Department of Computer Science and Information Systems

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Author: search.filters.author.Sharma, YashvardhanEnd date: 2009

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    New Approach to overcome the complexity issues raised by Simple Bitmap Indexing
    (Springer, 2006) Goyal, Navneet; Sharma, Yashvardhan
    Recently Data Warehouse System is becoming more and more important for decision makers. Most of the queries against a large Data Warehouse are complex and iterative. The ability to answer these queries efficiently is a critical issue in the Data Warehouse environment. If right Index Structures are built on the columns, performance of the queries, especially ad-hoc queries will be greatly enhanced. In this paper, we have concentrated on various implementation issues of Simple Bitmap Indexing and their analysis.
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    Improved Bitmap Indexing Strategy for Data Warehouses
    (IEEE, 2006) Sharma, Yashvardhan; Goyal, Navneet
    Improving the query performance is critical in data warehousing and decision support systems. A lot of methods have been proposed by various researches. Indexing the data warehouse is a common but effective technique. Bitmap indices play a very important role in improving query performance in data warehousing and decision support systems. In this paper we present a new bitmap indexing strategy that can be applied to any existing bitmap compression schemes that are based on run length encoding. The new strategy, in most cases, requires less space and provides performance gains as well. The new strategy is tested on two commonly used bitmap compression schemes namely, word-aligned hybrid (WAH) and byte-aligned bitmap code (BBC) and results are presented graphically. The proposed strategy simply sorts the field on which a bitmap is to be created. Sorting of the field ensures long runs of ones and zeros. These long runs of ones and zeros are desirable for any compression scheme that is based on run length encoding and its variants. The space required to store the bitmap indexes goes down dramatically. The effect of sorting on query response time is studied for equality and range queries and it is found that there is a considerable decrease in the response time of queries. The overheads associated with the proposed strategy are sorting a table on a particular field and maintaining a sorted table. These extra tasks could be easily performed during the ETL process or when the data warehouse is offline. The new strategy concentrates on reducing space requirement for the bitmap index and the response time of queries and achieves both objectives without incurring any processing overheads when the data warehouse is online.
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    An Efficient Multi-Component Indexing Embedded Bitmap Compression for Data Reorganization
    (Asian Network for Scientific Information Publications, 2008) Goyal, Navneet; Sharma, Yashvardhan
    In the present study, we discuss bitmap indices with compression using multi-component indexing for the efficient storage and fast retrieval of large scientific data. The bitmap compression indices embedded multi-component shows superiority over bitmap compressed indices. Gray Code ordering algorithm is used which runs in linear time in the order of the size of the database. Reduction in the number of columns is observed when multi-component indexing is applied on the binned data. An improvement in the space requirement for Bitmap Index by 25% is observed when one time component indexing is applied. Satisfactory improvement factor is observed when gray code ordering and WAH compression technique is used. Due to processing overhead, two component indexes is used. Tuple reordering problem is studied to reorganize database tuples for optimal compression rates. The experimental results on real data sets show that the compression ratio shows the improvement by a factor of 2 to 8.
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    New binning strategy for bitmap indices on high cardinality attributes
    (ACM Digital Library, 2009-01) Goyal, Navneet; Sharma, Yashvardhan
    Bitmap indices are the preferred indexing structures for read only & high dimensional data in data warehouses and scientific databases. High cardinality attributes pose a new challenge in terms of having space efficient bitmap indices. Binning is a common technique for reducing space requirements of bitmap indices. It is found that binning has an adverse affect on the query performance. A new efficient binning strategy is proposed for bitmap indices for high cardinality attributes. Exact bins are created based on query distribution. Exact bins are allowed to overlap. This gives a considerable performance advantage over the conventional non-overlapping bins at the expense of marginal increase in space overheads. Overlapping bins minimize the number of candidate-checks that need to be performed for a given set of queries. Algorithms are also presented for performing candidate checks more efficiently. Experimental results are presented in support of the new binning strategy.