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Data Lake for Enterprises

You're reading from Data Lake for Enterprises

Product type Book

Published in May 2017

Publisher Packt

ISBN-13 9781787281349

Pages 596 pages

Edition 1st Edition

Languages

Concepts

Data Processing

Authors (3):

Vivek Mishra

Tomcy John

Pankaj Misra

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Table of Contents (23) Chapters

Title Page

Credits

Foreword

About the Authors

About the Reviewers

www.PacktPub.com

Customer Feedback

Preface

Part 1 - Overview

Part 2 - Technical Building blocks of Data Lake

Part 3 - Bringing It All Together

1. Introduction to Data

2. Comprehensive Concepts of a Data Lake

3. Lambda Architecture as a Pattern for Data Lake

4. Applied Lambda for Data Lake

5. Data Acquisition of Batch Data using Apache Sqoop

6. Data Acquisition of Stream Data using Apache Flume

7. Messaging Layer using Apache Kafka

8. Data Processing using Apache Flink

9. Data Store Using Apache Hadoop

10. Indexed Data Store using Elasticsearch

11. Data Lake Components Working Together

12. Data Lake Use Case Suggestions

Hadoop for near real-time applications

Hadoop has been popular for its capability for fast and performant batch processing of large amounts of varied data with considerable variance and high velocity. However, there was always an inherent need for handling data for near real-time applications as well.

While Flume did provide some level of stream based processing in the Hadoop ecosystem, it required considerable amount of implementation for custom processing. Most of the source and sink implementations of flume are performing data ETL roles. For any flume processing requirement, it required implementation of custom sinks.

A more mature implementation for near real-time processing of data came with Spark Streaming, which works with HDFS, based on micro-batches as discussed earlier, and provided greater capabilities compared to flume, as pipeline-based processing in near real time.

However, even if the data was processed in near real time and stored in the Hadoop File System, there was an even...

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Authors (3)

Vivek Mishra

Vivek Mishra is an IT professional with more than nine years of experience in various technologies like Java, J2ee, Hibernate, SCA4J, Mule, Spring, Cassandra, HBase, MongoDB, REDIS, Hive, Hadoop. He has been a contributor for open source like Apache Cassandra and lead committer for Kundera(JPA 2.0 compliant Object-Datastore Mapping Library for NoSQL Datastores like Cassandra, HBase, MongoDB and REDIS). Mr Mishra in his previous experience has enjoyed long lasting partnership with most recognizable names in SCM, Banking and finance industries, employing industry standard full software life cycle methodologies Agile and SCRUM. He is currently employed with Impetus infotech pvt. ltd. He has undertaken speaking engagements in cloud camp and Nasscom Big data seminar and is an active blogger and can be followed at mevivs.wordpress.com

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Tomcy John

Tomcy John lives in Dubai (United Arab Emirates), hailing from Kerala (India), and is an enterprise Java specialist with a degree in Engineering (B Tech) and over 14 years of experience in several industries. He's currently working as principal architect at Emirates Group IT, in their core architecture team. Prior to this, he worked with Oracle Corporation and Ernst & Young. His main specialization is in building enterprise-grade applications and he acts as chief mentor and evangelist to facilitate incorporating new technologies as corporate standards in the organization. Outside of his work, Tomcy works very closely with young developers and engineers as mentors and speaks at various forums as a technical evangelist on many topics ranging from web and middleware all the way to various persistence stores.

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Pankaj Misra

Pankaj Misra has been a technology evangelist, holding a bachelor's degree in engineering, with over 16 years of experience across multiple business domains and technologies. He has been working with Emirates Group IT since 2015, and has worked with various other organizations in the past. He specializes in architecting and building multi-stack solutions and implementations. He has also been a speaker at technology forums in India and has built products with scale-out architecture that support high-volume, near-real-time data processing and near-real-time analytics.

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