: Experience in Extending Query Engine for Continuous Analytics Qiming Chen, Meichun Hsu HP Laboratories HPL-2010-44 In-Database Stream Processing Combining data warehousing and stream processing technologies has great potential in offering low-latency data-intensive analytics. Unfortunately, such convergence has not been properly addressed so far. The current generation of stream processing systems is in general built separately from the data warehouse and query engine, which can cause significant overhead in data access and data movement, and is not able to take advantage of the functionalities already offered by the existing data warehouse systems. In this work we tackle some hard problems not properly addressed previously in integrating stream analytics capability into the existing query engine. We define an extended SQL query model that unifies queries over both static relations and dynamic streaming data, and develop techniques to generalize query engines to support the unified ...