Book Image

Mastering Hadoop 3

By : Chanchal Singh, Manish Kumar
Book Image

Mastering Hadoop 3

By: Chanchal Singh, Manish Kumar

Overview of this book

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.
Table of Contents (23 chapters)
Title Page
Dedication
About Packt
Foreword
Contributors
Preface
Index

Chapter 6. Real-Time Processing Engines

Big data processing has become a priority for companies now, and there are plenty of tools and frameworks available for processing this data. The first distributed framework was MapReduce, and after that there were lots of tools being developed for it, such as Hive and Pig. The requirement of processing a larger dataset quickly resulted in the development of Apache Spark, and to be able to process data in real-time, we had Apache Storm. In this chapter, we will discuss some of the popular processing frameworks, such as Apache Spark, Apache Flink, and Apache Storm.

We are going to cover the following topics:

  • Apache Spark architecture and its internal
  • Example covering running the Spark application
  • Apache Flink architecture and its ecosystem
  • Apache Flink APIs
  • Apache Storm with Heron as its successor