| Popis: |
Software driven solutions are limited to the amount of memory size and storage capacity, but the sizes of databases are increasing every day. Hence, now a day, handling data and accessing it in an acceptable time is one of the biggest challenges especially in a large database system. In a database, the records can be categorized according to the access frequencies; some records are very frequently accessed (hot data), some records are hardly accessed (cold data) and other records accessed occasionally (warm data). In a conventional database we keep all hot, warm and cold records in a single database. In case of record access (query, update etc.) a query might takes longer time even if a good data accessing algorithm (clustering/mining) incorporate with the database. Thus categorizing of the data set, i. e. clustering in terms of access frequency may improve data accessibility. In this paper, we are proposing a data clustering mechanism based on data access frequency. Finally, the expected result shows how and why data accessibility time should outperform other available data clustering techniques. |
