18 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 discloses a multi-person cooperative bus database design method. The method comprises the following steps: an administrator creates each vehicle series and appoints a vehicle series administrator to generate vehicle type information; a vehicle system administrator creates vehicle system sub-vehicle models, creates network segments for the sub-vehicle models and sets network segment administrators, and network topology information of the sub-vehicle models is formed; each network segment administrator edits network segment data and uploads the network segment data to a server to generate a signal library; a vehicle manager creates a vehicle type routing table according to the signal library, and each network segment automatically generates a mapping message and a signal according to the vehicle type routing table; each network segment administrator edits a receiving signal of each node in respective network segment data; checking the consistency of the data of each network segment, uploading the data to a server, maintaining the version by a vehicle administrator, and releasing information to form a current version database; and the car administrator applies to release the current version database from the administrator, and the administrator freezes and releases the current version database after checking that the current version database has no problem. The multi-user collaborative design requirement of new vehicle type development is met.

The application realizes a privacy computing oriented scalable data fine-grained access control system through a method in the field of network security. A complete functional system is formed by setting three parts of a management center service, a high-availability agent and a data agent service. The management center service is managed by an administrator, sets a management authentication user, manages a security protection strategy, and issues a rule strategy to the data agent service and the high-availability agent. The high-availability agent is forwarded to the database agent service through an agent port. The data agent service is serially arranged between a business system and a database to control access of the business system to the database. The system provided by the application realizes horizontal expansion of data access control capability under high-concurrency database requests through a mode of dynamically increasing the database agent service. The system realizes more fine access control of the database by a business system or a database administrator through deep analysis of SQL.

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.

The invention discloses a forward security searchable encryption method and system supporting multiple data owners, and the method comprises the steps: a database administrator carries out key generation and distribution, the data owners carry out data updating encryption, and the data users carry out trap door generation and keyword retrieval. The information leakage risk of adding / deleting operation is effectively controlled, and the efficiency bottleneck caused by complex password operation of a traditional public key scheme is broken through. On the basis of a set limitation pseudo-random function, cross-epoch forward security is realized, the secret state data retrieval efficiency is remarkably improved through a parallel retrieval mechanism, and efficient ciphertext retrieval in a multi-data owner collaborative environment is supported. According to the system, symmetric cryptographic primitives are fused, data confidentiality and searchability are considered, the system is suitable for security storage and dynamic retrieval requirements of private data in a cloud / edge computing environment, and key technical support is provided for data privacy protection in a big data fusion environment.

The present invention discloses a memory-based dump method for a seismic database, comprising: obtaining database information of a source database and a target database; parsing an SQL model file in the source database to obtain database table dump information; creating a source database memory object and a target database memory object based on the database information and initializing the memory objects; reading memory data from the source database memory object based on the database table dump information, writing the memory data to a cache in a target database, and cyclically reading and writing to perform a database memory dump; writing the cache of the target database to a disk and closing the target database and the source database. The present invention also discloses a memory-based dump system for a seismic database. The present invention realizes fast memory dumping between different operating systems, helping database administrators complete data backup and recovery between databases on different platforms, which is not only efficient but also saves disk resources.

The invention relates to a method for preventing SQL (Structured Query Language) statement misoperation, which belongs to the technical field of databases and comprises the following steps: SQL statement marking: identifying SQL statements based on machine learning, and marking the SQL statements with potential misoperation possibility; judging an operation type: judging whether the SQL statement is read operation or write operation; evaluating an influence range: for the SQL statement of the write operation, analyzing a data size scale of a table related to modification of the SQL statement and whether the table is a key table or not; if the data size of a table related to the SQL statement exceeds a preset threshold value or modification of a key table is related, it is judged that the SQL statement is a high-risk SQL statement, and the SQL statement is submitted to a database administrator to be audited; and otherwise, judging that the SQL statement is a low-risk SQL statement, and providing an execution prompt. According to the method, comprehensive risk assessment and screening are carried out before the SQL statements are executed, the high-risk SQL statements can be effectively recognized, forced auditing is carried out, and the database safety problem caused by misoperation is avoided.

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 discloses a high-security and high-transparency transaction system, and the system comprises a transaction processing module which is used for processing a transaction request and packaging transaction information; the lightweight block chain node module is used for recording the transaction hash value to a distributed account book; the security protection module is used for guaranteeing the security of the transaction data; the auditing interface module is used for providing a financial auditing function; according to the method, the transaction hash value can be recorded to the distributed account book by integrating the lightweight block chain node, and the transaction data is effectively prevented from being maliciously tampered by using the non-tampering characteristic of the block chain; even if an administrator of the database tries to tamper the data, the tampering operation cannot be accepted by other nodes in the block chain network due to the distributed characteristics and the consensus mechanism of the block chain, so that the security and the integrity of the transaction data are guaranteed.

The invention relates to an SQL audit data monitoring method and device realized based on ES. The method comprises the following steps: starting an audit function of a Vastbase G100 database and configuring related parameters; collecting audit data by using an audit data collector, and storing the audit data to Elasticsearch; and storing and indexing the collected audit data for query and display. By efficiently collecting, storing and indexing the SQL audit data, real-time monitoring of database operation is achieved, and transparency and safety of database operation are effectively improved. The method has the advantages that a large amount of audit data can be analyzed in real time, detailed audit records are provided, a database administrator is helped to find and process abnormal operation in time, and the safety and compliance of a database are ensured. By combining the advantages of Vastbase G100 and ES, an efficient and reliable solution is provided for database auditing in a modern information system.

Architectures and techniques are described that can personalize, customize, or otherwise tailor a presentation of product version update information in accordance with certain embodiments of this disclosure. Such can be accomplished by comparing software product version data (e.g., release notes, data from a code repository, data from a documentation repository, . . . ) to customer data (e.g., customer equipment, topology, configuration, settings, . . . ). The tailored output can be tailored to a specific customer, a specific role within the customer organization (e.g., security officer, database administrator, . . . ), or a specific user within the customer organization. The tailored output can be targeted to appeal to a specific audience, increasing the likelihood of prompt acceptance of the new version of the software product.

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.