367 results about "Database connection" patented technology

The invention provides a different types of database visualization table management method and system, and relates to the technical field of computers.The method comprises the steps that a database general operation system comprising a general operation interface and a dialect abstract base class is constructed, and a query performance evaluation system is established based on performance data; and predicting an optimal database connection mode through deep reinforcement learning and generating a multi-stage execution plan. Meanwhile, an anomaly feature knowledge base based on a graph neural network is constructed, and anomaly prediction and preventive processing are carried out based on the anomaly feature knowledge base. A multi-stage execution plan is executed after a database operation request is subjected to grammar adaptation, and a distributed transaction processor dynamically adjusts a transaction isolation level and a concurrency control parameter. And finally, according to the terminal and the data volume, selecting a proper data display mode to carry out visual presentation.

The invention relates to the technical field of data processing, in particular to a knowledge graph construction method for multi-source heterogeneous data of power transformation main equipment and a related system.The method comprises the steps that multi-source heterogeneous data collection is carried out, and for structured database data, a database connection tool is adopted, and needed data is obtained by writing SQL query statements; analyzing the semi-structured data by using a corresponding analysis library to extract key information, and converting the key information into a structured data format; for unstructured text data and webpage data, a natural language processing technology and a web crawler technology are adopted; according to the knowledge graph construction method for the multi-source heterogeneous data of the power transformation main equipment, the data utilization rate is increased, and the data can be enhanced and supplemented by introducing a data enhancement algorithm in secondary data processing.

The invention provides a cross-database unified management and operation method and system, and relates to the technical field of databases, and the method comprises the following steps: establishing a connection by obtaining database connection information; extracting a database structure by using a dialect strategy processor and mapping the database structure into a unified description; converting the operation instruction into a standard intermediate statement; converting the intermediate statement into a target database execution statement by using a grammar analysis module and a conversion rule; and executing and monitoring in a transaction unit mode. Unified management and operation of different types of databases are realized, the consistency and reliability of database operation are improved, and the development difficulty of cross-database operation is reduced.

The invention provides a non-technician-oriented script intelligent adaptation and visual arrangement method and a non-technician-oriented script intelligent adaptation and visual arrangement system. The method comprises the following steps: acquiring a script file uploaded by a user, extracting a dependency library through an AST analysis technology, and constructing an isolation container environment; performing intelligent identification and conversion on a file path and database connection in the script to generate a standardized API call; carrying out input and output analysis on the basis of the converted script, and carrying out DAG workflow arrangement in a visual mode; performing function-level packaging and standardization processing on the script component in the workflow to realize component multiplexing and version management; and finally, configuring a scheduling strategy and carrying out automatic operation monitoring. According to the method, a script environment depends on automatic processing and intelligent path adaptation, and visual arrangement and modular multiplexing are combined, so that non-technical personnel can independently complete the whole process from AI script generation to a production-level automatic process, the problem of'last kilometer 'in script deployment is solved, and the working efficiency is improved.

The invention discloses an enterprise data link management and value management method and system, and the method comprises the steps: carrying out the real-time capturing of multi-source heterogeneous data of all business systems in an enterprise through a distributed data collection engine, and recognizing the types of original data in different formats through a preset data source adapter; if structured data is detected, a relational database connector is adopted for extraction, and if the structured data is recognized as unstructured data, a document analysis module is started for content extraction, and an initial data set containing metadata tags is obtained; performing format conversion and field mapping on the initial data set according to a pre-established data standardization rule base, eliminating duplicate records and abnormal values through a data cleaning algorithm, performing automatic evaluation on a data quality grade by adopting a naive Bayes classifier, if a data quality score is lower than a preset threshold value, triggering a data recovery process, and if the data quality score is lower than the preset threshold value, performing data recovery. And standardized data meeting a unified standard is obtained. The normativity and value utilization efficiency of data management are effectively improved.

The invention relates to the technical field of database migration verification, in particular to a cross-data-platform database migration verification method and system applied to autonomous controllable transformation. The method comprises the following steps: configuring a source database and a target database in a data source management module; newly establishing a comparison task in the task management module; a comparison database is connected through a dynamic data source assembly, different databases are connected through JDBC, and comparison verification is executed after database connection parameters are configured; database comparison is carried out in the task management module, wherein the database comparison comprises data volume verification and data consistency verification; a comparison report is generated and stored in a built-in mode. The problem of data integrity in the cross-platform data migration process is solved, the system fully considers the difference between the MySQL database and the local database in character set, function and technical characteristics, data verification and comparison work after migration of the MySQL database source and various local target databases is supported, consistency verification before and after data migration is achieved, and the verification efficiency is improved. And the risk of data loss caused by data migration is avoided.

The invention particularly relates to an automatic index creating method based on a large model. According to the automatic index creation method based on the large model, after a user inputs a demand and carries out preprocessing, named entity recognition is carried out by utilizing the large language model, key entity information is extracted, and a structured demand parameter is generated; matching a template from the SQL template library and dynamically filling the template, and obtaining an SQL statement after grammar verification and performance optimization; connecting a data source through a database connection technology, executing the SQL statement, and obtaining an index calculation result; and checking the result, defining parameters of the API interface according to the interface specification, generating an interface document, and issuing the interface document. According to the automatic index creation method based on the large model, the working efficiency is greatly improved, the labor cost is reduced, meanwhile, index calculation errors caused by manual understanding deviation can be avoided, the accuracy of an index calculation result is ensured, the interface adaptation and development workload is reduced, the system integration difficulty is reduced, and the implementation is easy. And the data sharing and interaction efficiency is improved.

An intelligent system for a photovoltaic cleaning robot includes: a control terminal, an intelligent control center, a stain detection database, and an intelligent device; where the intelligent device includes a camera shooting module, a motion flight module, and a cleaning module; the intelligent device and the intelligent control center are integrated on the photovoltaic cleaning robot; the intelligent control center and the control terminal are connected by a wireless communication; the intelligent control center is connected to the stain detection database through the wireless communication. In the intelligent system for the photovoltaic cleaning robot, even in a distributed photovoltaic power station with a harsh environment and terrain, it can also do the unmanned intelligent cleaning operation and maintenance work of the photovoltaic plate, where the operator only needs to operate the control terminal according to the attenuation of power generation of the power station to issue simple instructions.

The invention provides a construction method of an intelligent personalized interaction system. The construction method comprises the following steps: constructing a database; preparing a training set and a test set with problem texts, constructing a vocabulary of high-frequency words for the training set and the test set, and performing text coding; constructing a workflow scheduler for counting high-frequency problem types; the user portrait building module is used for obtaining a user portrait according to historical dialogues, user questions and high-frequency question types of the database; the intelligent personalized interaction system comprises a user question input interface, a question classification module and a database which are connected in sequence, and the database is connected with a workflow scheduler and a user portrait construction module. And outputting the user portrait and the high-frequency question type to a pre-trained large language model to generate a recommendation question. The invention further provides a corresponding system. According to the method, deep understanding, accurate analysis and personalized interaction of user questions are realized, so that the user experience is remarkably improved, and diversified requirements of users in different scenes are met.

The invention provides a dynamic database connection pool adjustment method and system, and relates to the technical field of computers, and the method comprises the steps: collecting the operation state data of a target dynamic database connection pool in real time, and sending the data to a configuration center; the configuration center determines a connection number adjustment index based on the received operation state data of the connection pool in combination with a connection request of the current target dynamic database connection pool; and based on the connection number adjustment index, the configuration center dynamically updates the maximum connection number of the connection pool, and notifies the connection pool module to update. The operation state data of the target dynamic database connection pool acquired in real time is calculated by using the configuration center in combination with the connection request to obtain the connection number adjustment index, and then the maximum connection number of the connection pool is dynamically updated by using the connection number adjustment index, so that the external service capability of the connection pool is effectively improved, and stable operation of a service system is ensured.

The invention discloses an intelligent SQL generation and optimization system and method based on an index semantic model, and relates to the technical field of data processing, and the system comprises a business configuration layer which is used for configuring basic information of indexes based on preset structured definition elements; the model assembly layer is used for assembling the basic information and the blood relationship information into a layered index semantic model according to the blood relationship of the indexes and database connection information, and automatically adjusting the structure of the index semantic model by adopting a semantic model dynamic optimization mechanism; and the model analysis and execution layer is used for analyzing the index semantic model, generating corresponding structured query language segments and splicing the structured query language segments to obtain a complete structured query language. Semantic elements of the structured index semantic model are intelligently disassembled through the model analysis engine, standardized SQL code blocks are dynamically generated, the query performance is improved, and calculation redundancy is reduced.

The invention relates to a double-token authorization refreshing method, device and system based on dynamic expiration tolerance. The method comprises the following steps: modeling the dynamic expiration tolerance according to the number of requests per second qps of a key API, the response time Tresp of the key API and the utilization rate U of a database connection pool; for a first request of which the access token is expired and the refresh token is not expired, if the expiration duration of the access token corresponding to the request is within the corresponding dynamic expiration tolerance, setting a distributed lock for the request, triggering a token refresh mechanism at the same time, and after the token refresh mechanism is executed, releasing the distributed lock; and for a subsequent request of the first request, if the expiration duration of the access token corresponding to the request is within the corresponding dynamic expiration tolerance, the token refreshing mechanism is not triggered, and normal access is directly allowed. According to the method, modeling is performed on the dynamic expiration tolerance, and the pain points and the problems that in the prior art, expiration tolerance time parameters are fixed, and static configuration is not flexible are solved.

The invention provides a graphical programming education system, which comprises a database used for storing coding information and drawing data; the scheduler is connected with the database and used for managing data flow between the database and the interpreter; the interpreter is connected with the scheduler and is used for analyzing the coding information and generating a task in an intermediate representation form which can be understood by the system; the judgment module is connected with the interpreter and is used for carrying out logic judgment on the task and providing a control signal for the operation module; the operation module is connected with the judgment module and is used for executing the task according to the control signal and transmitting the output to the output module; and the output module is used for displaying the result transmitted by the operation module. The system is used for realizing bidirectional mapping and real-time synchronization between the coded information and the graphical representation, and realizing dynamic visualization of the coded information logic based on the data flow.

The invention provides an automatic script generation method and system based on the Internet, and the method comprises the steps: obtaining a database connection address, a database name and a project name inputted by a user; determining a target database based on the database connection address and the database name; defining in a target database based on the item name, and determining field information of a target model; determining a Redis cache and a message queue plug-in corresponding to the target model based on the field information of the target model; determining model configuration of the target model based on the target task selected by the user and the field information; generating a basic function framework based on the model configuration of the target model, the Redis cache and the message queue plug-in; according to the parameter information configured by the user, generating an automatic script based on the basic function framework; according to the method and the system, the development efficiency can be improved, and the maintainability and the expandability of the project are enhanced.

The invention discloses an intelligent cloud management high-definition card printer system, and relates to the technical field of card printers, the intelligent cloud management high-definition card printer system comprises a processor, a database and a printing module, the processor is connected with the database through signal transmission, and the printing module is connected with the processor through signal transmission. The printing module comprises an information acquisition assembly and a printing assembly, the information acquisition assembly is used for acquiring material information and environment information, the printing assembly is used for printing cards, and the processor controls the printing module to start by receiving a primary starting signal and a secondary starting signal. The processor constructs a color compensation module through information collected by the information collection assembly to output a color compensation value to adjust the printing assembly. By designing and constructing the color compensation model, the function of high-precision card printing is realized, the problems of dependence on off-line measurement, color gamut deviation and response lag are solved, the color deviation can be compensated in real time, and the quality and specialty of card printing are improved.

The invention relates to the technical field of databases, and provides a data reading method, a client, a server and a storage system. The data reading method is applied to a client. The method comprises the following steps: receiving a first operation; according to the first operation, cyclically executing the following steps S1 to S3: S1, determining an idle connection from the N KV database connections; s2, a data reading request is sent to the server through the idle connection, the data reading request comprises a first command, a data identifier of the target data, a reading vernier and a reading step length, and the first command is used for instructing the server to read a data segment corresponding to the data identifier from the KV database according to the data identifier, the first reading vernier and the reading step length; s3, receiving a reading result returned by the server, wherein the reading result comprises a data segment corresponding to the target data; and when a first preset condition is met, stopping circulation, and splicing all the read data segments according to a reading sequence to obtain target data.

The invention discloses an intelligent service starting arrangement system based on container life cycles, and particularly relates to the field of containerized starting service management. Comprising an arrangement control layer, a pre-detection layer and a life cycle management layer. The arrangement control layer comprises a starting manager module, a dependency relationship analysis sub-module, an arrangement strategy control sub-module and a starting sequence scheduling sub-module; the pre-detection layer comprises a multi-dimensional pre-detection engine, a port availability detection sub-module, a database connection verification sub-module, a configuration integrity verification sub-module and a resource ready state check sub-module. The life cycle management layer comprises a container life cycle monitoring module, a construction stage management sub-module, an operation state tracking sub-module and a stop process control sub-module. A multi-dimensional pre-detection engine, DAG-based complex dependency relationship management, intelligent fault classification and adaptive recovery, container life cycle full-stage perception and dynamic starting of an arrangement strategy are realized.

The invention belongs to the technical field of data processing, and discloses an active intelligent operation and maintenance monitoring method for a data center, which comprises the following steps: step 1, component modeling and topology configuration; 2, carrying out distributed health detection and data acquisition; 3, performing real-time health assessment and anomaly detection; 4, performing intelligent alarm and root cause analysis; 5, unified operation and maintenance and closed-loop control are carried out; and step 6, dynamically optimizing the intelligent operation and maintenance strategy. According to the method, a monitoring object and a dependency relationship are clarified through component modeling and topological configuration, and specific scenes, such as multi-mode acquisition, active detection, index pulling, log analysis, coverage message queue theme accumulation and database connection pool exhaustion, of distributed health detection are combined. The quantitative health score is calculated based on the preset scoring model, and by combining with the dynamic baseline learned by the ARIMA or LSTM algorithm, the module abnormity can be actively detected in different periods and weekly updating, and the problems of fault discovery lagging and incomplete monitoring coverage are solved.

The invention provides a data probing method and system. The method comprises the steps of metadata basic information probing, metadata field security attribute probing and metadata blood relationship probing. Null value, NULL value and non-null-duty ratio exploration, data volume and distribution exploration, field attribute and distribution exploration and security exploration are carried out; data security analysis, data integrity and distribution analysis, and data relationship and distribution analysis are carried out. According to the invention, through intelligent automatic analysis and identification, null values, redundant information and performance bottlenecks in data are found in real time, and accurate support is provided for subsequent data governance; the probing task can be automatically completed only by inputting basic database connection information and related parameters, so that the efficiency is improved, and manual intervention is reduced; the universality is high, different database environments and data scales are adapted, and the probing process is efficient and accurate; the structure, the use condition and the potential risk of enterprise data assets can be deeply known, so that data management is accurate and efficient, and digital transformation and intelligent decision making are promoted.

The invention provides a data consanguinity analysis method and device for an ETL system and electronic equipment, and the device comprises an acquisition module, an analysis module, an integration module, a storage module and a display module. And the acquisition module is used for acquiring metadata information related to ETL operation from various data sources, and the acquisition modes comprise active data acquisition through an API interface, database connection and the like, or data push from other systems is received. According to the data consanguinity analysis method and device for the ETL system and the electronic equipment, the input and output data streams of the nodes are deeply analyzed, the transmission path of the data among the nodes is accurately identified, the data consanguinity of all the nodes in the flow is integrated, and a complete and consistent flow-level data consanguinity graph is generated.

The invention discloses a method and a system for generating and updating an atlas of a BOM table in prototype design and research and development, and the method comprises the following steps: regularly extracting BOM data of a main material and a sub-material from a source database, establishing a corresponding relation and a quantity detail table of the main material and the sub-material, and obtaining an atlas of the main material and the sub-material by adopting SQL query and recombination of a material hierarchical structure; converting the data according to the hierarchical relationship of the materials, generating a plurality of hierarchical conversion tables of the main materials and the sub-materials, and loading the tables into a target SQL Server database; database connection is established in Excel, a hierarchy conversion table is updated and inquired, and data of each hierarchy of BOM is extracted and put into a plurality of worktables to be displayed respectively; performing multi-row-to-multi-column reconstruction on the single-level BOM data respectively displayed in the plurality of worktables according to a hierarchical structure, and finally summarizing the single-level BOM data into the same multi-level BOM table; material information of each level is extracted from the multi-level BOM table at regular time, node relation data is automatically generated through conversion and job scheduling functions of Kettle, and the node relation data is updated to a Neo4j database at regular time; and according to the node relation information in the Neo4j graph database, using a D3 force oriented graph to realize the graphical display of the multi-level BOM table. According to the method, the automation degree and the visualization effect of BOM data processing are improved.

The invention discloses an intelligent teaching system based on artificial intelligence. The system comprises a user information acquisition module, an intelligent analysis module, an English teaching data database, a personalized learning path planning module, an interactive learning module and an evaluation module. The user information acquisition module is connected with the intelligent analysis module, the personalized learning path planning module is connected with the intelligent analysis module and the English teaching material database, the interactive learning module is connected with the personalized learning path planning module, and the evaluation module is connected with the English teaching material database and the interactive learning module. The beneficial effects are that learning efficiency is effectively improved; the learning interest is effectively improved; individual differences are effectively met; and the accuracy of learning effect evaluation is enhanced.

The invention relates to the technical field of data processing, in particular to a remote medical training system, which comprises a training module comprising a data transmission unit for transmitting medical training data from a database to a user terminal; the data processing module is connected with the training module and comprises a data synchronization unit used for synchronizing the medical training data and a data backup unit connected with the data synchronization unit and used for backing up the medical training data; the storage module is used for storing the medical training data, the simulation practice operation, the synchronized medical training data and the backed-up medical training data; and the control module is used for determining the capacity of the database connection pool according to the variance of the response duration for displaying the medical training data or determining the synchronization frequency of the medical training data according to the repetition proportion of the medical training data. The operation stability of the medical training system is improved.

The invention provides a heterogeneous data synchronization method and device for a database and a medium, and belongs to the technical field of database data processing. The method comprises the following steps: accessing a source end database through a preset database connection interface, and obtaining corresponding to-be-synchronized business data and source end table metadata; according to the source end table metadata and a preset type mapping rule, generating a target table of a target end database; constructing a binary assembler corresponding to the target table based on an underlying storage structure set obtained by pre-analyzing a target end database; wherein the binary assembler is used for converting to-be-synchronized service data into a binary stream containing a first data segment and a second data segment; the first data segment at least comprises a type identifier and storage format information corresponding to the target end database. And according to the to-be-synchronized business data and the corresponding binary assembler, generating a corresponding binary input stream, and writing the binary input stream into the target table so as to complete heterogeneous data synchronization of the source end database and the target end database.

The invention discloses a database performance optimization method and device based on an eBPF, equipment and a medium, and relates to the technical field of databases, and the method comprises the steps of deploying a probe on a key path of a database kernel by using a dynamic detection mechanism of the eBPF, obtaining various performance data of a database in a running process based on the probe, and storing the performance data in the database; establishing a mapping relationship between the network traffic and the database session ID by using a first preset data structure of the eBPF; identifying the abnormal connection condition of the database based on the mapping relation and the performance data, and analyzing the access condition of the lock and the disk in the operation process of the database to obtain a performance problem; and determining parameter indexes including lock waiting times per second, I / O queue depth and TCP retransmission rate based on the performance data, inputting the parameter indexes into a machine learning model, and generating problem root causes and optimization suggestions corresponding to the performance problems in combination with a root cause positioning rule engine. And the database performance problem is analyzed and optimized quickly and efficiently.

The invention relates to the technical field of data processing, in particular to a pandas-based cross-database query method, system and device and a medium. The method comprises the following steps: configuring and storing database connection information, receiving a cross-database query request, and decomposing the cross-database query request into sub-query requests; establishing database connection according to the sub-query and connection information, executing query by using a pandas function, and storing a result as a DataFrame object; processing the problem that data types and field names are inconsistent, and associating a plurality of DataFrame objects to generate a final result; and outputting the result in a specified format. The system comprises a configuration module, a request processing module, a query execution module, a data integration module and a result output module. According to the method, the efficient processing capacity of the pandas is utilized, and the query performance is improved; multiple databases are supported, and the development difficulty and cost are reduced; consistency and integrity are guaranteed in data integration, and data problems are avoided.

The invention discloses a database management service integration Dify method and system, belongs to the technical field of databases, and aims to solve the technical problem of how to improve the intelligence of database management services and realize the database capabilities of intelligent question and answer, index optimization and SQL (Structured Query Language) tuning. Integrating a Dify entry from an SQL window and an intelligent assistant, introducing a problem, database connection information and database table structure knowledge base information to Dify, calling a database management service database in Dify workflow to connect an API, and directly accessing a database according to the database connection information and the generated SQL to perform SQL execution; maintaining an association relationship between the database and the database table structure knowledge base in Dify, and regularly updating the database table structure knowledge base in Dify; a big language model is accessed to a database management service through Dify, and the Dify is connected with different databases through a database management service database.

The invention relates to the technical field of database security, in particular to an SQLite database transparent encryption method, system and device based on a national cryptographic algorithm and a storage medium, and the method comprises the following steps: S1, when an SQLite database is opened, loading and connecting a hardware cryptographic device to obtain an encryption master key and a corresponding key handle; s2, in response to the write-in operation, calling a national secret symmetric encryption algorithm through a key handle, encrypting a plaintext of a database page to generate a page, and writing the page into a database file; s3, reading the ciphertext page in response to the reading operation, decrypting the ciphertext page through a cryptographic symmetric decryption algorithm adjusted by a key handle after analysis, recovering a plaintext page and returning the plaintext page to the application; and S4, circularly executing encryption writing and decryption reading to process the continuous request, and releasing the key handle and disconnecting the hardware connection until the database connection is closed. According to the method, transparent full disk encryption, meeting the national secret standard, of the SQLite database is achieved, the secret key safety and the operation performance are guaranteed through hardware cryptographic equipment, and good application compatibility is kept.

The invention belongs to the technical field of databases, and discloses a method for efficiently and adaptively converting Python native SQL (Structured Query Language) into a domestic database, which comprises the following steps of: S1, analyzing a Python native SQL code, and identifying the type of an original database; s2, selecting a corresponding conversion rule set according to the original database type and the target database type; s3, converting the SQL statement of the original database by using the conversion rule set; s4, adjusting original database connection information according to the target database type; s5, integrating the converted SQL statement and the adjusted database connection information to generate a new operation code; and S6, testing the new operation code. The method has the advantages that the native SQL can be automatically converted into the grammar suitable for the domestic database, a large amount of modification and debugging work is reduced, the project migration efficiency is improved by 95% or above, and the Python project migration localization efficiency is greatly improved.

The invention provides a college entrance examination volunteer filling assisting method and system based on a large language model, and the method is characterized in that the method comprises the steps: presetting a question template and an SQL template according to the volunteer filling scene demands and a database schema; analyzing a natural language query Q by adopting a large language model and designing a cue word, and combining a question template sequence number and an analysis result to generate a structured query condition set CQ; generating a database SQL query statement according to the CQ in combination with a preset SQL template; and managing database connection by using a connection pool technology, executing SQL query, generating a result set RS, and outputting information to a user. Through the method, the query efficiency and the interaction friendliness of the volunteer filling auxiliary system are improved.