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Correctness and Performance of Apache Spark SQL with Bogdan Ghit and Nicolas Poggi Databricks

614 views · Published 10 October 2018 · 28:58 · Indexed 4 November 2026

Channel: Databricks · 2018 · Science & Technology

In this talk, we present a comprehensive framework we developed at Databricks for assessing the correctness, stability, and performance of our Spark SQL engine. Apache Spark is one of the most actively developed open source projects, with more than 1200 contributors from all over the world. At this scale and pace of development, mistakes bound to happen. We will discuss various approaches we take, including random query generation, random data generation, random fault injection, and longevity stress tests. We will demonstrate the effectiveness of the framework by highlighting several correctness issues we have found through random query generation and critical performance regressions we were able to diagnose within hours due to our automated benchmarking tools.

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Correctness and Performance of Apache Spark SQL with Bogdan Ghit and Nicolas Poggi Databricks

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