A data analysis program is running on a Spark cluster of 5 nodes. The data is...
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A data analysis program is running on a Spark cluster of 5 nodes. The data is partitioned on all 5 nodes. For each of the observations below. suggest what operations can the programmer perform to optimise the performance ? Name the operations in each case and describe in brief what they achieve [Marks: 6] 1. All 5 nodes are not always used. Some data/RDDs may use 4-way partitions. 2. Some of the operations could be faster because they repeatedly access same data. 3. Some of the data is used only once but is contributing to high memory usage A data analysis program is running on a Spark cluster of 5 nodes. The data is partitioned on all 5 nodes. For each of the observations below. suggest what operations can the programmer perform to optimise the performance ? Name the operations in each case and describe in brief what they achieve [Marks: 6] 1. All 5 nodes are not always used. Some data/RDDs may use 4-way partitions. 2. Some of the operations could be faster because they repeatedly access same data. 3. Some of the data is used only once but is contributing to high memory usage
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Answer rating: 100% (QA)
Spark is designed to be highly accessible offering simple APIs in Python Java Scala and SQL and rich builtin libraries It also integrates closely with other Big Data tools In particular Spark can run ... View the full answer
Related Book For
Computer Architecture A Quantitative Approach
ISBN: 978-8178672663
5th edition
Authors: John L. Hennessy, David A. Patterson
Posted Date:
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