At present, data generated by high-energy physical devices has reached the PB or EB level as it is constantly updated and running. Therefore, the technical requirements for physical analysis are constantly increasing with the mass of physical events generated by high-energy physical colliders. The physical analysis for high-energy physics events refers to the selection of thousands of meaningful events from massive physical events. The analysis process relies on different attribute parameters and different operators to obtain the final selection criteria. Because the traditional method of high-energy physics events analysis is less efficient and more complex, it is very important to design an efficient and convenient operator library for high-energy physics events processing. This paper proposes a new operator library system based on hbase coprocessor for high-energy physics events processing. It uses storage structure and endpoint coprocessor of the hbase as the framework of the physical analysis operator library, uses protocol buffer to customize the client and server RPC communication and encapsulates the operators in the object-oriented data analysis framework ROOT to hbase coprocessor. In this way, the complexity of the high-energy physics events analysis is reduced and the efficiency of the calculation is improved. In the experiment, we take the zc3900 analysis process as an example and apply it to the 10 nodes experimental cluster. The test results show that the proposed system is more efficient and avoids the complexity of the events processing.
[1]
李强,et al.
High Energy Physics Data Processing System with Parallel Heterogeneous Clusters
,
2015
.
[2]
陈刚,et al.
Design and Optimization of Storage System in HEP Computing Environment
,
2015
.
[3]
李强,et al.
HBase-based Storage and Analysis Platform for High Energy Physics Data
,
2015
.
[4]
F. Rademakers,et al.
ROOT — An object oriented data analysis framework
,
1997
.
[5]
Lorenzo Moneta,et al.
ROOT - A C++ framework for petabyte data storage, statistical analysis and visualization
,
2009,
Comput. Phys. Commun..
[6]
Ataur Rahman Belal,et al.
Data Analysis Framework
,
2016
.
[7]
Chen Gang,et al.
Design and Performance Optimization of Metadata Server in Mass Storage System
,
2012
.
[8]
Eleni Stroulia,et al.
Enhancing Query Support in HBase via an Extended Coprocessors Framework
,
2011,
ServiceWave.