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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
Author (1):
Shiva Achari Shiva Achari
Profile icon Shiva Achari
LinkedIn
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.
See other products by Shiva Achari

Table of Contents (15) Chapters

Hadoop Essentials
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
Introduction to Big Data and Hadoop Hadoop Ecosystem Pillars of Hadoop – HDFS, MapReduce, and YARN Data Access Components – Hive and Pig Storage Component – HBase Data Ingestion in Hadoop – Sqoop and Flume Streaming and Real-time Analysis – Storm and Spark Index

Distributed filesystem

In Hadoop, we know that data is stored in a distributed computing environment, so the files are scattered across the cluster. We should have an efficient filesystem to manage the files in Hadoop. The filesystem used in Hadoop is HDFS, elaborated as Hadoop Distributed File System.

HDFS

HDFS is extremely scalable and fault tolerant. It is designed to efficiently process parallel processing in a distributed environment in even commodity hardware. HDFS has daemon processes in Hadoop, which manage the data. The processes are NameNode, DataNode, BackupNode, and Checkpoint NameNode.

We will discuss HDFS elaborately in the next chapter.

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Authors (1)

Profile icon Shiva Achari
LinkedIn
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.
Read more
See other products by Shiva Achari

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