RSS 4 projects tagged "mapreduce"

No download Website Updated 09 Apr 2010 Hadoop Studio

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Pop 151.12
Vit 2.66

Hadoop Studio is a map-reduce development environment (IDE) based on Netbeans. It makes it easy to create, understand, and debug map-reduce applications based on Hadoop, without requiring development-time access to a map-reduce cluster. The studio provides a real-time workflow view of a map-reduce job, which displays the individual inputs, outputs, and interactions between the phases of a map-reduce job. The workflow view of a job updates in real time with the developer's code changes. It then generates Java sources and compiles them into a binary jar file, which can be run on a normal Hadoop cluster.

No download No website Updated 14 Jul 2011 Beanstalker

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Pop 21.00
Vit 31.85

Beanstalker is a set of Maven Plugins for Amazon Web Services (AWS) Elastic Beanstalk and Elastic MapReduce. Plugin Mojos are suitable not only for command-line usage, but for Continuous Integration as well.

Download Website Updated 04 Jun 2012 MapReduce-BitDew

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Pop 59.27
Vit 26.22

MapReduce-BitDew is an implementation of the MapReduce programming model proposed by Google for Internet Desktop Grids. Using MapReduce-BitDew, you can execute MapReduce applications on resources like Desktop PCs distributed on the Internet. MapReduce-BitDew features a firewall-friendly protocol, fault-tolerance, result-certification, 2-level schedulers, and more.

No download Website Updated 25 Oct 2012 dispy

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Pop 68.64
Vit 2.19

dispy is a Python framework for parallel execution of computations by distributing them across multiple processors in a single machine (SMP), or among many machines in a cluster or grid. The computations can be standalone programs or Python functions. dispy is well suited for the data parallel (SIMD) paradigm where a computation is evaluated with different (large) datasets independently (similar to Hadoop, MapReduce, Parallel Python). dispy features include automatic distribution of dependencies (files, Python functions, classes, modules), client-side and server-side fault recovery, scheduling of computations to specific nodes, encryption for security, sharing of computation resources if desired, and more.

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