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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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Hadoop's basic data flow

A basic data flow of the Hadoop system can be divided into four phases:

  1. Capture Big Data : The sources can be extensive lists that are structured, semi-structured, and unstructured, some streaming, real-time data sources, sensors, devices, machine-captured data, and many other sources. For data capturing and storage, we have different data integrators such as, Flume, Sqoop, Storm, and so on in the Hadoop ecosystem, depending on the type of data.

  2. Process and Structure: We will be cleansing, filtering, and transforming the data by using a MapReduce-based framework or some other frameworks which can perform distributed programming in the Hadoop ecosystem. The frameworks available currently are MapReduce, Hive, Pig, Spark and so on.

  3. Distribute Results: The processed data can be used by the BI and analytics system or the big data analytics system for performing analysis or visualization.

  4. Feedback and Retain: The data analyzed can be fed back to Hadoop and used for improvements...

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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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