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Learning Hadoop 2

You're reading from Learning Hadoop 2 Design and implement data processing, lifecycle management, and analytic workflows with the cutting-edge toolbox of Hadoop 2

Product type Paperback

Published in Feb 2015

Publisher Packt

ISBN-13 9781783285518

Length 382 pages

Edition 1st Edition

Tools

Hadoop

Concepts

Data Processing

Author (1):

GABRIELE MODENA

View More author details

Table of Contents (13) Chapters

Preface

1. Introduction FREE CHAPTER

2. Storage

3. Processing – MapReduce and Beyond

4. Real-time Computation with Samza

5. Iterative Computation with Spark

6. Data Analysis with Apache Pig

7. Hadoop and SQL

8. Data Lifecycle Management

9. Making Development Easier

10. Running a Hadoop Cluster

11. Where to Go Next

Index

Apache Spark

Apache Spark (https://spark.apache.org/) is a data processing framework based on a generalization of MapReduce. It was originally developed by the AMPLab at UC Berkeley (https://amplab.cs.berkeley.edu/). Like Tez, Spark acts as an execution engine that models data transformations as DAGs and strives to eliminate the I/O overhead of MapReduce in order to perform iterative computation at scale. While Tez's main goal was to provide a faster execution engine for MapReduce on Hadoop, Spark has been designed both as a standalone framework and an API for application development. The system is designed to perform general-purpose in-memory data processing, stream workflows, as well as interactive and iterative computation.

Spark is implemented in Scala, which is a statically typed programming language for the Java VM and exposes native programming interfaces for Java and Python in addition to Scala itself. Note that though Java code can call the Scala interface directly, there...

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Authors (1)

GABRIELE MODENA

GABRIELE MODENA

Gabriele Modena is a data scientist at Improve Digital. In his current position, he uses Hadoop to manage, process, and analyze behavioral and machine-generated data. Gabriele enjoys using statistical and computational methods to look for patterns in large amounts of data. Prior to his current job in ad tech he held a number of positions in Academia and Industry where he did research in machine learning and artificial intelligence. He holds a BSc degree in Computer Science from the University of Trento, Italy and a Research MSc degree in Artificial Intelligence: Learning Systems, from the University of Amsterdam in the Netherlands.

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