Hadoop Essentials

Delve into the key concepts of Hadoop and get a thorough understanding of the Hadoop ecosystem
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Hadoop Essentials

Shiva Achari

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Delve into the key concepts of Hadoop and get a thorough understanding of the Hadoop ecosystem
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Book Details

ISBN 139781784396688
Paperback194 pages

Book Description

This book jumps into the world of Hadoop ecosystem components and its tools in a simplified manner, and provides you with the skills to utilize them effectively for faster and effective development of Hadoop projects.

Starting with the concepts of Hadoop YARN, MapReduce, HDFS, and other Hadoop ecosystem components, you will soon learn many exciting topics such as MapReduce patterns, data management, and real-time data analysis using Hadoop. You will also get acquainted with many Hadoop ecosystem components tools such as Hive, HBase, Pig, Sqoop, Flume, Storm, and Spark.

By the end of the book, you will be confident to begin working with Hadoop straightaway and implement the knowledge gained in all your real-world scenarios.

Table of Contents

Chapter 1: Introduction to Big Data and Hadoop
V's of big data
Understanding big data
Who is creating big data?
Big data use case patterns
Hadoop
Pillars of Hadoop
Data access components
Data storage component
Data ingestion in Hadoop
Streaming and real-time analysis
Summary
Chapter 2: Hadoop Ecosystem
Traditional systems
The Hadoop use cases
Hadoop's basic data flow
Hadoop integration
The Hadoop ecosystem
Distributed filesystem
Distributed programming
NoSQL databases
Data ingestion
Service programming
Scheduling
Data analytics and machine learning
System management
Summary
Chapter 3: Pillars of Hadoop – HDFS, MapReduce, and YARN
HDFS
MapReduce
YARN
Summary
Chapter 4: Data Access Components – Hive and Pig
Need of a data processing tool on Hadoop
Pig
Hive
Summary
Chapter 5: Storage Component – HBase
An Overview of HBase
Advantages of HBase
The Architecture of HBase
The HBase data model
The Schema design
The Write pipeline
The Read pipeline
Compaction
Splitting
Commands
HBase Hive integration
Performance tuning
Summary
Chapter 6: Data Ingestion in Hadoop – Sqoop and Flume
Data sources
Challenges in data ingestion
Sqoop
Connectors and drivers
Sqoop 1 architecture
Sqoop 2 architecture
Imports
Exports
Apache Flume
Flume architecture
Examples of configuring Flume
Summary
Chapter 7: Streaming and Real-time Analysis – Storm and Spark
An introduction to Storm
Storm topology
Storm on YARN
Topology configuration example
An introduction to Spark
Spark framework
Spark architecture
Operations in Spark
Spark example
Summary

What You Will Learn

  • Get introduced to Hadoop, big data, and the pillars of Hadoop such as HDFS, MapReduce, and YARN
  • Understand different use cases of Hadoop along with big data analytics and real-time analysis in Hadoop
  • Explore the Hadoop ecosystem tools and effectively use them for faster development and maintenance of a Hadoop project
  • Demonstrate YARN's capacity for database processing
  • Work with Hive, HBase, and Pig with Hadoop to easily figure out your big data problems
  • Gain insights into widely used tools such as Sqoop, Flume, Storm, and Spark using practical examples

Authors

Table of Contents

Chapter 1: Introduction to Big Data and Hadoop
V's of big data
Understanding big data
Who is creating big data?
Big data use case patterns
Hadoop
Pillars of Hadoop
Data access components
Data storage component
Data ingestion in Hadoop
Streaming and real-time analysis
Summary
Chapter 2: Hadoop Ecosystem
Traditional systems
The Hadoop use cases
Hadoop's basic data flow
Hadoop integration
The Hadoop ecosystem
Distributed filesystem
Distributed programming
NoSQL databases
Data ingestion
Service programming
Scheduling
Data analytics and machine learning
System management
Summary
Chapter 3: Pillars of Hadoop – HDFS, MapReduce, and YARN
HDFS
MapReduce
YARN
Summary
Chapter 4: Data Access Components – Hive and Pig
Need of a data processing tool on Hadoop
Pig
Hive
Summary
Chapter 5: Storage Component – HBase
An Overview of HBase
Advantages of HBase
The Architecture of HBase
The HBase data model
The Schema design
The Write pipeline
The Read pipeline
Compaction
Splitting
Commands
HBase Hive integration
Performance tuning
Summary
Chapter 6: Data Ingestion in Hadoop – Sqoop and Flume
Data sources
Challenges in data ingestion
Sqoop
Connectors and drivers
Sqoop 1 architecture
Sqoop 2 architecture
Imports
Exports
Apache Flume
Flume architecture
Examples of configuring Flume
Summary
Chapter 7: Streaming and Real-time Analysis – Storm and Spark
An introduction to Storm
Storm topology
Storm on YARN
Topology configuration example
An introduction to Spark
Spark framework
Spark architecture
Operations in Spark
Spark example
Summary

Book Details

ISBN 139781784396688
Paperback194 pages
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