Transformation of Continuous Aggregation Join Queries over Data Streams

We address continuously processing an aggregation join query over data streams. Queries of this type involve both join and aggregation operations, with windows specified on join input streams. To our knowledge, the existing researches address join query optimization and aggregation query optimization as separate problems. Our observation, however, is that by putting them within the same scope of query optimization we can generate more efficient query execution plans. This is through more versatile query transformations, the key idea of which is to perform aggregation before join so join execution time may be reduced. This idea itself is not new (already proposed in the database area), but developing the query transformation rules faces a completely new set of challenges. In this paper, we first propose a query processing model of an aggregation join query. Then, we introduce the concrete query transformation rules specialized to work with streams. The rules are far more compact and...

• Type: Conference
• Year: 2007
• Where: SSD
• Authors: Tri Minh Tran, Byung Suk Lee
• Keywords: Aggregation Join Query, Join Query, Query Execution Plans, SSD 2007