September 2017
Beginner to intermediate
360 pages
8h 13m
English
book
Practical Real-time Data Processing and Analytics
by Shilpi Saxena, Selva raj Ramasamy, Prateek Bhati, Saurabh Gupta
Content preview from Practical Real-time Data Processing and Analytics
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Accumulators
This is the second method of sharing values/data across different nodes and/or drivers in a Spark job. As is evident from the name of this variable, accumulators are used for counting or accumulating the values. They are the answer to MapReduces counters, and they are different from broadcast variables because they are mutable—the value of an accumulator can change, while the jobs can change the value of an accumulator, but only the driver program can read its value. They work as a great aide for data aggregation and counting across distributed workers of Spark.
Let's assume there is a purchase log for a Walmart store and we need to write a Spark job to detect the count of each type of bad records out of the log. The following ...
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