An OLAP Tool Based on the Bitmap Join Index
نویسندگان
چکیده
Data warehouse and OLAP are core aspects of business intelligence environments, since the former store integrated and time-variant data, while the latter enables multidimensional queries, visualization and analysis. The bitmap join index has been recognized as an efficient mechanism to speed up queries over data warehouses. However, existing OLAP tools does not use strictly this index to improve the performance of query processing. In this paper, we introduce the BJIn OLAP tool to efficiently perform OLAP queries over data warehouses, such as roll-up, drill-down, slice-and-dice and pivoting, by employing the bitmap join index. The BJIn OLAP tool was validated through a performance evaluation to assess its efficiency and to corroborate the feasibility of adopting the bitmap join index to execute OLAP queries. The performance results reported that our BJIn OLAP tool provided a performance gain that ranged from 31% up to 97% if compared to existing solutions.
منابع مشابه
Querying data warehouses efficiently using the Bitmap Join Index OLAP Tool
Data warehouse and OLAP are core aspects of business intelligence environments, since the former store integrated and time-variant data, while the latter enables multidimensional queries, visualization and analysis. The bitmap join index has been recognized as an efficient mechanism to speed up queries over data warehouses. However, existing OLAP tools does not use strictly this index to improv...
متن کاملA Data Mining Approach for selecting Bitmap Join Indices
Index selection is one of the most important decisions to take in the physical design of relational data warehouses. Indices reduce significantly the cost of processing complex OLAP queries, but require storage cost and induce maintenance overhead. Two main types of indices are available: mono-attribute indices (e.g., B-tree, bitmap, hash, etc.) and multi-attribute indices (join indices, bitmap...
متن کاملParallel Star Join + DataIndexes : EÆcient Query Processing in Data Warehouses and OLAP
On-Line Analytical Processing (OLAP) refers to the technologies that allow users to eÆciently retrieve data from the data warehouse for decision-support purposes. Data warehouses tend to be extremely large it is quite possible for a data warehouse to be hundreds of gigabytes to terabytes in size [3]. Queries tend to be complex and ad-hoc, often requiring computationally expensive operations suc...
متن کاملParallel Star Join + DataIndexes: Efficient Query Processing in Data Warehouses and OLAP
On-Line Analytical Processing (OLAP) refers to the technologies that allow users to efficiently retrieve data from the data warehouse for decision-support purposes. Data warehouses tend to be extremely large—it is quite possible for a data warehouse to be hundreds of gigabytes to terabytes in size [3]. Queries tend to be complex and ad hoc, often requiring computationally expensive operations s...
متن کاملFastBit: An Efficient Indexing Technology For Accelerating Data-Intensive Science
FastBit is a software tool for searching large read-only datasets. It organizes user data in a column-oriented structure which is efficient for on-line analytical processing (OLAP), and utilizes compressed bitmap indices to further speed up query processing. Analyses have proven the compressed bitmap index used in FastBit to be theoretically optimal for onedimensional queries. Compared with oth...
متن کامل