How PostgreSQL Optimizer behaves when Cardinality is Zero?

In PostgreSQL, the optimizer uses cardinality estimates to determine the most efficient execution plan for a query. Cardinality refers to the number of rows in a table or the number of rows returned by a query. When the cardinality estimate is zero, it means that the optimizer believes that no rows will be returned by a query.

When the cardinality estimate is zero, the optimizer may choose a different execution plan than it would have if the cardinality estimate was non-zero. For example, the optimizer may choose to not use an index, to perform a full table scan, or to not use a particular join method.

In some cases, the optimizer may not be able to accurately estimate the cardinality of a query. This can result in a cardinality estimate of zero, even though the query will return rows. In these cases, the optimizer may not choose the most efficient execution plan, leading to suboptimal performance.

To address this issue, you can use various techniques to improve the accuracy of the cardinality estimates, such as updating statistics using the ANALYZE command, using more selective conditions in the query, or using more specific indexes.

In general, it is important to regularly monitor the performance of your PostgreSQL database and take steps to ensure that the optimizer is able to accurately estimate the cardinality of queries, in order to achieve the best performance possible.

How to monitor cardinality in PostgreSQL?

There are several ways to monitor cardinality in PostgreSQL:

  1. EXPLAIN Command: You can use the EXPLAIN command to view the execution plan for a query and see the estimated cardinality for each operation in the plan. The EXPLAIN command provides detailed information about how the optimizer will execute the query and can be useful for understanding why the optimizer is choosing a particular execution plan.
  2. pg_stat_statements Extension: The pg_stat_statements extension provides performance statistics for all SQL statements executed in a PostgreSQL database. You can use the extension to view the average number of rows returned by each query, as well as other performance statistics.
  3. Query Logs: PostgreSQL logs information about all queries that are executed in the database. You can use the query logs to view the number of rows returned by each query, as well as other performance statistics.
  4. Performance Metrics: PostgreSQL provides a variety of performance metrics that can be used to monitor the performance of the database. You can use metrics such as the number of rows returned by queries, the number of disk I/O operations, and the amount of CPU time used by queries to monitor the performance of the database and understand the impact of cardinality on query performance.

Overall, using a combination of these methods can provide a comprehensive picture of the cardinality of queries in your PostgreSQL database and help you identify any performance issues that may be related to cardinality.

About Shiv Iyer 452 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.