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You're reading from  Hadoop Essentials

Product typeBook
Published inApr 2015
Reading LevelIntermediate
PublisherPackt
ISBN-139781784396688
Edition1st Edition
Languages
Java
Tools
Hadoop
Concepts
Data Processing
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Author (1)
Shiva Achari
Shiva Achari
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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.
Read more about Shiva Achari

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HDFS

HDFS is the default storage filesystem in Hadoop, which is distributed, considerably simple in design and extremely scalable, flexible, and with high fault tolerance capability. HDFS architecture has a master-slave pattern due to which the slave nodes can be better managed and utilized. HDFS can even run on commodity hardware, and the architecture accepts that some nodes can be down and still data has to be recovered and processed. HDFS has self-healing processes and speculative execution, which make the system fault tolerant, and is flexible to add/remove nodes and increases the scalability with reliability. HDFS is designed to be best suited for MapReduce programming. One key assumption in HDFS is Moving Computation is Cheaper than Moving Data.

Features of HDFS

The important features of HDFS are as follows:

  • Scalability: HDFS is scalable to petabytes or even more. HDFS is flexible enough to add or remove nodes, which can achieve scalability.

  • Reliability and fault tolerance: HDFS replicates...

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Hadoop Essentials
Published in: Apr 2015Publisher: PacktISBN-13: 9781784396688
© 2015 Packt Publishing Limited All Rights Reserved

Author (1)

author image
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.
Read more about Shiva Achari

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