Spark Succinctly

Syncfusion Inc., 2015. — 111 p. Mastering big data requires an aptitude at every step of information processing. Post-processing, one of the most important steps, is where you find Apache Spark frequently employed. Spark Succinctly, by Marko Švaljek, addresses Spark’s use in the ultimate step in handling big data. Topics included: - Introduction - Installing Spark - Hello Spark - Spark Internals - Data Input and Output with Spark Introduction to Apache Spark for post-processing big data. Table of Contents 4 The Story behind the Succinctly Series of Books 6 Information is plentiful but harder to digest 6 The Succinctly series 6 The best authors, the best content 6 Free forever 7 Free? What is the catch? 7 Let us know what you think 7 About the Author 8 Introduction 9 Basics of Big Data Processing 10 A Brief History of Spark 15 Spark Overview 16 Chapter 1 Installing Spark 18 Installing Spark Prerequisites on Linux 18 Installing Java 18 Installing Python 19 Installing Scala 20 Installing Spark Prerequisites on Windows 21 Installing Java 21 Installing Python 24 Installing Scala 27 Spark Download and Configuration 32 Chapter 2 Hello Spark 35 Counting Text Lines Containing Text 35 Scala Example 36 Python Example 37 Java Example and Development Environment Setup 38 Counting Word Occurrences 51 Chapter 3 Spark Internals 56 Resilient Distributed Dataset (RDD) 56 Caching RDDs 62 Pair RDDs 66 Aggregating Pair RDDs 69 Data Grouping 74 Sorting Pair RDDs 78 Join, Intersect, Union, and Difference Operations on Pair RDDs 81 Chapter 4 Data Input and Output with Spark 92 Working with Text Files 92 Submitting Scala and Python Tasks to Spark 96 Working with JSON files 98 Spark and Cassandra 105 Conclusion 111 Apache,Spark;,big,data;,Cassandra;,Hadoop Apache Spark,big data,Cassandra,Hadoop