Demonstration of ScroogeDB: Getting More Bang For the Buck with Deterministic Approximation in the Cloud

We demonstrate ScroogeDB which aims at minimizing monetary cost of processing aggregation queries in the Cloud. It runs on top of a Cloud database that offers pay-as-you-go query processing where users pay according to the number of bytes processed. ScroogeDB exploits deterministic approximate query processing (DAQ) to achieve monetary savings. That is, ScroogeDB provides deterministic bounds, i.e., bounds that contain the true value with a 100% probability. ScroogeDB creates small synopses of the database and uses these synopses to answer aggregation queries. By rewriting a query on base tables into a query on smaller synopses, we significantly reduce the amount of processed data. We do not pre-compute synopses in advance of an analysis session. Instead, we generate them on the fly, interleaving synopsis generation with query execution. In our demonstration, we show that our system realizes impressive monetary savings with little precision loss. We run our system on top of the Google BigQuery Cloud platform and provide users with a graphical interface that visualizes deterministic bounds. The graphical interface also provides information regarding the generated synopses and how they contribute to monetary savings.