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	<title>Qingyuan Tang &#8211; Noise</title>
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		<title>Optimizing Flink’s join operations on Amazon EMR with Alluxio</title>
		<link>https://noise.getoto.net/2026/02/03/optimizing-flinks-join-operations-on-amazon-emr-with-alluxio/</link>
		
		<dc:creator><![CDATA[Qingyuan Tang]]></dc:creator>
		<pubDate>Tue, 03 Feb 2026 18:41:31 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we show you how to implement real-time data correlation using Apache Flink to join streaming order data with historical customer and product information, enabling you to make informed decisions based on comprehensive, up-to-date analytics. We also introduce an optimized solution to automatically load Hive dimension table data into Alluxio Universal Flash Storage (UFS) through the Alluxio cache layer. This enables Flink to perform temporal joins on changing data, accurately reflecting the content of a table at specific points in time.]]></description>
		
		
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