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	<title>Apache Hudi &#8211; Noise</title>
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		<title>Simplify operational data processing in data lakes using AWS Glue and Apache Hudi</title>
		<link>https://noise.getoto.net/2023/09/13/simplify-operational-data-processing-in-data-lakes-using-aws-glue-and-apache-hudi/</link>
		
		<dc:creator><![CDATA[Ravi Itha]]></dc:creator>
		<pubDate>Wed, 13 Sep 2023 14:56:41 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon EventBridge]]></category>
		<category><![CDATA[Amazon Simple Queue Service (SQS)]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[Apache Hudi]]></category>
		<category><![CDATA[AWS Big Data]]></category>
		<category><![CDATA[AWS Database Migration Service]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[AWS Step Functions]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[AWS has invested in native service integration with Apache Hudi and published technical contents to enable you to use Apache Hudi with AWS Glue (for example, refer to Introducing native support for Apache Hudi, Delta Lake, and Apache Iceberg on AWS Glue for Apache Spark, Part 1: Getting Started). In AWS ProServe-led customer engagements, the use cases we work on usually come with technical complexity and scalability requirements. In this post, we discuss a common use case in relation to operational data processing and the solution we built using Apache Hudi and AWS Glue.]]></description>
		
		
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		<item>
		<title>Create an Apache Hudi-based near-real-time transactional data lake using AWS DMS, Amazon Kinesis, AWS Glue streaming ETL, and data visualization using Amazon QuickSight</title>
		<link>https://noise.getoto.net/2023/08/03/create-an-apache-hudi-based-near-real-time-transactional-data-lake-using-aws-dms-amazon-kinesis-aws-glue-streaming-etl-and-data-visualization-using-amazon-quicksight/</link>
		
		<dc:creator><![CDATA[Raj Ramasubbu]]></dc:creator>
		<pubDate>Thu, 03 Aug 2023 14:46:38 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon Kinesis]]></category>
		<category><![CDATA[Amazon QuickSight]]></category>
		<category><![CDATA[Apache Hudi]]></category>
		<category><![CDATA[AWS Database Migration Service]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[Kinesis Data Streams]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[We recently announced support for streaming extract, transform, and load (ETL) jobs in AWS Glue version 4.0, a new version of AWS Glue that accelerates data integration workloads in AWS. AWS Glue streaming ETL jobs continuously consume data from streaming sources, clean and transform the data in-flight, and make it available for analysis in seconds. AWS also offers a broad selection of services to support your needs. A database replication service such as AWS Database Migration Service (AWS DMS) can replicate the data from your source systems to Amazon Simple Storage Service (Amazon S3), which commonly hosts the storage layer of the data lake. This post demonstrates how to apply CDC changes from Amazon Relational Database Service (Amazon RDS) or other relational databases to an S3 data lake, with flexibility to denormalize, transform, and enrich the data in near-real time.]]></description>
		
		
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			</item>
		<item>
		<title>Build a data lake with Apache Flink on Amazon EMR</title>
		<link>https://noise.getoto.net/2023/01/27/build-a-data-lake-with-apache-flink-on-amazon-emr/</link>
		
		<dc:creator><![CDATA[Jianwei Li]]></dc:creator>
		<pubDate>Fri, 27 Jan 2023 21:05:02 +0000</pubDate>
				<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[apache flink]]></category>
		<category><![CDATA[Apache Hudi]]></category>
		<category><![CDATA[Apache Iceberg]]></category>
		<category><![CDATA[AWS Glue]]></category>
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					<description><![CDATA[To build a data-driven business, it is important to democratize enterprise data assets in a data catalog. With a unified data catalog, you can quickly search datasets and figure out data schema, data format, and location. The AWS Glue Data Catalog provides a uniform repository where disparate systems can store and find metadata to keep […]]]></description>
		
		
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			</item>
		<item>
		<title>Build your Apache Hudi data lake on AWS using Amazon EMR – Part 1</title>
		<link>https://noise.getoto.net/2022/11/22/build-your-apache-hudi-data-lake-on-aws-using-amazon-emr-part-1/</link>
		
		<dc:creator><![CDATA[Suthan Phillips]]></dc:creator>
		<pubDate>Tue, 22 Nov 2022 18:32:01 +0000</pubDate>
				<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Apache Hudi]]></category>
		<category><![CDATA[AWS Big Data]]></category>
		<category><![CDATA[Best practices]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Apache Hudi is an open-source transactional data lake framework that greatly simplifies incremental data processing and data pipeline development. It does this by bringing core warehouse and database functionality directly to a data lake on Amazon Simple Storage Service (Amazon S3) or Apache HDFS. Hudi provides table management, instantaneous views, efficient upserts/deletes, advanced indexes, streaming […]]]></description>
		
		
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