Methods and systems for making effective use of system resources. A plurality of requests for access to a resource are received. Each request has an associated group of features. The group of features for each request is analyzed to collect observations about the plurality of requests. A function to predict an outcome of a subsequent request is generated based on the observations. Resources are allocated to service the subsequent request based on the function.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method comprising: receiving a plurality of requests for access to a resource with a training module of a database system provided by one or more computing devices, each request having an associated group of features to be mapped to classes in a database environment; generating a statistical model with the training module for each database instance within the database environment; predicting an execution time and a number of rows for a subsequent request based on the statistical model; and allocating resources in the database environment to service the subsequent request based on the predicted execution time and number of rows. 2. The method of claim 1 wherein the plurality of requests comprises database queries. 3. The method of claim 1 wherein the group of features comprises: a number of nested joins in the request; a number of hash joins in the request; and a sum of cardinalities for hash joins in the request. 4. The method of claim 1 wherein the group of features comprises: a cardinality estimate of a main table; a storage count of the main table; and a selectivity estimate of the main table. 5. The method of claim 1 wherein the group of features comprises a number of secondary queries in the request. 6. The method of claim 1 wherein the group of features comprises: an application server processor state; and an application server memory state. 7. The method of claim 1 wherein the group of features comprises: a database processor state; and a number of tables used. 8. A non-transitory computer readable medium having stored there on instructions that, when executed, cause one or more processors to: receive a plurality of requests for access to a resource with a training module of a database system provided by one or more computing devices, each request having an associated group of features to be mapped to classes in a database environment; generate a statistical model with the training module for each database instance within the database environment; predict an execution time and a number of rows for a subsequent request based on the statistical model; and allocate resources in the database environment to service the subsequent request based on the predicted execution time and number of rows. 9. The non-transitory computer-readable medium of claim 8 wherein the plurality of requests comprises database queries. 10. The non-transitory computer-readable medium of claim 8 wherein the group of features comprises: a number of nested joins in the request; a number of hash joins in the request; and a sum of cardinalities for hash joins in the request. 11. The non-transitory computer-readable medium of claim 8 wherein the group of features comprises: a cardinality estimate of a main table; a storage count of the main table; and a selectivity estimate of the main table. 12. The non-transitory computer-readable medium of claim 8 wherein the group of features comprises a number of secondary queries in the request. 13. The non-transitory computer-readable medium of claim 8 wherein the group of features comprises: an application server processor state; and an application server memory state. 14. The non-transitory computer-readable medium of claim 8 wherein the group of features comprises: a database processor state; and a number of tables used. 15. A system comprising one or more server systems communicatively coupled with one or more user systems to receive a plurality of requests for access to a resource with a training module of a database system provided by one or more computing devices, each request having an associated group of features to be mapped to classes in a database environment, to generate a statistical model with the training module for each database instance within the database environment, to predict an execution time and a number of rows for a subsequent request based on the statistical model, and to allocate resources in the database environment to service the subsequent request based on the predicted execution time and number of rows. 16. The system of claim 15 wherein the plurality of requests comprises database queries. 17. The system of claim 15 wherein the group of features comprises: a number of nested joins in the request; a number of hash joins in the request; and a sum of cardinalities for hash joins in the request. 18. The system of claim 15 wherein the group of features comprises: a cardinality estimate of a main table; a storage count of the main table; and a selectivity estimate of the main table. 19. The system of claim 15 wherein the group of features comprises a number of secondary queries in the request. 20. The system of claim 15 wherein the group of features comprises: an application server processor state; and an application server memory state. 21. The system of claim 15 wherein the group of features comprises: a database processor state; and a number of tables used.