Scalable Numerical Queries By Algebraic Inequality Transformations

To enable historical analyses of logged data streams by SQL queries, the Stream Log Analysis System (SLAS) bulk loads data streams derived from sensor readings into a relational database system. SQL queries over such log data often involve numerical conditions containing inequalities, e. g. to find suspected deviations from normal behavior based on some function over measured sensor values. However, such queries are often slow to execute, because the query optimizer is unable to utilize ordered indexed attributes inside numerical conditions. In order to speed up the queries they need to be reformulated to utilize available indexes. In SLAS the query transformation algorithm AQIT (Algebraic Query Inequality Transformation) automatically transforms SQL queries involving a class of algebraic inequalities into more scalable SQL queries utilizing ordered indexes. The experimental results show that the queries execute substantially faster by a commercial DBMS when AQIT has been applied to preprocess them.