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www.slideshare.net/SparkSummit
The document discusses 5 common mistakes people make when writing Spark applications: 1) Not properly sizing executors for memory and cores. 2) Having shuffle blocks larger than 2GB which can cause jobs to fail. 3) Not addressing data skew which can cause joins and shuffles to be very slow. 4) Not properly managing the DAG to minimize shuffles and stages. 5) Classpath conflicts from conflicting de
Deep Dive into Project Tungsten: Bringing Spark Closer to Bare Metal-(Josh Rosen, Databricks) This document summarizes Project Tungsten, an effort by Databricks to substantially improve the memory and CPU efficiency of Spark applications. It discusses how Tungsten optimizes memory and CPU usage through techniques like explicit memory management, cache-aware algorithms, and code generation. It prov
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