BESIU physical analysis on Hadoop platform

1Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

In the past 20 years, computing cluster has been widely used for High Energy Physics data processing. The jobs running on the traditional cluster with a Data-to-Computing structure, have to read large volumes of data via the network to the computing nodes for analysis, thereby making the I/O latency become a bottleneck of the whole system. The new distributed computing technology based on the MapReduce programming model has many advantages, such as high concurrency, high scalability and high fault tolerance, and it can benefit us in dealing with Big Data. This paper brings the idea of using MapReduce model to do BESIII physical analysis, and presents a new data analysis system structure based on Hadoop platform, which not only greatly improve the efficiency of data analysis, but also reduces the cost of system building. Moreover, this paper establishes an event pre-selection system based on the event level metadata(TAGs) database to optimize the data analyzing procedure.

Cite

CITATION STYLE

APA

Huo, J., Zang, D., Lei, X., Li, Q., & Sun, G. (2014). BESIU physical analysis on Hadoop platform. In Journal of Physics: Conference Series (Vol. 513). Institute of Physics Publishing. https://doi.org/10.1088/1742-6596/513/3/032044

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free