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Materialized Views in BigQuery
- Materialized views in BigQuery store precomputed query results on disk to improve query performance and reduce costs.
- Compared to standard views, materialized views do not need to execute the query each time, making them faster and more cost-effective.
- Benefits include improved performance, cost savings, and ideal usage for scenarios where data does not change frequently.
- Key points to remember: Materialized view and base table must be in the same dataset, can only use one base table without joins, and are mainly used for aggregation or filtering.
- Limitations include inability to use materialized views in copy, import, or export jobs and breakage if the base table is deleted.
- Steps for creating materialized views include defining the base table, inserting sample data, and creating materialized views for different aggregations.
- Examples of materialized views created include total sales per salesperson, daily sales total, total sales by region, and top salesperson daily summary.
- Materialized views are useful for speeding up repeated queries with aggregations and filtering in BigQuery but require monitoring freshness and caution with base table deletions.
- Query rerouting can automatically utilize existing materialized views for better query efficiency in BigQuery.
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