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[DOCX File]Table of Tables - Virginia Tech
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Spark uses a data structure called a Dataframe which is a distributed collection of data organized into named columns. These named columns can easily be queried and filtered into smaller datasets which could then be used to generate visualizations.
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[DOCX File]Abstract - Virginia Tech
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At present, we have deployed ArchiveSpark in a stand-alone machine due to the version conflict of Spark. The version of Spark for running ArchiveSpark is 1.6.0 or 2.1.0. Unfortunately, the Spark version is 1.5.0 in our Hadoop Cluster. Therefore, we need to upgrade the cluster and then deploy our framework to process big collections.
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[DOC File]Notes on Apache Spark 2 - The Risberg Family
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“Spark: The Definitive Guide” by Bill Chambers and Matei Zaharia. O’Reilly Press, January 2017, 450 pages. Not on Amazon yet, only available from OReilly. Updated for Spark 2.x. This is a pre-print, the printed copy is expected October 2017. “Spark in Action” by Petar Zecevic and Marko Bonaci. Manning Press, November 2016, 472 pages.
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[DOC File]WordPress.com
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Spark - Spark is a fast and general engine for large-scale data processing. Storm - Storm is a distributed realtime computation system. Impala - Real-time Query for Hadoop. DataMelt - Mathematics software for numeric computation, statistics, symbolic calculations, data analysis and data visualization.
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Office 365 - c.s-microsoft.com
for Apache Spark provides high performance DataFrame-level APIs for using Apache Spark from C# and F#. With these .NET APIs, you can access all aspects of Apache Spark including Spark SQL, for working with structured data, and Spark Streaming. Additionally, .NET for Apache Spark allows you to register and call user-defined functions written in ...
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Spark dataframe foreach