influence

Performance issues in PostgreSQL can arise as databases grow, leading to declines in query performance. To identify problematic queries, one can log long-running queries by setting the `log_min_duration_statement` parameter in the `postgresql.conf` file. The `pg_stat_statements` module can be enabled to monitor execution statistics of SQL statements, providing insights into query performance, including execution time and the number of calls. Queries with high standard deviation in execution time may indicate inconsistency, while sorting query statistics by total execution time can reveal excessive load from multiple fast queries. Real-time monitoring can be done using the `pg_stat_activity` view to check active queries and their states, and the `pg_locks` view can help identify blocked processes. The `EXPLAIN` command can analyze query execution plans, and using the `auto_explain` module can log plans for slow queries. Understanding cost parameters in query plans helps in optimizing performance, and different join methods (Nested Loop, Merge Join, Hash Join) have varying complexities and costs. To influence the planner's choice of scanning methods, configuration parameters can be adjusted, such as disabling sequential scanning. Extensions like `sr_plan`, `pg_hint_plan`, and `AQO` can further optimize query execution. Monitoring query progress can be done using dynamic views like `pg_stat_progress_*` for various commands.