By Michael Jaedicke (auth.)
ISBN-10: 3540427813
ISBN-13: 9783540427810
During the previous couple of years, parallel object-relational database administration platforms have emerged because the prime facts administration know-how out there. those platforms are extensible by means of user-defined information kinds and user-defined performance for the information.
This paintings makes a speciality of the effective parallel execution of user-defined performance. the most contributions describe recommendations to help information parallelism for user-defined scalar and combination features and intra-function parallelism for the execution of a scalar functionality on a wide item, and a brand new expertise to supply extensibility in regards to new set-oriented database operations which may successfully enforce user-defined performance in parallel object-relational database administration systems.
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Extra resources for New Concepts for Parallel Object-Relational Query Processing
Sample text
In fact, with user-defined combine functions the decompose/compose-approach can be used for all UDSF that operate on LOBs because the combine function can compute the correct return value. We provide now a very simple example of a UDSF that needs a combine function to support intra-function parallelism. Consider the UDSF: Compose/Decompose Operators for Intra-function Parallelism 37 CREATE FUNCTION count_char(CLOB text, CHAR(1) c) RETURNS INTEGER ... that counts how often the character c occurs in a given text.
Furthermore, the developer must specify if early termination is used. To enable parallel evaluation, the partitioning class has to be specified. In addition to ANY, EQUAL and RANGE partitioning, the developer can register a special (user-defined) partitioning function for a UDF. Figure 10 shows the extensions for the CREATE AGGREGATE statement. It now includes the local and global function options that are needed to register the aggregate functions that have to be used for the parallel evaluation of the new aggregate function.
For example in shared-every- Plausibility Considerations Regarding Performance 29 thing systems the costs for exchanging intermediate results between processors are negligible, if shared memory is used properly. g. a switched gigabit network or an ATM-based network). Therefore we will also ignore bandwidth problems for the moment. , cost (fl) + cost (fg) ≈ cost (f)). Thus, our cost model has the following three components: 1. F: CPU cost for evaluating the UDAF. F = cost (fl) + cost (fg) ≈ cost (f) 2.
New Concepts for Parallel Object-Relational Query Processing by Michael Jaedicke (auth.)
by James
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