Hadoop Projects

Hadoop Projects

            Hadoop Projects is a one of a kind service offered by us for your benefit. Recent trends are always an ideal platform for any researches to base their project on. One such attractive project area is Hadoop Projects. Because of its open source platform, Apache Hadoop is used most extensively. It business and solutions are more interested in Hadoop projects as it acts as a central hub for big data. This is what makes it much demanded domain in the field of research. We extend our hand to you for doing Hadoop projects and enhancing your knowledge in the field.

Hadoop Projects

            Our team of experts has put together an excellent list of topics for Hadoop projects for you to choose from. In order to make your projects stand out you should take risk by choosing a recent trend as a topic for your project. What makes Hadoop important is the fact that it can store enormous data and provide massive energy. Hadoop Projects is a mine worth digging as you will end up with more wealth than you imagined. Some of the key aspects of Hadoop is listed below for your references.

Significant Features of Hadoop:

  • Data Redundancy: It automatically maintains the various copies of data
  • Scalability: Scalable in data processing
  • Hardware Deployment: Huge group of cheap commodity hardware are easily deployed
  • Massive Data Processing: Large scale preprocessing of raw data, data exploration of complete datasets, mining huge datasets and data agility
  • Fast: Hadoop is faster access in data processing
  • Open source: Open source and freely available software that code can easily modified by programmer requirements.
  • Reliability: Due to the redundancy, data is reliable on Hadoop Clusters

Programming Languages:

  • Python (.py)
  • Haskell (.hs, lhs)
  • Java (.java)
  • Ruby (.rb, .rbw)
  • PHP (.php, .phtml, php3, .php4, .php5, .php7)
  • C# ( C sharp- .cs)
  • PERL (.pl, .pm, .t, .pocl)
  • R(.r)
  • Scala(.scala)
  • Matlab (.m)

Prerequisites for Hadoop Installation:

  • Require any of the following platforms: Ubuntu Linux, Unix, Mac OS X and Windows (needs Cygwin to run)
  • Java
  • SSH
  • Hadoop 2.7.2 latest version


Apache Hadoop Development Tools (version HDT 0.0.2)

  • Java classes for driver and mapper are created
  • Available jobs on MR cluster is listed
  • HDFS and Zookeeper nodes are inspected
  • Map reduce program on Hadoop cluster is launched


  • Independent platform
  • Platform for application development


  • Real time read/write operations big data is accessed by its distributed database
  • Linux and OSX are supported platform
  • It’s platform independent


  • Supported platform are OSX and Linux
  • Log data is collected from other sources and sent to Hadoop


  • Windows, Linux and OS X are the operating systems used
  • Hadoop clusters are monitored and managed by the provided web based interface to provision


  • Linux and OS C are the supported platform
  • Data from huge distributed systems are collected for the purpose for monitoring


  • It is OS independent
  • With rich data structures, data serialization is provided

Hadoop Distributed File System

  • OS X, Windows and Linux are the supported platform
  • Provides Hadoop file system


  • Platform independent
  • Hadoop uses it as data warehouse


  • Platform Independent
  • Large distributed datasets are processed by this model


  • OS X, Linux and Windows are supported
  • Complicated jobs are made easy


  • Linux, OS X and Windows are supported operating system
  • Data processing engine


  • Windows, MAC OS X and Linux are the platform supported


  • OS X and Linux are supported operating system
  • Hadoop jobs are managed and integrated with Hive, Sqoop, Pig, Map Reduce etc.


  • Algorithm for Scala and Spark environment and for data mining purpose are provided by it
  • Scalable machine learning applications are created by it


  • Works with the programming language called pig Latin
  • Serves as a platform for distributed big data analysis

Hadoop Databases Support:

Cassandra: Huge amount of data is handled by open source distributed database management system

Hbase: Non-relational, open source and distributed data base management

Hive: Large datasets from distributed storage is used to read and write with SQL

Mongo DB: Database based on free and open source document

NoSQL Database: Works by the big data’s demand

Apache Spark: Open source data analytics software that build top of the HDFS.

List of Hadoop Projects Ideas:

  • Data Consolidation
  • Hadoop Streaming Analytics
  • Complex Event Processing
  • Extraction, Translation and Load (ETL) Streaming
  • Augmenting/Replacing SAS
  • Integration of Amazon Elastic Map Reduce with Big Data
  • Big data Analytics for E-commerce
  • Yarn in Apache Spark for Visual analytics
  • Apache Hcatalog and Flume for Log collection and HDFS analysis
  • Apache Storm and Kafka for Real Time Stream Processing

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