Lahar Demonstration: Warehousing Markovian Streams

Lahar is a warehousing system for Markovian streams—a common class of uncertain data streams produced via inference on probabilistic models. Example Markovian streams include text inferred from speech, location streams inferred from GPS or RFID readings, and human activity streams inferred from sensor data. Lahar supports OLAP-style queries on Markovian stream archives by leveraging novel approximation and indexing techniques that efficiently manipulate stream probabilities. This demonstration allows users to interactively query a warehouse of imprecise text streams inferred automatically from audio podcasts. Through this interaction, the demonstration introduces users to the challenges of Markovian stream processing as well as technical contributions developed to address these challenges.