Database Reference
In-Depth Information
2.5 Additional Reading
Query optimization has received considerable attention in the past 30 years,
and there are many sources of information regarding every aspect of the prob-
lem. Chaudhuri summarizes many issues around query optimization discussed
in this chapter.
2
For information on specific systems, we refer the readers
to the seminal paper on System-R,
14
an overview of StarBurst,
10
and dif-
ferent references that discuss the Volcano/Cascades framework.
1
,
8
,
9
Several
references explain in depth many issues that we covered only superficially,
such as optimizing group-by queries,
4
,
15
queries with outer-joins,
6
plans that
leverage multiple indexes for single-table predicates,
12
generic treatments of
unnesting,
5
,
13
issues with materialized views,
3
,
7
and histograms and their use
during cardinality estimation.
11
References
1. Nicolas Bruno and Rimma Nehme. Configuration-parametric query op-
timization for physical design tuning. In
Proceedings of the ACM Inter-
national Conference on Management of Data (SIGMOD)
, 2008.
2. Surajit Chaudhuri. An overview of query optimization in relational sys-
tems. In
Proceedings of the ACM Symposium on Principles of Database
Systems (PODS)
, 1998.
3. Surajit Chaudhuri, Ravi Krishnamurthy, Spyros Potamianos, and
Kyuseok Shim. Optimizing queries with materialized views. In
Pro-
ceedings of the International Conference on Data Engineering (ICDE)
,
1995.
4. Surajit Chaudhuri and Kyuseok Shim. An overview of cost-based opti-
mization of queries with aggregates.
IEEE Data Engineering Bulletin
,
18(3), 1995.
5. Mostafa Elhemali, Cesar Galindo-Legaria, Torsten Grabs, and Milind
Joshi. Execution strategies for SQL sub-queries. In
Proceedings of the
ACM International Conference on Management of Data (SIGMOD)
,
2007.
6. Cesar A. Galindo-Legaria and Arnon Rosenthal. Outerjoin simplifi-
cation and reordering for query optimization.
ACM Transactions on
Database Systems
, 22(1), 1997.
7. Jonathan Goldstein and Per-Ake Larson. Optimizing queries using ma-
terialized views: A practical, scalable solution.
In
Proceedings of the
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