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Mastering Hadoop 3

Mastering Hadoop 3

By : Wong, Singh, Kumar
5 (1)
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Mastering Hadoop 3

Mastering Hadoop 3

5 (1)
By: Wong, Singh, 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 (21 chapters)
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1
Section 1: Introduction to Hadoop 3
6
Section 2: Hadoop Ecosystem
10
Section 3: Hadoop in the Real World
16
Section 4: Securing Hadoop

Summary

In this chapter, our focus was to cover the architecture of HDFS and its components. We covered the internals of NameNode and DataNode internals. We explained the work of the Quorum Journal Manager and HDFS high availability in Hadoop 3. Data management was also a focus of this chapter, and we covered edit logs and fsimage in detail. We looked at a brief overview of the checkpoint process. We also covered the internals of the HDFS write and read operations. The interface and HDFS commands were explained with examples.

In the next chapter, we will cover Yet Another Resource Manager (YARN) in detail. We will dive deep into the YARN architecture and will cover its components in detail. We will gain an understanding of the different types of schedulers that are available in YARN and their detailed uses. A few new features were added to YARN in the Hadoop 3 release...

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