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OPTIMIZATION FOR SPECULATIVE EXECUTION IN BIGDATA PROCESSING CLUSTERS Project in Java Spring Framework with source code and document free download.

Java Spring Framework project Publish on - July 12, 2018

vino vasanth

hadoop java php web development

2 Reviews 5

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149 Downloads

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In this page OPTIMIZATION FOR SPECULATIVE EXECUTION IN BIGDATA PROCESSING CLUSTERS project is a desktop application which is developed in Java Spring Framework platform. This Java Spring Framework project with tutorial and guide for developing a code. OPTIMIZATION FOR SPECULATIVE EXECUTION IN BIGDATA PROCESSING CLUSTERS is a open source you can Download zip and edit as per you need. If you want more latest Java Spring Framework projects here. This is simple and basic level small project for learning purpose. Also you can modified this system as per your requriments and develop a perfect advance level project. Zip file containing the source code that can be extracted and then imported into Eclipse. Here Project Source code for BE, BTech, MCA, BCA, Engineering, Bs.CS, IT, Software Engineering, Computer Science students and Devloper. Student can submit in college for final year project. This script developed by vino vasanth. This desktop application 100% working smooth without any bug. It is developed using java,hadoop and Database hdfs. This software code helpful in academic projects and research paper for final year computer science. You can explore great collection of other Java Spring Framework projects.

Document and Reports information of OPTIMIZATION FOR SPECULATIVE EXECUTION IN BIGDATA PROCESSING CLUSTERS

This doucment file contains project Synopsis, Reports, and various diagrams. Also Abstract in PDF, PPT file inside zip so that document link below the page. Class Diagrams, Use Case Diagrams, Entity–relationship(ER) Diagrams, Data flow diagram(DFD), Sequence diagram and software requirements specification (SRS) in report file. Complete ready made open source code free of cost download. You can find Top Downloaded Java Spring Framework projects here.

About Project

project Name	OPTIMIZATION FOR SPECULATIVE EXECUTION IN BIGDATA PROCESSING CLUSTERS
project ID	2439
Developer Name	vino vasanth
Publish Date	July 12, 2018
project Platform	Java Spring Framework
Programming Language	java,hadoop
Front End
Back End
IDE Tool	Eclipse
Database	hdfs
project Type	desktop Application
No of project Download	149
project Total View	5267
Today Trends	5
Current Month Trends	46
Last Month Trends	89

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Features of the OPTIMIZATION FOR SPECULATIVE EXECUTION IN BIGDATA PROCESSING CLUSTERS Project

A big parallel processing job can be delayed substantially as long as one of its many tasks is being assigned to an unreliableor congested machine. To tackle this so-called straggler problem, most parallel processing frameworks such as MapReduce haveadopted various strategies under which the system may speculatively launch additional copies of the same task if its progress isabnormally slow when extra idling resource is available. In this paper, we focus on the design of speculative execution schemes forparallel processing clusters from an optimization perspective under different loading conditions. For the lightly loaded case, we analyzeand propose one cloning scheme, namely, the Smart Cloning Algorithm (SCA) which is based on maximizing the overall system utility.Wealso derive the workload threshold under which SCA should be used for speculative execution. For the heavily loaded case, we proposethe Enhanced Speculative Execution (ESE) algorithm which is an extension of the Microsoft Mantri scheme to mitigate stragglers. Oursimulation results show SCA reduces the total job flowtime, i.e., the job delay/ response time by nearly 6% comparing to the speculativeexecution strategy of Microsoft Mantri. In addition, we show that the ESE Algorithm outperforms the Mantri baseline scheme by 71% interms of the job flowtime while consuming the same amount of computation resource

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OPTIMIZATION FOR SPECULATIVE EXECUTION IN BIGDATA PROCESSING CLUSTERS project in Java Spring Framework

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A big parallel processing job can be delayed substantially as long as one of its many tasks is being assigned to an unreliableor congested machine. To tackle this so-called straggler problem, most parallel processing frameworks such as MapReduce haveadopted various strategies under which the system may speculatively launch additional copies of the ... [ Download Source Code ]

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Like 2 | Views 5267 | Download 149