The article discusses how a developer unknowingly incurred $3,000 in costs while using Google Cloud BigQuery due to a poorly optimized query.
The article outlines three easy steps to optimize the query and reduce costs by 99.97%.
These steps include avoiding using "SELECT *", using a partitioned table and querying only subsets of data, and using materialized query results in stages. The article also dives into BigQuery's architecture and underlying computing engine, Dremel, providing useful references for further reading.
Share with your friends and followers
Start blogging about your favorite technologies, reach more readers and earn rewards!
Join other developers and claim your FAUN account now!
Only registered users can post comments. Please, login or signup.