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Dynamic Resource Allocation For MapReduce With Partitioning Skew project in Jakarta Servlet ( formerly Java Servlet ).

Jakarta Servlet ( formerly Java Servlet ) project   Last updated on - July 12, 2018
vino vasanth
vino vasanth
hadoop java php web development 
2 Reviews
5
2836 View
44 Downloads
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In this page Dynamic Resource Allocation For MapReduce With Partitioning Skew project is a desktop application which is developed in Jakarta Servlet ( formerly Java Servlet ) platform. This Jakarta Servlet ( formerly Java Servlet ) project with tutorial and guide for developing a code. Dynamic Resource Allocation For MapReduce With Partitioning Skew is a open source you can Download zip and edit as per you need. If you want more latest Jakarta Servlet ( formerly Java Servlet ) 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. This project can edit using a Eclipse IDE. Following Jakarta Servlet ( formerly Java Servlet ) project contains all the important features which can be in use for the BE, BTech, MCA, BCA, Engineering, Bs.CS, IT, Software Engineering, Computer Science students and Devloper for their college projects. 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. To download Dynamic Resource Allocation For MapReduce With Partitioning Skew project in Jakarta Servlet ( formerly Java Servlet ) with source code files, please scroll down to the bottom of this page for the Download Zip file of source code button.

About project

project Name

Dynamic Resource Allocation For MapReduce With Partitioning Skew

Project Complexityadvanced
Duration15 Days
project ID2440
Developer Namevino vasanth
Publish DateJuly 12, 2018
project PlatformJakarta Servlet ( formerly Java Servlet )
Programming LanguageFor this particular Jakarta Servlet ( formerly Java Servlet ) project, java,hadoop is required
Front EndHTML, CSS, JS, Bootstrap
Back EndJAVA, MySQL/Oracle/MariaDB
IDE ToolEclipse
Database Integrationhdfs
project Typedesktop Application
No of project Download44
project Total View2836
Today Trends27
Current Month Trends38
Last Month Trends35

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Features of the Dynamic Resource Allocation For MapReduce With Partitioning Skew project

We will implement the following feature in the Jakarta Servlet ( formerly Java Servlet ) Dynamic Resource Allocation For MapReduce With Partitioning Skew Project:
MapReduce has become a prevalent programming model for building data processing applications in the cloud. Whilebeing widely used, existing MapReduce schedulers still suffer from an issue known as partitioning skew, where the output of map tasksis unevenly distributed among reduce tasks. Existing solutions follow a similar principle that repartitions workload among reduce tasks.However, those approaches often incur high performance overhead due to the partition size prediction and repartitioning. In this paper,we present DREAMS, a framework that provides run-time partitioning skew mitigation. Instead of repartitioning workload amongreduce tasks, we cope with the partitioning skew problem by controlling the amount of resources allocated to each reduce task. Ourapproach completely eliminates the repartitioning overhead, yet is simple to implement. Experiments using both real and syntheticworkloads running on a 21-node Hadoop cluster demonstrate that DREAMS can effectively mitigate the negative impact of partitioningskew, thereby improving the job completion time by up to a factor of 2:29 over the native Hadoop YARN. Compared to thestate-of-the-art solution, DREAMS can improve the job completion time by a factor of 1:65.

User modules and function of Dynamic Resource Allocation For MapReduce With Partitioning Skew

We will implement the following functionalities in the Jakarta Servlet ( formerly Java Servlet ) Dynamic Resource Allocation For MapReduce With Partitioning Skew Project:

Software requirement to run this project

Platform : Jakarta EE 11 support with Java SE 21 Install a Java Development Kit (JDK). Please make sure you have Java SE 11 or higher (we have tested with Java SE 11 and Java SE 17). Install an application server that supports Jakarta EE. Install Maven 3 or higher. Install DBMS - MySQL, Oracle, MariaDB as project requirements. Create a new project with Eclipse Starter for Jakarta EE.

Hardware requirement to run this project

1. laptop/desktop. 2. minimum 8GB RAM. 3. minimum 250GB SDD for smooth performs.

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After you finish downloading the project, unzip the project file.

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