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Monday, October 20, 2014

What is Apache Hadoop definition and need of Hadoop

What is hadoop definition and need?

Definition of Hadoop:

Today our data growing so rapidly on internet and these data are unstructured format. The time has come for you to re-check your approach to data storage, data management, and data paralytics.

Hadoop framework for programming:

Hadoop is a free open source, Java-based framework for programming that supports the processing of large data sets in a distributed computing environment. It is part of the Apache project sponsored by the Apache Software Foundation.

Hadoop can handle all types of data from disparate systems: structured, unstructured, log files, pictures, audio files, text – just about anything you can think have, regardless of its native format. Furthermore, you can put it all in your Hadoop cluster with no prior need for a schema. In other words, you don’t need to know how you intend to query your data before you store it

What Is Apache Hadoop?

The Apache Hadoop project develops open-source software for reliable, scalable, distributed computing.
  • Framework that allows for the distributed processing.
  • It is designed to scale up from single servers to thousands of machines.
  • Highly-available service on top of a cluster of computers for storing large amount of data.

The Hadoop project includes these modules:
  • Hadoop Common: The common utilities that support the other Hadoop modules.
  • Hadoop Distributed File System: A distributed file system that provides high-throughput access to application data.
  • Hadoop YARN: A framework for job scheduling and cluster resource management.
  • Hadoop MapReduce: A YARN-based system for parallel processing of large data sets.

HDFS (Hadoop Distributed File System):

  • Support for POSIX-style filesystem extended attributes. See the user documentation for more details.
  • Using the OfflineImageViewer, clients can now browse an fsimage via the WebHDFS API.
  • The NFS gateway received a number of supportability improvements and bug fixes. The Hadoop portmapper is no longer required to run the gateway, and the gateway is now able to reject connections from unprivileged ports.
  • The SecondaryNameNode, JournalNode, and DataNode web UIs have been modernized with HTML5 and Javascript.

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