21 results about "Database engine" patented technology

Methods for replicating transactional tables of a transactional database to a recipient system, such as an analytical database, and maintaining updates to those transactional table representations are disclosed. More particularly, change-data-capture items are generated by a transport engine, that is separate from a database engine for the transactional database. Also, schema data is maintained out-of-band from the database engine and is stitched with committed change payload contents by the transport engine.

The invention relates to an interactive monitoring method and device for a database running state and electronic equipment. The method comprises the steps that when an interaction instruction in a digital or keyword form input by a user is received, a database running state index is obtained from the interior of a database engine; according to a preset diagnosis rule, key indexes are extracted from the database operation state indexes, the key indexes are integrated, and a refined index set is generated; the refining index set is used as an analysis object, index analysis of the corresponding analysis dimension is triggered according to the interaction instruction, and an analysis result is obtained; and performing layered display on the refining index set based on an analysis result. The technical problem that existing database monitoring lacks real-time performance, flexibility and operation efficiency is solved.

This application provides a data sorting method, a database engine, and a storage medium. In this application, for scenarios involving multi-column sorting, the data rows to be sorted are first grouped according to the clustering column. Then, the sorting is performed between and within each data group according to the sorting column, using the same sorting order. The sorting result obtained in this way retains the clustering characteristics of the clustered columns while essentially ensuring the global order of the data, which is beneficial for improving the computational performance related to the clustered columns. Especially when querying based on the sorting result, it ensures that the performance of queries by data range is largely unaffected, while significantly improving the performance of queries by data grouping.

The invention discloses a data query method, device and equipment and a storage medium, and relates to the technical field of data processing.The method comprises the steps that a data query instruction and a target query database corresponding to a current data query task are determined according to a data query request; detecting whether the data query instruction accords with a database grammar specification corresponding to the target query database; if not, performing grammar conversion on the data query instruction based on a preset grammar tree analysis mode to obtain a target data query instruction; and performing data query based on the target data query instruction. According to the method, when the data query instruction does not conform to the grammar specification of the target database, grammar conversion can be performed on the data query instruction, and data query is performed based on the target data query instruction obtained after conversion; therefore, the technical problems that in the prior art, during cross-database query, query scripts need to be frequently modified to adapt to grammar differences of different database engines, time is consumed, and errors are prone to occurring are solved.

A system and method include receiving, by a database engine of a database system associated with a virtual computing system, a user request via a dashboard for provisioning a source database with the database system, receiving, by the database engine via the dashboard, selection of a database engine type, and receiving, by the database engine via the dashboard, selection of a Service Level Agreement (“SLA”) and a protection schedule. The system and method also include provisioning, by the database engine, the source database based upon the database engine type, creating, by the database engine, an instance of a database protection system based upon the SLA and the protection schedule, including associating the instance of the database protection system with the source database, and displaying, by the database engine, the source database within the dashboard.

The application discloses a financial-grade database multidimensional security management and control system and method, relates to the technical field of financial data security management and control, and deploys a quantum encryption network and a backup key pool; initializes a data hierarchical management mechanism and a key management hub; transforms a database engine and builds a trusted audit hub, and deploys a security agent on a database node. Through the cooperation of the quantum encryption network and the post-quantum backup key pool, the high security of quantum encryption is utilized to resist traditional and quantum computing threats, and the encryption service is ensured not to be interrupted when the quantum network is abnormal, thereby meeting the continuity requirement of financial transactions; fine-grained data grading is combined with a differentiated security strategy, encryption algorithms, access permissions and retention periods are configured for high-sensitive, medium-sensitive and low-sensitive data respectively, precise protection is realized, and operation efficiency is taken into account; and a multi-role key cooperation mechanism avoids single-point key leakage, and the original key is destroyed after the key is generated, so that the key security is further improved.

The application relates to the technical field of data calculation, and provides an index calculation method and device, which comprises the following steps: storing a plurality of target index groups generated by an electronic spreadsheet software and corresponding configurable files; wherein the configurable files represent the calculation rules of the values of the plurality of original indexes for determining the values of the business indexes in the corresponding target index groups; determining an index calculation request; wherein the index calculation request carries a target index group or the identification of the target index group; determining the values of the plurality of original indexes matched by the target index group; calling a database engine to calculate the values of the plurality of original indexes matched by the target index group based on the calculation rules indicated by the configurable file matched by the target index group, so as to determine the values of the business indexes in the target index group. The configurable file of the target index group is maintained by using the electronic spreadsheet software, the dimension difficulty is reduced, the calculation process of the business indexes is converted into the execution process of the database engine, and the extension is facilitated.

The invention discloses a multi-stage verification method and system for a business object data migration process and a server. The method comprises the following steps: verifying a to-be-migrated object generated according to a migration demand; after a data migration packet generated based on the to-be-migrated object enters a mapping engine for migration data conversion, field-level verification is carried out; and after the mapping is completed, analyzing a return code of the database engine for returning a write-in result in real time. According to the method, the problems of incomplete coverage, lack of pertinence and low automation degree of data migration verification are solved, accurate identification and intelligent disposal of abnormal behaviors in each migration link are realized, and the integrity, accuracy and smoothness of data migration are improved.

A database engine may track granularity levels for accessing a spatial index. Granularity levels of a spatial index may be evaluated to identify those granularity levels that identify data objects in a data set. An indication of the identified granularity levels may be stored as part of metadata for the data set. When a spatial query directed to the data set is received, the spatial index may be accessed at the identified granularity levels indicated in the metadata for the data set as part of processing the spatial query.

Embodiments of the present application provide a table data batch synchronization method and device, a storage medium and a program product. In the present application, the application layer no longer needs to separately judge the existence of each data in the target table and construct an insertion or update instruction, but the decision-making right is given to the database engine layer, and the database engine is taken as the core execution unit to automatically complete based on the index field value; by integrating the data reading of the intermediate table and the conditional writing of the target table in a single batch synchronization statement, the number of interactions between the application layer and the database is significantly reduced, and the system overhead caused by high-frequency SQL parsing, transaction opening and network round trip in the piece-by-piece processing mode is avoided; at the same time, by batch deleting the intermediate table data after synchronization, and combining the single transaction submission mechanism, the atomicity and consistency of the data synchronization process are ensured. Based on this, while ensuring the accuracy of the data, the execution efficiency and system stability of large-scale data synchronization are greatly improved.

This invention provides a spatial planning data quality inspection method, device, and medium based on an embedded database. First, quality inspection configuration information is loaded, and the local data packets to be inspected are imported into an embedded database engine that supports spatial expansion, forming a local temporary quality inspection database. Based on the quality inspection configuration information, internal quality checks are performed on the data in the local temporary quality inspection database using spatial SQL functions. Then, an external consistency check is performed by loading a remote database through an external data connection. Finally, the results of the internal quality check and the external consistency check are structured and saved to the result table of the embedded database. This invention directly accesses local data packets and remote databases through the embedded database engine, and uses SQL spatial functions to implement integrated automatic quality inspection by executing quality inspection operators within the database kernel. This reduces the difficulty of developing quality inspection operators and significantly improves the efficiency and standardization of quality inspection of detailed land spatial planning data.

The invention relates to the technical field of data processing, in particular to a query optimization method and system based on an algorithm engine, and the method comprises the steps: firstly receiving an initial logic analysis instruction aiming at a target data storage cluster, then traversing all query columns of the initial logic analysis instruction to extract a trend query column containing a trend analysis function, and then, carrying out query optimization on the trend query column containing the trend analysis function; and performing logic rewriting on the trend query column by adopting a preset rewriter to obtain a query rewriting instruction containing multi-table association, and finally submitting the query rewriting instruction to a pre-configured database engine to return a query result related to trend analysis. Compared with the prior art, the method has the advantages that the content of the multi-associated data does not need to be inquired manually and independently, the possibility of memory overflow of a system end caused by multi-manual operation is reduced, the possibility of field repetition is also reduced, and therefore the method has higher stability and lower resource consumption.

The invention relates to the field of data analysis, in particular to an intelligent decision analysis method and system based on multi-source data fusion and a dynamic template, and the method comprises the steps: receiving structured and unstructured data sources through an API gateway, executing data updating operation in a preset time period to obtain a data updating record, and storing the data updating record as an Excel file; converting the Excel file into a table structure according to sheet through an Excel-to-database engine, judging a field type in the table structure, and storing the field type in a database to obtain a field type database; constructing an analysis data set based on the field type database; generating a vector curve graph, a natural language query result and a time dimension word cloud according to the analysis data set; and carrying out confidence verification by utilizing a cross-engine verification chain, and binding the vector curve graph, the natural language query result and the time dimension word cloud by utilizing a dynamic association generator after verification is completed to obtain a decision analysis report. The decision analysis report generation efficiency and accuracy can be improved.

The invention discloses a correction method and a generation system for converting a natural language into an SQL (Structured Query Language) of a large language model, and belongs to the technical field of artificial intelligence and databases. The correction method comprises the following steps: receiving a natural language query request and database mode information, and generating an initial SQL statement by utilizing the large language model; inputting the generated SQL statement into a static analysis module, and carrying out feature matching based on a preset logic inverse mode rule base; if the inverse mode is matched, logic correction feedback is generated, and rewriting is triggered; after the SQL statement passes the static analysis, submitting the SQL statement to a database engine for execution; if the execution is successful, obtaining a query execution plan of the query; analyzing the query execution plan, and identifying a performance bottleneck index; and if the performance bottleneck exists, generating performance optimization feedback and sending the performance optimization feedback to the large language model for rewriting. According to the method, manual intervention can be greatly reduced, correct SQL grammar can be ensured, and reliable logic and efficient execution can be ensured.

The invention discloses a dialogue type information query method for a structured database in the power field, which comprises the following steps: acquiring an initial structured query statement based on a natural language query text and database mode information; abstract syntax tree analysis is conducted on the initial structured query statement, a table name set and a column name set referenced in the initial structured query statement are extracted, a target database is inquired to obtain alignment auxiliary information, and the alignment auxiliary information comprises list alignment information and knowledge alignment information; based on the alignment auxiliary information, the natural language query text and the database mode information, performing fusion, generating optimization prompt information, inputting the optimization prompt information into a large language model, and generating candidate structured query statements; and submitting the candidate structured query statements to a database engine for pre-execution verification, and outputting the structured query statements passing the verification. The method solves the problems of illusion and lack of knowledge in the application of a large model in the electric power vertical field.

Systems and methods for apportioning cloud-based resources through the use of domain name services based on real-time cloud-based database engine traffic patterns. For example, the system may monitor incoming cloud-based database engine traffic over a plurality of disparate computer network resources. The system may generate a first recommendation for domain name service based on the first difference, wherein the first recommendation requests a modification of an allocation of the plurality of disparate computer network resources.

The invention discloses a TEE-based encrypted data dynamic desensitization query method and system, a terminal and a medium, and the method comprises the steps: a key management service module in a TEE distributes an exclusive authority key and a database file encryption key after receiving a desensitization rule configuration request; the security proxy service receives the encrypted query statement and rewrites the query statement into a desensitized statement; the database engine obtains plaintext data, and the data dynamic desensitization engine calls a desensitization rule through the exclusive permission key and executes dynamic desensitization operation; and the security proxy service encrypts the desensitization result and forwards the desensitization result to the client, so that the decrypted desensitization result is fed back to the authorized user. According to the method, the full-process security protection of'data secret state storage, query encryption transmission, security desensitization in TEE and result encryption return 'is realized, the integrated security control of'rule-authority-key-query' is also achieved, and the service availability of data query is ensured.

Embodiments of the present specification provide a method for data deletion of a distributed database, a storage architecture of the distributed database being a log-structured merge tree, the method being performed by a database engine of a first node of the distributed database, the first node storing first partition data of a target data table. The method comprises: obtaining a target transaction comprising a first data body, the first data body comprising a target data column of the target data table and a valid period threshold set for the target data column, the target data column indicating a data generation time; committing the target transaction and determining a commit version number; and executing the target transaction by performing a compression merge operation, wherein performing the compression merge operation comprises: for a data row in the first partition data whose transaction version number is less than the commit version number, if a time indicated by the target data column in the data row is less than the valid period threshold, deleting the data row.

This application discloses a data processing method, apparatus, computer equipment, and computer-readable storage medium, applicable to various scenarios such as cloud technology, artificial intelligence, intelligent transportation, and assisted driving. The method includes: acquiring data to be processed; determining a target storage space for the data to be processed based on a database engine file, wherein the database engine file includes a memory-mapped area and a non-memory-mapped area, the memory-mapped area providing memory data storage space and the non-memory-mapped area providing file storage space; and storing the data records corresponding to the data to be processed into the target storage space. This application provides a database capable of providing large-capacity data storage services while ensuring data security.

This invention discloses a large-model-enhanced query rewriting synthesis method for detecting logical errors in database engines. The method includes: constructing a rule tree and systematically traversing all applicable rewriting rules; implementing a large language model-enhanced Monte Carlo tree search, combining Monte Carlo tree search with the large language model; and performing root cause analysis, utilizing a historical error pattern repository to precisely locate the abstract syntax tree nodes leading to the logical errors. This invention systematically explores the query rewriting space by combining rule tree search and large language model-enhanced Monte Carlo tree search techniques, improving the efficiency and coverage of logical error detection.

This application relates to a multidimensional data query method based on an embedded engine and dynamic aggregation. It integrates factual data and their corresponding dimensional description data from different databases into a single table containing dimension and measure fields by constructing a wide data table. Based on this, different data processing methods are selected according to the parsing results of the user's multidimensional query request. For cases involving only basic aggregation tasks, the corresponding processing is performed directly in the target database containing the wide data table. For cases involving complex computational tasks, basic aggregation processing is first performed in the target database to obtain basic aggregated data. Then, the embedded database engine reads the aggregation file corresponding to the basic aggregated data and performs the processing operations corresponding to the complex computational tasks. This reduces intermediate steps in the query process, improves query efficiency, and ensures the standardization and consistency of the data used in complex calculations, thereby improving query accuracy.