Should not use vector index when order by function different from metric_type

[ZiheLiu]

Steps to reproduce the behavior (Required)

ADMIN SET FRONTEND CONFIG ("enable_experimental_vector" = "true");

CREATE TABLE t6 (
    id bigint(20) NOT NULL COMMENT "",
    vector ARRAY<FLOAT> NOT NULL COMMENT "",
    INDEX index_vector (vector) USING VECTOR (
        "index_type" = "hnsw", 
        "dim"="5", 
        "metric_type" = "cosine_similarity", 
        "is_vector_normed" = "false", 
        "M" = "16", 
        "efconstruction" = "40"
    )
) ENGINE=OLAP
DUPLICATE KEY(id)
DISTRIBUTED BY HASH(id) BUCKETS 1
PROPERTIES (
    "replication_num" = "1"
);

insert into t6 values 
    (1, [10,12,13,14,15]),
    (2, [1,2,3,4,5]),
    (3, [0.1,0.2,0.3,0.4,0.5]);


explain select id, vector, approx_l2_distance([0.1,0.2,0.3,0.4,0.5], vector), l2_distance([0.1,0.2,0.3,0.4,0.5], vector), cosine_similarity([0.1,0.2,0.3,0.4,0.5], vector) from t6 order by approx_l2_distance([0.1,0.2,0.3,0.4,0.5], vector)  limit 1000;

select id, vector, approx_l2_distance([0.1,0.2,0.3,0.4,0.5], vector), l2_distance([0.1,0.2,0.3,0.4,0.5], vector), cosine_similarity([0.1,0.2,0.3,0.4,0.5], vector) from t6 order by approx_l2_distance([0.1,0.2,0.3,0.4,0.5], vector)  limit 1000;

Expected behavior (Required)

> explain select id, vector, approx_l2_distance([0.1,0.2,0.3,0.4,0.5], vector), l2_distance([0.1,0.2,0.3,0.4,0.5], vector), cosine_similarity([0.1,0.2,0.3,0.4,0.5], vector) from t6 order by approx_l2_distance([0.1,0.2,0.3,0.4,0.5], vector)  limit 1000;

|   0:OlapScanNode                                                                                |
|      TABLE: t6                                                                                  |
|      PREAGGREGATION: ON                                                                         |
|      VECTORINDEX: FALSE                                                                            |

> select id, vector, approx_l2_distance([0.1,0.2,0.3,0.4,0.5], vector), l2_distance([0.1,0.2,0.3,0.4,0.5], vector), cosine_similarity([0.1,0.2,0.3,0.4,0.5], vector) from t6 order by approx_l2_distance([0.1,0.2,0.3,0.4,0.5], vector)  limit 1000;
+----+-----------------------+-------------------------------------------------------+------------------------------------------------+------------------------------------------------------+
| id | vector                | approx_l2_distance([0.1, 0.2, 0.3, 0.4, 0.5], vector) | l2_distance([0.1, 0.2, 0.3, 0.4, 0.5], vector) | cosine_similarity([0.1, 0.2, 0.3, 0.4, 0.5], vector) |
+----+-----------------------+-------------------------------------------------------+------------------------------------------------+------------------------------------------------------+
| 1  | [10,12,13,14,15]      | 0.9525018                                             | 793.75                                         | 0.9525017                                            |
| 2  | [1,2,3,4,5]           | 1.0                                                   |  44.55                                         | 1.0                                                  |
| 1  | [0.1,0.2,0.3,0.4,0.5] | 1.0                                                   |   0.0                                          | 0.9999999                                            |
+----+-----------------------+-------------------------------------------------------+------------------------------------------------+------------------------------------------------------+

+----+-----------------------+--------------------------------------

Real behavior (Required)

> explain select id, vector, approx_l2_distance([0.1,0.2,0.3,0.4,0.5], vector), l2_distance([0.1,0.2,0.3,0.4,0.5], vector), cosine_similarity([0.1,0.2,0.3,0.4,0.5], vector) from t6 order by approx_l2_distance([0.1,0.2,0.3,0.4,0.5], vector)  limit 1000;

|   0:OlapScanNode                                                                                |
|      TABLE: t6                                                                                  |
|      PREAGGREGATION: ON                                                                         |
|      VECTORINDEX: ON                                                                            |

> select id, vector, approx_l2_distance([0.1,0.2,0.3,0.4,0.5], vector), l2_distance([0.1,0.2,0.3,0.4,0.5], vector), cosine_similarity([0.1,0.2,0.3,0.4,0.5], vector) from t6 order by approx_l2_distance([0.1,0.2,0.3,0.4,0.5], vector)  limit 1000;
+----+-----------------------+-------------------------------------------------------+------------------------------------------------+------------------------------------------------------+
| id | vector                | approx_l2_distance([0.1, 0.2, 0.3, 0.4, 0.5], vector) | l2_distance([0.1, 0.2, 0.3, 0.4, 0.5], vector) | cosine_similarity([0.1, 0.2, 0.3, 0.4, 0.5], vector) |
+----+-----------------------+-------------------------------------------------------+------------------------------------------------+------------------------------------------------------+
| 1  | [10,12,13,14,15]      | 0.9525018                                             | 793.75                                         | 0.9525017                                            |
| 2  | [1,2,3,4,5]           | 1.0                                                   |  44.55                                         | 1.0                                                  |
| 1  | [0.1,0.2,0.3,0.4,0.5] | 1.0                                                   |   0.0                                          | 0.9999999                                            |
+----+-----------------------+-------------------------------------------------------+------------------------------------------------+------------------------------------------------------+

StarRocks version (Required)

main ada1be1