Reducing BigQuery Costs: How We Fixed A $1 Million Query - Shopify

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This post details how the team reduced BigQuery costs for a new marketing tool's data pipeline by applying table clustering. The initial query processed 75 GB of data, leading to an estimated monthly cost of nearly $1 million USD. By clustering the BigQuery table on two relevant columns from the WHERE clause, the data processed was reduced to 108.3 MB per query, bringing the estimated monthly cost down to approximately $1,370.67 USD. The post also provides additional tips for reducing BigQuery costs, such as avoiding SELECT*, partitioning tables, and using table preview options instead of running queries for data exploration.