May 2017
Intermediate to advanced
294 pages
7h 33m
English
Content preview from Apache Spark 2.x Cookbook
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Broadcast hash join
The easiest optimization is that if one of the datasets is small enough to fit in memory, it should be broadcasted to every compute node. This use case is very common as data needs to be combined with side data, such as a dictionary, all the time.
Mostly joins are slow due to too much data being shuffled over the network. With the Broadcast join, the smaller dataset is copied to all the worker nodes so the original parallelism of the larger DataFrame is maintained.
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