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This document is the report for the authors' joint effort in researching and designing a query optimizer for Fast's next-generation search platform, known as MARS. The work was done during our master thesis at the Department of Computer and Information Science at the Norwegian University of Science and Technology, spring 2009.

MARS does not currently employ any form of query optimizer, but does have a parser and a runtime system. The report therefore focuses on the core query optimizing aspects, like plan generation and optimizer design. First, we give an introduction to query optimizers and selected problems. Then, we describe previous and ongoing efforts regarding query optimizers, before shifting focus to our own design and results.

MARS supports DAG-structured query plans for more efficient execution, which means that the optimizer must do so too. This turned out to be a greater task than what it might seem like -- since we must use algorithms that greatly differ from the optimizers we were familiar with. The optimizer also needed to be extensible, including the ability to deal with future query operators, as well as supporting arbitrary cost models.

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