Machine-learning to alarm or pre-empt query execution

A computer program product comprising:

• a computer readable storage medium readable by one or more processors and storing instructions for execution by the one or more processors for performing a method comprising:
• monitoring, by the one or more processors, in a computing system comprising a database resource, communications between one or more clients to a query engine, to identify requests from the one or more clients to the query engine to execute queries on the database resource;
• based on identifying a requested query destined for execution by the query engine at a given time, applying, by the one or more processors, cognitive analysis algorithms to parse components of the requested query, to identify components in the requested query that indicate an execution success measure for the requested query, wherein the execution success measure is selected from the group consisting of:
• a prediction indicating an anticipated failure based on executing the requested query at the given time and a prediction indicating an anticipated success based on executing the requested query at the given time;
• determining, by the one or more processors, the execution success measure for the requested query at the given time and assigning an execution action to the requested query, based on the execution success measure, wherein the execution action is selected from the group consisting of:
• pre-empting the requested query based on the execution success measure being the prediction indicating the anticipated failure and executing the requested query based on the execution success measure being the prediction indicating the anticipated success;
• and
• facilitating, by the one or more processors, the execution action, on the requested query.

A system comprising:

• a memory;
• one or more processors in communication with the memory;
• program instructions executable by the one or more processors via the memory to perform a method, the method comprising:
• monitoring, by the one or more processors, in a computing system comprising a database resource, communications between one or more clients to a query engine, to identify requests from the one or more clients to the query engine to execute queries on the database resource;
• based on identifying a requested query destined for execution by the query engine at a given time, applying, by the one or more processors, cognitive analysis algorithms to parse components of the requested query, to identify components in the requested query that indicate an execution success measure for the requested query, wherein the execution success measure is selected from the group consisting of:
• a prediction indicating an anticipated failure based on executing the requested query at the given time and a prediction indicating an anticipated success based on executing the requested query at the given time;
• determining, by the one or more processors, the execution success measure for the requested query at the given time and assigning an execution action to the requested query, based on the execution success measure, wherein the execution action is selected from the group consisting of:
• pre-empting the requested query based on the execution success measure being the prediction indicating the anticipated failure and executing the requested query based on the execution success measure being the prediction indicating the anticipated success;
• and
• facilitating, by the one or more processors, the execution action, on the requested query.