Take a closer look at your Spark implementation

Apache Spark, the extremely popular data analytics execution engine, was initially released in 2012. It wasn’t until 2015 that Spark really saw an uptick in support, but by November 2015, Spark saw 50 percent more activity than the core Apache Hadoop project itself, with more than 750 contributors from hundreds of companies participating in its development in one form or another.

Spark is a hot new commodity for a reason. Its performance, general-purpose applicability, and programming flexibility combine to make it a versatile execution engine. Yet that variety also leads to varying levels of support for the product and different ways solutions are delivered.

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