Đang chuẩn bị nút TẢI XUỐNG, xin hãy chờ
Tải xuống
Tham khảo tài liệu 'advances in database technology- p14', công nghệ thông tin, cơ sở dữ liệu phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 632 N. Karayannidis T. Sellis and Y. Kouvaras Table 2. Data set configuration for the three series of experiments DLM SCALE QUERY Dimensions Varying 5 5 Tuples 100 000 Varying 1 142 527 Facts 1 1 1 Maximum chunking depth Depends on longest hierarchy 8 8 Bucket size bytes 8 192 8 192 8 192 UB-tree page size bytes 8 192 8 192 8 192 Bucket filling rate 80 80 80 UB-trcc leaf filling rate 80 80 80 Fig. 7. Impact of cube dimensionality increase to the CUBE File size We used synthetic data sets that were produced with an OLAP data generator that we have developed. Our aim was to create data sets with a realistic number of dimensions and hierarchy levels. In Table 1 we present the hierarchy configuration for each dimension used in the experimental data sets. The shortest hierarchy consists of 2 levels while the longest consists of 10 levels. We tried each data set to consist of a good mixture of hierarchy lengths. Table 2 shows the data set configuration for each series of experiments. In order to evaluate the adaptation to sparse data spaces we created cubes that were very sparse. Therefore the number of input tuples was kept from a small to a moderate level. To simulate the cube data distribution for each cube we created ten hyper-rectangular regions as data point containers. These regions are defined randomly at the most detailed level of the cube and not by combination of hierarchy values although this would be more realistic in order not to favor the CUBE File particularly due to the hierarchical chunking. We then filled each region with data points uniformly spread and tried to maintain the same number of data points in each region. Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark CUBE File A File Structure for Hierarchically Clustered OLAP Cubes 633 Fig. 8. Size ratio between the UB-tree and the CUBE File for increasing dimensionality Fig. 9. Size scalability in the number of input tuples i.e. stored data points 4.2 Structure Experiments .
