Handling Materialized Views - Automated Physical Database Design and Tuning - page 156

8.6 Additional Reading
Materialized views have been discussed in detail since 1985. 6 More recent work
specifically discusses materialized view matching during query optimization, 4 , 5
gives a treatment of the merging and reduction operations on views in the
context of physical design refinement, 3 and addresses the problem of recom-
mending materialized views in detail. 1 , 2 , 7
References
1. Sanjay Agrawal, Surajit Chaudhuri, and Vivek Narasayya. Automated
selection of materialized views and indexes in SQL databases. In Proceed-
ings of the International Conference on Very Large Databases (VLDB) ,
2000.
2. Nicolas Bruno and Surajit Chaudhuri. Automatic physical database tun-
ing: A relaxation-based approach. In Proceedings of the ACM Interna-
tional Conference on Management of Data (SIGMOD) , 2005.
3. Nicolas Bruno and Surajit Chaudhuri. Physical design refinement: The
“merge-reduce” approach. ACM Transactions on Database Systems ,
32(4), 2007.
4. Surajit Chaudhuri, Ravi Krishnamurthy, Spyros Potamianos, and
Kyuseok Shim. Optimizing queries with materialized views. In Proceed-
ings of the International Conference on Data Engineering (ICDE) , 1995.
5. Jonathan Goldstein and Per-Ake Larson. Optimizing queries using ma-
terialized views: A practical, scalable solution. In Proceedings of the
ACM International Conference on Management of Data (SIGMOD) ,
2001.
6. Paul Larson and H. Z. Yang. Computing queries from derived relations.
In Proceedings of the International Conference on Very Large Databases
(VLDB) , 1985.
7. Daniel Zilio, Calisto Zuzarte, Sam Lightstone, Wenbin Ma, Guy
Lohman, Roberta Cochrane, Hamid Pirahesh, Latha Colby, Jarek Gryz,
Eric Alton, Dongming Liang, and Gary Valentin. Recommending ma-
terialized views and indexes with IBM DB2 design advisor. In Interna-
tional Conference on Autonomic Computing , 2004.