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

Data ingestion


The data ingestion is the process of bringing data from one or more sources to a target data storage layer for processing. It is the first step of building any data pipeline. If you think about the two processes, which are Extract, Transform, and Load (ETL) and Extract, Load, and Transform (ELT), the first process is the extraction of data from the source system. In big data processing, the ingestion process has been categorized into multiple types. We will look into some of the design considerations while following these design patterns across the implementation.

Batch ingestion 

Batch ingestion is the process of extracting the data from the source system in longer duration intervals, for example, configuring the ingestion process to run on a daily basis at 5 am. The source of batch ingestion is generally the persistent storage such as database systems, persistent filesystems, and so on, where data is already available. The following diagram shows the design considerations...