Mastering Hadoop 3 · Big Data Processing at Scale to Unlock Unique Business Insights

This is a comprehensive guide to understand advanced concepts of Hadoop ecosystem. You will learn how Hadoop works internally, and build solutions to some of real world use cases. Finally, you will have a solid understanding of how components in the Hadoop ecosystem are effectively integrated to implement a fast and reliable Big Data pipeline.

A comprehensive guide to mastering the most advanced Hadoop 3 concepts

Key Features

Get to grips with the newly introduced features and capabilities of Hadoop 3

Crunch and process data using MapReduce, YARN, and a host of tools within the Hadoop ecosystem

Sharpen your Hadoop skills with real-world case studies and code

Book Description

Apache Hadoop is one of the most popular big data solutions for distributed storage and for processing large chunks of data. With Hadoop 3, Apache promises to provide a high-performance, more fault-tolerant, and highly efficient big data processing platform, with a focus on improved scalability and increased efficiency.

With this guide, you'll understand advanced concepts of the Hadoop ecosystem tool. You'll learn how Hadoop works internally, study advanced concepts of different ecosystem tools, discover solutions to real-world use cases, and understand how to secure your cluster. It will then walk you through HDFS, YARN, MapReduce, and Hadoop 3 concepts. You'll be able to address common challenges like using Kafka efficiently, designing low latency, reliable message delivery Kafka systems, and handling high data volumes. As you advance, you'll discover how to address major challenges when building an enterprise-grade messaging system, and how to use different stream processing systems along with Kafka to fulfil your enterprise goals.

By the end of this book, you'll have a complete understanding of how components in the Hadoop ecosystem are effectively integrated to implement a fast and reliable data pipeline, and you'll be equipped to tackle a range of real-world problems in data pipelines.

What you will learn

Gain an in-depth understanding of distributed computing using Hadoop 3

Develop enterprise-grade applications using Apache Spark, Flink, and more

Build scalable and high-performance Hadoop data pipelines with security, monitoring, and data governance

Explore batch data processing patterns and how to model data in Hadoop

Master best practices for enterprises using, or planning to use, Hadoop 3 as a data platform

Understand security aspects of Hadoop, including authorization and authentication

Who this book is for

If you want to become a big data professional by mastering the advanced concepts of Hadoop, this book is for you. You'll also find this book useful if you're a Hadoop professional looking to strengthen your knowledge of the Hadoop ecosystem. Fundamental knowledge of the Java programming language and basics of Hadoop is necessary to get started with this book.

Table of Contents

Journey to Hadoop 3

Deep Dive into Hadoop Distributed File System

YARN Resource Management in Hadoop

Internals of Map Reduce

SQL on Hadoop

Real Time Processing Engines

Widely used Hadoop Ecosystem Component

Designing Applications in Hadoop

Real Time/Micro Batch Processing in Hadoop

Machine Learning in Hadoop

Hadoop in Cloud

Hadoop Cluster Profiling

Who can do What in Hadoop

Network and Data Security

Monitoring Hadoop

**

A comprehensive guide to mastering the most advanced Hadoop 3 concepts

Key Features

Get to grips with the newly introduced features and capabilities of Hadoop 3

Crunch and process data using MapReduce, YARN, and a host of tools within the Hadoop ecosystem

Sharpen your Hadoop skills with real-world case studies and code

Book DescriptionApache Hadoop is one of the most popular big data solutions for distributed storage and for processing large chunks of data. With Hadoop 3, Apache promises to provide a high-performance, more fault-tolerant, and highly efficient big data processing platform, with a focus on improved scalability and increased efficiency.

With this guide, you'll understand advanced concepts of the Hadoop ecosystem tool. You'll learn how Hadoop works internally, study advanced concepts of different ecosystem tools, discover solutions to real-world use cases, and understand how to secure your cluster. It will then walk you through HDFS, YARN, MapReduce, and Hadoop 3 concepts. You'll be able to address common challenges like using Kafka efficiently, designing low latency, reliable message delivery Kafka systems, and handling high data volumes. As you advance, you'll discover how to address major challenges when building an enterprise-grade messaging system, and how to use different stream processing systems along with Kafka to fulfil your enterprise goals.

By the end of this book, you'll have a complete understanding of how components in the Hadoop ecosystem are effectively integrated to implement a fast and reliable data pipeline, and you'll be equipped to tackle a range of real-world problems in data pipelines.

What you will learn

Gain an in-depth understanding of distributed computing using Hadoop 3

Develop enterprise-grade applications using Apache Spark, Flink, and more

Build scalable and high-performance Hadoop data pipelines with security, monitoring, and data governance

Explore batch data processing patterns and how to model data in Hadoop

Master best practices for enterprises using, or planning to use, Hadoop 3 as a data platform

Understand security aspects of Hadoop, including authorization and authentication

Who this book is forIf you want to become a big data professional by mastering the advanced concepts of Hadoop, this book is for you. You'll also find this book useful if you're a Hadoop professional looking to strengthen your knowledge of the Hadoop ecosystem. Fundamental knowledge of the Java programming language and basics of Hadoop is necessary to get started with this book.

Table of Contents

Journey to Hadoop 3

Deep Dive into Hadoop Distributed File System

YARN Resource Management in Hadoop

Internals of Map Reduce

SQL on Hadoop

Real Time Processing Engines

Widely used Hadoop Ecosystem Component

Designing Applications in Hadoop

Real Time/Micro Batch Processing in Hadoop

Machine Learning in Hadoop

Hadoop in Cloud

Hadoop Cluster Profiling

Who can do What in Hadoop

Network and Data Security

Monitoring Hadoop

**