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Learning Apache Spark 2

You're reading from   Learning Apache Spark 2 A beginner's guide to real-time Big Data processing using the Apache Spark framework

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781785885136
Length 356 pages
Edition 1st Edition
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Author (1):
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Muhammad Asif Abbasi Muhammad Asif Abbasi
Author Profile Icon Muhammad Asif Abbasi
Muhammad Asif Abbasi
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Table of Contents (12) Chapters Close

Preface 1. Architecture and Installation FREE CHAPTER 2. Transformations and Actions with Spark RDDs 3. ETL with Spark 4. Spark SQL 5. Spark Streaming 6. Machine Learning with Spark 7. GraphX 8. Operating in Clustered Mode 9. Building a Recommendation System 10. Customer Churn Prediction Theres More with Spark

I/O tuning

I/O is critical when you are reading data to/from disk. The major things that you need to consider are:

Data locality

The closer your computer is to your data, the better the performance for your jobs. Moving compute to your data is more optimal compared to moving data to your compute, and therein lies the concept of data locality. Process and data can be quite close to each other, or in some cases on entirely different nodes. The locality levels are defined as follows:

  • PROCESS_LOCAL: This is the best possible option where data resides in the same JVM as the process, and hence is called local to the process.
  • NODE_LOCAL: This indicates that the data is not in the same JVM, but is on the same node. This provides a fast way to access the data, despite it being slower than PROCESS_LOCAL, since the data has to be transferred from either the disk or another process.
  • RACK_LOCAL: There can be multiple servers in the RACK. This option indicates that the data is on the same rack as the current...
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