What are the best practices for optimizing PostgreSQL query performance when dealing with millions of historical genealogy records on a local server
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
What are the best practices for optimizing PostgreSQL query performance when dealing with millions of historical genealogy records on a local server
1 real search · 1 real-search pass
PostgreSQL official documentation indexes multicolumn indexes partial indexes BRIN partitioning EXPLAIN ANALYZE pg_stat_statementsGoogle ↗
OBSERVEDInstruction
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (1)
Classes come from the query-classifier (a local Laya model). 1 of 1 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT1 real searches · gpt-6
PostgreSQL official documentation indexes multicolumn indexes partial indexes BRIN partitioning EXPLAIN ANALYZE pg_stat_statements Google ↗
- PostgreSQL partitioning documentation · postgresql.org
- pg_stat_statements · postgresql.org
- Using EXPLAIN · postgresql.org