Project Ideas Hadoop MapReduce

Project Ideas Hadoop MapReduce

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Project Ideas Hadoop MapReduce

   Project Ideas Hadoop MapReduce gives everlasting research network to boost students and research scholar’s skills to attain novel achievements continuously. We are masters in Hadoop MapReduce. Presently, we prepared 10000+ Hadoop MapReduce projects in various research domains such as social media, telecommunication, banking etc. Our surprisingly wonderful service is well suited for data management, IT and analytics professional looking to acquire knowledge in Hadoop MapReduce.

Our top experts train you in the following concepts:

  • Understand about MapReduce
  • Elements of MapReduce
  • How does MapReduce works?
  • Anatomy of MapReduce job
  • Types of I/O formats [Combine FileInputFormat, Multiple outputs, NLINE input format]
  • Brief description about classic MapReduce algorithms
  • Design patterns of MapReduce
  • MapReduce tools installation and configuration
  • MapReduce Programming [JAVA Programming]
  • MapReduce compression codec’s

MapReduce Processes:

  • Dache: Dataware cache
  • Data Centric Scheduling
  • Data Exchange Policy
  • Resource Provisioning
  • Hybrid Clouds

Characteristics/functionalities of Hadoop MapReduce:

  • It handles scheduling
  • It allocate workers to map and reduce large datasets
  • Data distribution is effectively performed
  • It process synchronization process
  • It can easily moves processes data
  • It handles faults and errors
  • Sorts, search, gathers, shuffle data
  • Detects failures and easily restarts
  • Everything done on top of a distributed file system

Hadoop MapReduce Concepts:

  • Projection and selection
  • Union, intersection and difference
  • Joining and Time series
  • Groupby and aggregation
  • Distinct values
  • Cross correlation
  • Distributed task execution
  • Parsing, validation and filtering
  • Summing and counting
  • Iterative message parsing

Typical Issues involving in MapReduce:

  • Iterate over a large number of records
  • Extract something of interest from each
  • Shuffle and sort intermediate results
  • Aggregate intermediate results
  • Generate final output

Application concepts in MapReduce:

  • ETL (Extraction, Translation and Load)
  • Machine Learning (Supervised and Unsupervised)
  • Data Validation
  • Performance Testing
  • Data Querying
  • Similar Item Detection
  • Data Warehousing
  • Information Retrieval
  • Log Analysis

List of Project Ideas Hadoop MapReduce:

  • Big Data Mining and Gathering Pipelines for Customer Relationship Management (CRM) Using Open-source
  • Small File Storage Based on Optimized MapFile in Hadoop Paradigm
  • Design Hadoop Platform by Seismic Data Analysis and Processing
  • Processing and Analysis of Higher Institution Academic Data Using Big Data Tools
  • Improved MapReduce Based SCAM (Scenario Based Clustering Algorithm for MANET) Algorithm to Detect Plagiarism on Big Data
  • Run-Time Capacity Allocation Using Game Theoretic Technique in MapRaduce
  • Load Massive Data Over HBase (Hadoop Database) on Distributed Database Frameworks
  • Roadside Air Quality Control Monitoring and Control Using Traffic Regulation Framework Based on Agent
  • Schedule Cross Platform Resource for MapReduce and Spark on Yet Another Resource Negotiator (YARN)
  • Relevant Subspace Based Scalable Mining Algorithm for Contextual Outliers
  • MapReduce for Analyze Geographical Based Distributed Big Data Processing
  • Enhance Vehicle Controls Using MapReduce Based Approach on Big Traffic Events
  • Predict Data Attacks Using LSTM (Long Short Term Memory) Based Memory Profile in Distributed Big Data Frameworks
  • Heterogeneous Hadoop Frameworks Using Adaptive Scheduling Algorithm
  • Investigate Hadoop Progress Control Based Adaptive Delay Scheduling Algorithm