Controlling Partition and File Counts in Spark

Landon Robinson shows how we can control the number of partitions (and therefore the number of output files) on reduce-style jobs in Spark:

Whatever the case may be, the desire to control the number of files for a job or query is reasonable – within, ahem, reason – and in general is not too complicated. And, it’s often a very beneficial idea.

However, a thorough understanding of distributed computing paradigms like Map-Reduce (a paradigm Apache Spark follows and builds upon) can help understand how files are created by parallelized processes. More importantly, one can learn the benefits and consequences of manipulating that behavior, and how to do so properly – or at least without degrading performance.

There’s good advice in here, so check it out.

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