Google Cloud Professional Data Engineer Exam

When repeatedly running queries that join multiple tables, what feature should be used to optimize query performance in BigQuery?

1. Views

2. Materialized views

3. Federated queries

4. Partitions

The correct answer is: Materialized views

Using materialized views is an effective way to optimize query performance in BigQuery, especially when repeatedly running queries that involve joining multiple tables. Materialized views store the results of a query physically, rather than recalculating them every time the query is executed. This means that when you run a query against a materialized view, the performance is significantly improved because BigQuery retrieves the precomputed results instead of executing the underlying query from scratch. Materialized views maintain data freshness and can automatically refresh when the underlying tables are updated, ensuring that users have access to up-to-date information without incurring the overhead of full query execution each time. This is particularly beneficial for complex queries involving joins, as it reduces the amount of processing and data scanning needed, leading to faster response times and reduced costs due to lower data processing requirements. In contrast, views in BigQuery are virtual tables that do not store data themselves; they simply execute the underlying SQL query each time they are accessed, which doesn’t provide performance optimization for repeated queries. Federated queries directly access data stored outside of BigQuery, such as in Google Cloud Storage, and do not take advantage of internal optimizations. Partitions help organize data for efficient storage and retrieval but don't specifically address the optimization of repeated