Diagnosing Performance Issues in Microservices with Heterogeneous Data Source

Author(s):  
Chuanjia Hou ◽  
Tong Jia ◽  
Yifan Wu ◽  
Ying Li ◽  
Jing Han
2014 ◽  
Vol 543-547 ◽  
pp. 2937-2940
Author(s):  
Xiao Xiao Liang ◽  
Shun Min Wang ◽  
Chong Gang Wei ◽  
Chuang Shen

According to the distribution, autonomy and heterogeneity of the university database, we designed the structure, main arithmetic, query distribution device, result processor and wrapper of the university heterogeneous data integration middle ware by using Java, XML and middle ware. We emphasized on introducing the designation of query distribution device, result processor and wrapper.


2009 ◽  
Vol 4 (8) ◽  
Author(s):  
Jinpeng Wang ◽  
Jianjiang Lu ◽  
Yafei Zhang ◽  
Zhuang Miao ◽  
Bo Zhou

2021 ◽  
Vol 10 (8) ◽  
pp. 528
Author(s):  
Raphael Witt ◽  
Lukas Loos ◽  
Alexander Zipf

OpenStreetMap (OSM) is a global mapping project which generates free geographical information through a community of volunteers. OSM is used in a variety of applications and for research purposes. However, it is also possible to import external data sets to OpenStreetMap. The opinions about these data imports are divergent among researchers and contributors, and the subject is constantly discussed. The question of whether importing data, especially large quantities, is adding value to OSM or compromising the progress of the project needs to be investigated more deeply. For this study, OSM’s historical data were used to compute metrics about the developments of the contributors and OSM data during large data imports which were for the Netherlands and India. Additionally, one time period per study area during which there was no large data import was investigated to compare results. For making statements about the impacts of large data imports in OSM, the metrics were analysed using different techniques (cross-correlation and changepoint detection). It was found that the contributor activity increased during large data imports. Additionally, contributors who were already active before a large import were more likely to contribute to OSM after said import than contributors who made their first contributions during the large data import. The results show the difficulty of interpreting a heterogeneous data source, such as OSM, and the complexity of the project. Limitations and challenges which were encountered are explained, and future directions for continuing in this field of research are given.


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