86 results about "Foreign key" patented technology

The invention relates to a data security processing method and system based on distributed storage, and relates to the technical field of computer information processing. The method comprises the following steps: cutting data into encryption fragments with a configurable number by adopting a dynamic fragmentation strategy, and generating a physically isolated dynamic check block in combination with a timestamp to realize tampering prevention; a dynamic threshold value is dynamically calculated based on the data sensitivity index and the node load, and the node is optimized through the reliability score for cooperative decryption; a database table is divided into independent marshalling storage according to main foreign key association, foreign key fields are encrypted by adopting cross keys, and cross-marshalling access needs to meet a multi-key threshold condition; an intelligent threat perception engine is constructed, access logs and threat intelligence are analyzed in real time, and key rotation, fragment replacement and joint defense response mechanisms are dynamically triggered. According to the invention, full life cycle protection of data is realized, and the problems of key leakage risk and cross-table association attack are effectively solved.

The invention discloses a multi-table combined natural language query SQL (structured query language) generation method, which comprises the following steps of: 1, constructing a database meta-knowledge graph, and establishing a triple storage comprising a table structure, a primary and foreign key relationship and business description for each data table; 2, receiving a natural language query request, and calculating the topic relevancy between query semantics and each database table through a pre-trained topic matching model; 3, dynamically constructing a view, and logically associating the database tables of which the theme relevancy exceeds a threshold value to form a temporary view; 4, generating a context enhancement prompt, and combining the temporary view structure, the field semantic description of the view and the view content sample to form a structured prompt; 5, inputting the natural language query and the structured prompt into the large language model to generate candidate SQL statements; and step 6, executing verification and iterative optimization on the candidate SQL statements, verifying logic correctness through SQL execution plan analysis and result sampling, and triggering and prompting a reconstruction mechanism when detection is abnormal.

Apparatuses, methods, and computer-readable media infer a graph model from a semantic model that describes source tables and relationships among the source tables. The apparatus identifies at least one primary key for each relationship of a plurality of relationships defined in the semantic model based on whether the relationship is a m:1 relationship or a 1:1 relationship, each relationship defining at least one from-table and one to-table. The apparatus creates a vertex table in the graph model for each source table having a primary key. The apparatus creates an edge table in the graph model for each from-table defined in a m:1 relationship of the semantic model and creates an edge table in the graph model for one of the from-table or the to-table in a 1:1 relationship of the semantic model. Each edge of the edge table is labeled with a source or destination vertex table and a foreign-key.

The invention discloses an Internet self-research operation and maintenance management method and device and a storage medium, and the method comprises the steps: analyzing a current operation and maintenance management demand, and determining and selecting at least one target instance according to an analysis result; extracting an associated foreign key of the target instance, and dynamically associating the target instance based on the associated foreign key to form a target entity set; service configuration information based on the target entity set is obtained, and dynamic key value pair configuration of the target entity set is updated according to the service configuration information; and generating a task flow arrangement template based on the updated target entity set, and scheduling a task object to execute a task chain through the task flow arrangement template. According to the method, a multi-level configuration management framework and a template task chain mechanism are established, environment self-adaptive differential execution is supported after multi-level configuration parameters are automatically combined, the operation and maintenance efficiency and the full-link execution monitoring and auditing tracing capability are improved, and the risk of manual operation errors is reduced.

The invention provides a database relationship intelligent discovery and ER graph construction method and a self-evolution learning method, and belongs to the technical field of ER graph construction, and the database relationship intelligent discovery and ER graph construction method comprises the steps of S1, metadata collection and preprocessing; s2, vectorizing domain sensing metadata; s3, recalling a multi-strategy candidate relationship; s4, performing LLM structured reasoning and verification; s5, carrying out data sampling inspection and cross validation; s6, hierarchical negative sample self-evolution learning; and S7, generating and visualizing an ER graph. According to the invention, a layered negative sample self-evolution learning mechanism and the structured reasoning ability of LLM are organically combined, and LoRA rapid fine tuning and a multi-stage verification process are supplemented. The defects of accuracy, generalization ability, cold start efficiency, reasoning transparency, automation integration and the like in the aspect of discovery of the primary and foreign key relationship of the relational database in the prior art are effectively overcome, and a more advanced and practical solution is provided.

The invention belongs to the technical field of database query and natural language processing, and provides an NL2SQL method based on foreign key completion and a knowledge graph, and the method comprises the steps: extracting a candidate foreign key relationship from database metadata and data content, and trimming and completing the candidate foreign key relationship through a three-layer funnel verification mechanism, a Schema knowledge graph is constructed; based on the natural language query, determining a seed table set directly related to the query intention; on the basis of the Schema knowledge graph, calculating a connection path between nodes of a seed table, complementing an intermediate table on the path, and expanding the seed table into a sub-graph set containing a complete connection relationship; generating a plurality of candidate SQL statements based on the sub-chart set; and executing the plurality of candidate SQL statements, and voting according to the consistency of execution results to select a final SQL statement.

The invention discloses a business domain division method and device for a database table, a medium and a product, and relates to the technical field of data processing. According to the scheme, when the business domain grouping requirement of the database table exists, from the three aspects of the structure, the semantics and the behavior of the database table, the similarity degree of three dimensions including the foreign key relation, the name similarity and the common current mode between the database tables is comprehensively considered; the problem that effective information in metadata is difficult to extract due to the fact that only an NLP model is used for unilaterally extracting database table information in a traditional method is effectively avoided; and finally, determining a corresponding comprehensive weight by utilizing the structure weight, the semantic weight and the behavior weight corresponding to each database table, namely dividing each database table into a plurality of business domain groups according to each comprehensive weight, so that manual intervention can be effectively reduced, and the method is suitable for a large-scale database scene.

The invention discloses a cross-platform power grid data conversion synchronization method and device, a terminal and a medium. According to the method, a master table in a source database is synchronized to a target database according to master-slave table dependency sequence information; in the synchronization process, an ID mapping table is constructed to record the mapping relation between a first primary key ID and a second primary key ID of each piece of primary table data, the second primary key ID corresponding to a foreign key field is dynamically calculated to be used for updating the foreign key field based on the foreign key field of the slave table in combination with foreign key mapping relation information and the ID mapping table, and the secondary table data is synchronized. Finally, after all the foreign key fields of the slave table are updated, the data synchronization action of the slave table is executed in combination with ORM data synchronization logic, dynamic remapping of the primary key ID is achieved by constructing the ID mapping table, the foreign key fields of the slave table are updated based on the foreign key mapping relation information, the foreign key reference integrity during cross-database synchronization is ensured, and the synchronization efficiency is improved. The problem of foreign key reference integrity caused by inconsistent primary key IDs in the cross-database synchronization process is effectively solved.

A machine-readable medium stores instructions that, when executed by a processor, cause the processor to execute operations. The operations include receiving information identifying a database table and preprocessing the table. The preprocessing includes extracting primary and foreign key relationships and generating sample data by combining frequency-based sampling of common values with random sampling. The operations also include generating, using an LLM, a unified metadata schema. The generating includes processing the table and the sample data using domain-specific prompts and outputting the unified metadata schema. The operations include embedding and indexing the unified metadata schema and converting a natural language question output from an end-user device into a SQL query. The converting includes identifying relevant metadata in the unified metadata schema matching query intent and generating the SQL query using the filtered metadata. The operations also include executing the SQL query and providing query results to the end-user device.

The invention discloses a data warehouse model design method, and belongs to the technical field of data warehouse modeling. According to the method, a dimension modeling method is adopted to construct and analyze a mart model, data is organized into a non-standardized relation model, and the relation between tables is defined through keywords and foreign keys. And designing a dimension table system comprising a product dimension, a calendar day dimension, an institution dimension, an insurance policy attribute dimension and a customer dimension, and a fact table system comprising an insurance claim settlement analysis fact table, a payment analysis fact table, a claim settlement efficiency analysis fact table and a corresponding intermediate fact table. The analysis subject domain data is formatted into a star model or snowflake model, where the analysis fact table is a lightly summarized transactional fact table, and the intermediate fact table is a versioned historical table. According to the method, repeated data construction is avoided through a unified modeling method, and the cost is reduced; an efficient query analysis function is provided by optimizing a model structure; and the data traceability is ensured through versioning management.

The application belongs to the technical field of data processing, and discloses a kind of information system business data integrity check method, comprising: the data entity class instance of information system is encoded based on the data structure of data entity class, and initial encoding is obtained;Data entity class instance is encoded again to obtain current time encoding;According to the initial encoding and current time encoding of data entity class check and output data integrity check result.The method can obtain understandable and directly related fine-grained integrity check result by participating in the encoding and encoding comparison process of business entity class, and the integrity of all information including the external information associated with foreign key can be checked out by directly checking the integrity of class instance used in business system, saving storage space and speeding up comparison speed.

The invention provides a data consanguinity analysis method and equipment, and is applied to the field of data governance. The method comprises the steps of obtaining a data dictionary corresponding to a target database; wherein the target database comprises a plurality of data tables; foreign key information is extracted from the target database, the foreign key information is used for representing the relation among the multiple data tables, and the foreign key information is obtained; performing data correlation analysis on the target database based on a correlation coefficient algorithm to obtain a correlation analysis result; and based on the data dictionary, the foreign key information and the correlation analysis result, constructing a data blood relationship map. As the data correlation analysis is performed on the target database based on the correlation coefficient algorithm, not only can the correlation between the data fields be accurately quantified, but also the correlation analysis result for revealing the potential data dependency relationship between the fields and the business logic can be obtained, so that the data correlation analysis efficiency is improved. The data blood relationship map constructed based on the data dictionary, the foreign key information and the correlation analysis result can reveal potential data dependency and business logic, and the accuracy is high.

The application discloses a test data generation method and device, equipment and a storage medium. The test data generation method comprises the following steps: obtaining a plurality of target record contents from a test data rule table, each target record content comprising a field type, data source information, test data generation rule information corresponding to the data source, and a record number; for each target record content, generating a test data table based on the data source information, the test data generation rule information, the record number, and a first table generated based on the field type; and finally, combining a plurality of test data tables based on the association relationship between the physical primary keys and the physical foreign keys of the plurality of database tables to obtain test data. According to the embodiment of the application, the test data is generated, the test data is rich in dimensions, the association relationship between the data is complete, and conforms to the real law.

The invention discloses an event inducement discovery system and method fusing deep reasoning and a graph neural network, and relates to the field of event analysis and processing. The system comprises: a knowledge base construction module, which is based on a news event database, constructs an event knowledge base through operations such as text partitioning, vector embedding, database foreign key association and the like, and is used for retrieval enhancement generation; the deep reasoning module is used for autonomously reasoning and collecting potential effective information of event inducements through operations such as retrieval statement generation, knowledge base retrieval, effective information extraction and sufficiency test by taking a large reasoning model as a base; the graph neural network module is based on the event relation graph, and assists in reasoning to obtain potential causal relations in the interlaced complex event text; the inducement mining module is used for mining event inducements from related materials by fully utilizing the reasoning capability of a large reasoning model through a professional cue word template; the invention further provides a method. The problems that event relations are complex and interlaced, and event inducements are difficult to analyze are solved.

The application discloses a low-code data interface calling method, equipment and medium, and the method comprises the following steps: confirming a target entity and an entity parameter corresponding to the target entity; the entity parameter comprises at least one of an entity name, a field name, a field type, a field position, whether to be filled in, an index and a foreign key; a database table corresponding to the target entity is constructed according to the entity parameter; the interface name, the interface parameter set and the interface parameter format of the target interface are defined according to the database table; the target interface of the target entity is generated according to the interface name, the interface parameter set, the interface parameter format and the entity parameter; the target interface is published, and an authorization key of the target interface is generated; it is determined that a target interface calling request from a calling party is received, and authorization signature information contained in the target interface calling request is acquired; the calling party is authorized and verified according to the authorization signature information and the authorization key, and if the verification is passed, the calling party is allowed to call the target interface.

In distributed data management traditional databases often struggle to maintain consistency and handle conflicts. Traditional solutions prioritize specific combinations of properties, resulting in trade-offs that impact user experience and application functionality. Present disclosure provides systems and methods that route incoming transaction associated with application to corresponding database server (DBS) by integrating geographical proximity mean value, and sender internet protocol affinity value. The incoming transaction is processed to extract data manipulation language (DML) operation written by the application and replicated to each DBS other than a DBS on which the application is directly applying a data through the incoming transactions. A primary key is generated by allocating an unique identifier if the DML operation is inserted on identified DBS. The primary key of record is updated from the incoming transaction. A conflict associated with parent and child association of the DML operation is dynamically monitored based on integrity Foreign key Constraint.

The invention provides a real-time wide table construction method, system and device based on the combination of Spark and Flink and a medium, and the method comprises the steps: S1, constructing a data link based on a Spark connector, and completing the rapid generation of a data set snapshot; s2, constructing a data link based on a FlinkCDC connector, and realizing incremental real-time updating of data; s3, stopping the Spark data synchronization program, setting the Flink CDC to consume increment change data in real time from the latest snapshot position generated in S1, and dividing a table needing to be associated into a master table and a plurality of slave tables; when the master table is changed, rechecking the related slave tables according to the association keys, combining to form wide table data, and writing the wide table data into a downstream wide table database in an upsert mode; and when the slave table changes, the corresponding data in the downstream wide table is directly updated according to the association key or the foreign key. Through the mechanism, changes of all the association tables can be fed back to the downstream wide table in real time, so that dynamic construction of the wide table is completed.

This disclosure describes an implementation of a computing system that utilizes accelerator hardware configured to perform parallel computation of matching pairs of a join operation of a database program. This computation is performed at least in part by, for each thread that determines a matching pair, computing an offset in an output tuple by adding a global rank of a respective block, an intra block rank of a respective warp, and an intra warp rank of a respective thread. This computation is further performed by storing index values for a primary key and a foreign key in a matching pair at the computed offset location in an output tuple, and outputting the output tuple.

The invention discloses a Hash connection implementation method, electronic equipment, a computer readable storage medium and a computer program product, and the method comprises the steps: creating a reference table according to an implementation method for foreign key reference and connection query based on an array index, automatically creating a reference array index for the reference table through a specified option when the reference table is created, and automatically creating a connection query result according to the reference array index. Meanwhile, a referenced array index is automatically created for the referenced table; a column of reference is added to the created reference array index, and a new reference array index is obtained; constructing a byte array according to [the maximum subscript used in the quoted array index corresponding to the quoted table / 8] + 1, and setting the content of the byte array as 0; for all records meeting conditions in the referenced table, setting a bit corresponding to the byte array as 1; all units in the reference array index are sequentially scanned, and for the matching condition, the required referenced table and the corresponding record information of the reference table are directly output to an upper-layer operator.

The embodiment of the invention provides a demonstration data extraction method and device, electronic equipment and a storage medium. The extraction method comprises the following steps: determining an extraction proportion and an extraction range of demonstration data in a source database; obtaining all data tables included in the sub-mechanisms in the extraction range; for all the data tables, determining a first association data table having an association relationship with each data table based on a primary key field of each data table or a combination of the primary key field and a foreign key field, so as to determine an association condition corresponding to the association relationship; determining a second association data table having an association relationship with an institution table in all the data tables, wherein the institution table defines hierarchy information and a membership relationship of each sub-mechanism in all the sub-mechanisms; determining the extraction priority of each data table in all the data tables according to the association condition and the second association data table; and extracting the data table to be demonstrated from all the data tables according to the extraction priority. According to the method, high business consistency and accuracy of the extracted demonstration data are ensured.

The invention discloses a method for establishing a miichthys miiuy germplasm resource library, and particularly relates to the technical field of germplasm resource information management. According to the method, a drift risk assessment model is constructed based on a main key variation sensitivity factor and a foreign key reference strength index, and when the risk level of a sample main key exceeds a set threshold value, a version control type database structure is automatically started to replace a traditional main and foreign key direct mapping relation; by introducing a version number and an activation identification field, multi-version coexistence and traceable management of a sample primary key are realized; meanwhile, through consistency verification and an automatic remapping mechanism, the problem of external key contact loss caused by primary key change in the sub-table is solved; the method has high reliability, structural elasticity and good expandability, is suitable for data structure long-term evolution and information traceability requirements in an aquatic product germplasm resource management system, and significantly improves the consistency and integrity of sample data and the stability of system operation.

This invention discloses a method for constructing logical associations and generating privacy-compliant code for heterogeneous databases in intelligent programming assistance. It introduces a custom metadata description file independent of the database's physical schema, defining cross-domain logical association attributes and data security attributes, including the target database identifier. The description file is parsed, comparing the associated target with the database identifier of the current context, and automatically selecting either an intra-database join strategy or an application-layer aggregation strategy based on the comparison result. An enhanced context hint containing architectural constraints and security rules is constructed, and the target code is generated by inputting a large language model. De-identification processing logic is automatically embedded based on the data security attributes. This invention effectively solves the problems of AI programming context breakage, cross-database association code generation errors, and data privacy compliance risks caused by missing physical foreign keys in microservice architectures, achieving automatic code generation and source-level data privacy protection for complex cross-service business logic.

The application relates to the technical field of detection, and particularly provides a foreign key constraint detection method and device, electronic equipment and a storage medium. The foreign key constraint detection method comprises the following steps: determining a target key value of a to-be-inquired foreign key in a to-be-inquired row according to a received target query instruction, and obtaining a key value set; at an executor level, a key value query task is constructed based on the key value set; the key value query task is executed by the executor, and a target query result is obtained. In this way, the system overhead is reduced, and the system performance is improved without SQL statement analysis and execution.

An import job associated with a data store update is inspected and schemas associated with target data tables that are to be updated with update data are analyzed. Referential integrity issues associated with foreign keys in the target tables are identified in the update data. The update data is broken into three portions, a first portion that is guaranteed to not have a referential integrity issue, a second portion this is known to have a referential integrity issue, and a third portion that cannot be determined at this stage of processing. The import job is modified to update the corresponding target tables with the first portion of the update data while the second and third portions are not updated to the target data base tables but a custom message is recorded in fields associated with the second and third portions that describes the issue for subsequent review / resolution.

The invention relates to the technical field of databases, and discloses a database table foreign key association reconstruction method and device. The method comprises the steps that columns of multiple target data tables are combined in pairs to generate column pairs, and a first set is constructed based on all the column pairs; pruning the first set based on the target unique key through the target large language model; constructing a second set based on column pairs reserved after pruning; performing foreign key association detection on the column pairs in the second set through the target large language model to obtain a detection result; traversing all the column pairs with foreign key association, and deleting at least one column pair with foreign key association through the target large language model under the condition that foreign key conflicts exist between the column pairs so as to eliminate the foreign key conflicts; under the condition that foreign key conflicts do not exist between the column pairs, foreign key association is reconstructed for the multiple target data tables. By adopting the method, the accuracy and generalization of foreign key association reconstruction of the database can be improved, and the reconstruction quality is improved.

The subject technology receives a key-value pair. The subject technology determines a value size of the key-value pair is greater than a threshold size for an out of line blob (OLB) key space. The subject technology performs a write operation of a key-pointer pair into a regular space. The subject technology performs a plurality of write operations for multiple key-value parts of the key-value pair into the OLB key space. The subject technology performs conflict checking of the regular space for the key-value pair.

This invention provides a method, system, and product for automatically extracting metadata and metadata relationships, relating to the field of big data technology. The method includes: extracting table information, table field information, and foreign key relationships between tables in the current database to obtain explicit metadata; extracting multiple sample data entries from each table; assembling the explicit metadata and the sample data entries to obtain model instruction prompts; using these prompts to call a large language model to output structured table semantic descriptions and field semantic descriptions, and outputting these as metadata; extracting semantic relationships between tables based on the table semantic descriptions, and extracting semantic relationships between fields based on the field semantic descriptions; and outputting the inter-table semantic relationships and inter-field semantic relationships as metadata relationships. This invention solves the problem that existing technologies mainly focus on explicit structured information while neglecting deep semantic mining, significantly improving the efficiency and fault tolerance of data querying, integration, and modeling processes.

The invention provides a metadata and metadata relationship automatic extraction method, system and product, and relates to the technical field of big data, the method comprises the following steps: extracting table information, table field information and inter-table foreign key relationship of all tables in a current database to obtain explicit metadata; extracting a plurality of pieces of table sample data from each table; the explicit metadata and the multiple pieces of table sample data are jointly assembled to obtain a model instruction prompt, the model instruction prompt is used for calling a large language model to output structured table semantic description and field semantic description, and the structured table semantic description and field semantic description serve as metadata to be output; extracting an inter-table semantic relationship based on the table semantic description, and extracting an inter-field semantic relationship based on the field semantic description; and outputting the semantic relationship between the tables and the semantic relationship between the fields as a metadata relationship. According to the method, the problem that explicit structured information is mainly focused and deep semantic mining is neglected in the prior art is solved, and the efficiency and fault tolerance of links such as data query, integration and modeling are improved to a great extent.

The application provides a purchase and sale contract generation method and device, equipment and a storage medium, including: when the order is approved, obtaining order information, the order information including: the number, the quantity; generating a pre-purchase and sale contract according to the order information; obtaining the input pre-purchase and sale contract that needs to be merged; judging whether the number of pre-purchase and sale contracts that need to be merged is greater than one; if yes, judging whether the pre-purchase and sale contract that needs to be merged meets the merging rule; if yes, merging the pre-purchase and sale contract that needs to be merged to generate a purchase and sale contract, and associating the pre-purchase and sale contract that needs to be merged with the purchase and sale contract through the way of an associated foreign key. Through the connection between the upstream order, the purchase and sale contract is quickly and efficiently made, and multiple pre-purchase and sale contracts are merged into one purchase and sale contract, so that the number of contracts is reduced, and the problems of printing waste and easy error are avoided. Again, by associating the pre-purchase and sale contract with the purchase and sale contract, the repeated storage of data is avoided, and the data redundancy is greatly reduced.

Embodiments of the present application disclose a data synchronization method, device, medium and electronic equipment. The method comprises: obtaining synchronization configuration information of a to-be-synchronized database, and determining target synchronization data in the to-be-synchronized database according to a data synchronization range in the synchronization configuration information; determining synchronization associated data associated with the target synchronization data according to a foreign key selection operation acting on the target synchronization data; generating a data synchronization task according to the target synchronization data and the synchronization associated data; and publishing the data synchronization task to distributed database nodes for each distributed database node to preempt and execute the data synchronization task. In the data synchronization process, the embodiments of the present application synchronize the association relationship between data in the to-be-synchronized database, thereby ensuring the data consistency of the synchronization data.