  This paper presents a proposal aiming at better understanding a workload of
SQL queries and detecting coherent explorations hidden within the workload. In
particular, our work investigates SQLShare [11], a database-as-a-service
platform targeting scientists and data scientists with minimal database
experience, whose workload was made available to the research community.
According to the authors of [11], this workload is the only one containing
primarily ad-hoc hand-written queries over user-uploaded datasets. We analyzed
this workload by extracting features that characterize SQL queries and we show
how to use these features to separate sequences of SQL queries into meaningful
explorations. We ran several tests over various query workloads to validate
empirically our approach.
