Hadoop Projects

Some Major Big data Hadoop projects of 2017

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Hadoop Projects are the projects developed on big data hadoop tool, it is most frequently used big data tool. Hadoop is a big data open source tool which greatly help in developing big projects in organization. Where as Hadoop projects are projects developed in hadoop ecosystem using hadoop commands and hadoop cluster. All projects developed using Hadoop tool are working efficiently and in user friendly manner. They have all seeds of big data like high speed, better storage system and hadoop security.

Hadoop Projects

And Hadoop projects help a lot in maintaining your business. Also Hadoop projects for beginners and Hadoop projects for students are some of trending projects. Some major Hadoop projects are:

PROJECT 1: HADOOP AS A SERVICE

In today’s big data world this project can be proved as a great project. ThisĀ  project is all about developing a big data cloud which can provide hadoop services and big data framework for big data users. It provide online storage space to you to work on it. Also it gives many helpful big data services.

Usage of this project can help you in making great tools and software for your organization. Hadoop as a service is an big data open source project, so it comes in use quite frequently.

PROJECT 2: BIG DATA AS AN E-HEALTH SERVICE

As we know big data architect is creating huge impact in transforming business, healthcare and indirectly society as well. In recent times with development in e-business, e-health care have also became one of the important section. E-healthcare is something which can be the most important field of upcoming time. So developing a great hadoop file system for e-health care is not a bad plan.

This project can greatly boost the hadoop technology. This project is able to perform action like, managing health records of patients around globe, can bring better medicines for one and much more. Also this Big Data e-Health Service have operation management capabilities.

PROJECT 3: SYONCLOUD LOGS

Syoncloud is among popular hadoop projects, from various applications and servers it basically processes log files. This project is a hadoop real time project. It works on web servers, hadoop server, backoffice applications and business applications by capturing important information from everyday details generated there. It generate log files by the help of Flume sinks. The data that it captures is stored in hadoop database and is filtered in database.

Installing Syoncloud is easy. It itself includes essential components such as hadoop, Flume and Zookeeper. This is a crucial hadoop based project. And it show how effective hadoop features are.

PROJECT 4: HADOOP STUDIO

Hadoop studio is a hadoop related project. It is based on Net-beans Integrated development environment (IDE). It basically works in development field of maps. With the help of this project you would be feeling easy to understand, debug and create map-reduce applications. You will be doing so without making much development time for map-reduced cluster. Hadoop studio works in real time hadoop system. Studio introduced flowchart view of each job by map-reduced cluster. This also displays seperate outputs, inputs and each interaction between phases of this job. These kind of views greatly help big data developers to create hadoop app.

Since it is a Net-beans project, it can also generate source code of java and convert them into Binary jar files. Also it store these files in hadoop cluster in form hadoop data format or haoop pdfs or may be in other ways as well.

PROJECT 5: DISPY

Dispy, a another framework based project developed with help hadoop big data tools. It is Python based framework in which multiple processors work in a single machine to show execution of parallel jobs. Dispy works best for parallel jobs, parallel data where computations are evaluated with help different different hadoop data sources through hadoop model. Hadoop data distribution is the base of this project.

Dispy have features like, recovery of faults on server-side and client-side, it automatic includes dependencies(classes, Python functions, file), computations of specific nodes is well scheduled, security by encryption and serialization and more make it a good hadoop benefits project.

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