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		<title>Why do we need Data Locality in Hadoop ?</title>
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		<pubDate>Mon, 12 Jul 2021 18:21:39 +0000</pubDate>
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					<description><![CDATA[Answer : Datasets in HDFS store as blocks in DataNodes...]]></description>
										<content:encoded><![CDATA[<div class="TextHeading">
<div class="hddn">
<h2 id="why-do-we-need-data-locality-in-hadoop" class="color-pink" style="text-align: justify;">Why do we need Data Locality in Hadoop ?</h2>
</div>
</div>
<div class="ImageContent" style="text-align: justify;">
<div class="hddn"><img decoding="async" class="img-responsive center-block aligncenter" src="https://cdn.wikitechy.com/interview-questions/hadoop/why-we-need-data-locality-in-hadoop.png" alt=" Data Locality in Hadoop " /></div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>Datasets in <a href="https://www.wikitechy.com/tutorials/sqoop/sqoop-vs-hdfs" target="_blank" rel="noopener">HDFS</a> store as blocks in DataNodes the Hadoop cluster.</li>
<li>During the execution of a <a href="https://www.wikitechy.com/tutorials/hive/hive-mapreduce-hadoop-mapreduce" target="_blank" rel="noopener">MapReduce</a> job the individual Mapper processes the blocks (Input Splits).</li>
<li>If the data does not reside in the same node where the Mapper is executing the job, the data needs to be copied from the DataNode over the <a href="https://www.wikitechy.com/errors-and-fixes/sql/cluster-network-name-showing-netbios-status-as-the-system-cannot-find-the-file-specified" target="_blank" rel="noopener">network</a> to the mapper DataNode.</li>
</ul>
</div>
</div>
<div class="ImageContent" style="text-align: justify;">
<div class="hddn"><img decoding="async" class="img-responsive center-block aligncenter" src="https://cdn.wikitechy.com/interview-questions/hadoop/data-locality-in-hadoop.gif" alt="Datasets in HDFS - Data Locality in Hadoop" /></div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>Now if a MapReduce job has more than 100 Mapper and each Mapper tries to copy the data from other DataNode in the cluster simultaneously, it would cause serious network congestion which is a big performance issue of the overall system.</li>
<li>Hence, data proximity to the computation is an effective and cost-effective solution which is technically termed as <a href="https://www.wikitechy.com/interview-questions/hadoop/what-are-the-features-of-hadoop/" target="_blank" rel="noopener">Data locality in Hadoop</a>. It helps to increase the overall throughput of the system.</li>
</ul>
</div>
</div>
<div class="ImageContent" style="text-align: justify;">
<div class="hddn"><img decoding="async" class="img-responsive center-block aligncenter" src="https://cdn.wikitechy.com/interview-questions/hadoop/mapreduce-job-data-locality.gif" alt=" " /></div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="types-of-data-locality" class="color-green">Types of data locality</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li><b>Data local</b>
<ul>
<li>In this type data and the mapper resides on the same node. This is the closest proximity of data and the most preferred scenario.</li>
</ul>
</li>
</ul>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li><b>Rack Local</b>
<ul>
<li>In this type data and the mapper resides on the same node. This is the closest proximity of data and the most preferred scenario.</li>
<li>In this scenarios mapper and data reside on the same rack but on the different data nodes.</li>
</ul>
</li>
</ul>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li><b>Different Rack</b>
<ul>
<li>In this scenario mapper and data reside on the different racks.</li>
</ul>
</li>
</ul>
</div>
</div>
<div class="ImageContent">
<div class="hddn"><img decoding="async" class="img-responsive center-block aligncenter" src="https://cdn.wikitechy.com/interview-questions/hadoop/types-of-data-locality.jpg" alt="Types of data locality" /></div>
</div>
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