planner-cost-model

The PostgreSQL query planner estimates costs by calculating startup and total costs for node types like SeqScan, IndexScan, and HashJoin. This analysis evaluates the internal cost functions defined in the planner's path costsize logic.

PostgreSQL chooses a sequential scan over an index scan when cost function estimates or inaccurate selectivity statistics mislead the planner. Debugging this requires analyzing whether the bad plan stems from incorrect cost estimates or outdated table statistics.

Tune PostgreSQL cost parameters like random_page_cost and parallel_setup_cost to align with specific hardware profiles such as SSDs. Adjusting these GUC parameters ensures the planner's cost estimations accurately reflect your high-memory system's physical disk access patterns.

Parallel execution settings impact PostgreSQL query paths by altering the estimated overhead of parallel worker setup. Modifying parallel_setup_cost within the planner's cost model directly influences whether the optimizer selects parallel execution plans for specific queries.

Debug a bad PostgreSQL query plan by evaluating the planner's cost estimation logic to identify performance bottlenecks. Use a structured approach to isolate whether suboptimal plan choices originate from inaccurate cost function estimates or flawed selectivity statistics.

Optimizing PostgreSQL query planning requires deep knowledge of database internals, specifically the source code handling cost estimation. Accurate diagnostic guidance for suboptimal plan choices depends on understanding the planner's path costsize logic and related cost-model internals.