collecting highly parallel data

Ngày tải lên: 20/02/2014, 04:20

... others. Such simultaneous input/output of several-bit data is referred to as parallel data input/output and the peripheral functions for parallel data input/output are called "I/O ports", ... Chapter 8 Parallel Data Input/Output Although the programs described in Chapter 6 use the memory and CPU registers only, this chapter explains how to input and output parallel data. Among ... ports", which have registers and pins as shown in Figure 8.1. Figure 8.1: Parallel Data Input/Output Parallel data input/output using I/O ports are performed through registers as shown...

Ngày tải lên: 29/09/2013, 11:20

... Introduction Pipeline Parallelism Intraoperation Parallelism (Parallel join) Intraoperation Parallelism (Parallel join) Intraoperation Parallelism (Parallel join) Join 1 Table 1 Mixed Parallelism Table ... From Databases To Data Warehousing To Data Mining: A Journey 428 16.2. Data Mining: A Brief Overview 431 16.2.1. Data Mining Tasks 431 16.2.2. Querying vs. Mining 433 16.2.3. Parallelism in Data ... 10 1.4. Forms of Parallelism 12 1.4.1. Interquery Parallelism 13 1.4.2. Intraquery Parallelism 14 1.4.3. Intraoperation Parallelism 15 1.4.4. Interoperation Parallelism 15 1.4.5. Mixed Parallelism—A...

Ngày tải lên: 21/01/2014, 18:20

... the data is distributed evenly. Since the aim of parallel processing, especially parallel database processing, is to achieve load balance in order to reduce the elapsed time of a job, then this data ... local searching method for parallel search algorithms. It can be deduced from the local searching method above that parallelism in the search algorithm is based on data parallelism, whereby parallelism is ... Describe the relationship between parallel databases and Grid databases. 1.10. Investigate your favourite Database Management Systems (DBMS) and outline what kind of parallelism features have been...

Ngày tải lên: 21/01/2014, 18:20

... work: a. Parallel merge-all sort b. Parallel binary-merge sort c. Parallel redistribution binary-merge sort d. Parallel redistribution merge-all sort e. Parallel partitioned sort 4.4. Given a data ... present various parallel sorting techniques, whereas Iyer and Dias (ICDE 1990) and DeWitt et al. (1992) discuss systems issues in parallel database sorting. Parallel sorting for databases uses ... of parallel external sort by basically considering the two factors mentioned above. 4.3 ALGORITHMS FOR PARALLEL EXTERNAL SORT In this section, five parallel external sort methods for parallel database...

Ngày tải lên: 21/01/2014, 18:20

... Chapter 6 Parallel GroupBy-Join Cost Models for Phase One (Data Partitioning and Broadcasting Phase) The cost components in the first phase (data partitioning phase) consist of scan cost, select data ... select data cost, finding destination cost, and data transfer cost. These are presented in more detail as follows. ž Scan cost is the cost of loading data from local disk in each processor. Since data ... structure is quite common in parallel database systems, since parallel searching on the table partitioning attribute can use the information on table partitioning, whereas parallel searching on the...

Ngày tải lên: 21/01/2014, 18:20

... the disjoint data partition- ing first, followed by the three parallel algorithms for collection-equi join queries. 8.4.1 Disjoint Data Partitioning The data partitioning method for parallel collection-equi ... in paralleliza- tion of these search queries are examined. These are then followed by a complete parallel algorithm. Parallel Exact-Match Search Queries There are three important factors in parallel ... are studied, particularly: ž Parallel collection-equi join algorithms, ž Parallel collection-intersect join algorithms, and ž Parallel subcollection join algorithms Parallel join algorithms are...

Ngày tải lên: 21/01/2014, 18:20

... using the parallel sort-merge nested-loop algorithm. 8.6. Discuss why parallel collection-equi join uses a disjoint data partitioning, whereas the other two parallel collection joins (i.e., parallel ... difference is that the data partitioning used in parallel collection-intersect join algorithms is non-disjoint data partitioning, not disjoint data partitioning. 8.5.1 Non-Disjoint Data Partitioning Unlike ... scheduling is for incor- porating parallelism scheduling into the query access plans. Parallelization models High-Performance Parallel Database Processing and Grid Databases, by David Taniar, Clement...

Ngày tải lên: 21/01/2014, 18:20

... distributed databases and parallel databases. 10.2. Outline the main differences between distributed databases and multidatabase systems. 10.3. Discuss the suitability of parallel databases, distributed ... offered by distributed database systems are transparent data access of physically distributed data, replicating the data at local sites for efficient access, and fast processing of data by divide-and-conquer ... data resources. Advanced scientific and business applications are data intensive. These applica- tions are collaborative in nature, and data is collected at geographically distributed sites. Databases...

Ngày tải lên: 21/01/2014, 18:20

... implement traditional ACPs in Grid environment. Grid databases will access data from globally separated data sites via WWW. Most of the distributed data architecture uses distributed objects for communication, for ... synchronous distributed database sys- tems cannot be implemented in Grid databases because of architectural lim- itations (Grid databases are heterogeneous and asynchronous). (2) Multidatabase systems, ... and multi- database), and the recovery model for DBMS without global information (Grid database). Figure 12.8 shows the recovery model for an individual database site. The stable database storage...

Ngày tải lên: 21/01/2014, 18:20

... an operational database keeps data of current value. Figure 16.2 shows the transfor- mation of data from operational data in a database into data warehousing data. The process involves data extraction, ... to apply parallelism techniques to data mining processes. Therefore, the focus of the two chapters on parallel data mining (Chapters 16 and 17) is twofold: High-Performance Parallel Database ... deletions, and insertions. The bottom line of databases is that the data be active. The data contained in a database is normally operational data. The data is required for day-to-day operation of...

Ngày tải lên: 21/01/2014, 18:20

... input data. More details about these two data mining parallelisms are given below. Data Parallelism In data parallelism, as the name states, parallelism is basically created because the data is ... between data parallelism and result paral- lelism in parallel clustering. Data Parallelism Parallel k -Means Like count distribution in parallel association rules and parallel sequential patterns, data ... whereas in data parallelism the data never moves out from a processor. Another difference between data parallelism and result parallelism for parallel clustering is that in result parallelism...

Ngày tải lên: 21/01/2014, 18:20

... whereas result parallelism is identical to parallel subqueries execution scheduling. Both data parallelism and result parallelism for a decision tree are described below. Data Parallelism for ... subqueries execution scheduling and parallel subqueries execution scheduling, whereas for parallel data mining, this chapter introduces data parallelism and result paral- lelism. A parallel decision tree ... www.verypdf.com to remove this watermark. 17.3 Parallel Classification 489 scheduling and parallel data mining, because both deal with tree parallelism. Data parallelism for a decision tree is basically...

Ngày tải lên: 26/01/2014, 15:20

... 430 data mining tasks, 431–433 descriptive data mining, 431 predictive data mining, 431 data parallelism, 437–438 data warehouse, 429 data- intensive applications, 428 definition, 430 from databases ... Handling Data Skew in Parallel Data Cube Computation”, Distributed and Parallel Databases, 13(2):181–202, 2003. Märtens, H., Rahm, E., and Stöhr, T., “Dynamic query scheduling in parallel data warehouses”, ... (CUME DIST) queries, parallelization, 419–420 Data computation cost, 46 Data distribution-based parallelism for association rule mining, 450 Data mining, parallel data mining association rules, 427–463 class...

Ngày tải lên: 26/01/2014, 15:20

... 430 data mining tasks, 431–433 descriptive data mining, 431 predictive data mining, 431 data parallelism, 437–438 data warehouse, 429 data- intensive applications, 428 definition, 430 from databases ... Handling Data Skew in Parallel Data Cube Computation”, Distributed and Parallel Databases, 13(2):181–202, 2003. Märtens, H., Rahm, E., and Stöhr, T., “Dynamic query scheduling in parallel data warehouses”, ... 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,...

Ngày tải lên: 26/01/2014, 15:20

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