How to implement multipass hash joins in PostgreSQL?

Multipass hash join is a technique used to optimize the performance of a hash join operation in a database management system. In a hash join, one table is used as the build input, and the other table is used as the probe input. The build input is hashed and stored in a hash table, while the probe input is probed against the hash table to find matching records.

In a multipass hash join, the join operation is performed in multiple passes, allowing the database management system to use more memory and to process the data in smaller chunks, improving the performance of the join operation.

Step by step implementation of multipass hash joins in PostgreSQL

Multipass hash joins are a technique for performing join operations in a database management system, where multiple passes are made over the data to reduce memory usage. Here is a step-by-step implementation of multipass hash joins in PostgreSQL:

  1. Determine the smaller of the two tables to be joined: In order to implement a multipass hash join in PostgreSQL, it is necessary to determine which of the two tables to be joined is smaller. This smaller table will be used as the build side of the join, while the larger table will be used as the probe side.
  2. Create a hash table for the build side: The next step is to create a hash table for the build side using the values of the join columns. This hash table will be used to store the values of the build side and the corresponding row IDs.
  3. Scan the probe side and probe the hash table: Once the hash table has been created, the next step is to scan the probe side and probe the hash table for each row in the probe side. If a match is found in the hash table, the corresponding row IDs are retrieved and used to join the two tables.
  4. Write the joined data to a temporary table: The joined data is then written to a temporary table, which can be used as the input for the next pass of the hash join.
  5. Repeat the process for additional passes: The process of scanning the probe side, probing the hash table, and writing the joined data to a temporary table is repeated for additional passes, until the memory usage is reduced to a manageable level.
  6. Return the final joined data: Finally, the final joined data is returned to the user.

Note: The exact number of passes required for a multipass hash join will depend on the amount of available memory and the size of the tables being joined. It may also be necessary to adjust the parameters used by the hash join algorithm to optimize performance.

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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.