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Spark is altering the massive knowledge world faster than the Hadoop vendors can redraw their platform diagrams. The project noticed not one however two major releases in 2016: 1.6 and a couple of.0 Both brought major efficiency improvements and main new options across the board (SQL, streaming, machine studying, and graph processing), but significantly in streaming In case you have been ready for Spark to be ready for manufacturing,” you no longer have any excuses. Spark is prepared in your workload, and it’s a pleasure to use.
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