January 2019
Beginner to intermediate
154 pages
4h 31m
English
Content preview from Apache Spark Quick Start Guide
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Wide transformations
Wide transformations involve a shuffle of the data between the partitions. The groupByKey(), reduceByKey(), join(), distinct(), and intersect() are some examples of wide transformations. In the case of these transformations, the result will be computed using data from multiple partitions and thus requires a shuffle. Wide transformations are similar to the shuffle-and-sort phase of MapReduce. Let's understand the concept with the help of the following example:
Wide transformations
We have an RDD-A and we perform a wide transformation such as groupByKey()and we get a new RDD-B with fewer partitions. RDD-B will have data ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.