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Cassandra Design Patterns

You're reading from   Cassandra Design Patterns Build real-world, industry-strength data storage solutions with time-tested design methodologies using Cassandra

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Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781785285707
Length 168 pages
Edition 2nd Edition
Languages
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Author (1):
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Rajanarayanan Thottuvaikkatumana Rajanarayanan Thottuvaikkatumana
Author Profile Icon Rajanarayanan Thottuvaikkatumana
Rajanarayanan Thottuvaikkatumana
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Toc

Map/Reduce pattern


Whenever there is a need to migrate from Hadoop MapReduce or to develop new Map/Reduce kind of data processing applications, Cassandra can be used in conjunction with Spark and a preferred programming language such as Scala, Java, Python, or R. Divide the data processing task into Mapper and Reducer kind of transformations and actions. Choose the appropriate Spark Transformations and Spark Actions to complete the task.

Motivations/solutions

Many of the day-to-day data processing needs commonly seen in applications can be divided into multiple smaller tasks and executed in parallel. The results can be combined together to produce the final result. A clustered data processing infrastructure in conjunction with a parallel and distributed data processing framework can divide a huge data processing task to smaller tasks and execute them in parallel, thus reducing the processing time considerably. The other advantage of performing data processing this way is that there is no need...

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