Analysis of the Influence Factors of Data Loading Performance Using Apache Sqoop


KIPS Transactions on Software and Data Engineering, Vol. 4, No. 2, pp. 77-82, Feb. 2015
10.3745/KTSDE.2015.4.2.77,   PDF Download:

Abstract

Big Data technology has been attracted much attention in aspect of fast data processing. Research of practicing Big Data technology is also ongoing to process large-scale structured data much faster in Relatioinal Database(RDB). Although there are lots of studies about measuring analyzing performance, studies about structured data loading performance, prior step of analyzing, is very rare. Thus, in this study, structured data in RDB is tested the performance that loads distributed processing platform Hadoop using Apache sqoop. Also in order to analyze the influence factors of data loading, it is tested repeatedly with different options of data loading and compared with data loading performance among RDB based servers. Although data loading performance of Apache Sqoop in test environment was low, but in large-scale Hadoop cluster environment we can expect much better performance because of getting more hardware resources. It is expected to be based on study improving data loading performance and whole steps of performance analyzing structured data in Hadoop Platform.


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from September 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article
[IEEE Style]
L. Chen and J. H. Ko, "Analysis of the Influence Factors of Data Loading Performance Using Apache Sqoop," KIPS Transactions on Software and Data Engineering, vol. 4, no. 2, pp. 77-82, 2015. DOI: 10.3745/KTSDE.2015.4.2.77.

[ACM Style]
Liu Chen and Jung Hyun Ko. 2015. Analysis of the Influence Factors of Data Loading Performance Using Apache Sqoop. KIPS Transactions on Software and Data Engineering, 4, 2, (2015), 77-82. DOI: 10.3745/KTSDE.2015.4.2.77.