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Discover whether PostgreSQL can dynamically adjust the number of worker threads during query execution and how splitting queries can optimize performance.
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Understanding PostgreSQL: Does it Adjust Worker Threads During Query Execution?

When working with PostgreSQL, one might find themselves questioning how the database system manages its resources when executing heavy queries. Specifically, can PostgreSQL adjust the number of worker threads during a query's execution to improve performance as more resources become available? In this article, we will delve into how PostgreSQL handles workers during query execution and offer insights into optimizing your queries based on these mechanisms.

The Question at Hand

Imagine you're running a resource-intensive query that can utilize multiple workers to expedite its execution. At the outset, only a limited number of worker threads (say 4) are available. As the query consumes processing time, other queries finish and free up additional workers. The important question arises: Does PostgreSQL increase the number of workers utilized for a currently running query as more become available?

How PostgreSQL Manages Worker Threads

Key Points of Worker Allocation

The determination of the number of parallel workers in PostgreSQL occurs at two significant stages:

During Query Planning:

The query optimizer assesses the query and decides how many workers it would like to utilize. This decision is based on various factors like the complexity of the query, expected workload, and available resources.

At Query Execution Start:

Once the query begins executing, PostgreSQL checks how many workers from the max_parallel_workers setting are currently in use. At this point, it fixes the number of workers for the ongoing execution based on the availability of resources.

No Dynamic Adjustment During Execution

It is essential to note that the number of workers will not change once the query execution has started. If the optimizer decided to run the query with a certain number of workers (let's say X), this number remains constant throughout the duration of that query execution, regardless of how many additional worker threads become available later.

Should You Split Your Query?

Given the fixed nature of worker allocation, you might wonder whether splitting a heavy query into multiple smaller queries that can each run on separate threads would be beneficial. Here’s how you can approach this:

Example Scenario

You were considering splitting a complex query into two simpler ones. Here’s what your original query looks like:

[[See Video to Reveal this Text or Code Snippet]]

You contemplated executing it as two separate queries like this:

Query for distance 1000

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Query for distance 1500

[[See Video to Reveal this Text or Code Snippet]]

Considerations for Splitting Queries

System Load: If your PostgreSQL server is handling multiple queries concurrently, breaking your original heavy query into two could allow for better resource utilization. Each query could leverage available worker threads independently.

Response Time: For queries that can return smaller subsets of data more quickly, splitting them can lead to faster overall response times, especially if concurrent execution is viable.

Conclusion

To summarize, PostgreSQL does not dynamically increase the number of worker threads for a running query based on changing availability. The allocation of workers is fixed from the start of execution. However, if multiple workers could be beneficial, consider splitting complex queries into smaller ones. This strategy may help in optimizing the use of available resources, especially in a multi-query environment.

If you're constantly dealing with complex queries in PostgreSQL, understanding these mechanics can help you better pre