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    4. Dynamic Job Ordering And Slot Configurations For MapReduce Workloads

    Dynamic Job Ordering And Slot Configurations For MapReduce Workloads project in Java Spring Framework with source code and document.

    Java Spring Framework project   Last updated on - July 11, 2018
    Kalaiselvi Elumalai
    Kalaiselvi Elumalai
    php java big data Html Css Javascript Jquery 
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    In this page Dynamic Job Ordering And Slot Configurations For MapReduce Workloads 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. Dynamic Job Ordering And Slot Configurations For MapReduce Workloads 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 Kalaiselvi Elumalai. 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.

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    About Dynamic Job Ordering And Slot Configurations For MapReduce Workloads project

    project Name

    Dynamic Job Ordering And Slot Configurations For MapReduce Workloads

    Project Complexityadvanced
    Duration15 Days
    project ID2435
    Developer NameKalaiselvi Elumalai
    Publish DateJuly 11, 2018
    project PlatformJava Spring Framework
    Programming Languagejava,hadoop
    Front End
    Back End
    IDE ToolEclipse
    Database Integrationhdfs
    project Typedesktop Application
    No of project Download170
    project Total View5192
    Today Trends1
    Current Month Trends43
    Last Month Trends78

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    Features and function of the Dynamic Job Ordering And Slot Configurations For MapReduce Workloads project

    MapReduce is a popular parallel computing paradigm for large-scale data processing in clusters and data centers. A MapReduce workload generally contains a set of jobs, each of which consists of multiple map tasks followed by multiple reduce tasks. Due to 1) that map tasks can only run in map slots and reduce tasks can only run in reduce slots, and 2) the general execution constraints that map tasks are executed before reduce tasks, different job execution orders and map/reduce slot configurations for a MapReduce workload have significantly different performance and system utilization. This paper proposes two classes of algorithms to minimize the makespan and the total completion time for an offline MapReduce workload. Our first class of algorithms focuses on the job ordering optimization for a MapReduce workload under a given map/reduce slot configuration. In contrast, our second class of algorithms considers the scenario that we can perform optimization for map/reduce slot configuration for a MapReduce workload. We perform simulations as well as experiments on Amazon EC2 and show that our proposed algorithms produce results that are up to 15% „ 80% better than currently unoptimized Hadoop, leading to significant reductions in running time in practice.

    User modules and function of Dynamic Job Ordering And Slot Configurations For MapReduce Workloads

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    How to import and run the project?

    drag and drop method or using pen drive access

    How to import database?

    using linux command

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    Download Dynamic Job Ordering And Slot Configurations For MapReduce Workloads source code

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