Design and Analysis of Optimization and Tuning in Data Warehouses Using Bitmap Indexes

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Author(s): Pankaj Dadheech*, Dinesh Goyal, Ankit Kumar, Amit Kumar Gupta

Journal Name: Recent Advances in Computer Science and Communications
Formerly Recent Patents on Computer Science


Article ID: e140921185590
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Abstract:

Introduction: An Index for Bitmaps is a special category that uses bitmaps or bit arrays in a database. Apache stores a bitmap for every index key in a bitmap file. Each main index stores multi-line pointers. Bitmap database management requires several time, but bitmap indexes are only appropriate for tables or tables that have occasionally updates.

Method: Each bit of the map corresponds to a possible row id. If the bit is 1, it means that the row id contains this key value. An internal Oracle function converts the bit position to the corresponding row id, so that bitmap indexes offer the same functionality as B-tree indexes, despite the different internal representation. If the number of different values of the index is small, then the bitmap index will become very efficient in terms of the use of physical space.

Result: Oracle involves the following compression features which are possible during the various operations in the database. This means we can compress the data on the following modes. There are several types of backup is possible in the database: • Whole Backup or partial backup • Full Backup or incremental backup • Cold or consistent backup • Hot or inconsistent backup

Discussion: We study the current compression technologies, and add the compression of the bitmap index via the data pump. The bitmap index is more effective, for a minimum unique value, according to conventional wisdom. But it doesn't need either a bitmap index built on a high degree of cardinality or a low degree of cardinality through the data pump. In this paper, after deletion of documents, we propose data pump utility for releasing disk space in database. Bitmap index points the old location even after the table deletes information, this function does not release disk space.

Conclusion: In this paper, we present the experiment evaluation of Bitmap Index Compression and release occupied disk space of database objects like table and indexes after deletion of records. Industrial database frequently allows the bulk data insertion and deletion. In database deletion of millions records from the table doesn't release occupied disk space immediately. Next steps in our research will be to release the disk space along with the deletion of records.

Keywords: Bitmap Index, compression techniques, data mining, data pump, query optimization, query performance

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Article Details

Article ID: e140921185590
(E-pub Ahead of Print)
DOI: 10.2174/2666255813999200904171105
Price: $95

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