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Apache Spark 2.x for Java Developers

You're reading from  Apache Spark 2.x for Java Developers

Product type Book
Published in Jul 2017
Publisher Packt
ISBN-13 9781787126497
Pages 350 pages
Edition 1st Edition
Languages
Authors (2):
Sourav Gulati Sourav Gulati
Profile icon Sourav Gulati
Sumit Kumar Sumit Kumar
Profile icon Sumit Kumar
View More author details

Table of Contents (19) Chapters

Title Page
Credits
Foreword
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Introduction to Spark 2. Revisiting Java 3. Let Us Spark 4. Understanding the Spark Programming Model 5. Working with Data and Storage 6. Spark on Cluster 7. Spark Programming Model - Advanced 8. Working with Spark SQL 9. Near Real-Time Processing with Spark Streaming 10. Machine Learning Analytics with Spark MLlib 11. Learning Spark GraphX

Some basic exercises using Spark shell


Note that Spark shell is available only in the Scala language. However, we have kept examples easy to understand by Java developers.

Checking Spark version

Execute the following command to check the Spark version using spark-shell:

scala>sc.version
res0: String = 2.1.1

It is shown in the following screenshot:

Creating and filtering RDD

Let's start by creating an RDD of strings:

scala>val stringRdd=sc.parallelize(Array("Java","Scala","Python","Ruby","JavaScript","Java"))
stringRdd: org.apache.spark.rdd.RDD[String] = ParallelCollectionRDD[0] at parallelize at <console>:24

Now, we will filter this RDD to keep only those strings that start with the letter J:

scala>valfilteredRdd = stringRdd.filter(s =>s.startsWith("J"))
filteredRdd: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[2] at filter at <console>:26

In the first chapter, we learnt that if an operation on RDD returns an RDD then it is a transformation, or else it is an action.

The...

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