1658 results about "Target database" patented technology

The invention relates to the technical field of data processing, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a database migration method, device, equipment and medium. And deploying a double-write control module of the application program layer to write the source database and the target database in parallel, and completing consistency verification through a data verification comparison task. And controlling a target database write-in channel according to a difference analysis result, closing a source database write-in channel in combination with a service takeover state, and completing a migration process from the source database to the target database. According to the method, full migration, application layer double writing, differential data verification and dynamic write-in channel control are combined, data consistency of the source database and the target database in the migration process is guaranteed, the source database and the target database are safely switched to after the service takeover capacity is verified, and the migration safety and continuity are improved.

The invention provides a method for generating an SQL (Structured Query Language) by a natural language based on bidirectional mapping and semantic parsing, which relates to the technical field of database query and comprises the following steps of: extracting natural language query elements and packaging the natural language query elements into structured data, and establishing a mapping relationship from a query field to a service attribute and a physical data table by adopting a bidirectional Hash index technology; and automatically identifying multi-table association keys, performing semantic extension and compliance verification, generating an abstract syntax tree, performing processing according to user permission, and finally converting the abstract syntax tree into an SQL statement conforming to a target database syntax specification. According to the method, the accuracy and the efficiency of converting the natural language into the SQL are improved, and the flexibility and the safety of the system are enhanced.

The invention provides an SQL (Structured Query Language) statement generation method and system based on a large language model. Target database metadata are collected, a structured dictionary is constructed, cue words adaptive to the large language model are generated in combination with a user query strategy, and accurate SQL generation is realized through a closed-loop execution optimization mechanism after model reasoning and SQL analysis. Through a large language model intelligent analysis technology, a multi-source heterogeneous database metadata dynamic adaptation technology and a closed-loop optimization mechanism for SQL statement generation, execution and feedback, the efficient and accurate SQL statement automatic generation function is achieved through the characteristics of cross-database grammar automatic adaptation, complex service requirement accurate analysis, intelligent error correction and the like. The system not only improves the working efficiency of developers, but also reduces the resource occupation and operation and maintenance cost of the system, and improves the accuracy and safety of data query and processing.

The embodiment of the invention discloses a database multi-source heterogeneous data synchronization method and device.The method comprises the steps that a data change event is monitored through an RPA robot deployed in a server where a source database is located, and when change operation of structured data or unstructured data is detected, an initial data set is generated; performing fragmentation processing on the initial data set to generate a plurality of data fragmentation tasks, and allocating the data fragmentation tasks to distributed computing nodes to execute parallel format conversion operation so as to generate a target data set; detecting a task execution state of the distributed computing node, and when a generation completion event of a target data set is detected, activating a data synchronization channel and transmitting the target data set to a target database; and performing conflict detection and identification based on an RPA conflict processing strategy configured in the target database, when a primary key conflict or a uniqueness constraint conflict is identified, updating the target database based on preset conflict merging indication information, and generating a data synchronization log.

The invention discloses a report chart automatic generation method based on natural language analysis and data query, which comprises the following steps: acquiring a natural language text, and constructing a slot set and an initial semantic fragment; executing consistency verification and ambiguity identification, and constructing a semantic framework; executing field standardization and mode alignment, generating a data query statement and establishing a traceability chain identifier; querying a target database to obtain an original data set, completing data quality self-correction, and generating a cleaned data set; calling an improved Mamba model to construct a constraint judgment matrix and outputting a target chart subset; generating a chart description grammar and an image annotation template, and executing image rendering, feature point recognition and image sidebar construction; and performing layout optimization and double compilation, and outputting a structured report file. According to the method, the chart generation automation level and the report compiling efficiency are improved, and the accuracy, traceability and specialty of the output content are ensured.

The invention relates to the technical field of intelligent agricultural equipment, and discloses an automatic agaricus bisporus picking method, device and equipment based on artificial intelligence and a medium. The method comprises the steps that RGB images and three-dimensional point cloud data of the agaricus bisporus growth environment are collected in real time through a binocular vision camera and a depth sensor which are installed at the tail end of a picking robot, and environment illumination parameters and cultivation bed coordinate information are obtained; inputting the RGB image into a pre-trained lightweight convolutional neural network, identifying a pileus contour, a stipe position and a maturity level of the agaricus bisporus, calculating a space coordinate, a height and a growth inclination angle of the agaricus bisporus based on the three-dimensional point cloud data, and constructing an agaricus bisporus target database; a mechanical arm picking path is generated based on the agaricus bisporus target database, and path weight parameters are optimized online through a preset reinforcement learning model; according to the maturity grade and morphological characteristics of the agaricus bisporus, the clamping force and the rotating angle of the end effector are dynamically adjusted, and automatic picking of the agaricus bisporus is completed.

The invention discloses a query statement conversion method and device based on a large model, equipment and a medium, and relates to the field of computer science, and the method comprises the steps: obtaining a natural language query statement sent by a user side, comparing the natural language query statement with a high-frequency problem in a target knowledge base, and obtaining a query statement conversion result; whether a high-frequency problem with the similarity with the natural language query statement exceeding a preset similarity threshold value exists in the target knowledge base or not is judged; if the high-frequency problem that the similarity with the natural language query statement exceeds a preset similarity threshold does not exist, determining a target database table corresponding to the natural language query statement based on the target knowledge graph, and extracting a creation statement corresponding to the target database table, so as to determine target information corresponding to the target database table according to the creation statement; and analyzing the target information by using a preset large model to generate an SQL statement corresponding to the natural language query statement. According to the method and the device, the natural language query statement can be efficiently and accurately converted into the structured SQL statement.

The invention relates to the technical field of databases, can be applied to the field of science and technology finance / digital medical treatment, and discloses a database migration method and device, electronic equipment and a storage medium. The method comprises the steps that database structured query language identifiers are defined, strategy classes corresponding to all databases are packaged, and a strategy context management container is created; receiving a target database type, dynamically loading a strategy type instance according to the type, and generating an executable query strategy chain according to the strategy type instance; when a database query request is received, matching a corresponding strategy type instance, and processing an original database query statement to generate a target database executable instruction; controlling a query strategy chain to execute a single-path or double-write-path mode through a common switch, and transmitting the instruction to a strategy type instance for execution; and analyzing a return result of the target database, performing conversion adaptation through the strategy type instance, and returning a conversion adaptation result. The method realizes automatic migration, reduces cost and risk, and improves system performance.

The invention discloses a webpage generation method and device, electronic equipment and a storage medium, and relates to the technical field of computer software or other related fields, the method comprises the following steps: receiving demand information of a user for an expected webpage, and inputting the demand information into a target language model to obtain N pieces of component information in the expected webpage, N being a positive integer; retrieving a target database based on the N pieces of component information to obtain a retrieval result; inputting fusion demand information of the retrieval result and the demand information into the target language model to obtain a configuration code which is used for describing the page layout, the component attribute and the application logic of the expected webpage; and analyzing the configuration code to obtain a corresponding source code, and rendering the page based on the source code to obtain a target webpage corresponding to the expected webpage. According to the method and the device, the technical problem that the generated webpage does not accord with the intention of the user due to understanding limitation of a low-code platform fused with a large language model in related technologies is solved.

The invention provides a Text2SQL generation method and system driven by a large language model, and the method comprises the steps: recognizing key entities and relationships in a natural language question through the large language model, and carrying out the construction to obtain a query graph; constructing a hierarchical graph representation model based on the database mode of the target database; searching candidate sub-image sets which have the same structure as the query graph and are in semantic association with the query graph from the constructed graph representation model; and constructing a structured Prompt template based on the candidate sub-image set and the user question, generating an initial SQL statement, and outputting a final query result after grammar and semantic detection correction. According to the method, a traditional database is converted into the graph knowledge base, so that the SQL generation accuracy and performance are improved; guiding the large model to generate an SQL (Structured Query Language) meeting business requirements through knowledge graph storage and retrieval table and column information; and the accuracy of the SQL is continuously optimized by utilizing a self-adaptive feedback mechanism, so that the method is particularly suitable for a large-scale complex query scene, and self-improvement and customization of the model are realized.

The invention discloses a multi-database compatible query processing method and device and a medium, and relates to the technical field of data query processing. The method comprises the steps that according to configuration information of all compatible databases, dialect types of all the compatible databases are dynamically recognized, and corresponding dialect configuration rule sets are loaded; when an original SQL statement of the database operation is received, intercepting the original SQL statement before the database operation is executed through a preset interceptor mechanism; according to a dialect configuration rule set of the target database to be operated corresponding to the original SQL statement, reflecting and modifying the original SQL statement in the BoundSql object to obtain a standard SQL statement; and submitting the standard SQL statement to the to-be-operated target database for execution, and returning an execution result.

The invention relates to the technical field of data import, in particular to an intelligent Excel data import method and system based on dynamic mapping, and the method comprises the steps that the system traverses all Excel fields for each database field, calculates the feature similarity and field matching degree of the Excel fields, and generates a field mapping template set according to all field matching results; reading the Excel content according to rows, cleaning each row of content into a standard value, performing quality scoring, and outputting a target format data structure set; screening a structure alignment data row and a field structure exception record set which conform to a threshold value; the system reads the structure alignment data rows line by line, processes the extraction value of each field and outputs a legal data set; and extracting a field sequence set, searching whether fields marked as primary keys or unique keys exist in the field sequence set, and combining the fields into a uniqueness judgment set to judge whether the currently written Excel data exists in the target database table.

The invention relates to the technical field of natural language processing, and discloses an intelligent slot filling and mode linking method based on RAG and M-Schema, and the method comprises the steps: rapidly matching a preset FAQ knowledge base through an RAG-FAQ module, and extracting a predefined medical intention and a slot structure; if the matching fails, starting an NLU module to perform intention classification and slot position extraction; performing entity linking and normalization on the slot value by utilizing an RAG-medical field knowledge base context enhancement module, performing multi-dimensional verification in combination with M-Schema metadata of a target database, and outputting a matching column and a confidence score; aiming at uncertainty types such as medical term ambiguity and business rule conflict, a clarification problem is dynamically generated, user feedback is received, SQL query conforming to business rules is generated after slot position information is corrected, and finally the SQL query is transmitted to a medical database execution module to output an analysis result. According to the invention, the availability and accuracy of the general framework in the scene facing the hospital management field can be improved.

The invention provides a data conversion method which can be applied to the technical field of big data. The data conversion method comprises the steps of obtaining metadata and relational statements in a source database; analyzing the metadata, converting the metadata into an intermediate format, and constructing a metadata intermediate model; analyzing the relation statement, extracting semantic levels in the relation statement, and constructing a semantic intermediate model; and associating the metadata intermediate model with the semantic intermediate model, converting the metadata intermediate model into metadata corresponding to a target database according to a preset conversion rule, and converting the semantic intermediate model into a relation statement corresponding to the target database. The invention further provides a data conversion device and equipment, a storage medium and a program product.

The invention discloses a method and a system for generating an SQL (Structured Query Language) query based on a natural language question. The method comprises the following steps: converting mode information of a target database and the natural language question into semantic vector representation; based on the semantic vector representation, a simplified database mode set related to SQL query is screened out through an attention mechanism; based on the natural language problem, the simplified database mode set and preset database constraint information, generating an SQL structural skeleton, and filling specific elements of the SQL structural skeleton to form a preliminary SQL query; and performing dynamic correction and verification on the initial SQL query by utilizing a large language model, and outputting a final SQL query. According to the method, association mining between user query and a database mode is effectively enhanced by utilizing a context-aware cross-encoder mechanism, and an implicit corresponding relation between a natural language problem and a database table / column can be more accurately identified and utilized.

The invention discloses a dynamic form generation and cross-database adaptation method based on metadata driving, and belongs to the technical field of data architectures. The method comprises the steps that an original metadata attribute graph is established; on the basis of the original metadata attribute graph and user roles and equipment parameters for calling the forms, generating an optimal equipment form interaction data graph corresponding to each user permission; verifying an interaction path between the forms and a cross-database demand of a target database type to carry out cross-database mapping adaptation analysis, and generating an optimal form data adaptation database of the corresponding equipment of each user permission; and performing rule compiling based on multi-source heterogeneous data input by a user in real time and execution logic in the original metadata attribute graph, marking an incremental propagation path in the optimal form interaction data graph of the corresponding equipment of each user permission, and updating the optimal form data adaptation database of the corresponding equipment of each user permission. The method has the advantages that the data interaction efficiency is improved, and the interaction round-trip times and redundant data transmission are reduced.

The invention relates to a query method based on multi-agent collaboration, and the method comprises the steps: generating a query structured representation after obtaining a natural language query text input by a user, and obtaining an associated database structure representation in combination with a constellation data model of a target database; and inputting the query structured representation and the database structure representation into a preset query statement generation agent to generate a plurality of first candidate query statements. And checking and correcting the first candidate query statement, and carrying out iterative checking and correcting on the corrected query statement which does not meet the condition. And obtaining a second candidate query statement with higher reliability through an iterative correction mechanism. And then, carrying out confidence evaluation on each second candidate query statement, selecting the second candidate query statement with the highest confidence as a target query statement, and executing query in the target database. According to the embodiment of the invention, the accuracy, reliability and practicability of natural language query are improved, and more convenient, efficient and accurate query experience is provided for users.

The invention provides a real-time data acquisition buffer throughput management method and device and electronic equipment, and relates to the field of data processing. Receiving a data object containing a sampling value, a timestamp, a measuring point number and a state mark through an input memory queue, and constructing a logic mapping identifier by a mapping agent unit to generate a logic write-in state; the logic write-in state is stored in a delay sensing buffer area, and a transaction confirmation delay sequence returned by a target database is monitored in combination with a distributed delay monitoring unit; establishing a time regression model based on the delay sequence, and generating a prediction projection window of transaction confirmation time; when the window meets a confidence threshold condition, releasing the logic write-in state to an output memory queue; and finally, writing into a database through an output thread, generating a completion mark table, and feeding back for delay buffer dynamic management. By implementing the technical scheme provided by the invention, the buffer data release rhythm and the database processing capability are conveniently coordinated, so that the overall throughput efficiency is improved.

The invention relates to a medical health big data exploration system, and the system comprises a demand understanding module which is used for converting a data exploration demand into a structured exploration task; the compliance review module is used for performing compliance review on the probing task; the code generation module is used for generating a query code according to the probing task and the target database characteristics; the query execution module is used for querying query result data corresponding to the query code from a target database according to the query code; the query result analysis module is used for performing multi-dimensional analysis on the query result data to obtain a multi-dimensional analysis result; a report generation module; and the result presentation module is used for presenting the exploration report in an interactive mode in a user interface and supporting iterative improvement of the report by providing a feedback mechanism, so that the problems of data isomerism, difficulty in quality evaluation, low exploration efficiency, high professional threshold, insufficient privacy protection and the like in the existing medical data exploration process are solved.

The invention discloses a complex SQL query dynamic rewriting method based on AST and a server, and relates to the field of data rewrite.The method comprises the steps that in response to a received target database type, an original SQL query statement is analyzed into AST; an SQL processor is initialized; recursively traversing a selection statement structure of the main query, and recursively traversing a sub-query structure nested in the selection statement structure; recursively traversing each selected statement structure in the joint query; recursively traversing conditional expressions in the updated statements, the deleted statements and the inserted statements or nesting and selecting statement structures; converting the rewritten AST into an SQL (Structured Query Language) query statement after dynamic rewriting; and returning the dynamically rewritten SQL query statement, and rewriting the SQL expression and the SQL statement structure in the AST according to a preset dynamic modification logic. The technical problem that a complex nested structure cannot be processed in a traditional SQL enhancement or modification mode can be effectively solved.

The invention discloses a method for generating statements from natural languages to SQL (Structured Query Language) based on a large language model agent. The method comprises the following steps of: constructing an LLM (Logical Language Model) guide table mode index for a target database; obtaining a user natural language question and extracting a keyword; searching in an LLM guidance table mode index according to the keyword, and screening related data tables; splicing the table mode information and the keywords of the related data table into a user natural language problem, and constructing an enhanced cue word; based on the large language model intelligent agent, generating SQL statements according to the enhanced cue words and verifying the SQL statements, if the SQL statements succeed in verification, obtaining the required SQL statements, and if the SQL statements fail in verification, performing iterative closed-loop correction on the generated SQL statements through an SQL statement closed-loop correction workflow; if the corrected SQL statement is successfully verified, the required SQL statement is obtained, and if the corrected SQL statement fails and the number of times of correction reaches a threshold value, the suggestions that the natural language problem of the user has defects and is modified are output. According to the method, the accuracy and success rate of SQL statement generation can be improved.

The invention discloses a scenarized hierarchical management and control method for an education application in a data space, and the method comprises the steps: obtaining a multi-modal input content in a corresponding preset period after the starting of the current time in response to a starting instruction of the education application in a target data space; calling a corresponding analysis strategy according to the content type of the multi-modal input content; extracting target features from the multi-modal input content based on an analysis strategy; according to an education scene corresponding to the target data space, obtaining a matching result of the target feature and a target database; determining a corresponding data space risk level according to a matching result; and calling and executing an application management and control strategy corresponding to the data space risk level. According to the method, education application hierarchical management and control adaptive to different scenes can be provided, the management and control precision is high, meanwhile, automatic analysis and management and control processes are achieved, and the method is suitable for scenes such as classroom teaching management, after-class and extracurricular training, remote examination and family interactive learning.

The invention belongs to the technical field of cloud storage, is suitable for the financial field and the medical field, and discloses a data table migration method, device, equipment and medium, and the method comprises the following steps: obtaining the name of an original database, a connection character string and a configuration file of a to-be-migrated data table, and analyzing the configuration file of the to-be-migrated data table to obtain a data table to be migrated; obtaining a table name and a table owner of the to-be-migrated data table; connecting the original database according to the connection character string of the original database, generating a table existence verification statement through the table name and the table owner of the to-be-migrated data table, and verifying the validity of the to-be-migrated data table according to the generated table existence verification statement; renaming the to-be-migrated data table in the target database according to a preset naming rule and performing compatibility processing; the migration instruction of the data table is generated in the target database, and the compatible data table to be migrated is migrated into the target database according to the generated migration instruction, so that the migration efficiency of the data table is effectively improved.

The invention relates to a heterogeneous database synchronization method and device, electronic equipment and a storage medium, and the method comprises the steps: analyzing a transaction log of a source database, extracting and generating an abstract syntax tree of a DDL event, and carrying out the node-level syntax conversion of the abstract syntax tree according to the database type of a target database and a preset syntax mapping rule base, and obtaining an equivalent DDL operation sequence of the target database, blocking a data processing operation corresponding to the database object associated with the DDL event, and executing the equivalent DDL operation sequence on the target database. The whole-process intelligent processing of the isomerous database DDL is realized without depending on manpower, the equivalent DDL operation sequence of the target database having semantic consistency with the DDL event of the source database is obtained through dynamic replenishment and deep analysis of the DDL event and the context semantics of the DDL event in combination with the grammar mapping rule base, the processing efficiency of isomerous database DDL synchronization is improved, and the processing efficiency of isomerous database DDL synchronization is improved. And meanwhile, the safety and reliability of synchronous processing can be ensured.

The invention relates to a migration method and system for a database table structure mapped by a metadata type, and the method comprises the following steps: obtaining table structures in a source database and a target database, and calling an interface to obtain metadata fields in the table structures; performing mapping analysis on the metadata fields to obtain candidate field mapping and corresponding mapping vectors; inputting the mapping vector into a gradient decision tree model to calculate a migration confidence coefficient mapped by each candidate field, wherein the migration confidence coefficient is a probability value for predicting successful mapping of the candidate field mapping; screening the candidate field mapping based on the migration confidence; if the migration confidence difference value mapped by the screened candidate fields is within a preset range, conflict arbitration is carried out according to a preset conflict resolution strategy, and a final migration decision is generated; and migrating the table structure of the source database to the target database based on the final migration decision.

The invention discloses a cross-heterogeneous database data migration method and system, and the method comprises the steps: building a multi-data-source connection among multiple data sources, and enabling the multi-data-source connection to be used for representing the incidence relation between a source database and a target database; obtaining a source data table based on the migration sql, and querying source data corresponding to the source data table from a source database; converting the source data based on a preset model mapping rule to obtain target data; determining a target database into which the source data is migrated according to the multi-data source connection, and writing the target data into the target database to realize data migration; and performing data verification on the target database according to the checking rule to obtain a migration result, and generating a result report according to the migration result. According to the method, the source data is converted into the target data through the preset model mapping rule, migration obstacles caused by structural differences among heterogeneous databases are effectively solved, the consistency of the data is ensured through the checking rule, and the accuracy of data migration is improved.

The invention discloses a distributed layout information reading method and system, a storage medium and electronic device.The distributed layout information reading method comprises the steps that a task configuration file is read through a master control node, the task configuration file comprises layout information configuration, and the layout information configuration comprises a layout processing area and a single task processing area; the main control node is used for dividing the layout processing area according to the single-task processing area to obtain a plurality of sub-task areas, and each sub-task area corresponds to one sub-task; adopting the master control node to respectively distribute the plurality of subtasks to the corresponding slave nodes according to the distribution strategy; the slave node sends a layout reading request corresponding to the subtask to a target database based on a load balancing mechanism; returning layout information corresponding to the layout reading request to the slave node through the target database; and performing corresponding task processing on the layout information through the slave node, and returning a processing result to the master control node. The layout information reading efficiency can be improved.

The invention belongs to the technical field of data statistics, and particularly discloses a Python-based dynamic SQL (Structured Query Language) generation and data statistics method and system, a terminal and a medium. The method comprises the following steps: acquiring statistical demand configuration in an Excel file; analyzing the Excel file to generate a structured data object, and carrying out semantic analysis and metadata consistency verification on the natural language description; constructing an SQL abstract syntax tree through a Python analysis module, and executing syntax mapping and function replacement according to a database adaptation rule; connecting a target database through a Python database driver and executing an SQL query statement; and after a query result is obtained, outputting an Excel file, a visual chart or interface data. According to the method, automatic analysis, SQL dynamic generation, safe execution and intelligent result output of data statistics requirements are realized.

An automated method is provided for comparing a source database and a target database that are intended to be kept in synchronization with each other. An application processes transactions that are posted to the source database, and a synchronization process processes transactions that are posted to the target database. Change log data is chunked from a change log associated with the source database to create first chunks of change log data. Change log data is also chunked from a change log associated with the target database to create second chunks of change log data. A comparison engine compares representations of the first chunks of change log data with representations of the second chunks of change log data, wherein the second chunks of change log data correspond to the same respective first chunks of change log data that were made to the source database and kept in synchronization with the target database via the synchronization process. The source database and the target database are presumed to be in synchronization with each other via the synchronization process when the comparison indicates that the representations of the first chunks of change log data match the representations of the second chunks of change log data. The source database and the target database are presumed not to be in synchronization with each other when the comparison indicates that the representations of the first chunks of change log data do not match the representations of the second chunks of change log data. An action is performed when the comparison indicates that the representations of the first chunks of change log data do not match the representations of the second chunks of change log data. The action may be a corrective action that resynchronizes the target database with the source database, or that suspends or stops the application from processing transactions.

The invention discloses a database traffic auditing method, device and equipment and a storage medium, and relates to the field of databases, and the method comprises the following steps: deploying a target extension program in a kernel layer of an operating system, and capturing a target data packet by using a target probe in the target extension program; performing protocol analysis on the target data packet to extract target data, determining execution time of a target SQL statement based on the target data, and performing semantic analysis on the target SQL statement by using a target analyzer and a way of performing analysis based on syntax imported based on a bypass to obtain a corresponding semantic analysis result; the target data comprises a target SQL statement and target metadata; and storing the target data, the execution time and the semantic analysis result to a target log database, so as to audit the flow of the target database based on the data in the target log database by using a pre-configured target audit strategy. According to the method and the device, efficient, safe and real-time auditing of database traffic is realized.