Apache Spark

Results: 128



#Item
31Higher-order functions / Functional programming / Functional languages / Concurrent programming languages / Programming language comparisons / List comprehension / Apache Spark / Oz / Monad / Fold / Scala / Map

Implicit Parallelism through Deep Language Embedding Alexander Alexandrov Asterios Katsifodimos Volker Markl

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Source URL: www.user.tu-berlin.de

Language: English - Date: 2016-07-21 07:25:50
32Apache Software Foundation / Apache Spark / Cluster computing / Hadoop / Java platform / University of California /  Berkeley / RDD / Disk partitioning / Disk formatting

Spark.jl: Resilient Distributed Datasets in Julia    Dennis Wilson, Martín Martínez Rivera, Nicole Power, Tim Mickel  [dennisw, martinmr, npower, tmickel]@mit.edu      

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Source URL: css.csail.mit.edu

Language: English - Date: 2015-01-21 21:28:03
33Parallel computing / Distributed computing architecture / Apache Software Foundation / Data management / MapReduce / Big data / Iteration / Apache Hadoop / Data analysis / Aster Data Systems / Apache Spark

The Stratosphere Platform: Big Data Analytics at Scale Database Systems and Information Management, Technische Universität Berlin Big Data Analysts Still Hard to Find Mathematical Programming

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Source URL: www.user.tu-berlin.de

Language: English - Date: 2016-07-21 07:25:51
34Hadoop / Cloud infrastructure / Apache Software Foundation / Cask / Apache Hadoop / Apache HBase / MapReduce / Big data / Cloudera / Hortonworks / Apache Spark / Microsoft Azure

Cask Data Application Platform (CDAP) CDAP is an open source, Apache 2.0 licensed, distributed, application framework for delivering Hadoop solutions. It integrates and abstracts the underlying Hadoop technologies to pr

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Source URL: customers.cask.co

Language: English - Date: 2016-07-31 17:55:06
35Java platform / Apache Software Foundation / Cloud infrastructure / Parallel computing / Distributed computing architecture / Akka / Apache Hadoop / Actor model / Storm / Apache Spark / Scala / Transmission Control Protocol

  GearPump  –  Real-­‐time  Streaming  Engine   Using  Akka*       Sean  Zhong,  Kam  Kasravi,  Huafeng  Wang,  Manu  Zhang,  Weihua  Jiang  

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Source URL: downloads.typesafe.com

Language: English - Date: 2014-12-15 11:49:41
36Apache Software Foundation / Hadoop / Data management / Business intelligence / Big data / Apache Hadoop / Apache Spark / Apache Flink / Erhard Rahm / Analytics / Pig / Extract /  transform /  load

DE GRUYTER OLDENBOURG it – Information Technology 2016; Galley Proof Editorial Erhard Rahm*

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Source URL: dbs.uni-leipzig.de

Language: English - Date: 2016-05-20 03:21:43
37Hadoop / Cloud infrastructure / Apache Software Foundation / Parallel computing / Apache Hadoop / Apache HBase / Data-intensive computing / Apache Spark / MapR / GraphLab / Big data / Solid-state drive

Big Data Meets HPC – Exploiting HPC Technologies for Accelerating Big Data Processing Keynote Talk at HPCAC-Switzerland (Marby Dhabaleswar K. (DK) Panda

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Source URL: www.hpcadvisorycouncil.com

Language: English - Date: 2016-04-06 01:18:06
38Apache Software Foundation / Cloud infrastructure / Hadoop / Data management / Cluster computing / Apache Spark / Apache Hadoop / Apache Flink / OpenStack / NoSQL / Apache Cassandra / Big data

NSF14start October 1, 2014 Datanet: CIF21 DIBBs: Middleware and High Performance Analytics Libraries for Scalable Data Science • 

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Source URL: www.nationaldataservice.org

Language: English - Date: 2016-04-06 11:00:39
39Parallel computing / Apache Software Foundation / File sharing networks / Computer networking / Telecommunications engineering / MapReduce / Apache Hadoop / Apache Spark / Computer cluster / Simulation / Network simulation / Peer-to-peer

Parallel Discrete-Event Simulation on Data Processing Engines Kazuyuki Shudo, Yuya Kato∗ , Takahiro Sugino† , and Masatoshi Hanai‡ Tokyo Institute of Technology Abstract—Development of a decent parallel simulato

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Source URL: www.shudo.net

Language: English - Date: 2016-07-21 20:34:37
40

We explore the trade-offs of performing linear algebra in Apache Spark versus the traditional C and MPI approach by examining three widely-used matrix factorizations: NMF (for physical plausibility), PCA (for its ubiquit

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Source URL: mmds-data.org

- Date: 2016-06-23 15:50:48
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