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    <title>DSpace Collection:</title>
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    <pubDate>Tue, 23 Jun 2026 06:30:13 GMT</pubDate>
    <dc:date>2026-06-23T06:30:13Z</dc:date>
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      <title>Study of Distributed File System for Big Data</title>
      <link>http://localhost:8080/xmlui/handle/123456789/2316</link>
      <description>Title: Study of Distributed File System for Big Data
Authors: Zalte, Sagar A.; Takate, Vishwas R.; Chaudhari, Saish R.
Abstract: The caption for Hadoop is big data analytics. That means perform Analytics over big data. Traditional&#xD;
technologies such as R, SQL, and Vertica cannot deal with big data. Hadoop can store unstructured semi structured and&#xD;
structured data. Two core component of Hadoop are 1.HDFS 2.Map Reduce. The Hadoop Distributed File System&#xD;
(HDFS) is designed to store very large data sets reliably, and to stream those data sets at high bandwidth to user&#xD;
applications. Map Reduce is an execution engine of Hadoop, it process the data stored in HDFS in distributed manner.</description>
      <pubDate>Wed, 01 Feb 2017 00:00:00 GMT</pubDate>
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      <dc:date>2017-02-01T00:00:00Z</dc:date>
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