Analysis of Query Optimization Components in Distributed Database

Objectives: This paper brings to light different query optimization components and their optimizing functionalities which are helpful to improve the response time of query and the efficiency of distributed database. A cache based optimization is also analyzed to highlight the query optimization process. Methods: As data is the most valuable asset for any organization due to this they want to get access and use it efficiently and in a timely manner. To evaluate the efficiency of query optimization its different components e.g. search space, search strategy and cost model are evaluated with the help of examples, tables and diagrams. By comparing the different results, a cache based optimization technique is also evaluated. Findings: It is observed that in search space generated plans are equivalent in the sense they provide same results but their operation, implementation and performance is different. Different algorithms of search strategy are also examined to get the quicker and accurate results and notice that movement of search strategy is greatly depend upon join ordering and cost model. It is also observed that the cost model is helpful to select the best query execution plan but it depends upon the different parameters for example queue length, sever distance, server capacity and load. The latest cache based query optimization technique is also examined and noted that it is key to improve the response time of query as its computational cost is very low. It will be more helpful if it is placed at each site. Applications and Future Improvements: Currently cache based query optimization is applicable only for homogeneous distributed databases. In future this technique can also be implemented for heterogeneous type of databases.