Main Reference PaperHeads-Join: Efficient Earth Mover’s Distance Similarity Joins on Hadoop, IEEE Transactions on Parallel and Distributed Systems, May 2016 [Java/Hadoop]
  • The Earth Mover’s Distance (EMD) similarity join operation is prohibited for medium datasets. To speed up the join operation, an algorithm is proposed named HEADS-JOIN, which transforms data into the space of EMD lower bounds, where the pruning and partitioning can be performed based on the EMD lower bounds that can be computed at a low cost. This algorithm is done using MapReduce Framework.

+ Description
  • The Earth Mover’s Distance (EMD) similarity join operation is prohibited for medium datasets. To speed up the join operation, an algorithm is proposed named HEADS-JOIN, which transforms data into the space of EMD lower bounds, where the pruning and partitioning can be performed based on the EMD lower bounds that can be computed at a low cost. This algorithm is done using MapReduce Framework.

  • Reducing computation cost.

  • To achieve the scalability.

+ Aim & Objectives
  • Reducing computation cost.

  • To achieve the scalability.

  • An effective technique is contributed to scale HEADS-JOIN to even larger scale datasets.

+ Contribution
  • An effective technique is contributed to scale HEADS-JOIN to even larger scale datasets.

  • Java JDK 1.8, Hadoop 1.2.1

  • Netbeans 8.0.1, J2SE, Hadoop

 

+ Software Tools & Technologies
  • Java JDK 1.8, Hadoop 1.2.1

  • Netbeans 8.0.1, J2SE, Hadoop

 

  • B.E/B.Tech/M.E/M.Tech

+ Project Recommended For
  • B.E/B.Tech/M.E/M.Tech

Professional Ethics: We S-Logix would appreciate the students those who willingly contribute with atleast a line of thinking of their own while preparing the project with us. It is advised that the project given by us be considered only as a model project and be applied with confidence to contribute your own ideas through our expert guidance and enrich your knowledge.