Parallel Hash Joins in PostgreSQL

Parallel Hash Joins in PostgreSQL are a type of join operation that can be executed in parallel, allowing for faster and more efficient execution of database queries. In a hash join, the database first builds a hash table of one of the join tables, and then uses this hash table to look up the matching rows from the other join table.

Parallel hash joins in PostgreSQL allow for the creation of multiple hash tables in parallel, and the parallel execution of multiple join operations using these hash tables. This results in faster execution times for large join operations, especially when multiple cores are available for execution.

To use parallel hash joins in PostgreSQL, the user must set the max_parallel_workers_per_gather parameter in the postgresql.conf file to a value greater than 0. This enables the database to use multiple parallel workers for join operations.

It’s important to note that parallel hash joins are only useful for larger join operations, as the overhead of creating and using multiple hash tables may outweigh the benefits for smaller join operations. Additionally, parallel hash joins may not be the best choice for all types of join operations, as other join methods such as nested loop joins or merge joins may be more efficient for specific use cases.

Parallel Hash Joins example in PostgreSQL

Here is an example of using a parallel hash join in PostgreSQL:

  1. Create two tables:

2. Insert data into the tables:

3. Enable parallel query execution in the postgresql.conf file by setting max_parallel_workers_per_gather to a value greater than 0:

4. Perform the join query:

5. The database will now use parallel hash joins to execute the query and return the result:

Note: The actual performance improvement of the parallel hash join will depend on the size of the data, the number of parallel workers, and the hardware configuration of the database server.

when to use parallel hash join in PostgreSQL?

Parallel hash joins in PostgreSQL are best used when:

  1. The size of the data being joined is large: Parallel hash joins are designed to handle large data sets and can be more efficient than traditional serial hash joins.
  2. The join operation is performance-critical: Parallel hash joins can greatly reduce the execution time of join operations, making them ideal for performance-critical queries.
  3. Multiple cores are available: Parallel hash joins can only be executed in parallel if multiple cores are available, so it is important to ensure that the database server has enough resources to support parallel execution.
  4. The join type is hash join: Parallel hash joins are only effective for hash join operations, so it is important to determine whether this is the appropriate type of join for the query being executed.
  5. The database is properly configured: To use parallel hash joins, the max_parallel_workers_per_gather configuration parameter must be set to a value greater than 0.

In conclusion, parallel hash joins in PostgreSQL are a powerful tool for improving the performance of join operations on large data sets, but they should be used carefully and with consideration for the specific needs of the database and the queries being executed.

About Shiv Iyer 444 Articles
Open Source Database Systems Engineer with a deep understanding of Optimizer Internals, Performance Engineering, Scalability and Data SRE. Shiv currently is the Founder, Investor, Board Member and CEO of multiple Database Systems Infrastructure Operations companies in the Transaction Processing Computing and ColumnStores ecosystem. He is also a frequent speaker in open source software conferences globally.