From 0947fe0efb83511c9b5d197c17521d7abf127098 Mon Sep 17 00:00:00 2001
From: Dustin Lo <dustinlo.pcc@gmail.com>
Date: Wed, 26 Oct 2022 14:23:35 -0700
Subject: [PATCH] HC-439: Purge datasets v1.2.0 job time out after new pcm
 deployment (#26)

* using the bulk API to purge datasets

* removed multiprocessing import

* edited msg details

* pulling only necessary fields in purge

* re-added multiprocessing for s3 deletion only

* debug info, debug is too verbose

* fixed bug, debug ERROR

* debug INFO

* added deleted datasets stats

* re-did some stuff

* re-did some stuff

* re-did some stuff

* removing objects from ES first before deleting from s3

* moving log line to after we delete from es

Co-authored-by: dustinlo <dustin.k.lo@jpl.nasa.gov>
---
 purge.py | 88 +++++++++++++++++++++++++++++++++++++++-----------------
 1 file changed, 61 insertions(+), 27 deletions(-)

diff --git a/purge.py b/purge.py
index 45ac6f1..1748934 100644
--- a/purge.py
+++ b/purge.py
@@ -1,16 +1,17 @@
 #!/bin/env python
 import json
 import logging
+
 import psutil
+from multiprocessing import Pool
 
 import osaka.main
 from hysds.celery import app
 from hysds.es_util import get_mozart_es, get_grq_es
 from utils import revoke, create_info_message_files
-from multiprocessing import Pool
 
 LOG_FILE_NAME = 'purge.log'
-logging.basicConfig(filename=LOG_FILE_NAME, filemode='a', level=logging.DEBUG)
+logging.basicConfig(filename=LOG_FILE_NAME, filemode='a', level=logging.INFO)
 logger = logging
 
 tosca_es = get_grq_es()
@@ -22,23 +23,21 @@ def read_context():
         return cxt
 
 
-def delete_dataset(es_result):
-    ident = es_result["_id"]
-    index = es_result["_index"]
+def delete_from_object_store(es_result):
+    _id = es_result["_id"]
     dataset = es_result["_source"]["dataset"]
-    # find the Best URL first
-    best = None
+
+    best = None  # find the Best URL first
     for url in es_result["_source"]["urls"]:
         if not url.startswith("http"):
             best = url
 
-    print('paramater being passed to osaka.main.rmall: ', best)  # making osaka call to delete product
     if best is not None:
+        print('paramater being passed to osaka.main.rmall:', best)  # making osaka call to delete product
         osaka.main.rmall(best)
-
-    tosca_es.delete_by_id(index=index, id=ident, ignore=404)  # removing the metadata
-    logger.info('Purged %s' % ident)
-
+        logger.info('Purged from object store %s' % _id)
+    else:
+        logger.warning("url not found for: %s" % _id)
     return dataset
 
 
@@ -55,27 +54,62 @@ def purge_products(query, component, operation):
     if component == "mozart" or component == "figaro":
         es = get_mozart_es()
         es_index = app.conf["STATUS_ALIAS"]
+        _source = ["uuid", "payload_id"]
     else:  # "tosca"
         es = get_grq_es()
         es_index = app.conf["DATASET_ALIAS"]
+        _source = ["dataset", "urls"]
+
+    results = es.query(index=es_index, body=query, _source=_source)  # Querying for products
+
+    # filter fields returned with the bulk API
+    filter_path = [
+        "items.delete.error.reason",
+        "items.delete._id",
+        "items.delete._index",
+        "items.delete.result"
+    ]
 
-    results = es.query(index=es_index, body=query)  # Querying for products
-    num_processes = psutil.cpu_count() - 2
-    p = Pool(processes=num_processes)
     if component == 'tosca':
-        deleted_datasets = dict()
-        updated_datasets = p.map(delete_dataset, results)
-        for dataset in updated_datasets:
-            if dataset in deleted_datasets:
-                count = deleted_datasets[dataset]
-                deleted_datasets[dataset] = count + 1
+        num_processes = psutil.cpu_count() - 2
+        p = Pool(processes=num_processes)
+
+        body = [{
+            "delete": {"_index": row["_index"], "_id": row["_id"]}
+        } for row in results]
+        bulk_res = es.es.bulk(index=es_index, body=body, filter_path=filter_path)
+        logger.info(json.dumps(bulk_res, indent=2))
+
+        logger.info("purging datasets from object store: ")
+        p.map(delete_from_object_store, results)  # deleting objects from storage (s3, etc.)
+
+        dataset_purge_stats = {}
+        deleted_docs_count = 0
+        failed_deletions = []
+        for row in bulk_res["items"]:
+            if row["delete"].get("result", None) == "deleted":
+                deleted_docs_count += 1
+                _index = row["delete"]["_index"]
+                logger.info("deleted from ES: %s" % row["delete"]["_id"])
+                if _index not in dataset_purge_stats:
+                    dataset_purge_stats[_index] = 1
+                else:
+                    dataset_purge_stats[_index] += 1
             else:
-                deleted_datasets[dataset] = 1
-        if len(deleted_datasets) != 0:
-            msg_details = "Datasets purged by type:\n\n"
-            for ds in deleted_datasets.keys():
-                msg_details += "{} - {}\n".format(deleted_datasets[ds], ds)
-
+                failed_deletions.append(row["delete"])
+
+        if deleted_docs_count or failed_deletions:
+            msg_details = ""
+            if deleted_docs_count > 0:
+                msg_details += "Datasets purged from ES:\n"
+                for k, v in dataset_purge_stats.items():
+                    msg_details += "{} - {}\n".format(k, v)
+            if len(failed_deletions) > 0:
+                msg_details += "\n\n"
+                msg_details += "Datasets failed to purge from ES:\n"
+                msg_details += json.dumps(failed_deletions)
+                logger.warning("datasets failed to delete: ")
+                logger.warning(json.dumps(failed_deletions))
             create_info_message_files(msg_details=msg_details)
     else:
         purge = True if operation == 'purge' else False  # purge job from index