > 1 and ws.ws_net_paid > 0 and ws.ws_quantity > 0 @@ -2399,40 +2401,40 @@ select channel, item, return_ratio, return_rank, currency_rank from group by ws.ws_item_sk ) in_web ) as web - where + where ( web.return_rank <= 10 or web.currency_rank <= 10 ) union - select + select 'catalog' as channel ,catalog.item ,catalog.return_ratio ,catalog.return_rank ,catalog.currency_rank from ( - select + select item ,return_ratio ,currency_ratio ,rank() over (order by return_ratio) as return_rank ,rank() over (order by currency_ratio) as currency_rank from - ( select + ( select cs.cs_item_sk as item ,(cast(sum(coalesce(cr.cr_return_quantity,0)) as decimal(15,4))/ cast(sum(coalesce(cs.cs_quantity,0)) as decimal(15,4) )) as return_ratio ,(cast(sum(coalesce(cr.cr_return_amount,0)) as decimal(15,4))/ cast(sum(coalesce(cs.cs_net_paid,0)) as decimal(15,4) )) as currency_ratio - from + from catalog_sales cs left outer join catalog_returns cr - on (cs.cs_order_number = cr.cr_order_number and + on (cs.cs_order_number = cr.cr_order_number and cs.cs_item_sk = cr.cr_item_sk) ,date_dim - where - cr.cr_return_amount > 10000 + where + cr.cr_return_amount > 10000 and cs.cs_net_profit > 1 and cs.cs_net_paid > 0 and cs.cs_quantity > 0 @@ -2442,21 +2444,21 @@ select channel, item, return_ratio, return_rank, currency_rank from group by cs.cs_item_sk ) in_cat ) as catalog - where + where ( catalog.return_rank <= 10 or catalog.currency_rank <=10 ) union - select + select 'store' as channel ,store.item ,store.return_ratio ,store.return_rank ,store.currency_rank from ( - select + select item ,return_ratio ,currency_ratio @@ -2466,14 +2468,14 @@ select channel, item, return_ratio, return_rank, currency_rank from ( select sts.ss_item_sk as item ,(cast(sum(coalesce(sr.sr_return_quantity,0)) as decimal(15,4))/cast(sum(coalesce(sts.ss_quantity,0)) as decimal(15,4) )) as return_ratio ,(cast(sum(coalesce(sr.sr_return_amt,0)) as decimal(15,4))/cast(sum(coalesce(sts.ss_net_paid,0)) as decimal(15,4) )) as currency_ratio - from + from store_sales sts left outer join store_returns sr on (sts.ss_ticket_number = sr.sr_ticket_number and sts.ss_item_sk = sr.sr_item_sk) ,date_dim - where - sr.sr_return_amt > 10000 + where + sr.sr_return_amt > 10000 and sts.ss_net_profit > 1 - and sts.ss_net_paid > 0 + and sts.ss_net_paid > 0 and sts.ss_quantity > 0 and ss_sold_date_sk = d_date_sk and d_year = 1998 @@ -2483,7 +2485,7 @@ select channel, item, return_ratio, return_rank, currency_rank from ) as store where ( store.return_rank <= 10 - or + or store.currency_rank <= 10 ) )as tab @@ -2492,7 +2494,7 @@ select channel, item, return_ratio, return_rank, currency_rank from -- end query 49 in stream 0 using template query49.tpl -- start query 50 in stream 0 using template query50.tpl -select +select s_store_name ,s_company_id ,s_street_number @@ -2503,14 +2505,14 @@ select ,s_county ,s_state ,s_zip - ,sum(case when (sr_returned_date_sk - ss_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days" - ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 30) and - (sr_returned_date_sk - ss_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days" - ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 60) and - (sr_returned_date_sk - ss_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days" + ,sum(case when (sr_returned_date_sk - ss_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days" + ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 30) and + (sr_returned_date_sk - ss_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days" + ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 60) and + (sr_returned_date_sk - ss_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days" ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 90) and - (sr_returned_date_sk - ss_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days" - ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 120) then 1 else 0 end) as ">120 days" + (sr_returned_date_sk - ss_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days" + ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 120) then 1 else 0 end) as ">120 days" from store_sales ,store_returns @@ -2618,7 +2620,7 @@ limit 100 ; -- end query 52 in stream 0 using template query52.tpl -- start query 53 in stream 0 using template query53.tpl -select * from +select * from (select i_manufact_id, sum(ss_sales_price) sum_sales, avg(sum(ss_sales_price)) over (partition by i_manufact_id) avg_quarterly_sales @@ -2636,8 +2638,8 @@ i_class in ('accessories','classical','fragrances','pants') and i_brand in ('amalgimporto #1','edu packscholar #1','exportiimporto #1', 'importoamalg #1'))) group by i_manufact_id, d_qoy ) tmp1 -where case when avg_quarterly_sales > 0 - then abs (sum_sales - avg_quarterly_sales)/ avg_quarterly_sales +where case when avg_quarterly_sales > 0 + then abs (sum_sales - avg_quarterly_sales)/ avg_quarterly_sales else null end > 0.1 order by avg_quarterly_sales, sum_sales, @@ -2649,7 +2651,7 @@ limit 100; with my_customers as ( select distinct c_customer_sk , c_current_addr_sk - from + from ( select cs_sold_date_sk sold_date_sk, cs_bill_customer_sk customer_sk, cs_item_sk item_sk @@ -2732,7 +2734,7 @@ where i_color in ('powder','orchid','pink')) and d_year = 2000 and d_moy = 3 and ss_addr_sk = ca_address_sk - and ca_gmt_offset = -6 + and ca_gmt_offset = -6 group by i_item_id), cs as ( select i_item_id,sum(cs_ext_sales_price) total_sales @@ -2751,7 +2753,7 @@ where i_color in ('powder','orchid','pink')) and d_year = 2000 and d_moy = 3 and cs_bill_addr_sk = ca_address_sk - and ca_gmt_offset = -6 + and ca_gmt_offset = -6 group by i_item_id), ws as ( select i_item_id,sum(ws_ext_sales_price) total_sales @@ -2773,9 +2775,9 @@ where i_color in ('powder','orchid','pink')) and ca_gmt_offset = -6 group by i_item_id) select i_item_id ,sum(total_sales) total_sales - from (select * from ss + from (select * from ss union all - select * from cs + select * from cs union all select * from ws) tmp1 group by i_item_id @@ -2835,14 +2837,14 @@ with v1 as( -- start query 58 in stream 0 using template query58.tpl with ss_items as (select i_item_id item_id - ,sum(ss_ext_sales_price) ss_item_rev + ,sum(ss_ext_sales_price) ss_item_rev from store_sales ,item ,date_dim where ss_item_sk = i_item_sk and d_date in (select d_date from date_dim - where d_week_seq = (select d_week_seq + where d_week_seq = (select d_week_seq from date_dim where d_date = '2001-06-16')) and ss_sold_date_sk = d_date_sk @@ -2856,7 +2858,7 @@ with ss_items as where cs_item_sk = i_item_sk and d_date in (select d_date from date_dim - where d_week_seq = (select d_week_seq + where d_week_seq = (select d_week_seq from date_dim where d_date = '2001-06-16')) and cs_sold_date_sk = d_date_sk @@ -2870,7 +2872,7 @@ with ss_items as where ws_item_sk = i_item_sk and d_date in (select d_date from date_dim - where d_week_seq =(select d_week_seq + where d_week_seq =(select d_week_seq from date_dim where d_date = '2001-06-16')) and ws_sold_date_sk = d_date_sk @@ -2885,7 +2887,7 @@ with ss_items as ,(ss_item_rev+cs_item_rev+ws_item_rev)/3 average from ss_items,cs_items,ws_items where ss_items.item_id=cs_items.item_id - and ss_items.item_id=ws_items.item_id + and ss_items.item_id=ws_items.item_id and ss_item_rev between 0.9 * cs_item_rev and 1.1 * cs_item_rev and ss_item_rev between 0.9 * ws_item_rev and 1.1 * ws_item_rev and cs_item_rev between 0.9 * ss_item_rev and 1.1 * ss_item_rev @@ -2898,7 +2900,7 @@ with ss_items as -- end query 58 in stream 0 using template query58.tpl -- start query 59 in stream 0 using template query59.tpl -with wss as +with wss as (select d_week_seq, ss_store_sk, sum(case when (d_day_name='Sunday') then ss_sales_price else null end) sun_sales, @@ -2924,7 +2926,7 @@ with wss as ,fri_sales fri_sales1,sat_sales sat_sales1 from wss,store,date_dim d where d.d_week_seq = wss.d_week_seq and - ss_store_sk = s_store_sk and + ss_store_sk = s_store_sk and d_month_seq between 1195 and 1195 + 11) y, (select s_store_name s_store_name2,wss.d_week_seq d_week_seq2 ,s_store_id s_store_id2,sun_sales sun_sales2 @@ -2933,7 +2935,7 @@ with wss as ,fri_sales fri_sales2,sat_sales sat_sales2 from wss,store,date_dim d where d.d_week_seq = wss.d_week_seq and - ss_store_sk = s_store_sk and + ss_store_sk = s_store_sk and d_month_seq between 1195+ 12 and 1195 + 23) x where s_store_id1=s_store_id2 and d_week_seq1=d_week_seq2-52 @@ -2961,7 +2963,7 @@ where i_category in ('Jewelry')) and d_year = 2000 and d_moy = 10 and ss_addr_sk = ca_address_sk - and ca_gmt_offset = -5 + and ca_gmt_offset = -5 group by i_item_id), cs as ( select @@ -2982,7 +2984,7 @@ where i_category in ('Jewelry')) and d_year = 2000 and d_moy = 10 and cs_bill_addr_sk = ca_address_sk - and ca_gmt_offset = -5 + and ca_gmt_offset = -5 group by i_item_id), ws as ( select @@ -3005,12 +3007,12 @@ where i_category in ('Jewelry')) and ws_bill_addr_sk = ca_address_sk and ca_gmt_offset = -5 group by i_item_id) - select + select i_item_id ,sum(total_sales) total_sales - from (select * from ss + from (select * from ss union all - select * from cs + select * from cs union all select * from ws) tmp1 group by i_item_id @@ -3028,14 +3030,14 @@ from ,promotion ,date_dim ,customer - ,customer_address + ,customer_address ,item where ss_sold_date_sk = d_date_sk and ss_store_sk = s_store_sk and ss_promo_sk = p_promo_sk and ss_customer_sk= c_customer_sk and ca_address_sk = c_current_addr_sk - and ss_item_sk = i_item_sk + and ss_item_sk = i_item_sk and ca_gmt_offset = -7 and i_category = 'Home' and (p_channel_dmail = 'Y' or p_channel_email = 'Y' or p_channel_tv = 'Y') @@ -3064,18 +3066,18 @@ limit 100; -- end query 61 in stream 0 using template query61.tpl -- start query 62 in stream 0 using template query62.tpl -select +select substr(w_warehouse_name,1,20) ,sm_type ,web_name - ,sum(case when (ws_ship_date_sk - ws_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days" - ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 30) and - (ws_ship_date_sk - ws_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days" - ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 60) and - (ws_ship_date_sk - ws_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days" + ,sum(case when (ws_ship_date_sk - ws_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days" + ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 30) and + (ws_ship_date_sk - ws_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days" + ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 60) and + (ws_ship_date_sk - ws_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days" ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 90) and - (ws_ship_date_sk - ws_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days" - ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 120) then 1 else 0 end) as ">120 days" + (ws_ship_date_sk - ws_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days" + ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 120) then 1 else 0 end) as ">120 days" from web_sales ,warehouse @@ -3099,7 +3101,7 @@ limit 100; -- end query 62 in stream 0 using template query62.tpl -- start query 63 in stream 0 using template query63.tpl -select * +select * from (select i_manager_id ,sum(ss_sales_price) sum_sales ,avg(sum(ss_sales_price)) over (partition by i_manager_id) avg_monthly_sales @@ -3249,7 +3251,7 @@ order by cs1.product_name -- end query 64 in stream 0 using template query64.tpl -- start query 65 in stream 0 using template query65.tpl -select +select s_store_name, i_item_desc, sc.revenue, @@ -3259,7 +3261,7 @@ select from store, item, (select ss_store_sk, avg(revenue) as ave from - (select ss_store_sk, ss_item_sk, + (select ss_store_sk, ss_item_sk, sum(ss_sales_price) as revenue from store_sales, date_dim where ss_sold_date_sk = d_date_sk and d_month_seq between 1176 and 1176+11 @@ -3269,7 +3271,7 @@ select from store_sales, date_dim where ss_sold_date_sk = d_date_sk and d_month_seq between 1176 and 1176+11 group by ss_store_sk, ss_item_sk) sc - where sb.ss_store_sk = sc.ss_store_sk and + where sb.ss_store_sk = sc.ss_store_sk and sc.revenue <= 0.1 * sb.ave and s_store_sk = sc.ss_store_sk and i_item_sk = sc.ss_item_sk @@ -3278,7 +3280,7 @@ limit 100; -- end query 65 in stream 0 using template query65.tpl -- start query 66 in stream 0 using template query66.tpl -select +select w_warehouse_name ,w_warehouse_sq_ft ,w_city @@ -3324,7 +3326,7 @@ select ,sum(nov_net) as nov_net ,sum(dec_net) as dec_net from ( - select + select w_warehouse_name ,w_warehouse_sq_ft ,w_city @@ -3333,49 +3335,49 @@ select ,w_country ,'ORIENTAL' || ',' || 'BOXBUNDLES' as ship_carriers ,d_year as year - ,sum(case when d_moy = 1 + ,sum(case when d_moy = 1 then ws_ext_sales_price* ws_quantity else 0 end) as jan_sales - ,sum(case when d_moy = 2 + ,sum(case when d_moy = 2 then ws_ext_sales_price* ws_quantity else 0 end) as feb_sales - ,sum(case when d_moy = 3 + ,sum(case when d_moy = 3 then ws_ext_sales_price* ws_quantity else 0 end) as mar_sales - ,sum(case when d_moy = 4 + ,sum(case when d_moy = 4 then ws_ext_sales_price* ws_quantity else 0 end) as apr_sales - ,sum(case when d_moy = 5 + ,sum(case when d_moy = 5 then ws_ext_sales_price* ws_quantity else 0 end) as may_sales - ,sum(case when d_moy = 6 + ,sum(case when d_moy = 6 then ws_ext_sales_price* ws_quantity else 0 end) as jun_sales - ,sum(case when d_moy = 7 + ,sum(case when d_moy = 7 then ws_ext_sales_price* ws_quantity else 0 end) as jul_sales - ,sum(case when d_moy = 8 + ,sum(case when d_moy = 8 then ws_ext_sales_price* ws_quantity else 0 end) as aug_sales - ,sum(case when d_moy = 9 + ,sum(case when d_moy = 9 then ws_ext_sales_price* ws_quantity else 0 end) as sep_sales - ,sum(case when d_moy = 10 + ,sum(case when d_moy = 10 then ws_ext_sales_price* ws_quantity else 0 end) as oct_sales ,sum(case when d_moy = 11 then ws_ext_sales_price* ws_quantity else 0 end) as nov_sales ,sum(case when d_moy = 12 then ws_ext_sales_price* ws_quantity else 0 end) as dec_sales - ,sum(case when d_moy = 1 + ,sum(case when d_moy = 1 then ws_net_paid_inc_ship * ws_quantity else 0 end) as jan_net ,sum(case when d_moy = 2 then ws_net_paid_inc_ship * ws_quantity else 0 end) as feb_net - ,sum(case when d_moy = 3 + ,sum(case when d_moy = 3 then ws_net_paid_inc_ship * ws_quantity else 0 end) as mar_net - ,sum(case when d_moy = 4 + ,sum(case when d_moy = 4 then ws_net_paid_inc_ship * ws_quantity else 0 end) as apr_net - ,sum(case when d_moy = 5 + ,sum(case when d_moy = 5 then ws_net_paid_inc_ship * ws_quantity else 0 end) as may_net - ,sum(case when d_moy = 6 + ,sum(case when d_moy = 6 then ws_net_paid_inc_ship * ws_quantity else 0 end) as jun_net - ,sum(case when d_moy = 7 + ,sum(case when d_moy = 7 then ws_net_paid_inc_ship * ws_quantity else 0 end) as jul_net - ,sum(case when d_moy = 8 + ,sum(case when d_moy = 8 then ws_net_paid_inc_ship * ws_quantity else 0 end) as aug_net - ,sum(case when d_moy = 9 + ,sum(case when d_moy = 9 then ws_net_paid_inc_ship * ws_quantity else 0 end) as sep_net - ,sum(case when d_moy = 10 + ,sum(case when d_moy = 10 then ws_net_paid_inc_ship * ws_quantity else 0 end) as oct_net ,sum(case when d_moy = 11 then ws_net_paid_inc_ship * ws_quantity else 0 end) as nov_net @@ -3393,9 +3395,9 @@ select and ws_sold_time_sk = t_time_sk and ws_ship_mode_sk = sm_ship_mode_sk and d_year = 2001 - and t_time between 42970 and 42970+28800 + and t_time between 42970 and 42970+28800 and sm_carrier in ('ORIENTAL','BOXBUNDLES') - group by + group by w_warehouse_name ,w_warehouse_sq_ft ,w_city @@ -3404,7 +3406,7 @@ select ,w_country ,d_year union all - select + select w_warehouse_name ,w_warehouse_sq_ft ,w_city @@ -3413,49 +3415,49 @@ select ,w_country ,'ORIENTAL' || ',' || 'BOXBUNDLES' as ship_carriers ,d_year as year - ,sum(case when d_moy = 1 + ,sum(case when d_moy = 1 then cs_ext_list_price* cs_quantity else 0 end) as jan_sales - ,sum(case when d_moy = 2 + ,sum(case when d_moy = 2 then cs_ext_list_price* cs_quantity else 0 end) as feb_sales - ,sum(case when d_moy = 3 + ,sum(case when d_moy = 3 then cs_ext_list_price* cs_quantity else 0 end) as mar_sales - ,sum(case when d_moy = 4 + ,sum(case when d_moy = 4 then cs_ext_list_price* cs_quantity else 0 end) as apr_sales - ,sum(case when d_moy = 5 + ,sum(case when d_moy = 5 then cs_ext_list_price* cs_quantity else 0 end) as may_sales - ,sum(case when d_moy = 6 + ,sum(case when d_moy = 6 then cs_ext_list_price* cs_quantity else 0 end) as jun_sales - ,sum(case when d_moy = 7 + ,sum(case when d_moy = 7 then cs_ext_list_price* cs_quantity else 0 end) as jul_sales - ,sum(case when d_moy = 8 + ,sum(case when d_moy = 8 then cs_ext_list_price* cs_quantity else 0 end) as aug_sales - ,sum(case when d_moy = 9 + ,sum(case when d_moy = 9 then cs_ext_list_price* cs_quantity else 0 end) as sep_sales - ,sum(case when d_moy = 10 + ,sum(case when d_moy = 10 then cs_ext_list_price* cs_quantity else 0 end) as oct_sales ,sum(case when d_moy = 11 then cs_ext_list_price* cs_quantity else 0 end) as nov_sales ,sum(case when d_moy = 12 then cs_ext_list_price* cs_quantity else 0 end) as dec_sales - ,sum(case when d_moy = 1 + ,sum(case when d_moy = 1 then cs_net_paid * cs_quantity else 0 end) as jan_net - ,sum(case when d_moy = 2 + ,sum(case when d_moy = 2 then cs_net_paid * cs_quantity else 0 end) as feb_net - ,sum(case when d_moy = 3 + ,sum(case when d_moy = 3 then cs_net_paid * cs_quantity else 0 end) as mar_net - ,sum(case when d_moy = 4 + ,sum(case when d_moy = 4 then cs_net_paid * cs_quantity else 0 end) as apr_net - ,sum(case when d_moy = 5 + ,sum(case when d_moy = 5 then cs_net_paid * cs_quantity else 0 end) as may_net - ,sum(case when d_moy = 6 + ,sum(case when d_moy = 6 then cs_net_paid * cs_quantity else 0 end) as jun_net - ,sum(case when d_moy = 7 + ,sum(case when d_moy = 7 then cs_net_paid * cs_quantity else 0 end) as jul_net - ,sum(case when d_moy = 8 + ,sum(case when d_moy = 8 then cs_net_paid * cs_quantity else 0 end) as aug_net - ,sum(case when d_moy = 9 + ,sum(case when d_moy = 9 then cs_net_paid * cs_quantity else 0 end) as sep_net - ,sum(case when d_moy = 10 + ,sum(case when d_moy = 10 then cs_net_paid * cs_quantity else 0 end) as oct_net ,sum(case when d_moy = 11 then cs_net_paid * cs_quantity else 0 end) as nov_net @@ -3473,9 +3475,9 @@ select and cs_sold_time_sk = t_time_sk and cs_ship_mode_sk = sm_ship_mode_sk and d_year = 2001 - and t_time between 42970 AND 42970+28800 + and t_time between 42970 AND 42970+28800 and sm_carrier in ('ORIENTAL','BOXBUNDLES') - group by + group by w_warehouse_name ,w_warehouse_sq_ft ,w_city @@ -3484,7 +3486,7 @@ select ,w_country ,d_year ) x - group by + group by w_warehouse_name ,w_warehouse_sq_ft ,w_city @@ -3553,19 +3555,19 @@ select c_last_name from (select ss_ticket_number ,ss_customer_sk ,ca_city bought_city - ,sum(ss_ext_sales_price) extended_price + ,sum(ss_ext_sales_price) extended_price ,sum(ss_ext_list_price) list_price - ,sum(ss_ext_tax) extended_tax + ,sum(ss_ext_tax) extended_tax from store_sales ,date_dim ,store ,household_demographics - ,customer_address + ,customer_address where store_sales.ss_sold_date_sk = date_dim.d_date_sk - and store_sales.ss_store_sk = store.s_store_sk + and store_sales.ss_store_sk = store.s_store_sk and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk and store_sales.ss_addr_sk = customer_address.ca_address_sk - and date_dim.d_dom between 1 and 2 + and date_dim.d_dom between 1 and 2 and (household_demographics.hd_dep_count = 3 or household_demographics.hd_vehicle_count= 4) and date_dim.d_year in (1998,1998+1,1998+2) @@ -3584,7 +3586,7 @@ select c_last_name -- end query 68 in stream 0 using template query68.tpl -- start query 69 in stream 0 using template query69.tpl -select +select cd_gender, cd_marital_status, cd_education_status, @@ -3598,7 +3600,7 @@ select where c.c_current_addr_sk = ca.ca_address_sk and ca_state in ('IL','TX','ME') and - cd_demo_sk = c.c_current_cdemo_sk and + cd_demo_sk = c.c_current_cdemo_sk and exists (select * from store_sales,date_dim where c.c_customer_sk = ss_customer_sk and @@ -3611,7 +3613,7 @@ select ws_sold_date_sk = d_date_sk and d_year = 2002 and d_moy between 1 and 1+2) and - not exists (select * + not exists (select * from catalog_sales,date_dim where c.c_customer_sk = cs_ship_customer_sk and cs_sold_date_sk = d_date_sk and @@ -3631,14 +3633,15 @@ select -- end query 69 in stream 0 using template query69.tpl -- start query 70 in stream 0 using template query70.tpl -select +select * +from (select sum(ss_net_profit) as total_sum ,s_state ,s_county ,grouping(s_state)+grouping(s_county) as lochierarchy ,rank() over ( partition by grouping(s_state)+grouping(s_county), - case when grouping(s_county) = 0 then s_state end + case when grouping(s_county) = 0 then s_state end order by sum(ss_net_profit) desc) as rank_within_parent from store_sales @@ -3657,10 +3660,10 @@ select and d_date_sk = ss_sold_date_sk and s_store_sk = ss_store_sk group by s_state - ) tmp1 + ) tmp1 where ranking <= 5 ) - group by rollup(s_state,s_county) + group by rollup(s_state,s_county)) as sub order by lochierarchy desc ,case when lochierarchy = 0 then s_state end @@ -3671,10 +3674,10 @@ select -- start query 71 in stream 0 using template query71.tpl select i_brand_id brand_id, i_brand brand,t_hour,t_minute, sum(ext_price) ext_price - from item, (select ws_ext_sales_price as ext_price, + from item, (select ws_ext_sales_price as ext_price, ws_sold_date_sk as sold_date_sk, ws_item_sk as sold_item_sk, - ws_sold_time_sk as time_sk + ws_sold_time_sk as time_sk from web_sales,date_dim where d_date_sk = ws_sold_date_sk and d_moy=12 @@ -3727,7 +3730,7 @@ join date_dim d3 on (cs_ship_date_sk = d3.d_date_sk) left outer join promotion on (cs_promo_sk=p_promo_sk) left outer join catalog_returns on (cr_item_sk = cs_item_sk and cr_order_number = cs_order_number) where d1.d_week_seq = d2.d_week_seq - and inv_quantity_on_hand < cs_quantity + and inv_quantity_on_hand < cs_quantity and d3.d_date > d1.d_date + 5 and hd_buy_potential = '1001-5000' and d1.d_year = 1998 @@ -3741,7 +3744,7 @@ limit 100; select c_last_name ,c_first_name ,c_salutation - ,c_preferred_cust_flag + ,c_preferred_cust_flag ,ss_ticket_number ,cnt from (select ss_ticket_number @@ -3749,13 +3752,13 @@ select c_last_name ,count(*) cnt from store_sales,date_dim,store,household_demographics where store_sales.ss_sold_date_sk = date_dim.d_date_sk - and store_sales.ss_store_sk = store.s_store_sk + and store_sales.ss_store_sk = store.s_store_sk and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk - and date_dim.d_dom between 1 and 2 + and date_dim.d_dom between 1 and 2 and (household_demographics.hd_buy_potential = '1001-5000' or household_demographics.hd_buy_potential = '5001-10000') and household_demographics.hd_vehicle_count > 0 - and case when household_demographics.hd_vehicle_count > 0 then + and case when household_demographics.hd_vehicle_count > 0 then household_demographics.hd_dep_count/ household_demographics.hd_vehicle_count else null end > 1 and date_dim.d_year in (2000,2000+1,2000+2) and store.s_county in ('Williamson County','Williamson County','Williamson County','Williamson County') @@ -3801,7 +3804,7 @@ with year_total as ( ,c_last_name ,d_year ) - select + select t_s_secyear.customer_id, t_s_secyear.customer_first_name, t_s_secyear.customer_last_name from year_total t_s_firstyear ,year_total t_s_secyear @@ -3844,7 +3847,7 @@ WITH all_sales AS ( ,cs_ext_sales_price - COALESCE(cr_return_amount,0.0) AS sales_amt FROM catalog_sales JOIN item ON i_item_sk=cs_item_sk JOIN date_dim ON d_date_sk=cs_sold_date_sk - LEFT JOIN catalog_returns ON (cs_order_number=cr_order_number + LEFT JOIN catalog_returns ON (cs_order_number=cr_order_number AND cs_item_sk=cr_item_sk) WHERE i_category='Sports' UNION @@ -3857,7 +3860,7 @@ WITH all_sales AS ( ,ss_ext_sales_price - COALESCE(sr_return_amt,0.0) AS sales_amt FROM store_sales JOIN item ON i_item_sk=ss_item_sk JOIN date_dim ON d_date_sk=ss_sold_date_sk - LEFT JOIN store_returns ON (ss_ticket_number=sr_ticket_number + LEFT JOIN store_returns ON (ss_ticket_number=sr_ticket_number AND ss_item_sk=sr_item_sk) WHERE i_category='Sports' UNION @@ -3870,7 +3873,7 @@ WITH all_sales AS ( ,ws_ext_sales_price - COALESCE(wr_return_amt,0.0) AS sales_amt FROM web_sales JOIN item ON i_item_sk=ws_item_sk JOIN date_dim ON d_date_sk=ws_sold_date_sk - LEFT JOIN web_returns ON (ws_order_number=wr_order_number + LEFT JOIN web_returns ON (ws_order_number=wr_order_number AND ws_item_sk=wr_item_sk) WHERE i_category='Sports') sales_detail GROUP BY d_year, i_brand_id, i_class_id, i_category_id, i_manufact_id) @@ -3929,8 +3932,8 @@ with ss as date_dim, store where ss_sold_date_sk = d_date_sk - and d_date between cast('2000-08-10' as date) - and (cast('2000-08-10' as date) + interval '30 days') + and d_date between cast('2000-08-10' as date) + and (cast('2000-08-10' as date) + interval '30 days') and ss_store_sk = s_store_sk group by s_store_sk) , @@ -3945,7 +3948,7 @@ with ss as and d_date between cast('2000-08-10' as date) and (cast('2000-08-10' as date) + interval '30 days') and sr_store_sk = s_store_sk - group by s_store_sk), + group by s_store_sk), cs as (select cs_call_center_sk, sum(cs_ext_sales_price) as sales, @@ -3955,8 +3958,8 @@ with ss as where cs_sold_date_sk = d_date_sk and d_date between cast('2000-08-10' as date) and (cast('2000-08-10' as date) + interval '30 days') - group by cs_call_center_sk - ), + group by cs_call_center_sk + ), cr as (select cr_call_center_sk, sum(cr_return_amount) as returns, @@ -3967,7 +3970,7 @@ with ss as and d_date between cast('2000-08-10' as date) and (cast('2000-08-10' as date) + interval '30 days') group by cr_call_center_sk - ), + ), ws as ( select wp_web_page_sk, sum(ws_ext_sales_price) as sales, @@ -3979,7 +3982,7 @@ with ss as and d_date between cast('2000-08-10' as date) and (cast('2000-08-10' as date) + interval '30 days') and ws_web_page_sk = wp_web_page_sk - group by wp_web_page_sk), + group by wp_web_page_sk), wr as (select wp_web_page_sk, sum(wr_return_amt) as returns, @@ -3997,7 +4000,7 @@ with ss as , sum(sales) as sales , sum(returns) as returns , sum(profit) as profit - from + from (select 'store channel' as channel , ss.s_store_sk as id , sales @@ -4065,7 +4068,7 @@ ss as where sr_ticket_number is null group by d_year, ss_item_sk, ss_customer_sk ) - select + select ss_customer_sk, round(ss_qty/(coalesce(ws_qty,0)+coalesce(cs_qty,0)),2) ratio, ss_qty store_qty, ss_wc store_wholesale_cost, ss_sp store_sales_price, @@ -4076,7 +4079,7 @@ from ss left join ws on (ws_sold_year=ss_sold_year and ws_item_sk=ss_item_sk and ws_customer_sk=ss_customer_sk) left join cs on (cs_sold_year=ss_sold_year and cs_item_sk=ss_item_sk and cs_customer_sk=ss_customer_sk) where (coalesce(ws_qty,0)>0 or coalesce(cs_qty, 0)>0) and ss_sold_year=1998 -order by +order by ss_customer_sk, ss_qty desc, ss_wc desc, ss_sp desc, other_chan_qty, @@ -4087,7 +4090,7 @@ limit 100; -- end query 78 in stream 0 using template query78.tpl -- start query 79 in stream 0 using template query79.tpl -select +select c_last_name,c_first_name,substr(s_city,1,30),ss_ticket_number,amt,profit from (select ss_ticket_number @@ -4097,11 +4100,11 @@ select ,sum(ss_net_profit) profit from store_sales,date_dim,store,household_demographics where store_sales.ss_sold_date_sk = date_dim.d_date_sk - and store_sales.ss_store_sk = store.s_store_sk + and store_sales.ss_store_sk = store.s_store_sk and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk and (household_demographics.hd_dep_count = 7 or household_demographics.hd_vehicle_count > -1) and date_dim.d_dow = 1 - and date_dim.d_year in (2000,2000+1,2000+2) + and date_dim.d_year in (2000,2000+1,2000+2) and store.s_number_employees between 200 and 295 group by ss_ticket_number,ss_customer_sk,ss_addr_sk,store.s_city) ms,customer where ss_customer_sk = c_customer_sk @@ -4122,7 +4125,7 @@ with ssr as item, promotion where ss_sold_date_sk = d_date_sk - and d_date between cast('2002-08-14' as date) + and d_date between cast('2002-08-14' as date) and (cast('2002-08-14' as date) + interval '30 days') and ss_store_sk = s_store_sk and ss_item_sk = i_item_sk @@ -4177,7 +4180,7 @@ group by web_site_id) , sum(sales) as sales , sum(returns) as returns , sum(profit) as profit - from + from (select 'store channel' as channel , 'store' || store_id as id , sales @@ -4208,14 +4211,14 @@ group by web_site_id) -- start query 81 in stream 0 using template query81.tpl with customer_total_return as (select cr_returning_customer_sk as ctr_customer_sk - ,ca_state as ctr_state, + ,ca_state as ctr_state, sum(cr_return_amt_inc_tax) as ctr_total_return from catalog_returns ,date_dim ,customer_address - where cr_returned_date_sk = d_date_sk + where cr_returned_date_sk = d_date_sk and d_year =2001 - and cr_returning_addr_sk = ca_address_sk + and cr_returning_addr_sk = ca_address_sk group by cr_returning_customer_sk ,ca_state ) select c_customer_id,c_salutation,c_first_name,c_last_name,ca_street_number,ca_street_name @@ -4225,7 +4228,7 @@ with customer_total_return as ,customer_address ,customer where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2 - from customer_total_return ctr2 + from customer_total_return ctr2 where ctr1.ctr_state = ctr2.ctr_state) and ca_address_sk = c_current_addr_sk and ca_state = 'TN' @@ -4261,10 +4264,10 @@ with sr_items as item, date_dim where sr_item_sk = i_item_sk - and d_date in + and d_date in (select d_date from date_dim - where d_week_seq in + where d_week_seq in (select d_week_seq from date_dim where d_date in ('2001-07-13','2001-09-10','2001-11-16'))) @@ -4277,10 +4280,10 @@ with sr_items as item, date_dim where cr_item_sk = i_item_sk - and d_date in + and d_date in (select d_date from date_dim - where d_week_seq in + where d_week_seq in (select d_week_seq from date_dim where d_date in ('2001-07-13','2001-09-10','2001-11-16'))) @@ -4293,10 +4296,10 @@ with sr_items as item, date_dim where wr_item_sk = i_item_sk - and d_date in + and d_date in (select d_date from date_dim - where d_week_seq in + where d_week_seq in (select d_week_seq from date_dim where d_date in ('2001-07-13','2001-09-10','2001-11-16'))) @@ -4314,7 +4317,7 @@ with sr_items as ,cr_items ,wr_items where sr_items.item_id=cr_items.item_id - and sr_items.item_id=wr_items.item_id + and sr_items.item_id=wr_items.item_id order by sr_items.item_id ,sr_item_qty limit 100; @@ -4347,12 +4350,12 @@ select substr(r_reason_desc,1,20) ,avg(wr_refunded_cash) ,avg(wr_fee) from web_sales, web_returns, web_page, customer_demographics cd1, - customer_demographics cd2, customer_address, date_dim, reason + customer_demographics cd2, customer_address, date_dim, reason where ws_web_page_sk = wp_web_page_sk and ws_item_sk = wr_item_sk and ws_order_number = wr_order_number and ws_sold_date_sk = d_date_sk and d_year = 1998 - and cd1.cd_demo_sk = wr_refunded_cdemo_sk + and cd1.cd_demo_sk = wr_refunded_cdemo_sk and cd2.cd_demo_sk = wr_returning_cdemo_sk and ca_address_sk = wr_refunded_addr_sk and r_reason_sk = wr_reason_sk @@ -4364,7 +4367,7 @@ select substr(r_reason_desc,1,20) cd1.cd_marital_status = cd2.cd_marital_status and cd1.cd_education_status = 'Primary' - and + and cd1.cd_education_status = cd2.cd_education_status and ws_sales_price between 100.00 and 150.00 @@ -4375,7 +4378,7 @@ select substr(r_reason_desc,1,20) and cd1.cd_marital_status = cd2.cd_marital_status and - cd1.cd_education_status = 'College' + cd1.cd_education_status = 'College' and cd1.cd_education_status = cd2.cd_education_status and @@ -4400,21 +4403,21 @@ select substr(r_reason_desc,1,20) ca_country = 'United States' and ca_state in ('NC', 'TX', 'IA') - and ws_net_profit between 100 and 200 + and ws_net_profit between 100 and 200 ) or ( ca_country = 'United States' and ca_state in ('WI', 'WV', 'GA') - and ws_net_profit between 150 and 300 + and ws_net_profit between 150 and 300 ) or ( ca_country = 'United States' and ca_state in ('OK', 'VA', 'KY') - and ws_net_profit between 50 and 250 + and ws_net_profit between 50 and 250 ) ) group by r_reason_desc @@ -4426,14 +4429,15 @@ limit 100; -- end query 85 in stream 0 using template query85.tpl -- start query 86 in stream 0 using template query86.tpl -select +select * +from (select sum(ws_net_paid) as total_sum ,i_category ,i_class ,grouping(i_category)+grouping(i_class) as lochierarchy ,rank() over ( partition by grouping(i_category)+grouping(i_class), - case when grouping(i_class) = 0 then i_category end + case when grouping(i_class) = 0 then i_category end order by sum(ws_net_paid) desc) as rank_within_parent from web_sales @@ -4443,7 +4447,7 @@ select d1.d_month_seq between 1186 and 1186+11 and d1.d_date_sk = ws_sold_date_sk and i_item_sk = ws_item_sk - group by rollup(i_category,i_class) + group by rollup(i_category,i_class)) as sub order by lochierarchy desc, case when lochierarchy = 0 then i_category end, @@ -4452,7 +4456,7 @@ select -- end query 86 in stream 0 using template query86.tpl -- start query 87 in stream 0 using template query87.tpl -select count(*) +select count(*) from ((select distinct c_last_name, c_first_name, d_date from store_sales, date_dim, customer where store_sales.ss_sold_date_sk = date_dim.d_date_sk @@ -4479,27 +4483,27 @@ select * from (select count(*) h8_30_to_9 from store_sales, household_demographics , time_dim, store - where ss_sold_time_sk = time_dim.t_time_sk - and ss_hdemo_sk = household_demographics.hd_demo_sk + where ss_sold_time_sk = time_dim.t_time_sk + and ss_hdemo_sk = household_demographics.hd_demo_sk and ss_store_sk = s_store_sk and time_dim.t_hour = 8 and time_dim.t_minute >= 30 and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or - (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2)) + (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2)) and store.s_store_name = 'ese') s1, - (select count(*) h9_to_9_30 + (select count(*) h9_to_9_30 from store_sales, household_demographics , time_dim, store where ss_sold_time_sk = time_dim.t_time_sk and ss_hdemo_sk = household_demographics.hd_demo_sk - and ss_store_sk = s_store_sk - and time_dim.t_hour = 9 + and ss_store_sk = s_store_sk + and time_dim.t_hour = 9 and time_dim.t_minute < 30 and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2)) and store.s_store_name = 'ese') s2, - (select count(*) h9_30_to_10 + (select count(*) h9_30_to_10 from store_sales, household_demographics , time_dim, store where ss_sold_time_sk = time_dim.t_time_sk and ss_hdemo_sk = household_demographics.hd_demo_sk @@ -4515,7 +4519,7 @@ from where ss_sold_time_sk = time_dim.t_time_sk and ss_hdemo_sk = household_demographics.hd_demo_sk and ss_store_sk = s_store_sk - and time_dim.t_hour = 10 + and time_dim.t_hour = 10 and time_dim.t_minute < 30 and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or @@ -4526,7 +4530,7 @@ from where ss_sold_time_sk = time_dim.t_time_sk and ss_hdemo_sk = household_demographics.hd_demo_sk and ss_store_sk = s_store_sk - and time_dim.t_hour = 10 + and time_dim.t_hour = 10 and time_dim.t_minute >= 30 and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or @@ -4536,7 +4540,7 @@ from from store_sales, household_demographics , time_dim, store where ss_sold_time_sk = time_dim.t_time_sk and ss_hdemo_sk = household_demographics.hd_demo_sk - and ss_store_sk = s_store_sk + and ss_store_sk = s_store_sk and time_dim.t_hour = 11 and time_dim.t_minute < 30 and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or @@ -4587,7 +4591,7 @@ where ss_item_sk = i_item_sk and i_class in ('history','school-uniforms','audio') ) or (i_category in ('Men','Sports','Shoes') and - i_class in ('pants','tennis','womens') + i_class in ('pants','tennis','womens') )) group by i_category, i_class, i_brand, s_store_name, s_company_name, d_moy) tmp1 @@ -4619,7 +4623,7 @@ select cast(amc as decimal(15,4))/cast(pmc as decimal(15,4)) am_pm_ratio -- end query 90 in stream 0 using template query90.tpl -- start query 91 in stream 0 using template query91.tpl -select +select cc_call_center_id Call_Center, cc_name Call_Center_Name, cc_manager Manager, @@ -4639,7 +4643,7 @@ and cr_returning_customer_sk= c_customer_sk and cd_demo_sk = c_current_cdemo_sk and hd_demo_sk = c_current_hdemo_sk and ca_address_sk = c_current_addr_sk -and d_year = 2000 +and d_year = 2000 and d_moy = 12 and ( (cd_marital_status = 'M' and cd_education_status = 'Unknown') or(cd_marital_status = 'W' and cd_education_status = 'Advanced Degree')) @@ -4650,31 +4654,31 @@ order by sum(cr_net_loss) desc; -- end query 91 in stream 0 using template query91.tpl -- start query 92 in stream 0 using template query92.tpl -select - sum(ws_ext_discount_amt) as "Excess Discount Amount" -from - web_sales - ,item +select + sum(ws_ext_discount_amt) as "Excess Discount Amount" +from + web_sales + ,item ,date_dim where i_manufact_id = 714 -and i_item_sk = ws_item_sk -and d_date between '2000-02-01' and +and i_item_sk = ws_item_sk +and d_date between '2000-02-01' and (cast('2000-02-01' as date) + interval '90 days') -and d_date_sk = ws_sold_date_sk -and ws_ext_discount_amt - > ( - SELECT - 1.3 * avg(ws_ext_discount_amt) - FROM - web_sales +and d_date_sk = ws_sold_date_sk +and ws_ext_discount_amt + > ( + SELECT + 1.3 * avg(ws_ext_discount_amt) + FROM + web_sales ,date_dim - WHERE - ws_item_sk = i_item_sk + WHERE + ws_item_sk = i_item_sk and d_date between '2000-02-01' and (cast('2000-02-01' as date) + interval '90 days') - and d_date_sk = ws_sold_date_sk - ) + and d_date_sk = ws_sold_date_sk + ) order by sum(ws_ext_discount_amt) limit 100; @@ -4698,7 +4702,7 @@ limit 100; -- end query 93 in stream 0 using template query93.tpl -- start query 94 in stream 0 using template query94.tpl -select +select count(distinct ws_order_number) as "order count" ,sum(ws_ext_ship_cost) as "total shipping cost" ,sum(ws_net_profit) as "total net profit" @@ -4708,7 +4712,7 @@ from ,customer_address ,web_site where - d_date between '2002-5-01' and + d_date between '2002-5-01' and (cast('2002-5-01' as date) + interval '60 days') and ws1.ws_ship_date_sk = d_date_sk and ws1.ws_ship_addr_sk = ca_address_sk @@ -4732,7 +4736,7 @@ with ws_wh as from web_sales ws1,web_sales ws2 where ws1.ws_order_number = ws2.ws_order_number and ws1.ws_warehouse_sk <> ws2.ws_warehouse_sk) - select + select count(distinct ws_order_number) as "order count" ,sum(ws_ext_ship_cost) as "total shipping cost" ,sum(ws_net_profit) as "total net profit" @@ -4742,7 +4746,7 @@ from ,customer_address ,web_site where - d_date between '2001-4-01' and + d_date between '2001-4-01' and (cast('2001-4-01' as date) + interval '60 days') and ws1.ws_ship_date_sk = d_date_sk and ws1.ws_ship_addr_sk = ca_address_sk @@ -4759,12 +4763,12 @@ limit 100; -- end query 95 in stream 0 using template query95.tpl -- start query 96 in stream 0 using template query96.tpl -select count(*) +select count(*) from store_sales - ,household_demographics + ,household_demographics ,time_dim, store -where ss_sold_time_sk = time_dim.t_time_sk - and ss_hdemo_sk = household_demographics.hd_demo_sk +where ss_sold_time_sk = time_dim.t_time_sk + and ss_hdemo_sk = household_demographics.hd_demo_sk and ss_store_sk = s_store_sk and time_dim.t_hour = 8 and time_dim.t_minute >= 30 @@ -4801,30 +4805,30 @@ limit 100; -- end query 97 in stream 0 using template query97.tpl -- start query 98 in stream 0 using template query98.tpl select i_item_id - ,i_item_desc - ,i_category - ,i_class + ,i_item_desc + ,i_category + ,i_class ,i_current_price - ,sum(ss_ext_sales_price) as itemrevenue + ,sum(ss_ext_sales_price) as itemrevenue ,sum(ss_ext_sales_price)*100/sum(sum(ss_ext_sales_price)) over (partition by i_class) as revenueratio -from +from store_sales - ,item + ,item ,date_dim -where - ss_item_sk = i_item_sk +where + ss_item_sk = i_item_sk and i_category in ('Men', 'Sports', 'Jewelry') and ss_sold_date_sk = d_date_sk - and d_date between cast('1999-02-05' as date) + and d_date between cast('1999-02-05' as date) and (cast('1999-02-05' as date) + interval '60 days') -group by +group by i_item_id - ,i_item_desc + ,i_item_desc ,i_category ,i_class ,i_current_price -order by +order by i_category ,i_class ,i_item_id @@ -4833,18 +4837,18 @@ order by -- end query 98 in stream 0 using template query98.tpl -- start query 99 in stream 0 using template query99.tpl -select +select substr(w_warehouse_name,1,20) ,sm_type ,cc_name - ,sum(case when (cs_ship_date_sk - cs_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days" - ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 30) and - (cs_ship_date_sk - cs_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days" - ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 60) and - (cs_ship_date_sk - cs_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days" + ,sum(case when (cs_ship_date_sk - cs_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days" + ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 30) and + (cs_ship_date_sk - cs_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days" + ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 60) and + (cs_ship_date_sk - cs_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days" ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 90) and - (cs_ship_date_sk - cs_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days" - ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 120) then 1 else 0 end) as ">120 days" + (cs_ship_date_sk - cs_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days" + ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 120) then 1 else 0 end) as ">120 days" from catalog_sales ,warehouse @@ -4865,5 +4869,3 @@ order by substr(w_warehouse_name,1,20) ,sm_type ,cc_name limit 100; - --- end query 99 in stream 0 using template query99.tpl diff --git a/tests/test_cases.py b/tests/test_cases.py index a6ebba8..0d23215 100644 --- a/tests/test_cases.py +++ b/tests/test_cases.py @@ -507,7 +507,8 @@ def stress_test(node): with open("tests/query_tpcds.sql",'r') as f: sql = f.read() commands = sql.split(';') - for i, cmd in enumerate(sql.split(';')): + for i, cmd in enumerate(commands): + commands[i] = cmd.replace('%','%%') if (len(cmd.strip()) == 0): del commands[i] @@ -530,5 +531,5 @@ def stress_test(node): finally: aq.close() conn.close() - if len(timeout_list) > 0: - print 'It was pg_query_state timeouts(10s) on queries: ', timeout_list + if len(timeout_list) > 0: + print 'It was pg_query_state timeouts(10s) on queries: ', timeout_list From 7e81aafdbbf10fdd17bf89749e069b4c52c4aed3 Mon Sep 17 00:00:00 2001 From: Alexey Kondratov Date: Fri, 25 Oct 2019 14:31:57 +0300 Subject: [PATCH 5/5] Remove extra linux-headers --- Dockerfile.tmpl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Dockerfile.tmpl b/Dockerfile.tmpl index 86e3fb5..3cf4b5b 100644 --- a/Dockerfile.tmpl +++ b/Dockerfile.tmpl @@ -4,7 +4,7 @@ FROM postgres:${PG_VERSION}-alpine RUN apk add --no-cache \ openssl curl \ perl perl-ipc-run \ - make musl-dev gcc bison flex coreutils linux-headers git\ + make musl-dev gcc bison flex coreutils git\ zlib-dev libedit-dev \ clang clang-analyzer linux-headers \ python2 python2-dev py2-virtualenv;