Query Transformation for Approximate Query Processing Using Synthetic Data from Deep Generative Models

In exploratory data analysis, interactive latency can make a significant impact on the data exploration space and user productivity. To provide low latency for the aggregation query, approximate query processing can be considered as a possible alternative. In this paper, we describe the transformation rules for processing approximation queries. We present the preliminary experimental results on the performance of approximate query processing with synthetic data.