PostgreSQL employs a Parallel Query feature that optimizes the execution of certain queries, boosting performance in multi-core systems.
Understanding Parallel Query
- Parallel Query is invoked when the optimizer deems it the most efficient strategy.
- It employs multiple background worker processes for concurrent execution.
The Plan Structure
- A query plan with Parallel Query includes a Gather or Gather Merge node.
- The Gather node assembles the parallel execution results.
Parallel Execution Scope
- If the Gather node is at the plan's top, the entire query runs in parallel.
- If within the plan tree, only the nodes below it run in parallel.
Optimal Worker Count
- The planner determines the number of workers.
- The chosen workers execute the parallel portion of the query.
- The number of workers can be capped by max_parallel_workers_per_gather.
Leader's Role
- The session's main process becomes the leader.
- The leader reads the tuples generated by the workers.
- For small result sets, the leader assists in query speed-up.
Gather Merge Insight
- When using Gather Merge nodes, workers produce sorted tuples.
- The leader merges and maintains the sort order.
Conclusion
PostgreSQL's Parallel Query mechanism is a powerful tool for enhancing query performance. By leveraging multiple background workers, parallel execution optimizes data retrieval, particularly on multi-core systems. Through careful planning and an understanding of parallel execution's nuances, developers can harness this feature to accelerate query processing, delivering improved responsiveness and efficiency.
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