2012Unpublished venueRequires access

Automatic Data Placement in MPP Databases

Carlos Garcia-Alvarado, Venkatesh Raghavan, Sivaramakrishnan Narayanan, Florian Waas

Open publisher page 6 citations

Abstract

Physical design for shared-nothing databases includes decisions regarding the placement of data across a cluster of database servers. In particular, for each table in the database a distribution policy must be specified. In general, the choice of distribution policy affects the performance of query workloads significantly as individual queries may have to redistribute data on-the-fly as part of the execution. As is the case with a number of other physical design decisions, the problem is hard and poses substantial difficulties for database administrators. In this paper, we present FINDER, a design tool that optimizes data placement decisions for a database schema with respect to any given query workload. We designed FINDER with portability in mind: The tool is fully external to the target database system, i.e., does not require any code-level integration with the system, and avoids reverse engineering of query optimization techniques. Our experiments show FINDER converges quickly and delivers superior results compared to state-of-the-art solutions.

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What this paper is about

Physical design for shared-nothing databases includes decisions regarding the placement of data across a cluster of database servers. In particular, for each table in the database a distribution policy must be specified. In general, the choice of distribution policy affects the performance of query workloads significantly as individual queries may have to redistribute data on-the-fly as part of the execution. As is the case with a number of other physical design decisions, the problem is hard and poses substantial difficulties for database administrators. In this paper, we present FINDER, a design tool that optimizes data placement decisions for a database schema with respect to any given query workload. We designed FINDER with portability in mind: The tool is fully external to the target database system, i.e., does not require any code-level integration with the system, and avoids reverse engineering of query optimization techniques. Our experiments show FINDER converges quickly and delivers superior results compared to state-of-the-art solutions.

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Available abstract

Physical design for shared-nothing databases includes decisions regarding the placement of data across a cluster of database servers. In particular, for each table in the database a distribution policy must be specified. In general, the choice of distribution policy affects the performance of query workloads significantly as individual queries may have to redistribute data on-the-fly as part of the execution. As is the case with a number of other physical design decisions, the problem is hard and poses substantial difficulties for database administrators. In this paper, we present FINDER, a design tool that optimizes data placement decisions for a database schema with respect to any given query workload. We designed FINDER with portability in mind: The tool is fully external to the target database system, i.e., does not require any code-level integration with the system, and avoids reverse engineering of query optimization techniques. Our experiments show FINDER converges quickly and delivers superior results compared to state-of-the-art solutions.

Key concepts: Computer science, View, Database tuning, Database, Database schema, Database testing, Database design, Database server

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