February 2019
Beginner to intermediate
544 pages
14h 36m
English
Content preview from Mastering Hadoop 3
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Accumulators and broadcast variables
Spark is a distributed processing framework where datasets are being processed in parallel. The values of the variables used in the program are not shareable and its scope is limited to that machine only. Think about a use case where you want to track the count of a particular record that occurs in a dataset without performing any RDD aggregation operation, or if you want to create central variables that can be modified by a Spark program. In such cases, there has to be a way to share variables across different workers. Spark provides two special types of shared variables:
- Broadcast variable: Broadcast variables are shared throughout the cluster, which means that a program running on a worker node can ...
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