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 processing


Data processing is a next step after the ingestion stage is successful. Each ingestion type we discussed previously has an equivalent data processing type. When we refer to data processing here, we generally talk about distributed data processing and there are a lot of scenarios that must be taken into consideration during the processing of data. It is also important to understand that a distributed system is designed to reduce the data processing time and we must take all the best practices into consideration before we start implementing a data processing application. In this section, we will walk you through each of the data processing types and some of the best practices that need to be taken into consideration.

Batch processing

Batch processing is the type of data processing where data elements are processed in a group of batches. For example, if we consider data to be arriving on a daily basis for processing, then we can consider a day as one batch and process the entire...