Fast processing of an XML data stream

• US 20080082484A1
• Filed: 09/28/2006
• Published: 04/03/2008
• Est. Priority Date: 09/28/2006
• Status: Abandoned Application

• Current Assignee: Ramot at Tel Aviv University Limited (Tel Aviv University)
• Original Assignee: Ramot at Tel Aviv University Limited (Tel Aviv University)
• Inventors: Averbuch, Amir, Harussi, Shachar
• Application Number:
  US11/528,568
• Publication Number:
  US 20080082484A1
• Time in Patent Office: Days
• US Class Current: 707/3
• CPC Class Codes: G06F 16/8373 Query execution

Abstract

To answer one or more queries of semistructured data, an answer automaton is constructed, based at least in part on the queries and on a schema of the data. The answer automaton is applied to the data to answer the queries. Preferably, to construct the answer automaton, a schema automaton is constructed for the schema, a query automaton is constructed for the queries, and the schema automaton and the query automaton are merged. If there are more than one query, separate query automata are constructed for the different queries and then are united to provide a joint query automaton. Preferably, all the automata are deterministic finite automata. Most preferably, all the automata are isostate automata.

Claims

1. A method of answering a query of semistructured data, comprising the steps of:

(a) constructing an answer automaton, based at least in part on the query and on a schema of the data; and

(b) applying said answer automaton to the data to answer the query.

2. The method of claim 1, wherein said constructing is effected by steps including:

(i) constructing a schema automaton for said schema;

(ii) constructing a query automaton for the query; and

(iii) merging said schema automaton and said query automaton to provide said answer automaton.

3. The method of claim 2, wherein said merging is effected by forming an intersection of said schema automaton and said query automaton.

4. The method of claim 2, wherein said automata are deterministic finite automata.

5. The method of claim 4, wherein said automata are isostate automata.

6. The method of claim 5, wherein said schema automaton first is constructed as a finite automaton that accepts an alphabet and then said alphabet is mapped into a set of transition indices that accept said alphabet, thereby transforming said finite automaton into an isostate automaton.

7. The method of claim 1, wherein said answer automaton is a deterministic finite automaton.

8. The method of claim 7, wherein said answer automaton is a isostate automaton.

9. The method of claim 1, further comprising the step of:

(c) building said schema from the data.

10. The method of claim 1, wherein said applying includes parsing the data, using said answer automaton, to provide a matched context.

11. The method of claim 10, wherein said applying also includes calculating a Boolean expression, that is included in the query, on a textual value of said matched context.

12. The method of claim 10, wherein said constructing is effected by steps including constructing a schema automaton for said schema, using a parser generator that also produces parser tables corresponding to the schema, and wherein said parsing of the data includes using said parser tables to parse the data, thereby producing parser symbols, followed by parsing said parser symbols, using said answer automaton.

13. The method of claim 1, wherein said constructing includes removing redundant symbols from said answer automaton.

14. The method of claim 1, further comprising the steps of:

(c) constructing a parsing table for the data, based on said schema; and

(d) validating the data, prior to said applying, using said parsing table.

15. A method of answering a plurality of queries of semistructured data, comprising the steps of:

(a) constructing an answer automaton, based at least in part on the queries and on a schema of the data; and

(b) applying said answer automaton to the data to answer the queries.

16. The method of claim 15, wherein said constructing is effected by steps including:

(i) constructing a schema automaton for said schema;

(ii) constructing a joint query automaton for the queries; and

(iii) merging said schema automaton and said joint query automaton to provide said answer automaton.

17. The method of claim 16, wherein said constructing of said joint query automaton is effected by steps including:

(A) for each query, constructing a respective query automaton; and

(B) uniting said query automata to provide said joint query automaton.

18. A device for processing semistructured data, comprising:

(a) a memory for storing executable code for answering at least one query of the data, said executable code including;

(i) executable code for constructing an answer automaton, based at least in part on said at least one query and on a schema of the data, and

(ii) executable code for applying said answer automaton to the data to answer said at least one query; and

(b) a processor for executing said executable code.

19. The device of claim 18, further comprising:

(c) a network interface for receiving the data from a network.

20. A computer-readable storage medium having computer-readable code embodied on said computer-readable storage medium, the computer-readable code for answering at least one query of semistructured data, the computer-readable code comprising:

(a) program code for constructing an answer automaton based at least in part on a schema of the data and on the at least one query; and

(b) program code for applying said answer automaton to the data to answer said at least one query.

21. A system for answering a query of semistructured data, comprising:

(a) a schema automaton constructor for constructing a schema automaton for a schema of the data;

(b) a query automaton constructor for constructing a query automaton for the query;

(c) an answer automaton constructor for merging said schema automaton and said query automaton to provide an answer automaton; and

(d) an answer automaton engine for applying the answer automaton to the data to answer the query.

22. The system of claim 21, further comprising:

(e) a schema constructor for constructing said schema from the data.

23. The system of claim 21, wherein said schema automaton constructor includes a parser generator for generating at least one parse table for the data, the system further comprising:

(e) a parser for using said at least one parse table to validate the data.

24. The system of claim 21, wherein said answer automaton parses the data to provide a matched context, the system further comprising:

(e) a text matcher for calculating a Boolean expression, that is included in the query, on a textual value of said matched context.

25. The system of claim 21, wherein said schema automaton constructor, said query automaton constructor, said answer automaton constructor and said answer automaton engine are implemented in a single common device.

26. The system of claim 21, wherein said schema automaton constructor, said query automaton constructor, said answer automaton constructor and said answer automaton engine are implemented in respective members of a plurality of devices that are operationally coupled by a network.

27. An apparatus for answering a plurality of queries of semistructured data, comprising:

(a) a schema automaton constructor for constructing a schema automaton for a schema of the data;

(b) a query automaton constructor for constructing respective query automata for the queries;

(c) a query automaton unite engine for uniting said query automata to provide a joint query automaton;

(d) an answer automaton constructor for merging said schema automaton and said joint query automaton to provide an answer automaton; and

(e) an answer automaton engine for applying the answer automaton to the data to answer the queries.

28. The apparatus of claim 27, wherein said schema automaton constructor, said query automaton constructor, said query automaton unite engine, said answer automaton constructor and said answer automaton engine are implemented in a single common device.

29. The apparatus of claim 27, wherein said schema automaton constructor, said query automaton constructor, said query automaton unite engine, said answer automaton constructor and said answer automaton engine are implemented in respective members of a plurality of devices that are operationally coupled by a network.

30. A method of answering a query of semistructured data, comprising the steps of:

(a) constructing an answer automaton, based at least in part on the query, said constructing including removing redundant symbols from said answer automaton; and

(b) applying said answer automaton to the data to answer the query.

31. A device for processing semistructured data, comprising:

(a) a memory for storing executable code for answering a query of the data, said executable code including;

(i) executable code for constructing an answer automaton, based at least in part on said query, said constructing including removing redundant symbols from said answer automaton, and

(ii) executable code for applying said answer automaton to the data to answer said query; and

(b) a processor for executing said executable code.

32. The device of claim 31, further comprising:

(c) a network interface for receiving the data from a network.

33. A computer-readable storage medium having computer-readable code embodied on said computer-readable storage medium, the computer-readable code for answering a query of semistructured data, the computer-readable code comprising:

(a) program code for constructing an answer automaton, based at least in part on the query, said constructing including removing redundant symbols from said answer automaton; and

(b) program code for applying said answer automaton to the data to answer the query.

34. A system for answering a query of semistructured data, comprising:

(a) an answer automaton constructor for constructing an answer automaton, based at least in part on the query, said constructing including removing redundant symbols from said answer automaton; and

(b) an answer automaton engine for applying said answer automaton to the data to answer the query.

35. A method of answering a query of semistructured data, comprising the steps of:

(a) constructing, for the query, a finite query automaton that accepts an alphabet;

(b) mapping said alphabet into a set of transition indices of said finite query automaton, thereby transforming said finite query automaton into an isostate query automaton;

(c) transforming said isostate query automaton into an answer automaton; and

(d) applying said answer automaton to the data to answer the query.

36. A device for processing semistructured data, comprising:

(a) a memory for storing executable code for answering a query of the data, said executable code including;

(i) executable code for constructing, for said query, a finite query automaton that accepts an alphabet,

(ii) executable code for mapping said alphabet into a set of transition indices of said finite query automaton, thereby transforming said finite query automaton into an isostate query automaton,

(iii) executable code for transforming said isostate query automaton into an answer automaton, and

(iv) executable code for applying said answer automaton to the data to answer said query; and

(b) a processor for executing said executable code.

37. The device of claim 36, further comprising:

(c) a network interface for receiving the data from a network.

38. A computer-readable storage medium having computer-readable code embodied on said computer-readable storage medium, the computer-readable code for answering a query of semistructured data, the computer-readable code comprising:

(a) program code for constructing, for the query, a finite query automaton that accepts an alphabet;

(b) program code for mapping said alphabet into a set of transition indices of said finite query automaton, thereby transforming said finite query automaton into an isostate query automaton;

(c) program code for transforming said isostate query automaton into an answer automaton; and

(d) program code for applying said answer automaton to the data to answer the query.

39. A system for answering a query of semistructured data, comprising:

(a) a query automaton constructor for;

(i) constructing, for the query, a finite query automaton that accepts an alphabet, and

(ii) mapping said alphabet into a set of transition indices of said finite query automaton, thereby transforming said finite query automaton into an isostate query automaton;

(b) an answer automaton constructor for transforming said isostate query automaton into an answer automaton; and

(c) an answer automaton engine for applying said answer automaton to the data to answer the query.