<ul><li>Partitioning in BigQuery splits a large table into smaller partitions based on a column, improving query performance and reducing costs.</li><li>Types of partitioning include Date/Time, Ingestion-Time, and Integer-Range partitioning.</li><li>Best practices include selecting the right low-cardinality partition column and filtering by it in queries.</li><li>Avoid using functions on the partition column to enable partition pruning and optimize performance.</li><li>Integer-Range partitioning is recommended for non-date data.</li><li>Combining partitioning with clustering enhances query efficiency in BigQuery.</li><li>Monitoring partition size and count is crucial to maintain efficiency and balance.</li><li>Using __PARTITIONTIME for Ingestion-Time partitioned tables is recommended.</li><li>Avoid over-partitioning to stay within the limit of 4,000 partitions per table.</li><li>Set expiration for temporary data to automatically delete old data in BigQuery.</li></ul>

Best Practices on Partitioning in BigQuery

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