30 results about "Logical query" patented technology

In some embodiments, there is provided generating a logical query plan for a query that includes a single fact table and multiple reducer tables; optimizing the logical query plan for query execution; and executing the optimized logical query plan.

The invention provides an enhanced symmetric searchable encryption method and system, and relates to the field of data security and privacy protection. The method comprises the steps that a plaintext document set is symmetrically encrypted, keywords are extracted, and an encryption index token is generated through a pseudo-random function; constructing a reverse index structure, and mapping the token to a document identifier; dynamic insertion, deletion and modification of documents are supported, and indexes are synchronously updated in real time; cipher query is realized by generating a search token, and after the server returns a matching result, the client decrypts the matching result to obtain an original text. According to the system, through multi-keyword Boolean logic query, an index structure is compressed by adopting a Bloom filter, the retrieval efficiency is improved in combination with a jump pointer or a B + tree, a false query strategy is introduced to hide an access mode, and the anti-attack ability is enhanced. Compared with an existing scheme, the method has the advantages that the searchability, the system performance and the privacy protection capability of the encrypted data are improved, and the method is suitable for security data retrieval application in cloud computing, database systems and block chain environments.

The application provides a database instruction statement execution method, device and equipment and a readable storage medium, which can be applied to the technical field of computers, and comprises the following steps: analyzing a database instruction statement to obtain a plurality of syntax structures of the database instruction statement and semantics of the plurality of syntax structures; constructing a target abstract syntax tree according to a predetermined mapping relationship; performing semantic analysis on the target abstract syntax tree to obtain a logical query plan tree; optimizing logical operators corresponding to standard nodes and extended nodes in the logical query plan tree according to preset optimization strategies matched with node types until the logical query plan tree no longer changes, to generate a physical execution plan tree; and executing physical execution operators corresponding to the standard nodes and the extended nodes in the physical execution plan tree according to preset execution strategies matched with node types, to obtain an execution result of the database instruction statement.

The invention discloses a building vector graph multi-scene intelligent simplification method and system, and belongs to the technical field of geographic information systems. Comprising the following steps: establishing a four-level data system comprising an original data layer, an engineering cache layer, a display cache layer and a terminal view layer; monitoring data change and user interaction events through an event bus; the event is responded, the current application scene is intelligently recognized, and the corresponding simplified parameter configuration is dynamically loaded; based on the configuration, executing simplification logic on the target building vector graph; querying a topological relation to carry out cooperative processing on the contours of the adjacent buildings; and synchronously updating a processing result to the four-level data system. Through four-stage data caching, dual-drive triggering and scene self-adaptive judgment, efficient, high-quality and self-adaptive processing of building simplification in multiple scenes such as cartographic integration, real-time display and spatial analysis is realized, and the system flexibility, the resource utilization rate and the user experience are improved.

The invention provides a data query method and device, equipment and a medium, and relates to the technical field of computer software, in particular to the technical field of databases. The method comprises the steps that a logic query request for a logic wide table is received, the logic wide table is constructed based on multiple physical tables, and multiple groups of dependency relationships exist among the multiple physical tables; analyzing the logic query request to determine a to-be-queried target table in a plurality of physical tables; sorting the plurality of groups of dependencies to obtain a global dependency sequence and a reference table in the plurality of physical tables; on the basis of the topological structure, determining a necessary dependence path from the reference table to the target table; respectively converting at least one necessary dependency relationship included in the necessary dependency path into physical table connection relationships, and sequentially combining the physical table connection relationships according to the sequence of the at least one necessary dependency relationship in the global dependency relationship sequence to obtain a physical query statement; and performing data query by utilizing the physical query statement.

The invention provides a database access method and system supporting unified authentication and business model mapping, and the method comprises the steps: uniformly converting a query request into a standard abstract syntax tree, and intercepting an identity certificate in the query request to construct a complete authority context object; mapping the permission context object into a temporary role name with the minimum required permission, and sending the temporary role name to a key management system to generate a temporary database connection voucher; the permission context object is received, and a specific RLS predicate character string and a CLS function expression are generated based on a preset RBAC strategy rule, an RLS constraint predicate template and a CLS constraint desensitization function template; based on the business model, mapping the standard abstract syntax tree to generate an initial logic query plan; and according to the RLS predicate character string and the CLS function expression, forcibly solidifying the security policy into the initial logic query plan to generate a target logic query plan. The technical problem that authentication and authorization mechanisms are separated in the prior art is solved.

In some embodiments, there is provided generating a logical query plan for a query that includes a single fact table and multiple reducer tables; optimizing the logical query plan for query execution; and executing the optimized logical query plan.

The invention relates to a query execution method and device for a heterogeneous distributed database and electronic equipment. The method comprises the steps that after an SQL query request initiated by a service application is received, the SQL query request is converted into a logic query plan; generating a plurality of candidate physical execution plans which aim at each database operator in the logic query plan and comprise different target computing nodes; for each candidate physical execution plan, combining the operator type, the data volume, the expected performance information of the target computing node and the real-time load information, performing cost evaluation to obtain the corresponding total cost; determining the candidate physical execution plan with the lowest total cost in all the candidate physical execution plans as a target execution scheme; and instantiating the target execution scheme into a distributed execution plan with a computing node identifier, and scheduling a distributed execution engine to execute the distributed execution plan. The technical problem that resource utilization is low in efficiency due to the fact that an optimizer lacks hardware perception is solved.

The invention discloses a method for solving complex query containing numerical values in knowledge graph reasoning. The method comprises the following steps: 1) establishing a model of complex logic query containing numerical values; the model comprises a numerical value-entity predictor and an entity filter; wherein the numerical value-entity predictor is used for deriving a numerical value, an entity or a statistic of a given sub-query; the entity filter is used for comparing the numerical value of the sub-query prediction with the entity attribute value obtained by calculation, and filtering out entities meeting constraints on the knowledge graph by taking the numerical value of the sub-query prediction as a constraint value; according to the method, the complex query related to statistics and the query with numerical constraint can be effectively processed, and the complex query related to statistics and the query with numerical constraint can be effectively processed.

The invention relates to the technical field of data processing, can be applied to the fields of medical health, financial science and technology and the like, and discloses a real-time data intelligent query method, device and equipment and a storage medium. The real-time data intelligent query method comprises the steps that multiple heterogeneous data sources are registered, field names, data types and service meanings in the heterogeneous data sources are recognized, and preliminary semantic fingerprints are generated; based on the preliminary semantic fingerprints, constructing multilayer semantic mapping; receiving a query request of a user, analyzing the query request based on the multilayer semantic mapping, and generating a logic query plan; acquiring a real-time data source state, and based on the logic query plan, performing dynamic path selection in combination with the real-time data source state to generate a cross-source query plan; and executing the cross-source query plan, obtaining query results of the heterogeneous data sources, performing result fusion on all the query results through the semantic consistency alignment model, and outputting a fusion result in a unified format. By means of the method, intelligent semantic association and real-time optimization access of cross-source data are achieved.

This invention discloses a conversational business query method and system based on permission semantic parsing and dynamic desensitization backtracking. The method receives multiple rounds of business queries from users; parses user identity, position, organizational level, authorized data domain, field sensitivity level, and display granularity into permission semantic vectors, and aligns them with a query semantic graph to form a permission envelope; generates candidate logical queries based on the query semantic graph, and constructs a fragment backtracking key for each answer fragment, including field source, aggregation function, filter condition hash value, permission version, desensitization rule version, minimum display granularity, and session inheritance tag; when there is follow-up questioning, error correction, drill-down, or permission changes, the fragment backtracking key is compared and the permission residual change is calculated, driving the fragment security state machine to execute valid, pending recalculation, frozen, downgraded, or rejected display. This method can improve the security, traceability, and interactive continuity of business query results.

To improve the technological process of computerized answering of logical queries over incomplete knowledge bases, obtain a first order logic query; with a trained, computerized neural network, convert the first order logic query into a logic embedding; and answer the first order logic query using the logic embedding.

Methods, systems, and computer programs are presented for generating and managing query plan representations using a unified framework based on a common query plan configuration. The system includes a memory with instructions and one or more computer processors. The instructions, when executed, cause the system to provide a user interface (UI) for a development tool to create a configuration for a plan builder. The UI offers options to create a plurality of query plans, including a logical query plan, a physical query plan, a query plan hash, and a query plan signature. The system receives parameters to create the configuration and select a query plan from the plurality of query plans. The system generates a first query plan based on the parameters and causes the presentation of the first query plan on a display.

The invention provides a database instruction statement execution method, device and equipment and a readable storage medium, which can be applied to the technical field of computers, and the method comprises the following steps: analyzing a database instruction statement to obtain a plurality of grammar structures of the database instruction statement and semantics of the plurality of grammar structures; constructing a target abstract syntax tree according to a predetermined mapping relation; performing semantic analysis on the target abstract syntax tree to obtain a logic query plan tree; according to a preset optimization strategy matched with the node type, logic operators corresponding to standard nodes and expansion nodes in the logic query plan tree are optimized until the logic query plan tree does not change any more, and a physical execution plan tree is generated; according to a preset execution strategy matched with the node type, physical execution operators corresponding to the standard nodes and the extension nodes in the physical execution plan tree are executed, and an execution result of the database instruction statement is obtained.

The invention discloses a temporal feature knowledge graph logic query answering method, medium and equipment, and the method comprises the steps: taking fixed entity embedding as input according to the post-order traversal of a query calculation tree, carrying out query single-hop projection operation when a projection operator is traversed, and converting entity embedding or query embedding into next-hop query embedding; when negative operators are traversed, complementation is carried out, and when intersection or union operators are traversed, query embedded input of the shunt pairs and relation feature vectors of the shunt pairs are extracted; mapping the semantic similarity of the relation feature vectors into initial weights of the three logic systems; splicing query embedding and relation feature vectors, inputting the spliced query embedding and relation feature vectors into MLP, and calculating dynamic weights of the three logic systems; generating a mixed weight of the three logic systems by utilizing a gating mechanism to obtain query embedding; and calculating a query score according to the query embedding and each entity embedding to obtain a query answer set. The problem that the query precision is restricted by a fixed logic strategy is solved.

The invention relates to the technical field of big data processing, in particular to a method for automatically converting query statements among heterogeneous databases, which comprises the following steps of: firstly, analyzing and reconstructing a logic query request of a user to obtain a logic query object, and carrying out information association and matching by using components of the logic query object; therefore, the optimal physical table and the corresponding target data source engine can be quickly found out, and the problem of low response speed caused by direct query in the prior art is solved; on the basis, after the optimal physical table and the corresponding target data source engine are obtained, the heterogeneous data type can be automatically converted into a preset unified data type, so that the problem of compatibility error reporting caused by cross-database is solved. Compared with the prior art, the method has the advantages that the optimal physical carrier can be automatically selected on the basis of semantic analysis, data processing of dialect-level grammar conversion is accurately completed, and query efficiency and universality between heterogeneous databases are improved.

The application discloses a kind of collaborative filtering methods based on logic box embedding inference, comprising the following steps: S1, original data is collected and data set is made;S2, original data is cleaned and handled, and user interaction sequence and score sequence are generated;S3, user interaction sequence and score sequence generate first-order logic query, and then generate logic calculation graph;S4, user interaction sequence generates multiple item box embedding, and score sequence generates multiple relationship vector embedding according to user interaction behavior and score in logic calculation graph;S5, item box embedding and relationship vector embedding are calculated according to logic calculation graph to obtain a target item box embedding;S6, the distance between target item box embedding and the nearest item box embedding is calculated, and the nearest n items are recommended to the current user as the most suitable project.This method can effectively integrate the recommendation algorithm framework of collaborative filtering and logical reasoning, effectively improve the performance of recommendation, and provide a new idea for subsequent engineering application.

The embodiment of the invention provides a streaming data query processing method and device, a storage medium and a program product, and relates to the field of data processing. In the query processing method, when a query statement of any target data in a data stream is processed, a non-equivalence space condition in a target query clause is rewritten, so that the rewritten query statement does not contain a non-equivalence relation, and therefore, in the process of generating a logic query plan, the query statement of any target data in the data stream is not subjected to the non-equivalence relation. The rewritten query statement can bypass the error report of the non-equivalence relation in the optimization stage. On the basis, the non-equivalence relation corresponding to the equivalence condition is recorded, the query operation corresponding to the query statement is executed according to the non-equivalence relation and the logic query plan, and the real relation of the space condition can be applied to the query process, so that the query result is matched with the real relation of the space condition; therefore, accurate query of non-equivalent space conditions is realized in a streaming data processing scene.

The application discloses a kind of based on permission semantic analysis and dynamic desensitization backtracking dialog business question method and system.The method receives user multi-round business question sentence;User identity, post, organizational level, authorized data domain, field sensitive level and displayable granularity are parsed into permission semantic vector, and are aligned with question semantic graph to form permission envelope;Based on question semantic graph, generate candidate logic query, and construct segment backtracking key for answer fragment, including field source, aggregation function, filter condition hash value, permission version, desensitization rule version, minimum display granularity and session inheritance mark;When follow-up question, error correction, drill down or permission changes, compare segment backtracking key and calculate permission residual change, drive segment safety state machine to execute effective, pending recalculation, frozen, degraded or refuse to display.The method can improve the security, traceability and interaction continuity of business question result.

This provides a computer-implemented method for responding to primary logical queries based on a knowledge graph. [Solution] The method includes supplying a knowledge graph and a primary logical query (302). The logical query defines logical operations on a first triplet and a second triplet. The method also includes, depending on the logical query, determining a directed acyclic computation graph in particular for the logical query (304). The computation graph defines the order in which rotation operations are performed. The method further includes determining a response to the logical query (306). Determining the response includes applying rotation operations to cone embeddings in the order defined by the computation graph.

The invention discloses a distributed query method and system based on a Pipeline model, belongs to the technical field of databases, and aims to solve the technical problem of how to improve query response speed and assembly line processing capacity for a time sequence database. Comprising the following steps: mapping a logic query plan into a physical query plan with a standardized Next interface based on a volcano model operator hierarchical architecture; the method comprises the following steps: splitting a physical query plan into a plurality of Pipeline Tasks based on time slices and operator complexity, and scheduling the Pipeline Tasks in a pull mode of a volcano model; based on the task type and the system load, setting a CPU time slice threshold value, dynamically adjusting the threshold value, and when the task execution time exceeds the CPU time slice threshold value, swapping out the currently executed task; and data transmission and query collaborative operation among distributed nodes is realized through outbound and inbound which are used as operators in the volcano model.

The invention provides a data space construction and quick query method and device and a readable storage medium. The method comprises the following steps: preprocessing 5G-A general sensing multi-modal data; constructing a 5G-A general sensing adaptive knowledge hypergraph; carrying out hypergraph matrix processing; extracting a 5G-A scene association relationship; executing relational storage mapping; and executing 5G-A intelligent query. According to the method, entity-attribute-association complete data logic is constructed through knowledge hypergraph modeling, many-to-many high-order association of multi-modal data can be accurately borne, and association relationship expression of general sensing data better meets 5G-A scene requirements; a technical path of hypergraph matrix-relational storage mapping is designed, and the existing 5G-A application ecology can be quickly fused; according to the 5G-A communication-sensing integrated core characteristic, storage logic specially associated with sensing is reserved, service data can be directly output during query, and the limitation that only single-dimension data is output in an existing scheme is avoided.

Embodiments autonomously test a logical model for inconsistencies. For example, metadata describing a logical model can be received, where the logical model includes an abstraction of a database schema, the database schema is implemented at a database, and the database schema includes fact tables and dimension tables. Logical queries including at least a first logical query and a second logical query can be automatically generated based on the retrieved metadata, where the first logical query and the second logical query target logical objects of the logical model. The at least first logical query and the second logical query can be issued to a server hosting the logical model, where, at the server, the first logical query and the second logical query are transformed into first database queries and second database queries, and the first database queries and the second database queries target at least fact tables and dimension tables from the database schema. Query results received from execution of the first database queries and the second database queries can be compared. When the comparison of the query results does not satisfy a criterion, an inconsistency can be identified.

The application discloses a method and system for generating a distributed execution plan based on Q-learning and belongs to the technical field of distributed databases; the technical problem to be solved by the application is how to apply reinforcement learning to a database for generating an optimal distributed physical execution plan so as to improve query performance and response speed; and the technical scheme adopted is as follows: the method is as follows: generating a logical plan: generating a planNode logical plan node, and each SQL has a corresponding planNode; generating a distributed physical plan: generating a distributed physical plan according to the logical plan; specifically as follows: a query optimizer receives a SQL query, and a logical query plan is constructed according to the query statement; the logical query plan is converted into a distributed physical query plan; and a Q-learning algorithm is adopted for each candidate physical execution plan to generate an optimal agent selection and task allocation scheme.

This disclosure presents an HTAP database query optimization method, device, and storage medium that significantly improves query performance by combining the advantages of row-based and column-based storage. The method includes: parsing SQL queries to generate logical query plans; evaluating the execution cost of each logical operator under different storage modes using a hybrid cost model, where the hyperparameters of the hybrid cost model are optimized using Bayesian search; selectively using dynamic programming or a greedy algorithm based on the number of tables to generate a hybrid physical query plan with the lowest execution cost; and executing the plan to obtain the query results. Furthermore, this disclosure utilizes the MCTS algorithm to select the optimal subset of columns within a preset memory budget limit based on query history, further optimizing subsequent query performance. This disclosure solves the problem of incompatibility between row-based and column-based storage in existing HTAP systems, achieving operator-level hybrid execution while optimizing memory resource utilization.

The application discloses a collaborative query processing method and system based on declarative reasoning, and electronic equipment, comprising the following steps: S1, inputting a query text into a syntax analyzer to obtain a syntax analysis tree, then replacing nodes and structures in the syntax analysis tree by using relational algebra operators to generate a relational algebra expression, and performing equivalent conversion by using algebra laws to obtain a logical query plan; S2, converting the logical query plan into an intermediate query plan; comprising: finding a NN model with the minimum cost for a DIF in the logical query plan based on category constraints and precision constraints; S3, converting the intermediate query plan into a physical query plan; comprising: selecting an implementation mode for each operator in the intermediate query plan by determining a running mode of the NN model for implementing the DIF, so as to obtain a physical query plan with the minimum cost.

The invention relates to the technical field of database management, and discloses a database query embedding method and a computer program product, the method comprises the following steps: respectively converting a query statement into a physical query plan and a logic query plan, respectively carrying out node feature coding on the physical query plan and the logic query plan, the method comprises the steps of generating a physical plan feature vector and a logic plan feature vector, performing global feature extraction through a tree convolutional neural network to obtain a physical plan global feature vector and a logic plan global feature vector, and fusing the physical plan global feature vector and the logic plan global feature vector to generate a final query feature vector. According to the method, through double-plan parallel embedding of the physical query plan and the logic query plan, query execution details and semantic intentions can be captured at a time in a static scene, information loss caused by traditional single-mode coding is avoided, and it is guaranteed that the query feature vectors are comprehensively and accurately extracted.

A computer-implemented procedure for answering a first-order logical query based on a knowledge graph, wherein the procedure comprises: providing (302) the knowledge graph and the first-order logical query, wherein the logical query defines a logical operation on a first triple and a second triple, wherein the first triple comprises a cone embedding representing a first set containing at least one entity of the knowledge graph, a cone embedding representing a second set containing at least one entity of the knowledge graph, and an embedding of a rotation operation between the two cone embeddings of the first triple in a complex embedding space, wherein the second triple comprises a cone embedding representing a third set containing at least one entity of the knowledge graph, a cone embedding representing a fourth set containing at least one entity of the knowledge graph,and comprises embedding a rotation operation between the two conical embeddings of the second triple in the complex embedding space, wherein one of the conical embeddings represents an answer to the logical query, determining (304) a directed acyclic computation graph for the logical query depending on the logical query, wherein the computation graph defines an order for performing the rotation operations, determining (306) the answer to the logical query, wherein determining the answer comprises applying the rotation operations to the conical embeddings in accordance with the order defined by the computation graph.