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In the above process, if the page containing the requested record is already in the memory, retrieval from the disk is not necessary. In such a situation, time taken for the whole operation will be less. Thus, if the records which are frequently used together, more records will be in the same page. Hence the number of pages to be retrieved will be less and this reduces the number of disk accesses which in turn gives a better performance. This method of storing logically related records, physically together is called clustering. For example, consider CUSTOMER table as shown below. Cust ID Cust Name Cust City…. 10001 Raj Delhi …. 10002 …. …. …. 10003 …. …. …. 10004 …. …. …. …. …. …. …. …. …. …. …. If queries retrieving Customers with consecutive Cust_IDs frequently occur in the application, clustering based on Cust_ID will help improving the performance of these queries. This can be explained as follows. Assume that he customer record size is 128 bytes and the typical size of a page retrieved by the File Manager is 1 kb (1024 bytes). If there is no clustering, it can be assumed that the customer records are stored at random physical locations. In the worst-case scenario, each record may be placed in a different page. Hence a query to retrieve 100 records with consecutive Cust_IDs (say 10001 to 10100), will require 100 pages to be accessed which in turn translates to 100 disc accesses. But, if the records are clustered, a page can contain 8 records. Hence the number of pages to be accessed for retrieving the 100 consecutive records will be ceil (100/8) =13. i.e., only 13 disk accesses will be require to obtain the query results. Thus, in the given example, clustering improves the speed by a factor of 7.7. * Intra-file Clustering - Clustered records belong to the same file (table) as in the above example. * Inter-file Clustering - Clustered records belong to different files (tables). This type of clustering may be required to enhance the speed of queries retrieving related records from more than one table. Here interleaving of records is used.
What else can I help you with?
Is Excel a database file?
No. Excel is a spreadsheet package, not a file. You can use some basic database functions within Excel and you can also use Excel to store database information. However, in this respect, Excel is better for databases that are essentially flat files - Excel is not best suited for complex database structures.
What are the features of deductive databases?
There are two primary variations of deductive database systems: expert database systems and knowledge-based database systems. Deductive databases differ from these two types of databases in one major respect: In the case of expert or knowledge-based databases, the data needs to be present in the primary memory of the computer. However, in a deductive database, this restriction is not present. The data can be in primary or secondary memory.
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