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

Capacity scheduler


The capacity scheduler makes sure that users get the guaranteed minimum amount of configured resources in the YARN cluster. The use of the Hadoop cluster increases with the use cases in the organization and it is very unlikely that organization creates separate Hadoop clusters for each use case because this will increase maintenance. One use case may be that different users in the same organization want to have a certain amount of resources reserved when they want to execute their tasks. The capacity scheduler helps in sharing the cluster resources in a cost-effective manner across different users in the same organization to meet the SLA by ensuring no other user uses resources configured for some other user in the cluster. In short, the cluster resources are shared across multiple user groups. The capacity scheduler works on the concept of queues. A cluster is divided into partitions known as queues and each queue is assigned with a certain percentage of resources. The...