Hadoop MapReduce Programming

2018 ◽  
pp. 125-146
Keyword(s):  
User Interfaces ◽  
Software Framework ◽  
Mapreduce Framework ◽  
Resource Manager ◽  
Research Issues ◽  
Entire Process ◽  
Hadoop Mapreduce

The second major component of Hadoop is MapReduce. It is the software framework for Hadoop environment. It consists of a single resource manager, one node manager per node, and one application manager per application. These managers are responsible for allocating necessary resources and executing the jobs submitted by clients. The entire process of executing a job is narrated in this chapter. The architecture of MapReduce framework is explained. The execution is implemented through two major operations: map and reduce. The map and reduce operations are demonstrated with an example. The syntax of different user interfaces available is shown. The coding to be done for MapReduce programming is shown using Java. The entire cycle of job execution is shown. After reading this chapter, the reader will be able to write MapReduce programs and execute them. At the end of the chapter, some research issues in the MapReduce programming is outlined.

scholarly journals Sampo-UI: A full stack JavaScript framework for developing semantic portal user interfaces

Semantic Web ◽  
2021 ◽  
pp. 1-16
Author(s):  
Esko Ikkala ◽  
Eero Hyvönen ◽  
Heikki Rantala ◽  
Mikko Koho
Keyword(s):  
User Interfaces ◽  
Linked Data ◽  
State Of The Art ◽  
Software Framework ◽  
End User ◽  
Faceted Search ◽  
Software Developer ◽  
Current State ◽  
Knowledge Graphs ◽  
User Friendly

This paper presents a new software framework, Sampo-UI, for developing user interfaces for semantic portals. The goal is to provide the end-user with multiple application perspectives to Linked Data knowledge graphs, and a two-step usage cycle based on faceted search combined with ready-to-use tooling for data analysis. For the software developer, the Sampo-UI framework makes it possible to create highly customizable, user-friendly, and responsive user interfaces using current state-of-the-art JavaScript libraries and data from SPARQL endpoints, while saving substantial coding effort. Sampo-UI is published on GitHub under the open MIT License and has been utilized in several internal and external projects. The framework has been used thus far in creating six published and five forth-coming portals, mostly related to the Cultural Heritage domain, that have had tens of thousands of end-users on the Web.

Weighted Finite Automata Based Image Compression on Hadoop MapReduce Framework

2015 ◽  
Author(s):  
U.S.N. Raju ◽  
Irlanki Sandeep ◽  
Nattam Sai Karthik ◽  
Rayapudi Siva Praveen ◽  
Mayank Singh Sachan
Keyword(s):  
Image Compression ◽  
Finite Automata ◽  
Mapreduce Framework ◽  
Hadoop Mapreduce ◽  
Weighted Finite Automata

An Expressive Hadoop MapReduce Framework

2017 ◽  
Vol 23 (11) ◽  
pp. 11197-11201
Author(s):  
Nathar Shah ◽  
Christopher Messom
Keyword(s):  
Mapreduce Framework ◽  
Hadoop Mapreduce

scholarly journals Similarity Measurement Technique for Measuring the Performance of Page Rank Algorithm Based on Hadoop

2020 ◽  
Vol 8 (5) ◽  
pp. 4712-4717
Keyword(s):  
Big Data ◽  
Search Engine ◽  
Measurement Technique ◽  
Similarity Measurement ◽  
Web Pages ◽  
Ranking Algorithm ◽  
Web Data ◽  
Mapreduce Framework ◽  
Page Rank ◽  
Hadoop Mapreduce

In this century big data manipulation is a challenging task in the field of web mining because content of web data is massively increasing day by day. Using search engine retrieving efficient, relevant and meaningful information from massive amount of Web Data is quite impossible. Different search engine uses different ranking algorithm to retrieve relevant information easily. A new page ranking algorithm is presented based on synonymous word count using Hadoop MapReduce framework named as Similarity Measurement Technique (SMT). Hadoop MapReduce framework is used to partition Big Data and provides a scalable, economical and easier way to process these data. It stores intermediate result for running iterative jobs in the local disk. In this algorithm, SMT takes a query from user and parse it using Hadoop and calculate rank of web pages. For experimental purpose wiki data file have been used and applied page rank algorithm (PR), improvised page rank algorithm (IPR) and proposed SMT method to calculate page rank of all web pages and compare among these methods. Proposed method provides better scoring accuracy than other approaches and reduces theme drift problem.

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