March 2019
Beginner to intermediate
182 pages
4h 6m
English
We know that partitioning and partitioners are the key components of Apache Spark. They influence how our data is partitioned, which means they influence where the data actually resides on which executors. If we have a good partitioner, then we will have good data locality, which will reduce shuffle. We know that shuffle is not desirable for processing, so reducing shuffle is crucial, and, therefore, choosing a proper partitioner is also crucial for our systems.
In this section, we will cover the following topics:
We will first examine our HashPartitioner and RangePartitioner. We will then compare them and test the code using both the partitioners. ...
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