Interactive Querying with Apache Spark SQL at Pinterest

Interactive Querying with Apache Spark SQL at Pinterest

摘要

To achieve our mission of bringing everyone inspiration through our visual discovery engine, Pinterest relies heavily on making data-driven decisions to improve the Pinner experience for over 475 million monthly active users. Reliable, fast, and scalable interactive querying is essential to make those data-driven decisions possible. In the past, we published how Presto at Pinterest serves this function. Here, we’ll share how we built a scalable, reliable, and efficient interactive querying platform that processes hundreds of petabytes of data daily with Apache Spark SQL. Through an elaborate discussion on various architecture choices, challenges along the way, and our solutions for those challenges, we share how we made interactive querying with Spark SQL a success.