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Fast Data Processing with Spark 2

You're reading from   Fast Data Processing with Spark 2 Accelerate your data for rapid insight

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Product type Paperback
Published in Oct 2016
Publisher Packt
ISBN-13 9781785889271
Length 274 pages
Edition 3rd Edition
Languages
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Authors (2):
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Krishna Sankar Krishna Sankar
Author Profile Icon Krishna Sankar
Krishna Sankar
Holden Karau Holden Karau
Author Profile Icon Holden Karau
Holden Karau
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Table of Contents (13) Chapters Close

Preface 1. Installing Spark and Setting Up Your Cluster 2. Using the Spark Shell FREE CHAPTER 3. Building and Running a Spark Application 4. Creating a SparkSession Object 5. Loading and Saving Data in Spark 6. Manipulating Your RDD 7. Spark 2.0 Concepts 8. Spark SQL 9. Foundations of Datasets/DataFrames – The Proverbial Workhorse for DataScientists 10. Spark with Big Data 11. Machine Learning with Spark ML Pipelines 12. GraphX

The Spark shell

The Spark shell is an excellent tool for rapid prototyping with Spark. It works with Scala and Python. It allows you to interact with the Spark cluster and as a result of which, the full API is under your command. It can be great for debugging, just trying things out, or interactively exploring new Datasets or approaches.

The previous chapter should have gotten you to the point of having a Spark instance running; now all you need to do is start your Spark shell and point it at your running instance with the command given in the table we're soon going to check out.

For local mode, Spark will start an instance when you invoke the Spark shell or start a Spark program from an IDE. So, a local installation on a Mac or Linux PC/laptop is sufficient to start exploring the Spark shell. Not having to spin up a real cluster to do the prototyping is an important and useful feature of Spark. The Quick Start guide at http://spark.apache.org/docs/latest/quick-start.html is a good...

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Fast Data Processing with Spark 2 - Third Edition
Published in: Oct 2016
Publisher: Packt
ISBN-13: 9781785889271
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