Yet Another Algorithms for Selecting Bitmap Join Indexes

One of the fundamental tasks that data warehouse (DW) administrator needs to perform during the physical design is to select the right indexes to speed up her/his queries. Two categories of indexes are available and supported by the main DBMS vendors: (i) indexes defined on a single table and (ii) indexes defined on multiple tables such as join indexes, bitmap join indexes, etc. Selecting relevant indexes for a given workload is a NP-hard problem. A majority of studies on index selection problem was focused on single table indexes, where several types of algorithms were proposed: greedy search, genetic, linear programming, etc. Parallel to these research efforts, commercial DBMS gave the same attention to single table indexes, where automated tools and advisors generating recommended indexes for a particular workload and constraints are developed. Unfortunately, only few studies dealing with the problem of selecting bitmap join indexes are carried out. Due to the high complexity of this problem, these studies mainly focused on proposing pruning solutions of the search space by the means of data mining techniques. The lack of bitmap join index selection algorithms motivates our proposal. This paper proposes selection strategies for single and multiple attributes BJI. Intensive experiments are conducted comparing the proposed strategies using mathematical cost model and the obtained results are validated under Oracle using APB1 benchmark.