Apache Spark

Results: 128



#Item
11Computing / Mathematics / Artificial neural networks / Cluster computing / Hadoop / Java platform / Reza Zadeh / Machine learning / Apache Spark / Matroid / Voxel / Spark

Scaled Machine Learning at Matroid Reza Zadeh @Reza_Zadeh | http://reza-zadeh.com Machine Learning Pipeline

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Source URL: matroid.com

Language: English - Date: 2016-08-06 02:51:40
12Computing / Data / Hadoop / Apache Software Foundation / Cask / Teradata / Data management / Cloud infrastructure / Big data / Apache Hadoop / Apache Spark / Extract /  transform /  load

Cask Data Application Platform (CDAP) Extensions CDAP Extensions provide additional capabilities and user interfaces to CDAP. They are use-case specific applications designed to solve common and critical big data challe

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Source URL: customers.cask.co

Language: English - Date: 2016-08-02 06:10:32
13Computing / Hadoop / Apache Software Foundation / Cloud infrastructure / Java platform / Inter-process communication / Apache Hadoop / Apache Spark / MapR FS / MapR / Pipeline / Franz Kafka

    StreamSets Data CollectorRelease Notes August 4, 2016

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Source URL: streamsets.com

Language: English - Date: 2016-08-04 21:52:48
14Computing / Hadoop / Apache Software Foundation / Parallel computing / Apache Spark / Cluster computing / Java platform / Apache Hadoop / Data-intensive computing / MapReduce / Apache HBase / PageRank

Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing Matei Zaharia, Mosharaf Chowdhury, Tathagata Das, Ankur Dave, Justin Ma, Murphy McCauley, Michael J. Franklin, Scott Shenker, I

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Source URL: nil.csail.mit.edu

Language: English - Date: 2015-01-05 06:37:34
15Computing / Hadoop / Apache Software Foundation / Parallel computing / Cluster computing / Java platform / Apache Spark / MapReduce / Data-intensive computing / Apache Hadoop / Apache Hive / Scala

Spark: Cluster Computing with Working Sets Matei Zaharia, Mosharaf Chowdhury, Michael J. Franklin, Scott Shenker, Ion Stoica University of California, Berkeley Abstract MapReduce/Dryad job, each job must reload the data

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Source URL: people.csail.mit.edu

Language: English - Date: 2016-08-21 15:09:53
16Computing / Network file systems / Data management / Apache Software Foundation / Supercomputers / Lustre / Cloud storage / K computer / Clustered file system / Scalability / Object storage / Apache Spark

Scaling Spark on HPC Systems Nicholas Chaimov Allen Malony University of Oregon

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Source URL: crd.lbl.gov

Language: English - Date: 2016-02-03 12:05:25
17Computing / Concurrent computing / Parallel computing / Hadoop / Distributed computing architecture / Cloud infrastructure / Apache Software Foundation / MapReduce / Apache Spark / MapR / Data-intensive computing / Apache Hadoop

Large-Scale Numerical Computation Using a Data Flow Engine Matei Zaharia Outline

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Source URL: mmds-data.org

Language: English - Date: 2014-06-24 03:07:59
18Computing / Concurrent computing / Distributed computing architecture / Apache Software Foundation / Parallel computing / Data management / Knowledge representation / Apache Spark / MapReduce / Workflow / Replication

Hurricane: Distributed real-time data-processing Jeffrey Warren, Vedha Sayyaparaju, Vikas Velagapudi, Zack Drach  {jtwarren, vedha, vvelaga, zdrach} @mit.edu    Demo link: https://www.youtube.com/watch?v=

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Source URL: css.csail.mit.edu

Language: English - Date: 2014-12-08 14:33:02
19Computing / Mathematics / Apache Software Foundation / Hadoop / Combinatorics / Apache Spark / Cluster computing / Java platform / MapReduce / Apache Hadoop / Partition / RDD

Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing Matei Zaharia, Mosharaf Chowdhury, Tathagata Das, Ankur Dave, Justin Ma, Murphy McCauley, Michael J. Franklin, Scott Shenker, I

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Source URL: www.cs.princeton.edu

Language: English - Date: 2013-03-09 18:36:36
20Computing / Data / Apache Software Foundation / Hadoop / Business intelligence / Query languages / Big data / Analytics / Apache Spark / Pig

Latency, Damned Latency, and Streaming Speaker: Jonathan Goldstein Microsoft Research This talk incorporates insights from 8 years of research and product development, with too many valued contributers to list, but a spe

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Source URL: www.hpts.ws

Language: English - Date: 2015-10-08 07:54:20
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