Books & Videos

Table of Contents

  1. Chapter 1 Meet Hadoop

    1. Data!

    2. Data Storage and Analysis

    3. Comparison with Other Systems

    4. A Brief History of Hadoop

    5. Apache Hadoop and the Hadoop Ecosystem

    6. Hadoop Releases

  2. Chapter 2 MapReduce

    1. A Weather Dataset

    2. Analyzing the Data with Unix Tools

    3. Analyzing the Data with Hadoop

    4. Scaling Out

    5. Hadoop Streaming

    6. Hadoop Pipes

  3. Chapter 3 The Hadoop Distributed Filesystem

    1. The Design of HDFS

    2. HDFS Concepts

    3. The Command-Line Interface

    4. Hadoop Filesystems

    5. The Java Interface

    6. Data Flow

    7. Data Ingest with Flume and Sqoop

    8. Parallel Copying with distcp

    9. Hadoop Archives

  4. Chapter 4 Hadoop I/O

    1. Data Integrity

    2. Compression

    3. Serialization

    4. Avro

    5. File-Based Data Structures

  5. Chapter 5 Developing a MapReduce Application

    1. The Configuration API

    2. Setting Up the Development Environment

    3. Writing a Unit Test with MRUnit

    4. Running Locally on Test Data

    5. Running on a Cluster

    6. Tuning a Job

    7. MapReduce Workflows

  6. Chapter 6 How MapReduce Works

    1. Anatomy of a MapReduce Job Run

    2. Failures

    3. Job Scheduling

    4. Shuffle and Sort

    5. Task Execution

  7. Chapter 7 MapReduce Types and Formats

    1. MapReduce Types

    2. Input Formats

    3. Output Formats

  8. Chapter 8 MapReduce Features

    1. Counters

    2. Sorting

    3. Joins

    4. Side Data Distribution

    5. MapReduce Library Classes

  9. Chapter 9 Setting Up a Hadoop Cluster

    1. Cluster Specification

    2. Cluster Setup and Installation

    3. SSH Configuration

    4. Hadoop Configuration

    5. YARN Configuration

    6. Security

    7. Benchmarking a Hadoop Cluster

    8. Hadoop in the Cloud

  10. Chapter 10 Administering Hadoop

    1. HDFS

    2. Monitoring

    3. Maintenance

  11. Chapter 11 Pig

    1. Installing and Running Pig

    2. An Example

    3. Comparison with Databases

    4. Pig Latin

    5. User-Defined Functions

    6. Data Processing Operators

    7. Pig in Practice

  12. Chapter 12 Hive

    1. Installing Hive

    2. An Example

    3. Running Hive

    4. Comparison with Traditional Databases

    5. HiveQL

    6. Tables

    7. Querying Data

    8. User-Defined Functions

  13. Chapter 13 HBase

    1. HBasics

    2. Concepts

    3. Installation

    4. Clients

    5. Example

    6. HBase Versus RDBMS

    7. Praxis

  14. Chapter 14 ZooKeeper

    1. Installing and Running ZooKeeper

    2. An Example

    3. The ZooKeeper Service

    4. Building Applications with ZooKeeper

    5. ZooKeeper in Production

  15. Chapter 15 Sqoop

    1. Getting Sqoop

    2. Sqoop Connectors

    3. A Sample Import

    4. Generated Code

    5. Imports: A Deeper Look

    6. Working with Imported Data

    7. Importing Large Objects

    8. Performing an Export

    9. Exports: A Deeper Look

  16. Chapter 16 Case Studies

    1. Hadoop Usage at Last.fm

    2. Hadoop and Hive at Facebook

    3. Nutch Search Engine

    4. Log Processing at Rackspace

    5. Cascading

    6. TeraByte Sort on Apache Hadoop

    7. Using Pig and Wukong to Explore Billion-edge Network Graphs

  1. Appendix Installing Apache Hadoop

    1. Prerequisites

    2. Installation

    3. Configuration

  2. Appendix Cloudera’s Distribution Including Apache Hadoop

  3. Appendix Preparing the NCDC Weather Data

  4. Colophon