[GLE-8861] feat(vector): built-in TG function for pairwise vector embedding; #175
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😛 [sv4] WIP#58069 on tg_4.2.0_dev(gle#5691 engine#2772 product#279 er#1219 regress#1181 gsql-graph-algorithms#175) FAIL
Jenkins Job: Check jenkins job
Result: Job failed! Error: Tests Failed with no_fail option enabled
Instance Type: cluster
Tested OS: ubuntu18,centos7,ubuntu20,centos8
Requestor: jue.yuan
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:beach: [sv4] build_job#58883 of WIP#58069 on tg_4.2.0_dev(gle#5691 engine#2772 product#279 er#1219 regress#1181 gsql-graph-algorithms#175) at 2024/12/03 16:55:36 (PST) BUILT
Reason: Build successful
Jenkins Job: Check jenkins job
Requestor: jue.yuan
masterUrl: http://192.168.99.101:30080/job/wip_test/58069
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gds/vector/cosine_distance.gsql
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| @@ -0,0 +1,56 @@ | |||
| CREATE FUNCTION gds.vector.cosine_distance(list<double> list1, list<double> list2) RETURNS(float) { | |||
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I think it should be short for graph database system, Neo4j used this as their built-in library.
https://neo4j.com/docs/graph-data-science/current/algorithms/similarity-functions/
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GDS means Graph Data Science.
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Would returning double be better since float has lower precision? Same applies below.
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It will introduce some type checking error since they are mainly used for float types.
| FOREACH i IN RANGE [0, @@myList1.size() - 1 ] DO | ||
| @@sqrSum += (@@myList1.get(i) - @@myList2.get(i)) * (@@myList1.get(i) - @@myList2.get(i)); | ||
| END; | ||
| @@myResult = sqrt(@@sqrSum); |
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Have you tested the cases where the sizes of myList1 and myList2 are 0?
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It should be good since the @@sqrSum should always be not less than 0.
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