Hadoop Thesis

Hadoop Thesis

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Hadoop Thesis

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Hadoop Thesis Format:

  • Table of Contents
  • Abstract
  • List of Tables
  • List of Figures
  • Introduction
  • Background Overview
  • Motivation of the Research
  • Aim of the Research
  • Thesis Organization
  • Research Methodologies
  • Algorithm Description
  • Pseudocode description
  • Simulation setup
  • Performance Analysis
  • Comparative Study
  • Conclusion
  • Future research
  • References
  • Appendices
  • Appendix Bioset

Main Hadoop Thesis Topics Covers:

  • Big Data Introduction and Data Analytics
  • Hadoop Fundamentals
  • HDFS, Hive, MapReduce
  • Sensors Dataset (Weather Datasets)
  • Wordcount problem
  • Social media datasets like twitter data analysis and YouTube
  • HBase, Pig and Sqoop
  • Spark and Scala
  • Apache Spark and Oozie
  • Installations: Hive, Sqoop and Hadoop
  • Complex MapReduce Jobs Functioning
  • Data ingestion into Hadoop
  • HDFS architecture and MapReduce framework
  • Understanding of Hadoop Design Patterns
  • Job Scheduling Oozie

Major Algorithms in Hadoop:

  • User and item based recommendations
  • Fuzzy-C-Means and K-Means Clustering
  • Collaborative filtering algorithm
  • Mean Shift Clustering
  • Latent Dirichlet Allocation
  • Dirichlet Process clustering
  • Singular Value Decomposition
  • Complementary Naïve Bayes Classifier
  • Random Forest Decision Tree
  • Parallel Frequent Pattern Mining
  • High performance java collections
  • KNN Algorithm
  • Genetic Algorithm
  • Scheduling using Tabular Approach
  • Machine Learning algorithm
  • Apriori based algorithms for MapReduce
  • K-mer counting
  • Secondary sorting
  • DNA Sequencing
  • Naïve Bayes Algorithm
  • Linear Regression
  • Bloom filtering on MapReduce
  • PageRank Algorithm
  • Job Scheduling Algorithms

Key Technologies over Hadoop:

  • Machine learning automation
  • Web Notebooks
  • Data Security and Governance
  • Global Resource Management
  • Data Fabrics spreading
  • Messaging Platforms
  • NoSQL Takeover

Stream Processing Technologies:

  • Apache Flink
  • Spark Streaming
  • Apache Apex
  • Apache Samza
  • Apache Storm
  • Akka Streams
  • Streamset

Topics include in Hadoop Thesis:

  • Hadoop for Frequent Accessed Data Files Using Flexible Replication Management
  • Hadoop MapReduce Paradigm for Mining Parallel Distributed Patterns
  • Organize and Enhance Online Search Results Using Hadoop Based Novel Approach in Big Data Ecosystem
  • Sun Grid Engine and Apache Hadoop Big Data Image Processing Empirical and Theoretical comparison
  • Clustering for Analyze Mobile Phone Usage in Pig and Spark MLLib
  • Bandwidth Reduction Using Multicast Based Replication in Hadoop HDFS
  • Local Scheduling Algorithm Policy Enhancement in Hadoop Cluster Platform
  • High Scalable Distributed Processing and Storage Paradigm in Big Data Framework for Unstructured Data
  • Naive Bayes Classifier for Predict Cancer Report Generation, and Query Providing
  • Survey Framework Based on Cloud Robotics to Solve Problem of Simultaneous Mapping and Localization
  • Develop Internet of Things in Industrial Educational IoT Case for Cloud Framework
  • Machine Learning Techniques for Analyze Microarray Data on Scalable Environment
  • Hadoop Processing Interface for Computationally Intensive Processes Service Offloading in Private Cloud
  • Ensemble Data Classification Approach Based on Iterative Hadoop on Distributed Medical Databases
  • Compare Large Volume of Data Distributed Processing Performance on Docker and Xen Based Virtual Clusters