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Optimizing nested queries with parameter sort orders

Published: 30 August 2005 Publication History

Abstract

Nested iteration is an important technique for query evaluation. It is the default way of executing nested subqueries in SQL. Although decorrelation often results in cheaper non-nested plans, decorrelation is not always applicable for nested subqueries. Nested iteration, if implemented properly, can also win over decorrelation for several classes of queries. Decorrelation is also hard to apply to nested iteration in user-defined SQL procedures and functions. Recent research has proposed evaluation techniques to speed up execution of nested iteration, but does not address the optimization issue. In this paper, we address the issue of exploiting the ordering of nested iteration/procedure calls to speed up nested iteration. We propose state retention of operators as an important technique to exploit the sort order of parameters/correlation variables. We then show how to efficiently extend an optimizer to take parameter sort orders into consideration. We implemented our evaluation techniques on PostgreSQL, and present performance results that demonstrate significant benefits.

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Cited By

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  • (2021)Distributed numerical and machine learning computations via two-phase execution of aggregated join treesProceedings of the VLDB Endowment10.14778/3450980.345099114:7(1228-1240)Online publication date: 12-Apr-2021
  • (2019)Guided automated learning for query workload re-optimizationProceedings of the VLDB Endowment10.14778/3352063.335212012:12(2010-2021)Online publication date: 1-Aug-2019
  • (2018)Effective and complete discovery of bidirectional order dependencies via set-based axiomsThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-018-0510-027:4(573-591)Online publication date: 1-Aug-2018
  • Show More Cited By

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cover image DL Hosted proceedings
VLDB '05: Proceedings of the 31st international conference on Very large data bases
August 2005
1392 pages
ISBN:1595931546

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VLDB Endowment

Publication History

Published: 30 August 2005

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View all
  • (2021)Distributed numerical and machine learning computations via two-phase execution of aggregated join treesProceedings of the VLDB Endowment10.14778/3450980.345099114:7(1228-1240)Online publication date: 12-Apr-2021
  • (2019)Guided automated learning for query workload re-optimizationProceedings of the VLDB Endowment10.14778/3352063.335212012:12(2010-2021)Online publication date: 1-Aug-2019
  • (2018)Effective and complete discovery of bidirectional order dependencies via set-based axiomsThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-018-0510-027:4(573-591)Online publication date: 1-Aug-2018
  • (2017)Effective and complete discovery of order dependencies via set-based axiomatizationProceedings of the VLDB Endowment10.14778/3067421.306742210:7(721-732)Online publication date: 1-Mar-2017
  • (2013)Expressiveness and complexity of order dependenciesProceedings of the VLDB Endowment10.14778/2556549.25565686:14(1858-1869)Online publication date: 1-Sep-2013
  • (2012)Fundamentals of order dependenciesProceedings of the VLDB Endowment10.14778/2350229.23502415:11(1220-1231)Online publication date: 1-Jul-2012
  • (2011)Efficient auditing for complex SQL queriesProceedings of the 2011 ACM SIGMOD International Conference on Management of data10.1145/1989323.1989396(697-708)Online publication date: 12-Jun-2011
  • (2006)Strategies for query unnesting in XML databasesACM Transactions on Database Systems10.1145/1166074.116608131:3(968-1013)Online publication date: 1-Sep-2006

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