queryopt.bib

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@comment{{Command line: /usr/bin/bib2bib -ob queryopt.bib -c 'class : "queryopt"' lib.bib}}

@inproceedings{bach05,
  author = {Brian Babcock and Surajit Chaudhuri},
  title = {Towards a Robust Query Optimizer: a Principled and Practical Approach},
  booktitle = {Proceedings of the 2005 ACM SIGMOD International Conference on Management
	of Data (SIGMOD'05)},
  year = {2005},
  pages = {119-130},
  annote = {User specified confidence threshold specifies how likely it should
	be that the actual cost of the plan is less than or equal to the
	reported (point) cost estimate. Cardinality estimates for base tables
	and intermediate query results are based on join synopses, under
	the restriction that only foreign-key joins are permitted. The cardinality
	distribution is determined using the join synopsis and Bayes' rule.},
  class = {queryopt},
  url = {http://www.db.uwaterloo.ca/~kmsalem/lib/lib/bach05.pdf}
}

@inproceedings{babi05,
  author = {Shivnath Babu and Pedro Bizarro and David J. {DeWitt}},
  title = {Proactive Re-optimization},
  booktitle = {Proceedings of the ACM SIGMOD International Conference on Management
	of Data (SIGMOD'05)},
  year = {2005},
  annote = {Represents uncertainty in operator estimates using intervals, and
	tries to identify plans that are robust (close to optimal) throughout
	the interval, or a set of switchable plans that cover the interval.
	Implements a run-time switch operation, and modifies other operators
	so that they initially produce a randomized sample of their output.},
  class = {queryopt},
  url = {http://www.db.uwaterloo.ca/~kmsalem/lib/lib/babi05.pdf}
}

@inproceedings{brch02,
  author = {Nicolas Bruno and Surajit Chaudhuri},
  title = {Exploiting statistics on query expressions for optimization},
  booktitle = {Proceedings of the ACM SIGMOD International Conference on Management
	of Data (SIGMOD'02)},
  year = {2002},
  class = {queryopt},
  url = {http://www.db.uwaterloo.ca/~kmsalem/lib/lib/brch02.pdf}
}

@inproceedings{cogr94,
  author = {Richard L. Cole and Goetz Graefe},
  title = {Optimization of Dynamic Query Evaluation Plans},
  booktitle = {Proceedings of the ACM SIGMOD International Conference on Management
	of Data (SIGMOD'94)},
  year = {1994},
  pages = {150-160},
  annote = {How to produce dynamic query evaluation plans that include ChoosePlan
	operators. Generalizes the optimizer so that it understands that
	cost estimates may only partially order the candidate evaluation
	plans.},
  class = {queryopt},
  url = {http://www.db.uwaterloo.ca/~kmsalem/lib/lib/cogr94.pdf}
}

@inproceedings{gaku09,
  author = {Archana Ganapathi and Harumi Kuno and Umeshwar Dayal and Janet Wiener
	and Armando Fox and Michael Jordan and David Patterson},
  title = {Predicting Multiple Performance Metrics for Queries: Better Decisions
	Enabled by Machine Learning},
  booktitle = {Proc. Int'l Conference on Data Engineering (ICDE'09)},
  year = {2009},
  class = {queryopt},
  timestamp = {13.10.2008},
  url = {http://radlab.cs.berkeley.edu/w/uploads/5/57/Ganapathi-ICDE2009.pdf},
  url2 = {http://www.db.uwaterloo.ca/~kmsalem/lib/lib/gaku09.pdf}
}

@inproceedings{ghpa02,
  author = {Antara Ghosh and Jignashu Parikh and Vibhuti S. Sengar and Jayant
	R. Haritsa},
  title = {Plan Selection Based on Query Clustering},
  booktitle = {International Conference on Very Large Data Bases (VLDB'22)},
  year = {2002},
  pages = {179-190},
  annote = {Classifies SPJ queries using features such as number of tables in
	the query, the number of SARGable predicates in the query, and the
	sizes of the tables. For each class of queries, the system maintains
	a plan template, which can be instantiated for any query in the class.
	To process a query, system first tries to match it to an existing
	class. If it can, the class plan template is instantiated and the
	resulting plan is used for the query. Otherwise, the query is compiled
	and used to start a new class.},
  class = {queryopt},
  url = {http://www.db.uwaterloo.ca/~kmsalem/lib/lib/ghpa02.pdf},
  url2 = {http://www.vldb.org/conf/2002/S06P02.pdf}
}

@article{grae93,
  author = {Goetz Graefe},
  title = {Query Evaluation Techniques for Large Databases},
  journal = {ACM Computing Surveys},
  year = {1993},
  volume = {25},
  pages = {73-169},
  number = {2},
  class = {queryopt},
  timestamp = {16.04.2009},
  url = {http://www.db.uwaterloo.ca/~kmsalem/lib/lib/grae93.pdf},
  url2 = {http://doi.acm.org/10.1145/152610.152611}
}

@inproceedings{ilra03,
  author = {Ihab F. Ilyas and Jun Rao and Guy M. Lohman and Dengfeng Gao and
	Eileen Lin},
  title = {Estimating Compilation Time of a Query Optimizer},
  booktitle = {ACM SIGMOD Conference},
  year = {2003},
  pages = {373-384},
  annote = {Claims average 30\% estimation time error with 3\% of compilation
	time overhead to produce the estimate.},
  class = {queryopt},
  url = {http://www.db.uwaterloo.ca/~kmsalem/lib/lib/r14p02.pdf},
  url2 = {http://www.acm.org/sigs/sigmod/sigmod03/eproceedings/papers/r14p02.pdf}
}

@inproceedings{iong92,
  author = {Yannis E. Ioannidis and Raymond T. Ng and Kyuseok Shim and Timos
	K. Sellis},
  title = {Parametric Query Optimization},
  booktitle = {18th International Conference on Very Large Data Bases (VLDB'92)},
  year = {1992},
  pages = {103-114},
  month = aug,
  class = {queryopt},
  url = {http://www.db.uwaterloo.ca/~kmsalem/lib/lib/iong92.pdf},
  url2 = {http://www.vldb.org/conf/1992/P103.PDF}
}

@inproceedings{kade98,
  author = {Navin Kabra and David J. DeWitt},
  title = {Efficient Mid-Query Re-Optimization of Sub-Optimal Query Execution
	Plans},
  booktitle = {Proceedings of the ACM SIGMOD International Conference on Management
	of Data (SIGMOD'98)},
  year = {1998},
  pages = {106-117},
  class = {queryopt},
  url = {http://www.db.uwaterloo.ca/~kmsalem/lib/lib/kade98.pdf},
  url2 = {http://www.cs.wisc.edu/~cs764-1/reopt.pdf}
}

@article{koss00,
  author = {Donald Kossmann},
  title = {The State of the Art in Distributed Query Processing},
  journal = {ACM Computing Surveys},
  year = {2000},
  volume = {32},
  pages = {422-469},
  number = {4},
  class = {queryopt},
  timestamp = {16.04.2009},
  url = {http://www.db.uwaterloo.ca/~kmsalem/lib/lib/koss00.pdf},
  url2 = {http://doi.acm.org/10.1145/371578.371598}
}

@inproceedings{mara04,
  author = {Volker Markl and Vijayshankar Raman and David Simmen and Guy Lohman
	and Hamid Pirahesh and Miso Cilimdzic},
  title = {Robust query processing through progressive optimization},
  booktitle = {Proceedings of the ACM SIGMOD International Conference on Management
	of Data (SIGMOD'04)},
  year = {2004},
  pages = {659-670},
  annote = {Hardcopy on file. Plan reoptimization is triggered by cardinality
	checking operators inserted into the plan. Checks determine whether
	the actual cardinality differs from the predicted cardinality by
	enough that the optimizer would have chosen a different plan. The
	plan transition cardinalities are determined at optimization time.
	Reoptimization considers the use of materialized intermediate results
	when reoptimizing the query.},
  class = {queryopt},
  url = {http://www.db.uwaterloo.ca/~kmsalem/lib/lib/mara04.pdf}
}

@inproceedings{stlo01,
  author = {Michael Stillger and Guy M. Lohman and Volker Markl and Mokhtar Kandil},
  title = {{LEO} - {DB2}'s {LEarning} {Optimizer}},
  booktitle = {Proceedings of the International Conference on Very Large Data Bases
	(VLDB)},
  year = {2001},
  pages = {19-28},
  class = {queryopt},
  url = {http://www.db.uwaterloo.ca/~kmsalem/lib/lib/stlo01.pdf},
  url2 = {http://www.vldb.org/conf/2001/P019.pdf}
}

@inproceedings{vopa02,
  author = {Kristofer Vorwerk and G. N. Paulley},
  title = {On Implicate Discovery and Query Optimization},
  booktitle = {Proc. International Database Engineering and Applications Symposium
	(IDEAS'02)},
  year = {2002},
  pages = {2-11},
  month = jul,
  class = {queryopt},
  url = {http://www.db.uwaterloo.ca/~kmsalem/lib/lib/vopa02.pdf}
}

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