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	<title>Spark &#8211; Noise</title>
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		<title>NVIDIA DGX Spark and Partner GB10 Firmware</title>
		<link>https://noise.getoto.net/2025/10/18/nvidia-dgx-spark-and-partner-gb10-firmware/</link>
		
		<dc:creator><![CDATA[Eric Smith]]></dc:creator>
		<pubDate>Fri, 17 Oct 2025 23:41:04 +0000</pubDate>
				<category><![CDATA[AI]]></category>
		<category><![CDATA[Dell]]></category>
		<category><![CDATA[DGX]]></category>
		<category><![CDATA[GB10]]></category>
		<category><![CDATA[Nvidia]]></category>
		<category><![CDATA[Spark]]></category>
		<category><![CDATA[Workstation]]></category>
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					<description><![CDATA[We show you how to update the firmware on your NVIDIA DGX Spark and partner systems as we discuss a key difference between the firmware
The post NVIDIA DGX Spark and Partner GB10 Firmware appeared first on ServeTheHome.
]]></description>
		
		
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		<title>NVIDIA DGX Spark Review The GB10 Machine is so Freaking Cool</title>
		<link>https://noise.getoto.net/2025/10/14/nvidia-dgx-spark-review-the-gb10-machine-is-so-freaking-cool/</link>
		
		<dc:creator><![CDATA[Patrick Kennedy]]></dc:creator>
		<pubDate>Tue, 14 Oct 2025 15:07:20 +0000</pubDate>
				<category><![CDATA[AI]]></category>
		<category><![CDATA[ARM]]></category>
		<category><![CDATA[Blackwell]]></category>
		<category><![CDATA[ConnectX-7]]></category>
		<category><![CDATA[GB10]]></category>
		<category><![CDATA[Grace]]></category>
		<category><![CDATA[Nvidia]]></category>
		<category><![CDATA[Spark]]></category>
		<category><![CDATA[Workstation]]></category>
		<guid isPermaLink="false">https://www.servethehome.com/?p=91130</guid>

					<description><![CDATA[In our NVIDIA DGX Spark review, we see how these Arm and NVIDIA Blackwell powered systems with 200GbE RDMA networking are just freaking cool
The post NVIDIA DGX Spark Review The GB10 Machine is so Freaking Cool appeared first on ServeTheHome.
]]></description>
		
		
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		<item>
		<title>Detect and handle data skew on AWS Glue</title>
		<link>https://noise.getoto.net/2024/05/01/detect-and-handle-data-skew-on-aws-glue/</link>
		
		<dc:creator><![CDATA[Salim Tutuncu]]></dc:creator>
		<pubDate>Wed, 01 May 2024 16:27:24 +0000</pubDate>
				<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Apache Spark]]></category>
		<category><![CDATA[AWS Analytics]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[Best practices]]></category>
		<category><![CDATA[Big Data]]></category>
		<category><![CDATA[Expert (400)]]></category>
		<category><![CDATA[Optimization]]></category>
		<category><![CDATA[Spark]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=ac6e0a0c43720a34b439d0d7b7faf802</guid>

					<description><![CDATA[AWS Glue is a fully managed, serverless data integration service provided by Amazon Web Services (AWS) that uses Apache Spark as one of its backend processing engines (as of this writing, you can use Python Shell, Spark, or Ray). Data skew occurs when the data being processed is not evenly distributed across the Spark cluster, […]]]></description>
		
		
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		<title>Run fault tolerant and cost-optimized Spark clusters using Amazon EMR on EKS and Amazon EC2 Spot Instances</title>
		<link>https://noise.getoto.net/2022/12/19/run-fault-tolerant-and-cost-optimized-spark-clusters-using-amazon-emr-on-eks-and-amazon-ec2-spot-instances/</link>
		
		<dc:creator><![CDATA[Kinnar Kumar Sen]]></dc:creator>
		<pubDate>Mon, 19 Dec 2022 21:57:57 +0000</pubDate>
				<category><![CDATA[Amazon EC2]]></category>
		<category><![CDATA[Amazon Elastic Kubernetes Service]]></category>
		<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon EMR on EKS]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Best practices]]></category>
		<category><![CDATA[Compute]]></category>
		<category><![CDATA[Spark]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Amazon EMR on EKS is a deployment option in Amazon EMR that allows you to run Spark jobs on Amazon Elastic Kubernetes Service (Amazon EKS). Amazon Elastic Compute Cloud (Amazon EC2) Spot Instances save you up to 90% over On-Demand Instances, and is a great way to cost optimize the Spark workloads running on Amazon […]]]></description>
		
		
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		<title>Design considerations for Amazon EMR on EKS in a multi-tenant Amazon EKS environment</title>
		<link>https://noise.getoto.net/2022/09/21/design-considerations-for-amazon-emr-on-eks-in-a-multi-tenant-amazon-eks-environment/</link>
		
		<dc:creator><![CDATA[Lotfi Mouhib]]></dc:creator>
		<pubDate>Wed, 21 Sep 2022 16:03:06 +0000</pubDate>
				<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon EMR on EKS]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Apache Spark]]></category>
		<category><![CDATA[Best practices]]></category>
		<category><![CDATA[EKS]]></category>
		<category><![CDATA[Kubernetes]]></category>
		<category><![CDATA[Spark]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=2d8d7a599ba488e42b682d29ad6bd035</guid>

					<description><![CDATA[Many AWS customers use Amazon Elastic Kubernetes Service (Amazon EKS) in order to take advantage of Kubernetes without the burden of managing the Kubernetes control plane. With Kubernetes, you can centrally manage your workloads and offer administrators a multi-tenant environment where they can create, update, scale, and secure workloads using a single API. Kubernetes also […]]]></description>
		
		
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		<title>Disaster recovery considerations with Amazon EMR on Amazon EC2 for Spark workloads</title>
		<link>https://noise.getoto.net/2022/06/28/disaster-recovery-considerations-with-amazon-emr-on-amazon-ec2-for-spark-workloads/</link>
		
		<dc:creator><![CDATA[Bharat Gamini]]></dc:creator>
		<pubDate>Tue, 28 Jun 2022 16:03:45 +0000</pubDate>
				<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Spark]]></category>
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					<description><![CDATA[Amazon EMR is a cloud big data platform for running large-scale distributed data processing jobs, interactive SQL queries, and machine learning (ML) applications using open-source analytics frameworks such as Apache Spark, Apache Hive, and Presto. Amazon EMR launches all nodes for a given cluster in the same Amazon Elastic Compute Cloud (Amazon EC2) Availability Zone […]]]></description>
		
		
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		<item>
		<title>Simplify and optimize Python package management for AWS Glue PySpark jobs with AWS CodeArtifact</title>
		<link>https://noise.getoto.net/2022/06/10/simplify-and-optimize-python-package-management-for-aws-glue-pyspark-jobs-with-aws-codeartifact/</link>
		
		<dc:creator><![CDATA[Ashok Padmanabhan]]></dc:creator>
		<pubDate>Thu, 09 Jun 2022 21:03:52 +0000</pubDate>
				<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Analytics]]></category>
		<category><![CDATA[AWS CodeArtifact]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[Developer Tools]]></category>
		<category><![CDATA[devops]]></category>
		<category><![CDATA[python]]></category>
		<category><![CDATA[Spark]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Data engineers use various Python packages to meet their data processing requirements while building data pipelines with AWS Glue PySpark Jobs. Languages like Python and Scala are commonly used in data pipeline development. Developers can take advantage of their open-source packages or even customize their own to make it easier and faster to perform use […]]]></description>
		
		
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		<item>
		<title>A new Spark plugin for CPU and memory profiling</title>
		<link>https://noise.getoto.net/2022/05/13/a-new-spark-plugin-for-cpu-and-memory-profiling/</link>
		
		<dc:creator><![CDATA[Bo Xiong]]></dc:creator>
		<pubDate>Fri, 13 May 2022 19:56:42 +0000</pubDate>
				<category><![CDATA[*Learning Levels]]></category>
		<category><![CDATA[Amazon CodeGuru]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[CodeGuru]]></category>
		<category><![CDATA[EMR]]></category>
		<category><![CDATA[Expert (400)]]></category>
		<category><![CDATA[Industries]]></category>
		<category><![CDATA[profiling]]></category>
		<category><![CDATA[Spark]]></category>
		<category><![CDATA[Uncategorized]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=ae5a11d04089d7805bf2839570816c90</guid>

					<description><![CDATA[Introduction Have you ever wondered if there are low-hanging optimization opportunities to improve the performance of a Spark app? Profiling can help you gain visibility regarding the runtime characteristics of the Spark app to identify its bottlenecks and inefficiencies. We’re excited to announce the release of a new Spark plugin that enables profiling for JVM […]]]></description>
		
		
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