Google Increased the Maximum Number of Partitions for BigQuery

The limit has increased from 4,000 to 10,000.

Why Is This Important?

Partitions are crucial for optimizing storage and queries. They allow large datasets to be broken down into smaller, more manageable segments. Each partition represents a subset of data within a table, grouped by a specific criterion, such as a date column value or a range of values. BigQuery supports various types of partitions, including:

1. Integer Range Partitioning

2. Time-Unit Column Partitioning

3. Ingestion Time Partitioning

Consider a table with an event log, where each event has a timestamp. By creating a partitioned table based on the timestamp column, queries looking for events on a specific day or month will only process the relevant partitions instead of the entire table. This greatly improves query speed and reduces costs.

That is why it is the excellent news for data engineers working with Google Cloud Platform!

If you work with GA4 to BigQuery exports, be sure to check out my SQL cheat sheet.