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

HBase


Although Hadoop was getting popular after its invention, it was still only suitable for batch processing use cases where a huge set of data could be processed in a single batch. Hadoop came from the Google research paper called Hadoop Distributed File System (HDFS) from the Google File System Research paper and MapReduce from the Google MapReduce research paper. Google has one more popular product, which is Big Table, and to support random read/write access over large sets of data, HBase was discovered. HBase  runs on top of Hadoop and uses the scalability of Hadoop by running its daemon—HDFS, with real-time data access as a key/value store. 

Note

Apache HBase is an open source, distributed, NoSQL database that provides real-time random read/write access to large datasets over HDFS.

HBase architecture and its concept

Apache HBase is a distributed column storage database that also follows the master/slave architecture. Below is a picture representation of HBase architecture and its components...