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Making Spark and Hadoop Run SQL Better And Faster

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Here’s an image for you. There is no such thing as a data lake. The multi-petabyte storage racks nearly overflowing with unstructured and semi-structured data that are being built by hyperscalers, enterprises, and governments can probably be best described as a vast data lava lamp, with different kinds of data rising and falling as it warms and then cools.

Systems of record – you know, boring ERP, supply chain, customer relationship, and other systems – sit off to the side, with relatively small amounts of white-hot data that needs to be correlated with this larger pool of churning data. The

Making Spark and Hadoop Run SQL Better And Faster was written by Timothy Prickett Morgan at The Next Platform.


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