Abstract
Problem statement: Features and challenges of the PACS server solutions are elaborated in the context of large scale computing. Approach: Hadoop is a pivotal piece of the data mining renaissance offers the ability to tackle large data sets in ways that weren’t previously feasible and clarifies certain functionalities such as MapReducer and Hadoop distributed file system. Results: The PACS server was highlighted in Health Care System with primary Functions of DICOM and basic operations of query, retrieval and routing were performed on various images. The study attempted to propose a concept called Hadoop Picture Archiving and Communication System (HPACS) same as any other PACS server except that is uses distributed storage and distributed computing on commodity of hardware. Conclusion/Recommendations: The features of PACS and HPACS are compared in terms of storage, backup, cost, performance, turnaround time and backup. Finally, the advantages of Hadoop solution were explained.
Highlights
Hadoop is one of the most salient pieces of the data mining renaissance which offers the ability to tackle large data sets in ways that weren’t previously possible due to time and cost constraints It is a part of the apache software foundation and its being built by the community of contributor in all over the world
The Hadoop project promotes the development of open source software and it supplies a framework for the development of highly scalable distributed computing applications (Venner, 2009)
Semantic search directions are presented followed by a detailed comparison of the tools in the direction based on functionality and Interface with future research avenues
Summary
Hadoop is one of the most salient pieces of the data mining renaissance which offers the ability to tackle large data sets in ways that weren’t previously possible due to time and cost constraints It is a part of the apache software foundation and its being built by the community of contributor in all over the world. The Hadoop project promotes the development of open source software and it supplies a framework for the development of highly scalable distributed computing applications (Venner, 2009). The Hadoop framework handles the processing details, leaving developers free to focus on application logic. Hadoop handles thousands of terabytes and pitabytes on thousands of nodes. The study begins with a status of the current search engine followed by the discussion of related work for semantic search. Semantic search directions are presented followed by a detailed comparison of the tools in the direction based on functionality and Interface with future research avenues
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