PostgreSQL Clustering_Factor
In PostgreSQL, the clustering factor is a statistic that shows how closely the physical order of rows matches the logical order defined by the clustering key.This metric becomes especially important for tables that use index-organized storage or rely on indexes frequently scanned or used in range queries.
The clustering factor is a measure of data locality. Indicating how close the physical order of rows is to the order of the clustering key. When the clustering factor is low, data locality is high. In other words, PostgreSQL stores rows in a way that closely follows the clustering key’s order. This alignment significantly improves the performance of certain queries. For example, range scans or queries that fetch adjacent rows based on the clustering key benefit from better data locality.
The clustering factor is calculated by examining the order of index blocks and the position of table rows within those blocks. A lower clustering factor indicates that related rows are stored in close proximity to each other, reducing the number of disk I/O operations required to fetch the data. On the other hand, a higher clustering factor suggests that the physical order of rows is more scattered, requiring more I/O operations to retrieve the desired data.
To obtain the clustering factor in PostgreSQL, you can use the pg_stats system catalog view or the pgstattuple extension. Here’s an example query using pg_stats:
SELECT tablename, indexname, relpages, reltuples, relpages * reltuples AS total_rows, reltuples / relpages AS clustering_factor
FROM pg_stats
WHERE schemaname = ‘public’ — replace with your schema
AND tablename = ‘your_table’
AND attname = ‘your_clustering_key’;
In the above query, replace ‘your_table’ with the name of your table and ‘your_clustering_key’ with the name of the column that serves as the clustering key.
Conclusion:
It’s important to note that the clustering factor is specific to a particular index and clustering key combination. Regularly monitoring and analyzing the clustering factor can help identify potential performance bottlenecks and guide decisions on index maintenance, table reorganization, or query optimizations to improve data locality and overall query performance.
