Spark is quickly becoming a standard for writing deep analytics that leverage in-memory performance, streaming data, machine learning libraries, SQL, and graph analytics. The Spark environment provides big data developers and data scientists a quicker way to build advanced analytics programs with its abilities to overcome shortcomings of MapReduce and to meet the demand for faster and more powerful processing for the full data pipeline. This paper guides the reader through the hype surrounding Spark to distill salient points on why Spark matters. We explore:
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