In situ Statistics Generation within partially reconfigurable Hardware Accelerators for Query Processing

Hardware Accelerators for Query Processing are often optimized to filter as much data as possible before the results are stored to memory or sent to the user. However, the static nature of such optimized accelerators limits the amount of operators they can implement to a fixed amount configured at synthesis time. If not all operators can be pushed down to the accelerator, the decision which operators should be pushed down has therefore a big impact on the resulting data size and overall query execution time. Statistics are therefore used to determine which operators to push onto the hardware accelerators. Gathering these statistics is therefore of utmost importance. In this paper we present multiple possibilities to gather statistics within an accelerator while executing a partial query. These statistics can be gradually improved with every execution of the accelerator be of use in future queries during the query planning phase.