Iterators, Schedulers, and Distributed-memory Parallelism

In previous work, we demonstrated the advantages of encapsulating query evaluation algorithms as ‘iterators’ for sequential and parallel query evaluation. Unfortunately, those earlier models have a severe drawback with respect to resource allocation in distributed‐memory systems. Since threads may b...

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Veröffentlicht in:	Software, practice & experience Jg. 26; H. 4; S. 427 - 452
1. Verfasser:	GRAEFE, GOETZ
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York John Wiley & Sons, Ltd 01.04.1996 Wiley
Schlagworte:	abstraction Applied sciences bottom-up activation communication Computer science; control theory; systems Computer systems and distributed systems. User interface database query processing encapsulation Exact sciences and technology extensibility Information systems. Data bases iterators Memory organisation. Data processing parallelism Software software engineering Encapsulation Query Resource allocation Database Parallelism Data processing Distributed system Abstraction Shared memory Software engineering
ISSN:	0038-0644, 1097-024X
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Abstract	In previous work, we demonstrated the advantages of encapsulating query evaluation algorithms as ‘iterators’ for sequential and parallel query evaluation. Unfortunately, those earlier models have a severe drawback with respect to resource allocation in distributed‐memory systems. Since threads may be initiated long before they actually perform useful work, thread placement decisions may be suboptimal. In this paper, we briefly review the iterator model and then extend it to support bottom‐up, just‐in‐time activation of appropriate query plan fragments as well as local and global synchronization and communication among sibling threads. Some of the algorithms described here may seem intricate; however, the intricacy is encapsulated entirely in the parallelism or ‘exchange’ iterator, thus freeing developers of data manipulation iterators to focus on the specific algorithms at hand, instead of on mechanisms for parallelism. Moreoever, code fragments extracted from an operational prototype demonstrate the ease with which our suggestions can be implemented. Run‐time overhead and performance of our techniques are identical to those of earlier, less extensible techniques for bottom‐up activation; the benefits of the presented techniques are their clean design, ion, extensibility, and the resulting ease of maintenance and enhancement.
AbstractList	In previous work, we demonstrated the advantages of encapsulating query evaluation algorithms as 'iterators' for sequential and parallel query evaluation. Unfortunately, those earlier models have a severe drawback with respect to resource allocation in distributed-memory systems. Since threads may be initiated long before they actually perform useful work, thread placement decisions may be suboptimal. In this paper, we briefly review the iterator model and then extend it to support bottom-up, just-in-time activation of appropriate query plan fragments as well as local and global synchronization and communication among sibling threads. Some of the algorithms described here may seem intricate; however, the intricacy is encapsulated entirely in the parallelism or 'exchange' iterator, thus freeing developers of data manipulation iterators to focus on the specific algorithms at hand, instead of on mechanisms for parallelism. Moreover, code fragments extracted from an operational prototype demonstrate the ease with which our suggestions can be implemented. Run-time overhead and performance of our techniques are identical to those of earlier, less extensible techniques for bottom-up activation; the benefits of the presented techniques are their clean design, abstraction, extensibility, and the resulting ease of maintenance and enhancement. In previous work, we demonstrated the advantages of encapsulating query evaluation algorithms as ‘iterators’ for sequential and parallel query evaluation. Unfortunately, those earlier models have a severe drawback with respect to resource allocation in distributed‐memory systems. Since threads may be initiated long before they actually perform useful work, thread placement decisions may be suboptimal. In this paper, we briefly review the iterator model and then extend it to support bottom‐up, just‐in‐time activation of appropriate query plan fragments as well as local and global synchronization and communication among sibling threads. Some of the algorithms described here may seem intricate; however, the intricacy is encapsulated entirely in the parallelism or ‘exchange’ iterator, thus freeing developers of data manipulation iterators to focus on the specific algorithms at hand, instead of on mechanisms for parallelism. Moreoever, code fragments extracted from an operational prototype demonstrate the ease with which our suggestions can be implemented. Run‐time overhead and performance of our techniques are identical to those of earlier, less extensible techniques for bottom‐up activation; the benefits of the presented techniques are their clean design, ion, extensibility, and the resulting ease of maintenance and enhancement.
Author	GRAEFE, GOETZ
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References_xml	– reference: A. N. Wilschut and P. M. G. Apers, 'Dataflow query execution in a parallel main-memory environment', Distr. and Parallel Databases, 1, (1), 103 (1993). – reference: Reprinted in M. Stonebraker, Readings in Database Systems, 2nd edn, Morgan Kaufmann, San Mateo, CA, 1993. – reference: G. Graefe, 'Query evaluation techniques for large databases', ACM Computing Surveys, 25, (2), 73-170 (1993). – reference: G. Graefe, 'Volano, an extensible and parallel dataflow query processing system', IEEE Trans. Knowledge and Data Eng., 6, (1), 120 (1994). – reference: L. D. Shapiro, 'Join processing in database systems with large main memories', ACM Trans Database Sys., 11, (3), 239 (1980). – reference: Reprinted in M. Stonebraker, Readings in Database Systems, Morgan Kaufmann, San Mateo, CA, 1988. – reference: M. Kitsuregawa, H. Tanaka and T. Motooka, 'Application of hash to data base machine and its architecture', New Generation Computing, 1, (1), 63 (1983). – reference: G. Graefe and D. L. Davison, 'Encapsulation of parallelism and architecture-independence in extensible database query processing', IEEE Trans. Softw. Eng., 19 (8), 749 (1993). – reference: D. J. DeWitt, S. Ghandeharizadeh, D. Schneider, A. Bricker, H. I. Hsiao and R. Rasmussen, 'The Gamma database machine project', IEEE Trans. Knowledge and Data Eng., 2, (1), 44 (1990). – volume: 2 start-page: 44 issue: 1 year: 1990 article-title: The Gamma database machine project publication-title: IEEE Trans. Knowledge and Data Eng. – year: 1986 – start-page: 468 year: 1988 – start-page: 209 year: 1986 – start-page: 102 year: 1990 1993 – start-page: 268 year: 1991 – start-page: 1 year: 1984 – volume: 25 start-page: 73 issue: 2 year: 1993 end-page: 170 article-title: Query evaluation techniques for large databases publication-title: ACM Computing Surveys – start-page: 257 year: 1989 – volume: 11 start-page: 239 issue: 3 year: 1980 article-title: Join processing in database systems with large main memories publication-title: ACM Trans Database Sys. – volume: 1 start-page: 63 issue: 1 year: 1983 article-title: Application of hash to data base machine and its architecture publication-title: New Generation Computing – volume: 19 start-page: 749 issue: 8 year: 1993 article-title: Encapsulation of parallelism and architecture‐independence in extensible database query processing publication-title: IEEE Trans. Softw. Eng. – volume: 6 start-page: 120 issue: 1 year: 1994 article-title: Volano, an extensible and parallel dataflow query processing system publication-title: IEEE Trans. Knowledge and Data Eng. – start-page: 228 year: 1986 1988 – volume: 1 start-page: 103 issue: 1 year: 1993 article-title: Dataflow query execution in a parallel main‐memory environment publication-title: Distr. and Parallel Databases – year: 1990 – year: 1994 – start-page: 103 year: 1992 – start-page: 469 year: 1990
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SubjectTerms	abstraction Applied sciences bottom-up activation communication Computer science; control theory; systems Computer systems and distributed systems. User interface database query processing encapsulation Exact sciences and technology extensibility Information systems. Data bases iterators Memory organisation. Data processing parallelism Software software engineering
Title	Iterators, Schedulers, and Distributed-memory Parallelism
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