1009 results about "Target database" patented technology

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 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 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 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 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 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 relates to a service data distributed storage method and device, computer equipment, a medium and a product. Comprising the steps of generating a corresponding target data fragment identifier according to data fragment information of business data under the condition that a write-in request of the business data is detected; first mapping information and second mapping information are extracted from a preset storage routing mapping table, the first mapping information represents the mapping relation between the data fragment identifier and the storage group of the distributed database, and the second mapping information represents the mapping relation between the storage group and the database node of the distributed database; querying a target storage group identified by the target data fragment from a distributed database according to the first mapping information; querying a target database node corresponding to the target storage group according to the second mapping information; and performing distributed storage on the business data through the target database node. By adopting the method, the limitation of distributed storage of the service data is reduced.

The invention discloses a heterogeneous database migration strategy generation method and device and a medium, and the method comprises the steps: respectively obtaining structures and constraint conditions of a source database and a target database, carrying out the structured conversion of the structures and the constraint conditions, and generating a structured parameter set; performing risk analysis on the target database constraint condition to generate a migration verification data strategy; acquiring a migration verification data set according to the migration verification data strategy; in a preset isolation environment, executing a data migration operation on the migration verification data set, and recording behavior parameters generated in a data migration process; performing risk analysis on the behavior parameters to generate risk assessment parameters; and according to the risk assessment parameter, matching a corresponding migration strategy type from a preset migration processing rule set to generate a migration strategy parameter which can be directly applied to formal migration. The defects that in the prior art, manual experience is relied on, and risk discovery is lagged are overcome, and the certainty and overall efficiency of the migration process are remarkably improved.

The embodiment of the invention discloses a batch writing method and equipment for a PostgreSQL database, relates to the technical field of cross-database migration, and is used for solving the problems of poor compatibility and low reliability of an existing mode. The method comprises the steps of performing cross-database dialect semantic mapping on a heterogeneous data source based on a cross-database semantic mapping engine to obtain a global concurrent import control parameter set of a target database, and extracting the heterogeneous data source based on analysis configuration of the global concurrent import control parameter set to obtain a standard record object; performing flow control on a task channel of the target database based on a self-adaptive backpressure strategy so as to assemble the standard record objects into data batches and distribute the data batches to a working coroutine of the target database; the batch writing protocol is called through the working coroutine, the batch direct writing request is initiated to the target database for batch writing, and the writing abnormity is processed based on the preset fault-tolerant mechanism to obtain the writing result, so that the data writing risk is effectively reduced while the compatibility is ensured, and the reliability of cross-database batch writing is improved.

The invention discloses a multi-round dialogue system and method based on conversion from a natural language to an SQL, and relates to the technical field of artificial intelligence, and the system comprises a user interaction module which is used for supporting a user to input a query problem and displaying a corresponding SQL query result; the context processing module is used for screening the effective dialogue history of the current question and re-integrating the effective dialogue history into a complete dialogue; the ambiguity processing module is used for identifying an entity from a dialogue history to define a user intention, processing a fuzzy keyword in a current question and guiding the user to complement a query condition; the re-splicing module is used for reconstructing a complete dialogue according to a time sequence, eliminating ambiguity, generating a summary through a large model, and combining the summary with a current problem to construct a complete problem; the SQL generation module is used for performing semantic analysis on the complete problem and outputting an SQL query instruction with the highest matching degree; and the execution and rendering module is used for executing the instruction on the target database and returning a query result. The conversation processing capability can be improved.

The invention relates to the technical field of natural language processing, and discloses a structured query statement generation method and device.The method comprises the steps that a natural language problem input by a user and related information of a target database are received; performing mode linking processing on the natural language question and the related information of the target database to obtain database structured mode information related to the semantics of the natural language question; based on the natural language problem and the database structured mode information, self-driven exploration operation is executed, and a corresponding exploration result is generated; inputting the database structured mode information and the exploration result into a preset language model to generate an initial structured query statement; and performing verification and iterative correction on the initial structured query statement to generate a final structured query statement. According to the method, the structured query statements which are matched with natural language question semantics and can be effectively executed can be efficiently generated, and the accuracy and effectiveness of generation of the structured query statements are effectively improved.

The invention discloses a user ad-hoc query report realization method and device based on a large language model, and relates to the technical field of natural language processing. The method comprises the following steps: constructing an ad hoc query report system based on the large language model, wherein the ad hoc query report system comprises a semantic analysis module, an analysis engine module and a query statistics module; a natural language query statement input by a user is input into a semantic analysis module to be analyzed through a fine-tuned large language model, a structured query condition set and a structured query result index column set are output and input into an analysis engine module, and according to permission information of the current user, through pre-constructed index metadata and SQL semantic analysis rules, the query result index column set is analyzed, and the query result index column set is analyzed. Generating a query SQL statement; and inputting the query SQL statement into a query statistics module, connecting a target database to execute query operation to obtain a query result set, and performing data formatting processing on the query result set to obtain a final query result. By adopting the method, complex query requirements can be met.

The invention relates to the technical field of database management and data migration, and discloses a database metadata migration method, device, equipment and medium, comprising: configuring a metadata type mapping correspondence between a source database and a target database, establishing a source database read connection and a target database write connection, and obtaining a source data definition statement of the source database, storing the source data definition statement in a standard format, reading the source data definition statement from the intermediate storage medium, converting the source data definition statement into a target data definition statement conforming to the grammar specification of the target database, and finally executing the target data definition statement in the target database to complete the creation of the metadata object. By introducing the metadata type mapping corresponding relation and the standardized storage mechanism, the metadata difference between the heterogeneous databases is converted into a conversion process capable of being automatically processed, so that manual intervention is reduced, the migration error rate is reduced, and the automation level and reliability of database metadata migration are improved.

The invention discloses a transformer substation-oriented multi-source heterogeneous data checking method and system. The method comprises the following steps of obtaining various types of data sources, executing a preliminary data cleaning process and outputting standardized data; aiming at database systems of different manufacturers, designing a customized migration tool for each database; extracting specific attribute information contained by the special domain analysis module by constructing the special domain analysis module; sequentially verifying the source database and the target database by adopting a progressive consistency verification strategy, and recording data difference information detected in each stage; a change rationality verification module is configured to analyze an SCD file of the transformer substation, and change rationality judgment is performed on difference items from a source database to a target database; performing unified modeling and graphical display on the obtained difference information through a difference data visualization module; according to the method, the data consistency and correctness in the upgrading and transformation process of the transformer substation monitoring system database are comprehensively verified, so that the stability and the operation reliability of the system are improved.

The invention provides a prompt information evaluation method and device, electronic equipment, a medium and a program product, and can be applied to the technical field of artificial intelligence. The method comprises the steps that a pre-constructed query statement test data set is obtained, the query statement test data set at least comprises a plurality of error query statements, and each error query statement is used for triggering a target database to generate error prompt information in the execution process; inputting the error query statement into the target database, obtaining return information of the target database, and generating error prompt information based on the return information; based on the error prompt information, utilizing a large language model to obtain at least one corresponding correction query statement; and verifying the corrected query statement in the target database, and evaluating the quality of the error prompt information based on a verification result.

The invention provides a database migration method, device and equipment based on AI assistance and a medium, and belongs to the technical field of data migration. The method comprises the steps that a migration prediction result is generated based on a pre-trained migration knowledge graph model according to feature information of a source database and a target database; based on the minimum downtime, the data loss amount and the migration cost as optimization targets, an optimal migration strategy is generated according to the migration prediction result, the data playback state is monitored while the data migration task is started to be executed according to the optimal migration strategy, and migration parameters of the data migration task are adjusted according to the monitoring result; and according to a monitoring result, predicting an optimal switching opportunity and evaluating a rollback risk, and according to an evaluation result, adjusting an execution state of the data migration task. The database migration process is intelligent, self-adaptive and high in reliability, and migration efficiency and success rate are remarkably improved.

The disclosure describes a data sharing system, method, apparatus, a device and a medium. In the data sharing method, a device to which a first application belongs determines, according to a pre-stored correspondence between application identifiers and access addresses, a target access address corresponding to a target application identifier of a second application, and sends to the target access address a sharing request for sharing data of the second application, where the sharing request carries the target application identifier; and a device to which the target access address belongs obtains data stored in a target database, determines a target encryption key corresponding to the target application identifier, decrypts the obtained data according to the target encryption key, and sends the decrypted data to the device to which the first application belongs.

The invention discloses a card type DSL generation method for mass spectrum metadata standardization, and relates to the field of mass spectrum data analysis, and the card type DSL generation method comprises the following steps: constructing an initial mass spectrum metadata card type DSL model based on a mass spectrum experiment process and a standard term; analyzing causal association between the historical mass spectrum data set and fields in the initial mass spectrum metadata card type DSL model by adopting a causal discovery algorithm, generating a field diagnosis report, and generating a core version mass spectrum metadata card type DSL model based on the field diagnosis report; compiling the core version mass spectrum metadata card type DSL model through a DSL compiler to generate a data checker, a user data entry form and a data access API interface; and integrating a metadata quality score deployment engine in the user data entry form. Integrity verification of submitted data is completed through the data verifier, compliance data is stored in the target database through the data access API interface, and the technical problems of field redundancy, low input efficiency and difficult quality control in the mass spectrum metadata standardization process are solved.

The invention discloses an agent training method, a data processing method and a related device, and relates to the field of artificial intelligence. In an agent training process, key information in target interaction data generated by interaction between an initial agent and a target user is automatically extracted to generate a structured memory; and a context basis for supporting training can be constructed without manually annotating data, so that the training cost of the intelligent agent is reduced. Traceable historical context support is provided for the intelligent agent by processing the target interaction data and updating the target database based on the processing result; a comprehensive basis is provided for agent behavior evaluation by acquiring whole-process trajectory data generated when an initial agent executes a task in a target task environment; the scoring model constructed by the user for the feedback information of the full interaction trajectory scores the trajectory data, and the initial agent parameters are updated, so that the agent can continuously optimize the strategy, and the accuracy of the agent is effectively improved.

The invention discloses a heterogeneous data migration method and device, equipment and a storage medium, and relates to the technical field of data migration, and the method comprises the steps: obtaining a heterogeneous mapping rule between a source database and a target database; creating a migration transition table in the target database according to the heterogeneous mapping rule, and synchronizing the to-be-migrated data in the source database to the migration transition table to generate isomorphic mirror image data; performing batch screening on the isomorphic mirror image data based on the target migration factor to generate a batch migration list; and performing format conversion on the batch migration list according to a heterogeneous mapping rule to obtain target format data, and writing the target format data into a target database. The data heterogeneous difference is shielded through the migration transition table, the format conversion process is postposed, and the precision and stability of format conversion are improved; and the risk of single migration is reduced through gradual batch migration, so that the risk of switching between a new system and an old system is reduced. The heterogeneous data migration complexity can be reduced, and the migration efficiency can be integrally improved.

The invention provides a cloud platform database storage use prediction method based on time sequence modeling, and belongs to the technical field of cloud computing operation and maintenance management. The method comprises the steps that historical storage use data of a target database in a cloud platform is collected, a time sequence prediction model is built based on the historical storage use data, and the time sequence prediction model is a Prophet model supporting trend term and periodic term modeling; using the time sequence prediction model to predict the storage usage amount of the target database in a future preset period, and generating a prediction result value; and comparing the prediction result value with a preset capacity threshold value, and if the prediction result value exceeds the preset capacity threshold value, generating capacity early warning information. By automatically and accurately predicting the use trend of database storage and providing early warning information, the automation and foresight of database capacity management are improved.

The embodiment of the invention provides a database table structure repairing method and device, equipment, a medium and a product, and relates to the field of big data. The method comprises the steps of obtaining connection information of a source database and a target database; based on the connection information, obtaining first table structure metadata of a data table of the source database and second table structure metadata of a data table of the target database. And comparing the first table structure metadata with the second table structure metadata to obtain table structure difference information of the source database and the target database. And based on the table structure difference information, obtaining a table structure repair suggestion of the target database by utilizing a difference analysis model constructed based on a large language model. And repairing the table structure of the target database according to the repairing suggestion. According to the method, the database table structure difference is automatically and intelligently recognized and repaired, the efficiency and accuracy of database table structure consistency maintenance are greatly improved, and errors possibly caused by manual operation are reduced.

The invention discloses a data query method and device based on a natural language. The method comprises the following steps: receiving natural language input of a user; performing semantic analysis on the natural language input, and determining a user intention and a plurality of semantic elements; based on the user intention, target query operators corresponding to the semantic elements respectively are determined in a query operator sequence, and the query operator sequence comprises a plurality of query operators arranged according to the execution sequence; generating a query plan based on the target query operators, the semantic elements corresponding to the target query operators and the execution sequence of the multiple target query operators; a query statement is generated based on the query plan and target database object identifiers corresponding to the semantic elements respectively, and the target database object identifiers comprise at least one of table names and field names; and performing data query based on the query statement. According to the embodiment of the invention, the accuracy and the interpretability of the query statement can be improved, so that the accuracy and the reliability of the query result are improved.

The invention discloses a task alignment Text-to-SQL (Structured Query Language) method and system based on a code style thinking chain. The method comprises the following steps: constructing a three-layer structured knowledge base comprising mode-level knowledge, instance-level knowledge and example-level knowledge; generating an initial query based on the target database and the user query; according to the list information in the initial query, constructing an instruction sequence represented by a similar SQL code, and forming a code style thinking chain; based on user query and initial query, acquiring multi-dimensional knowledge from the three-layer structured knowledge base and constructing an enhanced prompt context; and integrating the code style thinking chain and the enhanced prompt context based on the prompt template, and generating an executable final query through a multi-stage task alignment mechanism and a final prompt. According to the method, the problems of incoherence and inaccuracy of logical reasoning, insufficient knowledge generalization ability and multi-type model illusion existing in cross-domain, multi-table connection and complex query in the prior art are solved.

The invention discloses a server cluster monitoring data processing method and device and a medium, and the method comprises the steps: scanning a target directory structure to analyze a directory name, and dynamically recognizing a server node address based on a predefined rule to generate server node list data; executing the data acquisition script on each server node to obtain original monitoring index data, and converting the original monitoring index data into a standardized monitoring data file; based on the historical processing record data and the characteristic value of the monitoring data file, whether the monitoring data file is a to-be-transmitted incremental file is judged through an incremental recognition algorithm, and if yes, the incremental file is transmitted to a central processing node based on a pre-constructed secure connection channel to execute transmission integrity verification, and transmission state data is generated; and performing standardization processing on the transmission state data, importing the processed to-be-imported data file into a target database, and comparing the number of records before and after importing to generate a data integrity report.

The invention provides a heterogeneous database query method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out security verification processing on a plurality of SQL execution requests sent by a user side, and carrying out SPI mechanism scanning processing on a plurality of database plug-ins in a heterogeneous database plug-in directory based on a high-performance database connection pool after the security verification processing is passed, determining a target database plug-in package corresponding to each SQL execution request; and performing metadata query processing on the SQL execution request in the target data source based on a database operation client interface and a metadata service interface under the target database plug-in package, and determining a structured tree result. According to the method, an extensible and dynamically integrated heterogeneous database plug-in mechanism is realized, unified access of various databases is supported, the platform maintenance cost is remarkably reduced, hierarchical metadata of any type of databases is obtained through a consistent metadata service interface, and the user experience and the cross-database query efficiency are improved.

The invention relates to the technical field of computers, and discloses a business data synchronization method and device, equipment, a storage medium and a program product. The method comprises the steps that under the condition that it is detected that a service message corresponding to an associated service node exists in a message queue, to-be-synchronized service data is extracted from the service message, the to-be-synchronized service data is stored in a first database bound with the associated service node, and the service message is generated by the associated service node based on the to-be-synchronized service data; according to a business mapping rule between the target service node and the associated service node, a target database used for storing business data to be synchronized is selected from a plurality of second databases bound to the target service node, and the first database and any second database belong to different technology stacks; and synchronizing the to-be-synchronized service data to the target database. By adopting the method, the synchronization effect of performing data synchronization on the business data between the cross-technology stack databases can be improved.