Peter Mork - Rockville MD, US Adriane Chapman - Arlington VA, US Ken Samuel - McLean VA, US Irina Vayndiner - Oak Hill VA, US David Moore - Manassas VA, US
Assignee:
The MITRE Corporation - McLean VA
International Classification:
G06F 11/00
US Classification:
714 37, 714 25, 707713
Abstract:
Methods, systems and computer program products for detecting anomalies for a database system are provided. A method may include extracting workload features from a query optimizer based on a query workload and generating feature models for the extracted workload features. The method may also include extracting instance features from the query optimizer based on a query instance. Instance feature values may be obtained. The method may further include applying a query instance to the workload feature models to produce a prediction value for each workload feature. Anomalies may be reported based on a comparison of each instance feature value with a corresponding prediction value. A system for detecting anomalies for a database system may include a query optimizer, a feature modeler and an anomaly detector.
Interactive Schema Translation With Instance-Level Mapping
Philip Bernstein - Bellevue WA, US Sergey Melnik - Kirkland WA, US Peter Mork - Rockville MD, US
Assignee:
Microsoft Corporation - Redmond WA
International Classification:
G06F 7/00
US Classification:
707100000
Abstract:
A system and method facilitating data access operations is provided. The system can facilitate an executable, instance-level interaction between a source model (e.g., schema) expressed in a first metamodel (e.g., object-oriented metamodel) and a target model expressed in a second metamodel (e.g., SQL metamodel). The system can produce instance mappings to round-trip the data between the source schema and the generated target schema. For example, the system can support object-to-relational mapping scenarios that are common in business applications. Typically, in such applications the business logic runs on top of an object model, whereas the actual data is persisted in SQL databases. To shield the applications from impedance mismatch and storage management issues, an abstraction component can be employed to translate the data access operations on the object model into SQL queries and updates.
Tools And Methods For Semi-Automatic Schema Matching
Leonard J. Seligman - Silver Spring MD, US Peter D.S. Mork - Rockville MD, US Joel G. Korb - Arlington VA, US Kenneth B. Samuel - McLean VA, US Christopher S. Wolf - Fairfax VA, US
International Classification:
G06F 7/00 G06F 17/00
US Classification:
707101
Abstract:
Tools and methods for schema matching that generate schema graphs, populate match matrices and display the schema graphs and the match matrices. These tools and methods characterize potential matches between disparate schemata in terms of both a strength of evidence indicating the potential match and an amount of evidence indicating the potential match. A number of match voters generate a set of match scores for each potential match, and these match scores are combined by a vote merger to form a single confidence value for each potential match. A number of filters display the confidence value for each potential match as a link on a graphical user interface. Machine-learning techniques may be employed to adaptively determine confidence values based on previously established matches.