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I’ve had the pleasure of having had to analyse multi-gigabyte JSON dumps in a project context recently. JSON itself is actually a rather pleasant format to consume, as it’s human-readable and there is a lot of tooling available for it. JQ allows expressing sophisticated processing steps in a single command line, and Jupyter with Python and Pandas allow easy interactive analysis to quickly find what you’re looking for.
However, with multi-gigabyte files, analysis becomes quite a lot more difficult.

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,Apache Beam ,Command Line ,Json ,Q ,Parallel ,Analysis ,Python ,Jupyter ,

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