Best Practices for Spark Performance Management

Presented by

Alex Pierce, Field Engineer at Pepperdata

About this talk

Gain the knowledge of Spark veteran Alex Pierce on how to manage the challenges of maintaining the performance and usability of your Spark jobs. Apache Spark provides sophisticated ways for enterprises to leverage big data compared to Hadoop. However, the increasing amounts of data being analyzed and processed through the framework is massive and continues to push the boundaries of the engine. This webinar draws on experiences across dozens of production deployments and explores the best practices for managing Apache Spark performance. Learn how to avoid common mistakes, improve the usability, supportability and performance of Spark. Topics include: – Serialization – Partition sizes – Executor resource sizing – DAG management

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Pepperdata is the Big Data performance company. Fortune 1000 enterprises depend on Pepperdata to manage and optimize the performance of Hadoop and Spark applications and infrastructure. Developers and IT Operations use Pepperdata soluions to diagnose and solve performance problems in production, increase infrastructure efficiencies, and maintain critical SLAs. Pepperdata automatically correlates performance issues between applications and operations, accelerates time to production, and increases infrastructure ROI. Pepperdata works with customer Big Data systems on-premises and in the cloud.