14. The method as recited in claim 10 , wherein said using machine learning to build said prediction of query runtime tree further comprises: terminating construction of an element of said prediction of query runtime tree based upon occurrence of a pre-defined termination condition.
14. The method as recited in claim 10 , wherein said using machine learning to build said prediction of query runtime tree further comprises: terminating construction of an element of said prediction of query runtime tree based upon occurrence of a pre-defined termination condition. 15. The method as recited in claim 14 , wherein said terminating construction of an element of said prediction of query runtime tree based upon occurrence of a pre-defined termination condition comprises: terminating construction of said element upon occurrence of a pre-defined termination condition selected from the group of termination conditions consisting of: dropping below a predetermined time range threshold for said element; dropping below a predetermined threshold number of historical database queries grouped in said element; and dropping below a predetermined accuracy of runtime estimation for said element.