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Today I’m continuing my series on HDInsight with the focus on Spark clusters. HDInsight Spark clusters provide the required baseline for in-memory cluster computing. This technology has gained momentum over the last few years as the required levels of memory have increased, as well as the hardware.
So, being able to load a large amount of data into memory has become much more possible. In-memory data allows us to load and cache the data, so it’s much more responsive when working within the data, with querying off it or visualizing for instance.
Some benefits and features of HDInsight Spark are:
Best uses for Spark:
Be sure to check out my next post on HDInsight HBase. If you interested in learning more about any of the big data technologies with HDInsight or any Azure product or service, you’re in the right place. Click the link below or contact us—we are your best resource and we’d love to help.
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