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

Deep dive into the HDFS architecture


As a big data practitioner or enthusiast, you must have read or heard about the HDFS architecture. The goal of this section is to explore the architecture in depth, including the main and essential supporting components. By the end of this section, you will have a deep knowledge of the HDFS architecture, along with the intra-process communication of architecture components. But first, let's start by establishing definition of HDFS (Hadoop Distributed File System). HDFS is the storage system of the Hadoop platform, which is distributed, fault-tolerant, and immutable in nature. HDFS is specifically developed for large datasets (too large to fit in cheaper commodity machines). Since HDFS is designed for large datasets on commodity hardware, it purposely mitigates some of the bottlenecks associated with large datasets.

We will understand some of these bottlenecks and how HDFS mitigates them here:

  • With large datasets comes the problem of slow processing they...