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CSE726 Data Intensive Distributed Computing Spring 2011 A Review of Panache: A Parallel File System for Global File Access M. Ethel et al., .FAST 10 Presented by: Slinky Reviewed by: Right Saldana

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What is data intensive distributed computing?

Data intensive distributed computing is a computing paradigm that involves processing and analyzing large volumes of data by distributing the workload across multiple computers or servers.

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Filling out data intensive distributed computing involves designing and implementing distributed computing systems, using frameworks like Apache Hadoop or Apache Spark, to effectively process and analyze large amounts of data.

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The purpose of data intensive distributed computing is to enable efficient processing and analysis of large datasets that cannot be handled by a single machine.

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The specific information reported on data intensive distributed computing varies depending on the nature of the data and the objectives of the computing task. It may include data sources, processing steps, algorithms used, and results obtained.

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