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Hadoop Essentials

You're reading from Hadoop Essentials

Product type Book

Published in Apr 2015

Publisher Packt

ISBN-13 9781784396688

Pages 194 pages

Edition 1st Edition

Languages

Concepts

Data Processing

Author (1):

Shiva Achari

Table of Contents (15) Chapters

Hadoop Essentials

Credits

About the Author

Acknowledgments

About the Reviewers

www.PacktPub.com

Preface

1. Introduction to Big Data and Hadoop

2. Hadoop Ecosystem

3. Pillars of Hadoop – HDFS, MapReduce, and YARN

4. Data Access Components – Hive and Pig

5. Storage Component – HBase

6. Data Ingestion in Hadoop – Sqoop and Flume

7. Streaming and Real-time Analysis – Storm and Spark

Index

Apache Flume

Flume is extremely popular data ingestion system, which can be used to ingest data from different multiple sources and can put it in multiple destinations. Flume provides a framework to handle and process data on a larger scale, and it is very reliable.

Flume is usually described as distributed, reliable, scalable, manageable, and customizable to ingest and process data from different multiple data sources to multiple destinations.

As we already discussed about the different type of data sources. One thing which makes the design more difficult is that data formats changes frequently in some cases especially social media data in JSON, and usually a Big Data systems has multiple data sources. Flume is extremely efficient in handling such scenarios and provides a greater control over each data source and the processing layer. Flume can be configured in three modes: single node, pseudo-distributed, and fully-distributed mode.

Flume is adapted due to its capability to be highly reliable...

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Authors (1)

Shiva Achari

Shiva Achari has over 8 years of extensive industry experience and is currently working as a Big Data Architect consultant with companies such as Oracle and Teradata. Over the years, he has architected, designed, and developed multiple innovative and high-performance large-scale solutions, such as distributed systems, data centers, big data management tools, SaaS cloud applications, Internet applications, and Data Analytics solutions. He is also experienced in designing big data and analytics applications, such as ingestion, cleansing, transformation, correlation of different sources, data mining, and user experience in Hadoop, Cassandra, Solr, Storm, R, and Tableau. He specializes in developing solutions for the big data domain and possesses sound hands-on experience on projects migrating to the Hadoop world, new developments, product consulting, and POC. He also has hands-on expertise in technologies such as Hadoop, Yarn, Sqoop, Hive, Pig, Flume, Solr, Lucene, Elasticsearch, Zookeeper, Storm, Redis, Cassandra, HBase, MongoDB, Talend, R, Mahout, Tableau, Java, and J2EE. He has been involved in reviewing Mastering Hadoop, Packt Publishing. Shiva has expertise in requirement analysis, estimations, technology evaluation, and system architecture along with domain experience in telecoms, Internet applications, document management, healthcare, and media. Currently, he is supporting presales activities such as writing technical proposals (RFP), providing technical consultation to customers, and managing deliveries of big data practice groups in Teradata.

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