Big Query SQL Query Optimizer-SQL Query Optimization for BigQuery

Example

Optimizing a query that joins two large tables by recommending the use of partitioning and clustering, resulting in faster execution times.

Scenario

A retail company runs a query that joins sales data with customer data across millions of rows. The optimizer suggests using date-based partitioning on the sales data to minimize the number of scanned partitions, thereby reducing query runtime and costs.

Example

Identifying unnecessary full-table scans and suggesting strategies like column pruning or filtering early in the query.

Scenario

A marketing team running an ad-hoc analysis query on millions of rows accidentally selects all columns when only a few are needed. The optimizer suggests limiting the selected columns to only those required, reducing the amount of processed data and saving on query costs.

Example

Rewriting complex subqueries or nested queries into more efficient, flat structures that BigQuery can parallelize more effectively.

Scenario

An analyst writes a query with deeply nested subqueries for hierarchical data processing. The optimizer suggests flattening the query structure and using common table expressions (CTEs) for better parallelism and improved execution speed.