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Dynamic Job Ordering And Slot Configurations For MapReduce Workloads project in Java Spring Framework.

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. This project can edit using a Eclipse IDE. Following Java Spring Framework 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 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. To download Dynamic Job Ordering And Slot Configurations For MapReduce Workloads project in Java Spring Framework 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 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 LanguageFor this particular Java Spring Framework project, java,hadoop is required
Front EndHTML, CSS, Bootstrap
Back EndJAVA, MySQL, Oracle, MariaDB
IDE ToolEclipse
Database Integrationhdfs
project Typedesktop Application
No of project Download173
project Total View6016
Today Trends425
Current Month Trends456
Last Month Trends63

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

We will implement the following feature in the Java Spring Framework 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

We will implement the following functionalities in the Java Spring Framework Dynamic Job Ordering And Slot Configurations For MapReduce Workloads Project:

Software requirement to run this project

Java Development Kit (JDK) Version: Java 8 or higher (Java 11 or Java 17 is recommended as of 2024 for LTS support). Spring Framework IDE: Eclipse, IntelliJ IDEA, or VS Code with Java and Spring Boot extensions. Database: MySQL, PostgreSQL or MongoDB. Application Server : Need a web server like Apache Tomcat or Jetty.

Hardware requirement to run this project

Processor (CPU): Minimum: 2-core processor (e.g., Intel Core i3 or equivalent) Recommended: 4-core or better (e.g., Intel Core i5/i7, AMD Ryzen 5/7) RAM (Memory): Minimum: 8 GB of RAM Recommended: 16 GB of RAM (especially if running Docker, multiple services, or heavy IDEs) Hard Disk: Minimum: 50 GB of free disk space (SSD is recommended for faster performance) Recommended: 100 GB or more (for large projects or multiple repositories) Display: Minimum: 1080p resolution (1920x1080) for better productivity, especially if using modern IDEs with multiple panes (for coding, testing, etc.) Recommended: Dual monitors for multitasking (optional but helpful) Operating System: Windows 10/11, macOS, or Linux (Ubuntu, CentOS, etc.) Linux is often preferred for server-side development due to its compatibility with Spring and deployment environments.

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How to import database?

using linux command

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