Big Data Applications Using Workflows for Data Parallel Computing

2014 ◽  
Vol 16 (4) ◽  
pp. 11-21 ◽  
Author(s):  
Jianwu Wang ◽  
Daniel Crawl ◽  
Ilkay Altintas ◽  
Weizhong Li
Keyword(s):  
Big Data ◽  
Parallel Computing ◽  
Data Parallel ◽  
Big Data Applications ◽  
Data Parallel Computing

A Practical Approach for Scalable Record Linkage on Hadoop

2013 ◽  
Vol 753-755 ◽  
pp. 3018-3024 ◽  
Author(s):  
Fen Gyu Yang ◽  
Ying Chen ◽  
Ye Zhang
Keyword(s):  
Parallel Computing ◽  
Record Linkage ◽  
Practical Approach ◽  
Massive Data ◽  
Traditional Methods ◽  
High Recall ◽  
Data Parallel ◽  
Computing Framework ◽  
Data Parallel Computing ◽  
Hadoop Cluster

As increasing data have been collected in many applications, we have to face with millions of data in record linkage. With respect to traditional methods, there comes out a big challenge in performance while dealing with massive data. Parallel computing framework, such as MapReduce, has become an efficient and practical way to address this problem. In this paper, we propose a practical 3-phase MapReduce approach that fulfills blocking, filtering, and linking in 3 consecutive processes on Hadoop cluster. Experiments show that our approach functions efficiently and effectively with keeping high recall in contrast to tradition method.

scholarly journals Apache Hama: An Emerging Bulk Synchronous Parallel Computing Framework for Big Data Applications

IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 8879-8887 ◽  
Author(s):  
Kamran Siddique ◽  
Zahid Akhtar ◽  
Edward J. Yoon ◽  
Young-Sik Jeong ◽  
Dipankar Dasgupta ◽  
...  
Keyword(s):  
Big Data ◽  
Parallel Computing ◽  
Bulk Synchronous Parallel ◽  
Big Data Applications ◽  
Computing Framework
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