30 results about "Datalog" patented technology

A method for communicating test information from a source to a destination is disclosed. The method includes providing a modular test system, where the modular test system comprises a system controller for controlling at least one site controller, the at least one site controller for controlling at least one test module. The method further includes providing a datalog framework for supporting extension of user-defined datalog formats, providing support classes for supporting user-initiated datalog events, receiving a datalog event requesting for communicating input test information from the source to the destination, configuring output test information based upon the destination, the datalog framework and the support classes, and transferring the output test information to the destination.

What is disclosed are a novel system and method for inferring types of database queries. In one embodiment a program and associated database schema that includes a type hierarchy is accessed. The program includes query operations to a database that contains relations described by a database schema. Types are inferred from definitions in the program by replacing each database relationship in the program by the types in the database schema. A new program is generated with the types that have been inferred with the new program only accessing unary relations in the database. In another embodiment, testing of each of the types that have been inferred is performed for type emptiness. In response to type emptiness being found for a type that have been inferred, a variety of different operations are performing including removing the type, providing a notification regarding the emptiness found for the type, and more.

What is disclosed are a novel system and method for inferring types of database queries. In one embodiment a program and associated database schema that includes a type hierarchy is accessed. The program includes query operations to a database that contains relations described by a database schema. Types are inferred from definitions in the program by replacing each database relationship in the program by the types in the database schema. A new program is generated with the types that have been inferred with the new program only accessing unary relations in the database. In another embodiment, testing of each of the types that have been inferred is performed for type emptiness. In response to type emptiness being found for a type that have been inferred, a variety of different operations are performing including removing the type, providing a notification regarding the emptiness found for the type, and more.

The invention discloses a large-scale graph data query method in a distributed environment based on Datalog. The method comprises the following steps of: 1) performing grammatical analysis on a large-scale graph query instruction based on a Datalog rule set input by a user, and producing a corresponding grammatical tree; 2) constructing an execution plan in which a Datalog rule is used as a unit according to the grammatical tree, and constructing a corresponding Map execution function and a Reduce execution function according to each Datalog rule; and 3) implementing inter-rule optimization, inner-rule optimization and operation function optimization by using an equivalence rule and statistical data, and improving the efficiency of a large-scale graph query execution plan. By the large-scale graph data query method, the cost that a final user writes a graph query script is simplified; expanded recursion Daralog query is provided; and the user can express the corresponding large-scale graph query by using a simple description language. The invention also provides a method for constructing a MapReduce environment execution plan for recursion Daralog query. Datalog graph query can be executed under a MapReduce framework.

The invention discloses a query method and device for multidimensional data. The method comprises the steps that a table set meeting a query condition is acquired from multiple fact data tables, wherein the query condition comprises a query dimension chain, and the query dimension chain comprises at least one query dimension; to-be-distributed fields are distributed to the corresponding fact data tables in the table set to obtain a first target table set, wherein the to-be-distributed fields are needed column fields acquired from the query condition; a target filtering condition is sunk into a target data table in the first target table set to obtain a second target table set; a data structure used for reflecting a data flow process is generated according to a connection relation between the fact data tables in the second target table set; and a corresponding data query language is generated according to the data structure, and data query is executed through the data query language. Through the query method and device, the technical problem of low execution efficiency of multidimensional data query is solved.

The invention relates to an ontology query reasoning approximation method based on minimal explanation, which belongs to the field of artificial intelligence. The applicable object of the method is the datalog± ontology with strong expressive ability and wide application range. It is characterized in that the query for the datalog± ontology is automatically converted into a set of minimum interpretations whose length does not exceed the threshold specified by the user, and then directly accesses the ABox part of the ontology through each minimum interpretation to obtain the respective query answer sets. The union of these sets is a subset of the original query answer set, and its closeness to the original set is controlled by the minimum interpretation length threshold. The key to the method is to automatically compile the TBox part of the datalog± ontology into a Prolog program that can receive joint queries from users, and invoke the efficient Prolog system to automatically calculate all the minimum explanations whose length does not exceed the threshold specified by the user. The overall data complexity of the method is polynomial time. The invention is applicable to various application occasions based on datalog± ontology, and provides efficient information query service for these occasions.

The embodiment of this specification provides a data query method and device, the method includes: acquiring the first sentence used for data query of the data storage system, the first sentence is based on natural language; determining the natural semantics of the first sentence, the natural semantics Including the query condition on which the data query is based, and a description of the target data item that the data query is intended to obtain; based on natural semantics, a query logic tree is generated, and the query logic tree indicates an intermediate logical step for obtaining the target data item according to the query condition, Moreover, the intermediate logic steps have nothing to do with the data storage structure; according to the query logic tree, the second statement based on the data query language is generated.

The invention discloses a data multi-dimensional query method and apparatus. The method comprises the steps of obtaining a query condition, wherein the query condition comprises a dimension analysis chain and to-be-queried indexes, and the dimension analysis chain consists of at least one dimension and is used for filtering a plurality of fact data tables; obtaining the fact data tables associated with the query condition, thereby obtaining an associated fact data table set; generating an analytic tree according to connection relationships of the fact data tables in the associated fact data table set, wherein the analytic tree is generated by the query condition and the connection relationships and used for reflecting a data structure of a data flow process; and generating a corresponding data query language according to the analytic tree, and executing query processing through the data query language. Through the method and the apparatus, the problem of relatively low efficiency of data multi-dimensional query is solved.