We present the idea of an approach to database query sharding that makes use of knowledge about data structure and purpose. It is based on a case study for a database system that contains information about documents. By making use of knowledge about the data structure and the specific top-k queries to be processed we demonstrate a method for avoiding costly and unnecessary steps in query answering. We also demonstrate how the knowledge of data structure may be used to perform sharding and how

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... ch sharding may improve performance. We propose generalization of our findings that could lead to self-optimization and self-tuning in RDBMS engines, especially for column-based solutions.