HQ-Filter: Hierarchy-Aware Filter For Empty-Resulting Queries in Interactive Exploration
Akil Sevim, Ahmed Eldawy · 2021
Modern visual data exploration systems are designed as client-server applications where the front-end interface generates a large number of queries to the back-end which are handled by a database server. As data exploration being a trial and error process, a significant amount of these queries return an empty result, which does not change the state of the visualization. These requests still add a significant overhead on network communication, request handling, and data processing. Moreover, given the virtually unlimited query space, it is impractical to enumerate and send all empty (or all non-empty) queries to the client to filter them. This paper introduces HQ-Filter, a hierarchy-aware filter for empty resulting queries, which utilizes the hierarchical nature of the data to construct a configurable and probabilistic filter. HQ-Filter can filter out empty-resulting queries at the client-side with a minimal size and processing overhead. HQ-Filter is applied to two existing data exploration systems for geospatial data, UCR-Star and Cloudberry. In both cases, it can successfully eliminate hundreds of queries per user which results in up-to 66% increase in server capacity by providing up to 15x speedup for average response time and up to 90% decrease in the server workload.