Zansa › Answers › Integration and BI tools
How do partitioning and clustering speed up queries in BigQuery?
Partitioning splits a table into segments, usually by date, so queries that filter on date read only the relevant segments. Clustering sorts data within a table by chosen columns, so filters on those columns scan less data. Both can reduce cost and improve speed.
Good practice:
- Partition large fact tables on a date column you filter by often.
- Cluster on columns commonly used in filters or joins, such as customer or product ID.
- Require a partition filter on very large tables to prevent accidental full scans.
Small tables gain little from either. Check current documentation, as features and limits are updated over time.
Want this applied to your business? Zansa builds dashboards and forecasts for small and mid-sized companies worldwide. Start with a free intro call.
Book a call