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Modern Big Data Processing with Hadoop

You're reading from Modern Big Data Processing with Hadoop Expert techniques for architecting end-to-end big data solutions to get valuable insights

Product type Paperback

Published in Mar 2018

Publisher Packt

ISBN-13 9781787122765

Length 394 pages

Edition 1st Edition

Languages

Processing

Tools

Apache Spark

Concepts

Big Data

Authors (3):

R Patil

Shindgikar

Kumar

View More author details

Table of Contents (17) Chapters

Title Page

Copyright and Credits

Packt Upsell

Contributors

Preface

1. Enterprise Data Architecture Principles

2. Hadoop Life Cycle Management FREE CHAPTER

3. Hadoop Design Consideration

4. Data Movement Techniques

5. Data Modeling in Hadoop

6. Designing Real-Time Streaming Data Pipelines

7. Large-Scale Data Processing Frameworks

8. Building Enterprise Search Platform

9. Designing Data Visualization Solutions

10. Developing Applications Using the Cloud

11. Production Hadoop Cluster Deployment

Index

Batch processing versus real-time processing

Before we dive deep into different data ingestion techniques, let's discuss the difference between batch and real-time (stream) processing. The following explains the difference between these two ecosystems.

Batch processing

The following points describe the batch processing system:

Very efficient in processing a high volume of data.
All data processing steps (that is, data collection, data ingestion, data processing, and results presentation) are done as one single batch job.
Throughput carries more importance than latency. Latency is always more than a single minute.
Throughput directly depends on the size of the data and available computational system resources.
Available tools include Apache Sqoop, MapReduce jobs, Spark jobs, Hadoop DistCp utility, and so on.

Real-time processing

The following points describe how real-time processing is different from batch processing:

Latency is extremely important, for example, less than one second
Computation is relatively...

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Authors (3)

R Patil

R Patil

Manoj R Patil is the Chief Architect in Big Data at Compassites Software Solutions Pvt. Ltd. where he overlooks the overall platform architecture related to Big Data solutions, and he also has a hands-on contribution to some assignments. He has been working in the IT industry for the last 15 years. He started as a programmer and, on the way, acquired skills in architecting and designing solutions, managing projects keeping each stakeholder's interest in mind, and deploying and maintaining the solution on a cloud infrastructure. He has been working on the Pentaho-related stack for the last 5 years, providing solutions while working with employers and as a freelancer as well. Manoj has extensive experience in JavaEE, MySQL, various frameworks, and Business Intelligence, and is keen to pursue his interest in predictive analysis. He was also associated with TalentBeat, Inc. and Persistent Systems, and implemented interesting solutions in logistics, data masking, and data-intensive life sciences.

See other products by R Patil

Shindgikar

Shindgikar

Prashant Shindgikar is an accomplished big data Architect with over 20 years of experience in data analytics. He specializes in data innovation and resolving data challenges for major retail brands. He is a hands-on architect having an innovative approach to solving data problems. He provides thought leadership and pursues strategies for engagements with the senior executives on innovation in data processing and analytics. He presently works for a large USA-based retail company.

See other products by Shindgikar

Kumar

Kumar

Naresh has more than a decade of professional experience in designing, implementing and running very large scale Internet Applications in Fortune Top 500 Companies. He is a Full Stack Architect with hands-on experience in domains like E-commerce, Web-hosting, Healthcare, Bigdata & Analytics, Data Streaming, Advertising and Databases. He believes in Opensource and contributes to them actively. He keeps himself up-to-date with emerging technologies starting from Linux Systems Internals to Frontend technologies. He studied in BITS-Pilani, Rajasthan with Dual Degree in Computer Science & Economics.

See other products by Kumar

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