Search Results for "mapreduce" - Page 2
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Showing 54 open source projects for "mapreduce"
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Mr.FSM
Large-Scale Frequent Subgraph Mining in MapReduce
This is the program used in the following paper: Wenqing Lin, Xiaokui Xiao, and Gabriel Ghinita. Large-Scale Frequent Subgraph Mining in MapReduce. In Proceedings of the 30th IEEE International Conference on Data Engineering (ICDE), pages 844-855, 2014. Please cite the paper if you choose to use the program. If having any problems, please report to {wlin1 at ntu dot edu dot sg}. -
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Flamingo Project
Workflow Designer, Hive Editor, Pig Editor, File System Browser
Flamingo is a open-source Big Data Platform that combine a Ajax Rich Web Interface + Workflow Engine + Workflow Designer + MapReduce + Hive Editor + Pig Editor. 1. Easy Tool for big data 2. Use comfortable in Hadoop EcoSystem projects 3. Based GPL V3 License Supporting Pig IDE, Hive IDE, HDFS Browser, Scheduler, Hadoop Job Monitoring, Workflow Engine, Workflow Designer, MapReduce. -
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qMongoFront
qMongoFront is a GUI tools for Mongodb. It is developed using QT
qMongoFront is a native QT mongodb application for Linux that gives you an usable GUI interface to work with mongodb. It's free and open source. -
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Aspose for Hadoop
This project holds source code for Aspose for Hadoop project.
Aspose for Hadoop project enables Apache Hadoop / MapReduce developers to work with various binary file formats. The developers can create and convert binary sequence files into text sequence files. -
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PageRank for wikipedia
PageRank algorithm for wikipedia pages on Amazon Elastic MapReduce
• Implemented the project using PageRank algorithm for Wikipedia pages on Amazon Elastic MapReduce. • Designed MapReduce jobs for red links removal, outlink adjacency graph, compute the total number of pages, PageRank calculation, sorting of PageRanks. • To run the project on amazon Elastic MapReduce specify jar location. Pass the directory locations as an argument of input and output respectively. -
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MapReduce++ is a project for implementation of parallel algorithms. It has currently two C++ implementations of the MapReduce abstraction: the MapMP library (multiprocessors) and the MaPI framework (multicomputers).
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MROrder
MROrder: Automated MapReduce Job Ordering Optimizaton Prototype System
MROrder is an automated MapReduce job ordering optimizaton prototype system. It targets at the online MapReduce workloads where MapReduce jobs arrives over time for various perfomane metrics, such as makespan, total completion time. There are two core components for MROrder, i.e., policy module and ordering module. The policy module decides when and how to perform job ordering dynamcially. -
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JUMMP
JUMMP: Job Uninterrupted Maneuverable MapReduce Platform
...W.C. Moody; L. Ngo; E. Duffy; A. Apon; "JUMMP: Job Uninterrupted Maneuverable MapReduce Platform", Cluster Computing (CLUSTER), 2013 IEEE International Conference on , 23-27 Sept. 2013 -
Add Two Lines of Code. Get Full APM.Works out of the box for Rails, Django, Express, Phoenix, and more. Monitoring exceptions and performance in no time.
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DHFS
A dynamic slot allocation technique to improve performance for HFS.
...It is based on the observation that at different period of time there may be idle map (or reduce) slots, as the job proceeds from map phase to reduce phase. We can use the unused map slots for those overloaded reduce tasks to improve the performance of the MapReduce workload, and vice versa, by breaking the implicit assumption that map tasks are run on map slots and reduce tasks are run on reduce slots. For example, at the beginning of MapReduce workload computation, there will be only computing map tasks and no computing reduce tasks, i.e., all the computation workload lies in the map-side. ... -
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distmap
A toolkit for distributed short read mapping
DistMap is a user-friendly pipeline designed to map short reads in a MapReduce framework on a local Hadoop cluster. It is designed to be easily implemented by researchers who do not have expert knowledge of bioinformatics. As it does not have any dependencies, DistMap provides full flexibility and control to the user. The user can use any version of a compatible mapper and any reference genome assembly. There is no need to maintain the mapper, reference or DistMap source code on each of the slaves (nodes) in the Hadoop cluster, making maintenance extremely easy. -
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HadStat
HadStat is service on cloud,for data analysis using Hadoop MapReduce.
HadStat is service on the cloud, allow you to analysis the data on the cloud and return the result in nice graph,this service is free, you can redistribute it and/or modify it under the terms of the GNU General Public License. this service using many technologies , like Hadoop mapreduce, HTML, PHP, Web Service applications, linux server, java, eclipse IDE, with many indicators:Simple moving average (SMA),Exponential moving average (EMA),Smoothed simple moving average (SMMA),Linear weighted moving average (LWMA )on DATA from NYSE daily prices..... -
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MGMF: MapReduce-based Graph Mining Framework provides carefully designed frameworks for various graph mining algorithms and it is fast, efficient, and scalable. The implementation of MGMF is available in this website.
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Hadoop is a great project for deep analytics based on the MapReduce features. It also includes a powerful distributed file system designed to ensure that the analytics workloads can locally access the data to be processed to minimize the network bandwidth impact. I found this filesystem very useful to leverage storage from all my PCs and even from some of my online storage such as S3. However i did not want to deploy the full hadoop stack.
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mapred-propertypath
to create a jar to help controle input-paths of mapreduce
Sometimes, the input-paths of a mapreduce programs are complex. Files and directories are mixed together, it is difficult and boring to write and examine the input paths. This project aims to create a jar to help control the input paths. The basic method is adding a property-file which contains some input-paths and filter-conditions, and the jar generates the input-paths for MR automatically and correctly. -
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A web-based interface for the Hadoop MapReduce framework that simplifies the process of writing and running MapReduce jobs. Aimed at introducing parallelism concepts in introductory computer science courses.
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SOAPstreaming
Hadoop-based Framework for Analyzing Large Scale NGS Data
SOAPstreaming, a flexible hadoop-based framework for systematically analyzing large scale NGS data. SOAPstreaming uses an enhanced Hadoop streaming strategy of MapReduce model to parallelize tools, which offers great scalability and efficiently reduces running time of large NGS datasets. Moreover, it has nice expansion capability to integrate new tools for different analysis needs, which more and more tools will be added in this framework. -
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MapReduce Brazil
Aggregates MapReduce projects
Nowadays the production and storage of Big Data is common, both in the academy and in the enterprises. To process this huge amount of data it is essential the use of high performance platforms and programming models like MapReduce -
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SECTOR: A Distributed Data Storage and Processing Platform
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mrMAQ
mrMAQ is a MapReduce implementation of MAQ short read aligner
mrMAQ is a MapReduce implementation of MAQ short read aligner. It's composed of a few classes that implement map and reduce interfaces, plus an optional combiner. -
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Ocean Sync
Hadoop Management System
OceanSync is an Hadoop Management System that allows users to control a variety of aspects of Hadoop. This includes a Graphical User Interface that allows a user to perform HDFS maintenance tasks and submit new jobs to the cluster. The OceanSync product sits on top of any Hadoop Architecture. -
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Framework for development of simple evolutionary algorithms / island models programs in distributed environment using MapReduce programming model based on hadoop.
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We are dedicated to develop a web based hadoop including automatically hadoop cluster configuration, hadoop distributed file system access, MapReduce job submission and hadoop cluster monitoring environment.
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HadoopDB is a hybrid of parallel database and MapReduce technologies. It approaches parallel databases in performance and efficiency, yet still yields the scalability, fault tolerance, and flexibility of MapReduce systems.
