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You're reading from  Hadoop Essentials

Product typeBook
Published inApr 2015
Reading LevelIntermediate
PublisherPackt
ISBN-139781784396688
Edition1st Edition
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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.
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Flume architecture


Flume architecture is a very flexible and customizable composed agent that can be configured as multitiered for a data flow process. The data flow design allows the source or data to be transferred or processed from the source to the destination. The components are wired together in chains and in different tiers called the logical node's configuration. The logical nodes are configured in three tiers, namely, Client, Collector, and Storage. The first tier is the Client that captures the data from data source and forwards the it to the Collector, which consolidates the data after processing and sends it to the Storage tier.

The Flume process and the logical components are controlled by the Flume Master. The logical nodes are very flexible and can be added or deleted dynamically by the Master.

Multitier topology

In Flume, Agents can be configured to be a Client, Collector, or Storage. A Client Agent ingests the data from a data source and pushes it to another Agent, using an...

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Hadoop Essentials
Published in: Apr 2015Publisher: PacktISBN-13: 9781784396688

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