Query comprehensions

• US 7,730,079 B2
• Filed: 08/30/2005
• Issued: 06/01/2010
• Est. Priority Date: 08/30/2005
• Status: Expired due to Fees

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Hejlsberg, Anders, Vick, Paul A., Meijer, Henricus Johannes Maria, Silver, Amanda
• Primary Examiner(s): Alam; Shahid A
• Assistant Examiner(s): NGUYEN, PHONG H
• Application Number:
  US11/215,089
• Publication Number:
  US 20070050347A1
• Time in Patent Office: 1,736 Days
• Field of Search: 707/2, 707/3, 707/4, 707/5, 707/101, 707/104.1, 707/999.002, 707/999.003, 707/999.004, 707/999.005, 707/999.101, 707/999.107, 715/968
• US Class Current: 707/760
• CPC Class Codes: G06F 16/332 Query formulation
• CPC Class Codes: Y10S 715/968 interface for database querying and retrieval

Abstract

The subject disclosure pertains to interaction with one or more collections of data. Queries and domains are presented as separate entities. A number of compositional operators are provided to manipulate a generic collection of data at a low level. Query comprehensions can specify interactions with one or more collections at a higher or more intuitive level. The query comprehensions can be translated or mapped to operators that can be employed to interact with one or more data collections and return results where applicable.

Claims

1. A computer-implemented data query system comprising the following computer executable components:

a processor communicatively coupled to a memory having stored thereon a query component that receives a query comprehension that provides a compositional mechanism for specifying expressions of queries, wherein the compositional mechanism enables individual sub-expressions of a particular query to be understood in isolation from other sub-expressions of the query, and wherein the compositional mechanism of the query comprehension specifies a query that is independent of language type, data type, and shape type on which actions are to be performed;

a translation component that translates the query comprehension into a plurality of different sets of primitive operators, the different sets of primitive operators including sequence operators that provide operations including filtering, mapping, transforming, accumulation, and folding, the plurality of different sets of primitive operators including a first set of primitive operators configured for operations on a first language type, a first data type, and a first shape type, and a second set of primitive operators configured for operations on a second language type, a second data type, and a second shape type, wherein the second language type, data type, and shape type are different from the first language type, data type, and shape type, wherein the translation component includes an inference component that infers types associated with the query comprehension, the inference component including an artificial intelligence element that includes one or more of a support vector machine, a neural network, an expert system, a Bayesian belief network, fuzzy logic, data fusion engines, and classifiers;

the processor executing the first set of primitive operators on a first data collection to evaluate data included in the first data collection in accordance with the query specified by the query comprehension;

the processor executing the second set of primitive operators on a second data collection to evaluate data included in the second data collection in accordance with the query specified by the query comprehension; and

a component for returning results of the evaluation of data included in the first collection and results of the evaluation of data included in the second collection.

2. The system of claim 1, wherein evaluation of the data from the first and second data collections comprises retrieving the data and/or manipulating the data.

3. The system of claim 2, the translation component includes a map component that maps query comprehension elements to the first set of primitive operators and to the second set of primitive operators.

4. The system of claim 2, the first and/or second data collections are one of relational and XML data or objects.

5. The system of claim 2, wherein the first data collection is a non-relational data collection, wherein the query comprehension is specified in a SQL style format and the processor component executes the first set of primitive operators on the first data collection.

6. The system of claim 1, further comprising an abbreviation component that receives an abbreviation and translates the abbreviation into a query comprehension.

7. The system of claim 6, further comprising a generation component that facilitates production of a user-defined abbreviation and a map component that persists mapping information with respect to the defined abbreviation and query comprehension elements.

8. The system of claim 6, the abbreviation denotes one or more of accumulation, aggregation, naming, grouping, ordering, mapping, flattening results, and a query fragment.

9. A computer-implemented query processing method comprising the following computer executable acts:

acquiring a query comprehension that specifies a query over first and second generic collections of data wherein the query comprehension provides a compositional mechanism for specifying expressions of queries, wherein the compositional mechanism enables individual sub-expressions of a particular query to be understood in isolation from other sub-expressions of the query, and wherein the compositional mechanism of the query comprehension specifies a query that is independent of language type, data type, and shape type on which actions are to be performed;

translating the query comprehension to a first set of one or more primitive operators configured for operations on a first language type, a first data type, and a first shape type and that are able to interact with the first generic collection of data, wherein the one or more primitive operators include sequence operators that provide operations including filtering, mapping, transforming, accumulation, and folding;

translating the query comprehension to a second set of one or more primitive operators configured for operations on a second language type, a second data type, and a second shape type and that are able to interact with the second generic collection of data, wherein the second language type, data type and shape type are different from the first language type, data type and shape type, and wherein the translating is performed by a translation component that includes an inference component that infers types associated with the query comprehension, the inference component including an artificial intelligence element that includes one or more of a support vector machine, a neural network, an expert system, a Bayesian belief network, fuzzy logic, data fusion engines, and classifiers;

executing the first set of one or more primitive operators on the first generic collection of data to evaluate data included in the first generic collection of data in accordance with the query specified by the query comprehension;

executing the second set of one or more primitive operators on the second generic collection of data to evaluate data included in the second generic collection of data in accordance with the query specified by the query comprehension; and

returning results of the evaluation of data included in the first collection and results of the evaluation included in the second collection for storage in system memory at a computer system.

10. The method of claim 9, wherein evaluation of the data from the first and second generic collections of data comprises retrieving the data and/or manipulating the data.

11. The method of claim 9, the first and/or second set of operators retrieve data from one of a relational and XML source and objects.

12. The method of claim 9, the first and/or second set of operators retrieve data from multiple sources.

13. The method of claim 9, further comprising:

acquiring a query abbreviation; and

translating the query abbreviation to a query comprehension.

14. The method of claim 13, further comprising receiving a user defined query abbreviation that maps to a query comprehension.

15. The method of claim 9, further comprising type checking a query comprehension when the type of the collection is denoted explicitly and/or inferred.

16. The method of claim 15, type checking comprises statically type checking a query comprehension.