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Mastering Hadoop 3

You're reading from  Mastering Hadoop 3

Product type Book
Published in Feb 2019
Publisher Packt
ISBN-13 9781788620444
Pages 544 pages
Edition 1st Edition
Languages
Authors (2):
Chanchal Singh Chanchal Singh
Profile icon Chanchal Singh
Manish Kumar Manish Kumar
Profile icon Manish Kumar
View More author details

Table of Contents (23) Chapters

Title Page
Dedication
About Packt
Foreword
Contributors
Preface
Journey to Hadoop 3 Deep Dive into the Hadoop Distributed File System YARN Resource Management in Hadoop Internals of MapReduce SQL on Hadoop Real-Time Processing Engines Widely Used Hadoop Ecosystem Components Designing Applications in Hadoop Real-Time Stream Processing in Hadoop Machine Learning in Hadoop Hadoop in the Cloud Hadoop Cluster Profiling Who Can Do What in Hadoop Network and Data Security Monitoring Hadoop Other Books You May Enjoy 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...

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