AIQO: SQL tuning & AI-powered PostgreSQL optimization reports

Description: This is an UPDATE on data_vault.tbl_alpha using a complex subquery that aggregates and deduplicates data from several large tables (tbl_alpha, tbl_beta, tbl_gamma, tbl_delta), with multiple joins and a heavy use of sorting, aggregation, and memoization. The plan shows very high buffer usage, significant disk I/O, and large temporary files, indicating a resource-intensive operation on a massive dataset.

Initial summary

• The HashAggregate node is a major cost and memory driver, processing nearly 20M rows and spilling to disk (632GB temp usage).
• The Sort node processes over 41M rows, using external merge sort with 2.2TB of temp files, indicating insufficient memory for in-memory sort.
• The Seq Scan on tbl_alpha reads 8.6M pages, showing a full table scan on a very large table.
• The Index Only Scan on tbl_beta is efficient but still processes 16M rows, with 372k heap fetches.
• The Index Scan on tbl_gamma (via Memoize) is executed 17M times, with 11M buffer dirties and 432k writes, showing heavy random access.

Detailed diagnosis

• HashAggregate: Consumes over 1GB RAM and spills to disk, grouping 19M+ rows. This is likely due to the high cardinality of associe_interlo_coord_red and the need to deduplicate a huge intermediate result set.
• Sort: The external merge sort on 41M rows (2.2TB temp) is a major bottleneck, indicating work_mem is insufficient for the sort workload, causing heavy disk I/O.
• Seq Scan on tbl_alpha: The plan reads the entire table (127M rows), which is unavoidable given the join/filter conditions and lack of more selective indexes.
• Memoize + Index Scan on tbl_gamma: The Memoize node is hit 24M times but still has 17M misses, leading to 17M index lookups. This is a significant source of random I/O and buffer dirties.
• Hash Join/Index Only Scan on tbl_beta: The index is used efficiently, but the join cardinality is very high, and the filter is not highly selective.

Optimization paths

1. Indices

• Composite index on tbl_alpha for join/filter columns:
  The plan shows a full sequential scan on tbl_alpha followed by a hash join on col_beta_id and a nested loop join on col_delta_id and col_gamma_id. There is no composite index covering these columns.
  Recommendation:
  CREATE INDEX CONCURRENTLY idx_tbl_alpha_beta_gamma_delta ON data_vault.tbl_alpha (col_beta_id, col_gamma_id, col_delta_id);
  This index will allow the planner to use an index scan instead of a sequential scan, significantly reducing I/O and buffer usage for the join, especially if the join/filter conditions are frequently used together.

2. Configuration parameters

• Increase work_mem for this session/query:
  The Sort and HashAggregate nodes spill to disk, with temp files exceeding 2TB. While work_mem is already set to 1GB, this query's sort/aggregate operations are exceptionally large.

3. Data architecture

• Review fillfactor for tbl_alpha:
  The table is heavily updated and dirtied (40M+ pages dirtied, 29M+ written). If not already set, ensure fillfactor is at 70 or lower to reduce page splits and improve update performance. This is already a best practice for large, update-heavy tables.