10 results about "Database administrator" patented technology

The application provides an intelligent diagnosis method and related device of a database cluster. The intelligent diagnosis method of the database cluster comprises: collecting running state data of each database instance in the database cluster at a preset time interval; selecting a target database cluster in a working state from the database cluster according to the running state data; determining an abnormal score of each target database in the target database cluster according to a preset weighting rule and a running index parameter of the target database cluster; when the abnormal score is higher than an abnormal threshold, collecting abnormal event data in a first target database corresponding to the abnormal score according to a preset collection rule, calling a pre-trained intelligent diagnosis model to analyze the abnormal event data, and generating a diagnosis report and a stop-loss suggestion set. The application reduces the experience dependence on experienced database administrators.

The invention relates to the technical field of database management, in particular to a database operation condition detection method and system based on a LoRA fine-tuning large model, and the method comprises the following steps: data collection, LoRA fine-tuning large model construction, real-time detection, and abnormity positioning and processing. The method has the beneficial effects that the big language model is finely adjusted through the LoRA technology, so that the model can learn complex features and rules of database operation data, and compared with a traditional method, abnormal conditions in the database operation process can be more accurately recognized, and the false alarm rate and the missing report rate are reduced. Meanwhile, the method not only can detect anomalies, but also can utilize the reasoning ability of the model to locate the reason of the anomalies and provide optimization suggestions, thereby providing intelligent decision support for database administrators, and improving the efficiency and level of database management.

The application relates to an interest calculation management method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: obtaining a safe operation parameter of an interest calculation task; the interest calculation task comprises an interest calculation batch task and a log file duplication task; performing the interest calculation task according to the safe operation parameter; in the process of performing the interest calculation task, the running state of a database and the CPU running state of a first server satisfy a preset running condition; the database is used for storing a log file corresponding to the log file duplication task. The interest calculation management method is an automatic interest calculation management method, manual adjustment of related parameters of the interest calculation task and subsequent operation and maintenance operations are not needed, uncertainty caused by manual operation is reduced, and it is ensured that the interest calculation task can be safely operated.

The invention is applicable to the technical field of computers, and provides an SQL (Structured Query Language) statement auditing method which comprises the following steps: receiving a to-be-audited SQL statement, generating an execution plan tree from the SQL statement, and extracting an operator node sequence from the execution plan tree; performing atomic feature extraction on each operator node in the operator node sequence to obtain a multi-modal feature vector; for each operator node, cost prediction and performance prediction are carried out based on the multi-modal feature vector, and a multi-modal feature portrait is constructed; performing multi-target causal analysis on the basis of the multi-modal feature portrait, and determining dominant features; on the basis of the dominant features, optimization suggestions are generated in combination with a large language model, the limitation of single-dimensional analysis is broken through, multi-objective collaborative optimization of performance and cost is achieved, the professional threshold and workload of database administrators and developers are greatly reduced, and the efficiency of SQL auditing is improved.

The application discloses a complex connection load generation method for different connection shapes, comprising the following steps: step one: connection graph generation: according to the number of user-defined participating connection tables, the queried connection shape and the reference relationship between the tables, a connection template generation method suitable for different connection shapes is used to generate a load template with different connection shapes; step two: filter predicate generation: according to the connection graph, a filter predicate is randomly generated for each table in the template; step three: parameter instantiation: the filter predicate is filled with parameters through a result-oriented parameter instantiation method, so that the query result is not empty. The application also discloses a load generation system for implementing the load generation method and application of the load generation system in complex connection load generation. The application can automatically generate large-scale, rich, diverse and effective complex connection loads, provide rich test scenarios for query optimizer evaluation, and help database administrators effectively evaluate query optimization performance.

The application discloses a cloud-native distributed database load index risk statement identification system and method, and belongs to the technical field of distributed databases. The technical problem to be solved by the application is how to improve the accuracy of database load index, reduce the knowledge reserve and ability requirement of a database administrator, simplify the difficulty of index maintenance and optimization of the database administrator and users, improve work efficiency, and adopt the technical scheme. The system comprises a health analysis rule engine unit and a machine learning analysis unit. The health analysis rule engine unit is used for establishing a rule engine, considering rules from multiple dimensions, and establishing a mathematical statistical model based on the data distribution of the application load portrait multidimensional features to form a parameter-based rule. Each rule has corresponding parameters, which are default experience values and can be adjusted by users. Different analysis sensitivities are set by adjusting the analysis parameters to identify SQL statements that may have missing indexes and SQL statements that have optimization space.

The invention relates to a database technology, in particular to a database procedural program running state display method and a related product. The display method comprises the steps of creating a stack corresponding to a procedural program in response to an execution instruction of the procedural program; dynamically updating the stack based on the execution state of the nested statement of the procedural program in the execution process; and according to the updated stack, refreshing a sub-query field in a view of the database so as to display a nested statement which is currently executed in the procedural program. According to the display method, the stack and the view additionally provided with the sub-query fields are utilized, real-time visual display of the currently executed nested statements in the procedural program is achieved, the limitation that a traditional view can only display a top-layer program is broken through, the real-time performance and effectiveness of running state display of the procedural program are guaranteed, and the user experience is improved. And a database administrator can quickly master the execution progress of the procedural program, so that a foundation is laid for subsequent performance analysis and problem positioning.

An embedded next generation access control system imposes fine-grained access control on data in a resource database and includes a resource database, NGAC database, administrator, and mediator. The resource database includes controlled resource data and a mediator. The NGAC database includes an adjudicator and access control policy data. The administrator communicates access control policy input to the NGAC database upon which access control policy data is made in the NGAC database. The controlled resource data is access controlled by access control policy data via calls of an adjudicator API, which implements Next Generation Access Control standard by NIST, by the resource database to obtain access decisions. The adjudicator determines which controlled resource data are accessed by a user and provides an access control list for each user and user attribute. The adjudicator also provides a prohibited access control list for a user and user attributes in the access control policy data if there are any.

This application relates to the field of computer technology, specifically disclosing a database lock location method and apparatus, storage medium, and computer device. The method includes: when a database lock is detected in a target database, determining the database view corresponding to the target database; obtaining first target information from the database view, and determining second target information from the first target information using a preset lock model; parsing the second target information, determining a target blocking session from the second target information, and locating the database lock based on the target blocking session. This application determines the first target information through a database view, determines the second target information based on the first target information and a preset lock model, and finally locates the database lock based on the second target information. This achieves the technical effect of accurate and rapid database lock location, improving the efficiency of database lock location and greatly enhancing the user experience for database administrators.

The invention relates to the technical field of big data. The dynamic data sub-library and sub-table strategy generation method based on large model driving comprises the steps of collecting operation indexes of a database and business, and obtaining a business data access mode portrait in combination with business topology and consistency requirements; according to the business data access mode portrait, obtaining a candidate sub-library sub-table strategy scheme through a large language model reasoning technology; performing risk assessment on the candidate sub-library and sub-table strategy schemes to generate a strategy verification list and a risk prompt; according to the strategy verification list and the risk prompt, an executable operation and maintenance operation manual is obtained through a migration path planning technology, and the executable operation and maintenance operation manual is used for being manually executed by a database administrator DBA; obtaining strategy implementation effect monitoring data according to the implementation effect of the executable operation and maintenance operation manual; and performing database and table division rule constraint extraction on the strategy implementation effect monitoring data to generate a strategy knowledge base.