Topic

pg_partman

1 post about pg_partman. Every summary links to the original.

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Heroku
Handling Very Large Tables in Postgres Using Partitioning
Very large Postgres tables containing application events or log-like data can degrade query performance, slow index updates, and make vacuum disproportionately long. The article explains table partitioning through inheritance, using a master table, child partitions, CHECK constraints, and a trigger that routes inserts according to created_at; for an events workload with 10 million daily inserts and short-lived data, it uses daily partitions. It then introduces pg_partman, whose create_parent command configures time-based partitioning and whose run_maintenance function creates new partitions and removes old ones according to retention settings. Partitioning can improve performance and simplify deletion of expired data, but it should follow indexing and usage analysis, especially when queries cover a small time range and older data has little value.

The best engineering reads, once a week.

Topic

1 post about pg_partman. Every summary links to the original.

Paid picks we use ourselves. Links carry a referral code — a subscription through one earns us a commission at no extra cost to you.

Newest first

Heroku
Handling Very Large Tables in Postgres Using Partitioning
Very large Postgres tables containing application events or log-like data can degrade query performance, slow index updates, and make vacuum disproportionately long. The article explains table partitioning through inheritance, using a master table, child partitions, CHECK constraints, and a trigger that routes inserts according to created_at; for an events workload with 10 million daily inserts and short-lived data, it uses daily partitions. It then introduces pg_partman, whose create_parent command configures time-based partitioning and whose run_maintenance function creates new partitions and removes old ones according to retention settings. Partitioning can improve performance and simplify deletion of expired data, but it should follow indexing and usage analysis, especially when queries cover a small time range and older data has little value.

The best engineering reads, once a week.