December 15, 2019

175 words 1 min read

Breaking Spark: The top five mistakes to avoid when using Apache Spark in production

Breaking Spark: The top five mistakes to avoid when using Apache Spark in production

Drawing on his experiences across 150+ production deployments, Neelesh Srinivas Salian focuses on five common issues observed in a cluster environment setup with Apache Spark (Core, Streaming, and SQL) to help you improve the usability and supportability of Apache Spark and avoid such issues in future deployments.

Talk Title Breaking Spark: The top five mistakes to avoid when using Apache Spark in production
Speakers
Conference Strata + Hadoop World
Conf Tag Make Data Work
Location New York, New York
Date September 27-29, 2016
URL Talk Page
Slides Talk Slides
Video

Apache Spark has been growing in deployments for the past two years. The increasing amount of data being analyzed and processed through the framework is massive, and it continues to push the boundaries of the engine. Drawing on his experiences across 150+ production deployments, Neelesh Srinivas Salian focuses on five common issues observed in a cluster environment setup with Apache Spark (Core, Streaming, and SQL) to help you improve the usability and supportability of Apache Spark and avoid such issues in future deployments. Topics include:

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