⚡ Optimize _consolidate_merge with executemany - #11
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This commit replaces the loop of individual `conn.execute` calls for `UPDATE` and `DELETE` operations in the `_consolidate_merge` function with two `conn.executemany` calls. This change reduces the number of database roundtrips from $2N$ to 2, significantly improving performance when merging a large number of duplicate observations. Benchmarks showed that for 50 duplicates, individual `execute` calls dropped from 100 to 0, replaced by only 2 `executemany` calls. Co-authored-by: LeandroPG19 <151863062+LeandroPG19@users.noreply.github.com>
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💡 What:
Optimized the
_consolidate_mergefunction insrc/cuba_memorys/handlers.pyto useconn.executemanyfor batchingUPDATEandDELETEoperations.🎯 Why:
The original implementation executed individual
UPDATEandDELETEqueries for every pair of duplicates found, leading to an N+1 query pattern. This caused unnecessary database roundtrips and latency during memory consolidation.📊 Measured Improvement:
Using a mock-based benchmark script for 50 duplicates:
conn.executecalls.conn.executecalls, replaced by 2conn.executemanycalls.PR created automatically by Jules for task 222610981640595802 started by @LeandroPG19