PostgreSQL multipass hash joins Explained.

In PostgreSQL, multipass hash joins are a type of join algorithm used to efficiently process join operations between large tables. Unlike traditional hash joins that require loading the entire hash table into memory, multipass hash joins utilize a two-step process that allows for efficient memory usage and improved performance. Let’s dive into the details of multipass hash joins with examples:

Overview of Multipass Hash Joins:

Multipass hash joins involve two passes: a build phase and a probe phase.

  • Build Phase: In the build phase, the smaller of the two join relations, known as the inner relation, is read and used to construct the hash table. The hash table is created by hashing the join keys and storing the corresponding rows or pointers in memory or on disk.
  • Probe Phase: In the probe phase, the larger relation, known as the outer relation, is read and the hash table is probed using the join keys. Matching rows are retrieved from the hash table and combined with the corresponding rows from the outer relation to produce the join results.

Example Scenario:

Let’s consider an example scenario where we have two tables, orders and customers, with a common join column customer_id. The customers table is smaller, containing information about customers, while the orders table is larger and contains order details. We want to join these tables based on the customer_id column.

Execution Steps:

When executing a multipass hash join, the following steps occur:

a. Build Phase:

  • The customers table, being the smaller relation, is read and used to build the hash table. The hash function is applied to the customer_id column, and the corresponding rows or pointers are stored in memory or on disk.

b. Probe Phase:

  • The orders table, being the larger relation, is read. The hash function is applied to the customer_id column, and the hash table is probed using the join keys.
  • For each row in the orders table, the hash value is computed and used to look up matching rows in the hash table.
  • Matching rows from the orders table and the hash table are combined to produce the join results.

Benefits of Multipass Hash Joins:

Multipass hash joins offer several advantages:

  • Reduced Memory Usage: Multipass hash joins efficiently utilize memory by storing the hash table in memory or on disk, allowing for join operations on large tables without requiring excessive memory.
  • Improved Performance: By dividing the join process into two phases and leveraging hashing techniques, multipass hash joins can significantly improve the performance of join operations, especially for large tables.

Configuration and Optimization:

  • PostgreSQL automatically selects the appropriate join algorithm based on various factors, including table size, available memory, and configuration parameters. However, you can influence the choice of join algorithm by adjusting the relevant configuration parameters, such as work_mem, to control the amount of memory allocated for hash joins.
  • It’s important to note that the effectiveness of multipass hash joins depends on the characteristics of the specific join operation and the available system resources. Careful monitoring, performance testing, and query optimization techniques should be employed to ensure the best utilization of join algorithms for specific scenarios.

In summary, multipass hash joins in PostgreSQL provide an efficient method for joining large tables by using a two-step process involving a build phase and a probe phase. This approach reduces memory usage and improves performance, making it particularly useful for scenarios where memory constraints exist or when joining large tables.

About Shiv Iyer 456 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.