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	<title>why impala is faster than hive - Wikitechy</title>
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	<title>why impala is faster than hive - Wikitechy</title>
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		<title>What is the difference between Impala and Apache Hive ?</title>
		<link>https://www.wikitechy.com/interview-questions/cloudera-impala/what-is-the-difference-between-impala-and-apache-hive/</link>
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		<dc:creator><![CDATA[Editor]]></dc:creator>
		<pubDate>Mon, 19 Jul 2021 06:40:04 +0000</pubDate>
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					<description><![CDATA[Answer : Impala does runtime code generations
for “big loops ” using llvm...]]></description>
										<content:encoded><![CDATA[<div class="TextHeading">
<div class="hddn">
<h2 id="difference-between-impala-and-apache-hive" class="color-purple">Difference between Impala and Apache Hive</h2>
</div>
</div>
<table class="table-bordered table-striped table table-responsive">
<tbody>
<tr>
<th>Impala</th>
<th>Apache hive</th>
</tr>
<tr>
<td class="text-leftalign">Impala does runtime code generations<br />
for “big loops ” using llvm.</td>
<td class="text-leftalign">Apache hive generates query<br />
expressions at compile time.</td>
</tr>
<tr>
<td class="text-leftalign">Hadoop 2.6.0</td>
<td class="text-leftalign">Hadoop 2.7.3</td>
</tr>
<tr>
<td class="text-leftalign">Runtime Filtering Optimization Enabled</td>
<td class="text-leftalign">All queries run through LLAP</td>
</tr>
<tr>
<td class="text-leftalign">Parquet format with snappy compression</td>
<td class="text-leftalign">ORCFile format with zlib compression</td>
</tr>
<tr>
<td class="text-leftalign">Impala avoids startup overhead<br />
as daemon processes are started at boot<br />
time itself, always being ready to processes a query.</td>
<td class="text-leftalign">Every hive query has this problem<br />
of “cold start”.</td>
</tr>
<tr>
<td class="text-leftalign">Impala is meant for interactive computing.</td>
<td class="text-leftalign">Apache Hive might not be ideal<br />
for interactive computing .</td>
</tr>
<tr>
<td class="text-leftalign">Impala is more like MPP database.</td>
<td class="text-leftalign">Hive is batch based Hadoop MapReduce .</td>
</tr>
<tr>
<td class="text-leftalign">Impala does not support complex types.</td>
<td class="text-leftalign">Hive supports complex types .</td>
</tr>
<tr>
<td class="text-leftalign">Impala does not support fault tolerance</td>
<td class="text-leftalign">Apache Hive is fault tolerant</td>
</tr>
</tbody>
</table>
<div class="text-center row">
<div class="col-sm-12">
<div id="bsa-zone_1590522538159-8_123456"></div>
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]]></content:encoded>
					
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			</item>
		<item>
		<title>What is the Difference between apache hive and impala ?</title>
		<link>https://www.wikitechy.com/interview-questions/hive/what-is-the-difference-between-apache-hive-and-impala/</link>
					<comments>https://www.wikitechy.com/interview-questions/hive/what-is-the-difference-between-apache-hive-and-impala/#respond</comments>
		
		<dc:creator><![CDATA[Editor]]></dc:creator>
		<pubDate>Tue, 13 Jul 2021 22:18:19 +0000</pubDate>
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					<description><![CDATA[Answer : Hive generates query expressions at compile
time...]]></description>
										<content:encoded><![CDATA[<h2 id="apache-hive-vs-impala" class="color-green">Apache hive Vs Impala</h2>
<table class="table-bordered table-striped table table-responsive">
<tbody>
<tr>
<th>Apache hive</th>
<th>Impala</th>
</tr>
<tr>
<td class="text-leftalign">Hive generates query expressions at compile<br />
time;Hive is batch based Hadoop MapReduce</td>
<td class="text-leftalign">Impala does not support for complex types<br />
and fault tolerance.</td>
</tr>
<tr>
<td class="text-leftalign">Apache does not generations runtime code<br />
for “big loops ” using llvm.</td>
<td class="text-leftalign">Impala does generations runtime code<br />
for “big loops ” using llvm.</td>
</tr>
<tr>
<td class="text-leftalign">Hadoop 2.7.3</td>
<td class="text-leftalign">Hadoop 2.6.0</td>
</tr>
<tr>
<td class="text-leftalign">All queries run through LLAP</td>
<td class="text-leftalign">Runtime Filtering Optimization Enabled</td>
</tr>
<tr>
<td class="text-leftalign">ORCFile format with zlib compression</td>
<td class="text-leftalign">Parquet format with snappy compression</td>
</tr>
<tr>
<td class="text-leftalign">Every hive query has this problem of “cold start”.</td>
<td class="text-leftalign">Impala avoids startup overhead as daemon<br />
processes are started at boot time itself,<br />
always being ready to processes a query.</td>
</tr>
<tr>
<td class="text-leftalign">Apache <b>Hive</b> might not be ideal for interactive computing</td>
<td class="text-leftalign">Impala is meant for interactive computing.</td>
</tr>
<tr>
<td class="text-leftalign"><b>Hive</b> is batch based Hadoop MapReduce.</td>
<td class="text-leftalign">Impala is more like MPP database.</td>
</tr>
<tr>
<td class="text-leftalign"><b>Hive</b> supports complex types.</td>
<td class="text-leftalign"><b>Impala</b> does not support complex types.</td>
</tr>
<tr>
<td class="text-leftalign">Apache Hive is fault tolerant.</td>
<td class="text-leftalign">Impala does not support fault tolerance.</td>
</tr>
<tr>
<td class="text-leftalign">It is more universal, versatile and pluggable language.</td>
<td class="text-leftalign">It is used unleash its brute processing power<br />
and give lightning fast analytic results.</td>
</tr>
</tbody>
</table>
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