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.
Neelesh Srinivas Salian is a software engineer on the data platform team at Stitch Fix, where he works on the compute infrastructure used by the company’s data scientists. Previously, he worked at Cloudera, where he worked with Apache projects like YARN, Spark, and Kafka.
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