State-of-the-art database design tools rely on the query optimizer for comparing between physical design alternatives. Although it provides an appropriate cost model for physical design, query optimization is a computationally expensive process. The significant time consumed by optimizer invocations poses serious performance limitations for physical design tools, causing long running times, especially for large problem instances. So far it has been impossible to remove query optimization overhead without sacrificing cost estimation precision. Inaccuracies in query cost estimation are detrimental to the quality of physical design algorithms, as they increase the chances of “missing ” good designs and consequently selecting sub-optimal ones. Precision loss and the resulting reduction in solution quality is particularly undesirable and it is the reason the query optimizer is used in the first place. In this paper we eliminate the tradeoff between query cost estimation accuracy and performance. We introduce the INdex Usage Model (INUM), a cost estimation technique that returns the same values that would have been returned by the optimizer, while being three orders of magnitude faster. Integrating INUM with existing index selection algorithms dramatically improves their running times without precision compromises. 1.

This paper presents the design of a read-optimized relational DBMS that contrasts sharply with most current systems, which are write-optimized.

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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.