Online Index Recommendations for High Dimensional Databases Using Query Workloads projects
main idea is to provide solution for problems caused from using lower dimensional indexes using a parametreizable method for specified indexes based on index types which are mainly used in high dimensional data sets and to use a dynamic method for auto changing of indexes as work load changes. In general users use small set of attributes for searching data at a time. In order to accurately represent access patters it is better to use low dimensional indexes. The problem with this query process is when query patterns changes performance of database changes because in physical database design workload will decrease.
Existing System:
- In existing system performance of query response is slow if there is any pattern change.
- This problem arise because of using static query workload.
- Performance of the system depends on the size of database.
- There is no data pruning capability available in this system.
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