8. The method as recited in claim 1 , wherein said processing said database query through said prediction of query runtime tree further comprises: traversing said prediction of query runtime tree on the basis of one or more attributes of a feature vector associated with said database query.
8. The method as recited in claim 1 , wherein said processing said database query through said prediction of query runtime tree further comprises: traversing said prediction of query runtime tree on the basis of one or more attributes of a feature vector associated with said database query. 9. The method as recited in claim 8 , further comprising: determining a time range estimate of said loaded execution runtime based upon a similarity of said at least one attribute of said query vector to a classifier function derived from a grouping of historical database queries stored in an element of said prediction of query runtime tree.