Data Replication Using Data Mining Techniques

Database Replication is the successive electronic duplicating of information from a database in one PC or server to a database in another with the goal that all clients share a similar dimension of data. The outcome is a conveyed database in which clients can get to information significant to their assignments without meddling with crafted by others. Anyway information replication is an entrancing theme for both hypothesis and practice. On the hypothetical side, numerous solid outcomes requirement what should be possible as far as consistency: e.g., the difficulty of achieving agreement in offbeat frameworks the blocking idea of CAP hypothesis, and the requirement for picking an appropriate rightness foundation among the numerous conceivable. On the pragmatic side, information replication assumes a key job in a wide scope of settings like storing, back-up, high accessibility, wide territory content dissemination, expanding versatility, parallel preparing, and so forth. Finding a replication arrangement that is reasonable in whatever number such settings as could reasonably be expected remains an open test.

Evaluation of Replication Mechanisms on Selected Database Systems

This paper is focused on comparing database replication over spatial data in PostgreSQL and MySQL. Database replication means solving various problems with overloading a single database server with writing and reading queries. There are many replication mechanisms that are able to handle data differently. Criteria for objective comparisons were set for testing and determining the bottleneck of the replication process. The tests were done over the real national vector spatial datasets, namely, ArcCR500, Data200, Natural Earth and Estimated Pedologic-Ecological Unit. HWMonitor Pro was used to monitor the PostgreSQL database, network and system load. Monyog was used to monitor the MySQL activity (data and SQL queries) in real-time. Both database servers were run on computers with the Microsoft Windows operating system. The results from the provided tests of both replication mechanisms led to a better understanding of these mechanisms and allowed informed decisions for future deployment. Graphs and tables include the statistical data and describe the replication mechanisms in specific situations. PostgreSQL with the Slony extension with asynchronous replication synchronized a batch of changes with a high transfer speed and high server load. MySQL with synchronous replication synchronized every change record with low impact on server performance and network bandwidth.

A Case Study of Snapshot Replication and Transfer of Data in Distributed Databases

The database replication refers to distributing a database among multiple locations. There are three kinds of database replication system: snapshot, transactional and merge. The snapshot replication refers to the fragment of database items and distributing them to multi databases at once. An important goal in this paper is to experiment with a distributed database study the snapshot replication and examine the issues associated with it. In this work, the data from another database is used to increase availability and flexibility as well as provide the information exchange between databases. In this process, the data is infrequently updated at specified periods by copying and changing the data from the original database towards the subscriber database. The work of agents in this technology will do the most of the work to achieve the stated goal. The experimental results show that at both vertical and horizontal fragmentation, the proposed approach of replicating distributed database is efficient and the performance is significantly improved in terms of data transfer time, load sharing and update of database fragmentation. Hence the snapshot replication system is much schedulable and protective replication in business markets. http://dx.doi.org/10.25130/tjps.23.2018.177