Understanding BigQuery Caching: Features, Limitations, and Best Practices

BigQuery is a powerful tool for querying large datasets, but to optimize performance and reduce costs, it's important to understand how its caching mechanism works. This article provides an overview of BigQuery's caching features, when caching is used, and its limitations. It also covers how caching can be controlled and disabled for specific queries.

 

1. Features and Limitations

1. Default Caching Behavior: BigQuery automatically caches the results of queries by default. If you run the same query again within approximately 24 hours and the underlying data hasn't changed, BigQuery will serve the results from the cache. This reduces query processing time and costs.

 

2. When Queries Are Not Cached:

·      Destination Tables: If you specify a destination table to store the result, the query results will not be cached.

·      Query Changes: Any change to the query, including even minor modifications like changes in whitespace or capitalization, will get the results from actual database.

·      Non-deterministic Functions: Queries that use non-deterministic functions (e.g., NOW(), CURRENT_TIMESTAMP(), etc.) will not have their results cached as these functions generate different results each time.

·      External Data Sources: Queries running against external data sources, like Cloud Storage, do not cache the results.

·      Modified Data: If the underlying data in the queried table changes (e.g., new rows are added), the cache will be invalidated, and the query will be executed again.

 

3. Query Cache Invalidations: Several factors can invalidate the query cache:

 

·      Modifications to the queried tables (e.g., new rows).

·      Disabling caching through query settings.

 

4. Caching Scope: The cache is specific to the user and project. This means that different users or projects will have their own independent caches, ensuring no cross-project cache usage.

 

5. Cache Storage Costs: Although using cached query results reduces processing costs, storage costs still apply to the cached results. It's important to factor in these costs when designing your queries.

 

6. Disabling Cache: You can disable caching for a query by using the setting "Use cached results." If this setting is unchecked, BigQuery will ignore the cache and execute the query as if it were the first time. You can also choose not to use cached results by adjusting query settings when required.

 

In summary, while BigQuery’s caching features can significantly improve query performance and reduce costs, it is essential to understand when the cache is used, its limitations, and how to manage caching. Keep in mind that queries with destination tables, non-deterministic functions, or those involving external data sources will not benefit from caching.

 

By optimizing your query strategy and managing cache usage efficiently, you can strike the right balance between cost, performance, and accuracy.

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