Physical database design for relational databases
ACM Transactions on Database Systems (TODS)
AutoPart: Automating Schema Design for Large Scientific Databases Using Data Partitioning
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
Index Selection for Databases: A Hardness Study and a Principled Heuristic Solution
IEEE Transactions on Knowledge and Data Engineering
Automatic physical database tuning: a relaxation-based approach
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
COLT: continuous on-line tuning
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
DB2 design advisor: integrated automatic physical database design
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Efficient use of the query optimizer for automated physical design
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
An index selection method without repeated optimizer estimations
Information Sciences: an International Journal
An Integrated Approach to Performance Monitoring for Autonomous Tuning
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
An Integer Linear Programming Approach to Database Design
ICDEW '07 Proceedings of the 2007 IEEE 23rd International Conference on Data Engineering Workshop
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One of the most challenging tasks for the database administrator is to physically design the database to attain optimal performance for a given workload. Physical design is hard because it requires the selection of an optimal set of design features from a vast search space. There have been many commercial tools available to automatically suggest the physical design, for a given a set of queries. These tools are, however, based on greedy heuristic pruning, which reduces their usefulness. Furthermore, they are not interactive, as the APIs to simulate the indexes and tables are product specific and hidden from the database administrators. Finally, all these tools are built specifically for commercial systems and there is lack of automated physical designers for open source DBMSs. In this demonstration we introduce -PARINDA - an interactive physical designer for an open source DBMS. Given a workload containing a set of queries, this tool allows the DBA to efficiently simulate various physical design features and get immediate feedback on their effectiveness. It also incorporates recent advances in non-greedy physical design techniques to provide close to optimal suggestions. Although it has been prototyped for several different DBMSs, we demonstrate the usefulness and efficiency of the tool while running on the open source DBMS---PostgreSQL--using large real-world scientific datasets and query workloads.