Understanding and Monitoring pg_stat_user_indexes in PostgreSQL: When to Drop Unused Indexes

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Indexes play a crucial role in PostgreSQL, boosting read performance by allowing faster access to data. However, maintaining too many indexes can slow down write operations, as each insert, update, or delete operation requires index maintenance. So, how can you determine if an index is beneficial or just creating unnecessary overhead? In this post, we’ll dive into pg_stat_user_indexes, a built-in PostgreSQL view that helps you monitor index usage and make informed decisions about which indexes can be safely dropped.

In my previous posts, we explored How to Check for Indexes on Foreign Key Columns in PostgreSQL and Automating Index Creation for Foreign Keys in PostgreSQL. Now, we’ll build on that foundation by examining how to identify underutilized indexes and understand when it’s time to let them go.

What is pg_stat_user_indexes?

The pg_stat_user_indexes view in PostgreSQL is a powerful tool that provides statistics about index usage. It includes information such as how often an index is scanned (idx_scan), the number of rows read (idx_tup_read), and the rows fetched (idx_tup_fetch). These statistics can help you evaluate whether an index is actively used or if it may be a candidate for removal.

Key Columns in pg_stat_user_indexes

• indexrelname: The name of the index.
• idx_scan: The total number of scans that have used this index. If this value is consistently low or zero, it suggests the index is rarely accessed by queries.
• idx_tup_read: The number of rows the index scan has read.
• idx_tup_fetch: The number of rows fetched by the index scan, which can indicate the utility of the index in terms of data retrieval.

How to Find Underutilized Indexes

To identify which indexes may be suitable for dropping, you can query pg_stat_user_indexes for indexes with low or zero idx_scan counts:

SELECT
    schemaname,
    relname AS table_name,
    indexrelname AS index_name,
    idx_scan,
    idx_tup_read,
    idx_tup_fetch
FROM
    pg_stat_user_indexes
WHERE
    schemaname = 'public'
ORDER BY
    idx_scan ASC, idx_tup_read ASC;

Look for indexes with low or zero idx_scan values. These indexes are rarely accessed and may not be significantly contributing to query performance.

Remember, idx_scan Counters Reset

It’s important to note that idx_scan counters reset in certain situations:

• Server Restart: All statistics, including idx_scan, are reset when the PostgreSQL server restarts.
• Manual Reset: You can reset statistics manually using pg_stat_reset() for all indexes, or pg_stat_reset_single_table_counters(oid) for specific tables.

To track index usage trends over time, consider regularly exporting pg_stat_user_indexes data to a logging table or monitoring system, allowing you to make informed decisions about index retention even after resets.

Dropping Unused Indexes: Things to Consider

1. Monitor Over Time: Make sure an index is consistently underutilized before dropping it. Regular data collection helps you observe patterns and avoid dropping indexes that may be essential during specific workloads.
2. Check for Dependencies: Verify that no queries, functions, or stored procedures depend on the index. Also, consider if the index supports any foreign key or unique constraints that are vital for data integrity.
3. Simulate the Impact: Use EXPLAIN on queries that could potentially use the index and check for performance changes without it. If dropping the index significantly impacts query performance, consider keeping it.
4. Assess the Overall Cost: While an index may not see frequent scans, it could still justify its existence if it speeds up critical queries. Balance the performance benefit against the maintenance cost.

Conclusion

By regularly reviewing pg_stat_user_indexes, you can identify underused indexes and improve overall database performance. Removing indexes that don’t provide significant read benefits can reduce the overhead on write operations, keeping your database optimized for both reads and writes.

For a comprehensive approach, you might also be interested in our previous discussions on Detecting Unindexed Foreign Keys and Automating Index Creation for Foreign Keys. Together, these strategies ensure that you have essential indexes in place while avoiding unnecessary ones that can hinder performance.

By combining these monitoring and automation techniques, you can maintain a well-balanced and efficient PostgreSQL environment, ultimately benefiting both read and write performance.

This approach gives you a robust framework to evaluate your indexes, enabling you to make data-driven decisions about which ones to keep and which to let go. Happy indexing!