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[...]... 480–488 structure, 478–479 result parallelism for the decision tree, 492–495 High-Performance Parallel Database Processing and Grid Databases, by David Taniar, Clement Leung, Wenny Rahayu, and Sushant Goel Copyright  2008 John Wiley & Sons, Inc 541 542 INDEX Classification, parallel (Continued) splitting attributes or feature selection, 481–484 Cluster/Clustering, parallel, 464–499 architectures, 23... clustering, parallel, 81–82, 471–477 algorithm, 468–471 data parallelism parallel k-means, 472–475 Leaf nodes, 189–190 Left-deep tree parallelization, 258 Linear scale up, 8 Linear search, 69 Linear speed up objective, parallel query processing, 7 Literals, 441 Load cost parallel binary-merge sort, 100 parallel merge-all sort, 99 parallel partitioned sort, 104 parallel redistribution binary-merge sort, 102 parallel. .. costs, 38–39 data parameters, 34–35 query parameters, 37 systems parameters, 36 time unit costs, 37–38 parallel database, operations in, See Databases, parallel skew model, 39–43 Architectures, grid database, 26–28 data-intensive applications working in, 26 grid middleware, 27 Architectures, parallel database, 19–26 interconnection networks, 24–26 shared-disk architectures, 20–21 shared-memory architectures,... 200–203 Case 1 (NRI-1 and NRI-3), 201 Case 2 (NRI-2), 201 Case 3 (PRI), 201 Case 4 (FRI), 201–203 Online analytic processing (OLAP) and business intelligence, 9, 401–426 cube queries, parallelization of, 412–417 cume dist queries, parallelization, 419–420 histogram queries, parallelization, 420–422 moving average queries, parallelization, 422–424 NTILE queries, parallelization, 420–422 parallel multidimensional... 440–450, See also Association rule mining 548 INDEX Parallel universal qualification, See Collection join queries Parallelism forms of, 12–19 independent parallelism, 15 interoperation parallelism, 12, 15–18 interquery parallelism, 12, 13–14 intraoperation parallelism, 12, 15, 16 intraquery parallelism, 12, 14–15 mixed parallelism, 18–19 pipeline parallelism, 15–18 Partial CUBE queries, analysis of,... analysis, 402–405 parallelization without using ROLLUP, 412 ranking queries, parallelization of, 418–419 rollup queries, parallelization, 405–412 top-N queries, parallelization of, 418–419 windowing queries, parallelization of, 422–424 Open Grid Service Architecture (OGSA), 27 Optimistic algorithms, 309 Optimistic Plan Correction (OPC), 278 Originator’s algorithm for Grid- ACP, 345 Page, 34 Parallel association... notations, parallel GroupBy-Join, 151–153 join selectivity, 153 projectivity, 152 selectivity, 152 parallel binary-merge sort, 100–101 parallel groupby, 104–108 parallel merge-all sort, 98–100 parallel partitioned sort, 103–104 parallel redistribution binary-merge sort, 101–102 parallel redistribution merge-all sort, 102–103 serial external merge-sort, 96–97 543 Count distribution-based parallelism... notation, parallel GroupBy-Join, 152 Projectivity ratio, 37 Query processing, parallel, 5–6 motivations, 5–6 objectives, 7–12 communication, 11–12 interference, 11–12 parallel obstacles, 10–12 scale up, 8–10 skew, 12 speed up, 7–8 parameters, 37 results generation cost, 45 Query scheduling and optimization, 256–287 cluster query processing model, 270–275 degree of parallelization, 258 bushy-tree parallelization,... traversal, 192–194 parallel exact-match search queries, 192–194 parallel range selection query, 194–195 processor involvement, 192–193 record loading, 192, 194 Select cost, 45, 70, 72 disjoint partitioning, 129 divide and broadcast, 128 local join, 130 parallel binary-merge sort, 100 parallel merge-all sort, 98–99 parallel partitioned sort, 104 parallel redistribution binary-merge sort, 102 parallel redistribution... mining, 431 data parallelism, 437–438 data warehouse, 429 data-intensive applications, 428 definition, 430 from databases to data warehousing to data mining, 428–431 parallel association rules, 440–450 parallel sequential patterns, 450–461 parallelism, 436–440 querying vs mining, 433–436 read-only queries, 429 result parallelism, 438–440 sequential patterns, 427–463 write queries, 429 Data parallelism, . and Parallel Databases, 19(1):29–62, 2006. Dehne, F., Eavis, T., Hambrusch, S.E., and Rau-Chaplin, A., “Parallelizing the Data Cube”, Distributed and Parallel. Conference on Parallel Processing Workshops (ICPPW), pp. 383–390, 2002. CHAPTERS 16 AND 17: PARALLEL AND GRID DATA MINING Brezany, P., Kloner, C., and Tjoa,