How do you troubleshoot PostgreSQL's buffer cache bloat and fragmentation issues and reclaim wasted space?

1 What is buffer cache?

Buffer cache is the memory area where PostgreSQL stores the most frequently accessed data blocks from the disk. It reduces the need for disk I/O and speeds up the query execution. PostgreSQL uses a least recently used (LRU) algorithm to evict the oldest blocks from the cache when it is full. You can control the size of the buffer cache by setting the shared_buffers parameter in the postgresql.conf file.

2 What is cache bloat?

Cache bloat is a situation where the buffer cache contains too many blocks that are rarely or never accessed. This can happen when a large table or index is scanned once and then not used again, or when a table or index is updated frequently and the old versions of the blocks are not removed. Cache bloat wastes memory and reduces the cache hit ratio, which is the percentage of blocks that are found in the cache instead of the disk. You can monitor the cache hit ratio by using the pg_stat_database view or the pg_buffercache extension.

3 What is cache fragmentation?

Cache fragmentation is a situation where the buffer cache contains many blocks that are partially filled or have gaps between them. This can happen when a table or index is subject to frequent insertions, deletions, or updates that change the size or location of the data. Cache fragmentation reduces the effective use of the cache space and increases the disk I/O. You can measure the cache fragmentation by using the pg_freespacemap extension or the pgstattuple function.

4 How to prevent cache bloat and fragmentation?

To prevent or reduce cache bloat and fragmentation in PostgreSQL, you can use appropriate vacuum settings to remove dead tuples and free up space in tables and indexes. Autovacuum daemon or manual vacuum commands can be used periodically. Partitioning or sharding can also be used to split large tables or indexes into smaller, more manageable chunks, which can improve cache efficiency and reduce scan time. Additionally, it is important to use indexes wisely and avoid creating unnecessary or redundant indexes. The pg_stat_user_indexes view or the pg_index_usage extension can be used to identify unused or underused indexes. Lastly, fillfactor settings can be used to leave some space in blocks for future updates, which can reduce page splits and fragmentation. Fillfactor can be set at the table or index level or using the default_storage_params parameter in the postgresql.conf file.

5 How to troubleshoot cache bloat and fragmentation?

If you suspect that your PostgreSQL database is suffering from cache bloat or fragmentation, you can use some tools and commands to diagnose and fix the issues. For example, the pg_buffercache extension can be used to examine the contents and usage of the buffer cache, while the pg_freespacemap extension can be used to analyze the free space map of the tables and indexes. Additionally, the pgstattuple function or the pgstattuple extension can be used to get the physical and logical statistics of the tables and indexes. Finally, the pg_repack extension or the CLUSTER command can be used to reorganize the tables and indexes and eliminate the bloat and fragmentation, which can improve the cache utilization and the query performance.