Using semantic knowledge for transaction processing in a distributed database

1983 ◽  
Vol 8 (2) ◽  
pp. 186-213 ◽  
Author(s):  
Hector Garcia-Molina
Keyword(s):  
Distributed Database ◽  
Transaction Processing ◽  
Semantic Knowledge

scholarly journals A Heterogeneous Distributed Computing Model Based on Web Service

CONVERTER ◽  
2021 ◽  
pp. 100-106
Author(s):  
Haitao Li
Keyword(s):  
Distributed Computing ◽  
Web Service ◽  
Distributed Database ◽  
Transaction Processing ◽  
Database System ◽  
Heterogeneous Database ◽  
Two Phase ◽  
Cross Platform ◽  
Heterogeneous Distributed Computing ◽  
Distributed Database System

Based on the in-depth study of the existing database synchronization model, in order to improve the cross platform ability of the system and facilitate the construction of small and medium-sized enterprise information platform, this paper proposes a heterogeneous distributed computing scheme based on Web service. The scheme uses JMS to realize the message transmission between systems, and uses web service technology to realize cross platform data reading and writing. In the aspect of distributed transaction processing, the two-phase commit protocol is improved to reduce the probability of system deadlock and effectively ensure the consistency of distributed database data. In order to improve the performance of distributed database system, cache technology is introduced, and the way of integrating cache and database transaction processing is proposed, which effectively ensures the validity of cache data. The architecture is oriented to program developers, who can develop efficient and convenient distributed database system on the basis of this architecture. Finally, this architecture is applied to the background management system of mobile express service. The running results show that the architecture can well meet the business requirements of distributed heterogeneous database system synchronization.

scholarly journals Prediction of Mineralization Prospects Based on Geological Semantic Model and Mobile Computer Machine Learning

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Zhengzhen An ◽  
Yue Zhao ◽  
Yanfei Zhang ◽  
Xuguang Li
Keyword(s):  
Random Forest ◽  
Mobile Computing ◽  
Association Rules ◽  
Distributed Database ◽  
Semantic Knowledge ◽  
Human Society ◽  
Semantic Model ◽  
Semantic Retrieval ◽  
Random Forest Algorithm ◽  
Mobile Computer

Mineral resources are indispensable in the development of human society and are the foundation of national economic development. As the prospecting target shifts from outcrop ore to concealed ore, from shallow to deep, the difficulty of prospecting becomes more and more difficult. Therefore, the prediction of mineralization prospects is of great significance. This paper is aimed at completing the prediction of mineralization prospects by constructing geological semantic models and using mobile computer learning to improve the accuracy of prediction of mineralization prospects and expanding the application of semantic mobile computing. We use five different semantic relations to build a semantic knowledge library, realize semantic retrieval, complete information extraction of geological text data, and study mineral profiles. Through the distributed database of mobile computing, the association rules and random forest algorithm are used to describe the characteristics of minerals and the ore-controlling elements, find the association rules, and finally combine the geological and mineral data of the area and use the random forest algorithm to realize the prospect of mineralization district forecast. The geological semantic model constructed in the article uses the knowledge library for associative search to achieve an accuracy rate of 87.9% and a recall rate of 96.5%. The retrieval effect is much higher than that of traditional keyword retrieval methods. The maximum value of the posterior result of the mineralization prospect is 0.9027, the average value is 0.0421, and the standard deviation is 0.1069. The picture is brighter, and the probability of mineralization is higher.

scholarly journals Research and implementation of HTAP for distributed database

2021 ◽  
Vol 39 (2) ◽  
pp. 430-438
Author(s):  
Changhong Jing ◽  
Wenjie Liu ◽  
Jintao Gao ◽  
Ouya Pei
Keyword(s):  
Data Analysis ◽  
Relational Databases ◽  
Distributed Databases ◽  
Distributed Database ◽  
Transaction Processing ◽  
Complex Data ◽  
Main Application ◽  
On Line ◽  
Analytical Processing ◽  
Implementation Method

Data processing can be roughly divided into two categories, online transaction processing OLTP(on-line transaction processing) and online analytical processing OLAP(on-line analytical processing). OLTP is the main application of traditional relational databases, and it is some basic daily transaction processing, such as bank pipeline transactions and so on. OLAP is the main application of the data warehouse system, it supports some more complex data analysis operations, focuses on decision support, and provides popular and intuitive analysis results. As the amount of data processed by enterprises continues to increase, distributed databases have gradually replaced stand-alone databases and become the mainstream of applications. However, the current business supported by distributed databases is mainly based on OLTP applications, lacking OLAP implementation. This paper proposes an implementation method of HTAP for distributed database CBase, which provides an implementation method of OLAP analysis for CBase, and can easily deal with data analysis of large amounts of data.

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