Anomalous query identification using query clustering

Abstract

Techniques are disclosed relating to managing database queries. In some embodiments, a server system receives a query from a computer system and determines a set of aspects for the query, including at least a number of columns specified in the query and a computational cost of executing the query. The system generates a query vector based on the set of aspects determined for the query. The system then compares the query vector with a plurality of clusters, ones of the plurality of clusters comprising two or more previously generates query vectors generated based on aspects of queries previously received by the server system. Based on the comparing, specifically a distance between the query vector and the plurality of clusters of previously generated query vectors, the system classifies the query. Based on a classification of the query determined during the classifying, the system manages the query.