21 results about "Relational database management system" patented technology

Techniques discussed herein relate to an object-relational database management system (ODMS) (e.g., a PostgreSQL ODMS) that provides in-line materialization of database pages corresponding to read requests. A replica node of the ODMS may be configured to share access to a shared block storage volume with a primary node. The replica node may receive log updates from the primary indicating changes to the object-relational database. The read replica, in response to receiving a read request, may update a previous version of a database page, store the database page in local memory, and replay the log updates to update the database page in local memory. Data may be provided from the updated database page in response to the read request.

The present disclosure relates to efficiently constructing in-memory HNSW vector indexes in a database management system (DBMS). A DBMS may store in memory a segmented array, wherein the segmented array may store representations of a plurality of vectors from a database. A hierarchical navigable small world (HNSW) vector index may be constructed in the memory, wherein the HNSW vector index may index the plurality of vectors. A similarity search may be performed using the HNSW vector index.

The present disclosure relates to efficiently constructing in-memory HNSW vector indexes in a database management system (DBMS). A DBMS may store in memory a segmented array, wherein the segmented array may store representations of a plurality of vectors from a database. A hierarchical navigable small world (HNSW) vector index may be constructed in the memory, wherein the HNSW vector index may index the plurality of vectors. A similarity search may be performed using the HNSW vector index.

The application discloses a pressure monitoring and analysis method and device for a rural water supply network based on digital twinning, and the method comprises the following steps: collecting historical basic data of a predicted area in the countryside; acquiring monitoring data by deploying flow and pressure sensors at nodes of the rural water supply network; uploading data to a server and preprocessing the data by using a data flow processing framework to obtain preprocessed data; constructing a relational database management system to batch process the preprocessed data to obtain batch-processed historical basic data and monitoring data; constructing a rural pipe network water pressure prediction model; constructing a pipe burst detection and water pressure control model; constructing a rural water supply network geometric model based on ArcGIS according to physical data; and constructing a rural water supply network system data model and realizing visualization of a running state of the water supply network. The application fully considers the characteristics of rural water supply and water use, realizes intelligent management and control of the rural water supply system, and effectively guarantees the reliability and safety of rural water supply.

A digital processing system for assessing urban resilience, consisting of: a central server, equipped with a multi-core processor and dedicated storage units; a relational database management system connected to the aforementioned centralization server and configured to store spatial geodata, demographic datasets, historical hazard events, land use datasets, building inventory, infrastructure systems, government policies, and stakeholder information; a geodata processing module that is operated via the multi-core processor and has mapping and spatial analysis functions; a vulnerability calculation engine that runs on the multi-core processor and is configured to calculate sensitivity and exposure indices; an adaptive capacity assessment engine that runs on the multi-core processor and is configured to assess coping and adaptation mechanisms; an urban planning attribute analyzer that is powered by the aforementioned multi-core processor and configured to process data on land use diversity, infrastructure robustness, and resource decentralization; a governance assessment module that runs on the multi-core processor and is configured to assess institutional frameworks and stakeholder engagement mechanisms; an integration and synthesis engine connected to the central server and configured to correlate data from the aforementioned modules and to take into account the five Ws of urban resilience; and a reporting and visualization module integrated into a user interface configured to display assessment results, recommendations, and interactive maps.

The invention discloses a data conversion method, device and equipment and a computer readable medium, and relates to the technical field of big data. A specific embodiment of the method comprises the following steps: analyzing a Partial Range statement of a date column in an open source relational database management system into a syntax tree, wherein the syntax tree comprises a syntax structure of the Partial Range statement; traversing each Partial Range statement of the syntax tree, extracting a starting clause, an ending clause and a process clause according to the syntax structure, and sorting the Partial Range statements according to the date value of the extracted starting clause; and in the sorted Partial Range statements, according to the starting clause, the ending clause and the process clause, determining a partition range mode of the Partial Range statement, so as to generate the Partial Range statement of the GBASE according to the partition range mode of the Partial Range statement. According to the embodiment, the statement conversion efficiency can be improved.

A method for functionally rewriting an iterative query of a relational database management system (RDBMS) is provided. The method includes receiving a first iterative query having a first non-iterative portion defining a first main table and a first iterative portion generating values in rows of a first work table based on values in rows of the first main table, determining that the first iterative portion modifies all rows of the first work table, and rewriting the first iterative portion including: adding a rename operation to rename the first work table to a new first main table and rename the first main table to a new first work table; adding a first delete operation to delete each row of the new first main table; and adding a first loop operation to repeat the first iterative portion until a first termination condition is satisfied.

An apparatus, method and computer program product for neural network training over very large distributed datasets, wherein a relational database management system (RDBMS) is executed in a computer system comprised of a plurality of compute units, and the RDBMS manages a relational database comprised of one or more tables storing data. One or more local neural network models are trained in the compute units using the data stored locally on the compute units. At least one global neural network model is generated in the compute units by aggregating the local neural network models after the local neural network models are trained.

The invention discloses a method for optimizing the nested loop connection query efficiency of a relational database, relates to the field of relational database management system query, and aims at preliminarily completing data acquisition, processing empty sets and no intersection in advance and eliminating invalid query actions. Bidirectional data simplification is carried out in advance, and a result record set needing comparison is reduced to the maximum extent. And performing optimization selection, selecting a minimum result set as an outer-layer driving data set, completing loop comparison with minimum memory overhead, and outputting the result set to a user. And after each comparison is completed, invalid array members are discarded in time, and the size of the driven array is reduced, so that the overhead of the memory is further reduced.

Embodiments of the present application provide a data auditing method and related device, which are used to realize asynchronous auditing of machine auditing and manual auditing, and prevent business data loss in the process of machine auditing. The method comprises the following steps: storing target business data in a relational database management system by using a message queue; calling the target business data stored in the relational database management system by using the message queue according to a preset frequency; generating a business auditing table according to the target business data, generating an identity ID of the business auditing table, and returning the ID to a business side, wherein the business auditing table is used to describe the target business data and a business auditing strategy corresponding to the target business data; detecting the target business data based on the business auditing strategy to obtain a label result set, wherein the label result set comprises a plurality of label data; and determining an auditing result of the target business data according to the label result set.

A method, apparatus, and computer program product for executing a relational database management system (RDBMS) in a computer system, wherein the RDBMS manages a relational database storing data in a table having an open table format (OTF). The RDBMS maintains a cache for the data stored in the table, and determines whether the cache is stale using metadata for the table that is stored in the cache. The RDBMS incrementally updates the cache when the cache is stale.

Techniques discussed herein relate to an object-relational database management system (ODMS) (e.g., a PostgreSQL ODMS) that utilizes a shared block storage volume (SBSV) for storage. The SBSV may utilize a file system that enables a single-writer-multiple reader model in which a primary computing node may read or write to the SBSV and one or more replica computing nodes are restricted from writing to the SBSV. To enable the primary computing node to write data at its own pace, regardless of the status of synchronization at each of the one or more replica computing nodes, the SBSV may include a staging area that maintains data that has not yet been updated at one or more of the replica computing nodes. When the primary computing node no longer maintains the data in local memory, the one or more replica computing nodes may obtain the data from the staging area of the SBSV.

Hyperparameter tuning for a machine learning model is performed in a massively parallel database system. A computer system comprised of a plurality of compute units executes a relational database management system (RDBMS), wherein the RDBMS manages a relational database comprised of one or more tables storing data. One or more of the compute units perform the hyperparameter tuning for the machine learning model, wherein the hyperparameters are control parameters used in construction of the model, and the tuning of the hyperparameters is implemented as an operation in the RDBMS that accepts training and scoring data for the model, constructs the model using the hyperparameters and the training data, and generates goodness metrics for the model using the scoring data.

The application provides a method for automatically writing a relational expression of a Creo-based standard part, comprising the following steps: using a relational database management system to build a standard part parameter database, creating a corresponding data table, and storing parameter information of the standard part; writing a relational expression automatic writing program according to a Creo secondary development interface, and realizing the following steps: connecting with the standard part parameter database; obtaining standard part information selected by a user; generating a corresponding relational expression; writing the generated relational expression into a Creo standard part model; when the relational expression is generated, setting parameter association rules according to relationships between parameters of the standard part and design requirements; in the Creo standard part model, monitoring changes of the standard part parameters in real time by registering an event listener; and an event processing function automatically updating other parameters associated with the parameter according to preset parameter association rules, so as to ensure consistency and accuracy of the model.

The subject technology provides embodiments for integrating data lake functionality within a relational database management system (RDBMS) through a specialized RDBMS Data Lake Module. The subject technology enables database systems to natively support data lake table formats using SQL syntax. The system implements dual-mode access patterns supporting both internal operations through standard RDBMS interfaces and external operations via a catalog API, enabling multiple systems to access the same data lake tables without duplication. The RDBMS Data Lake Module comprises three integrated components: a lake format engine for translating SQL queries to object storage operations, a catalog manager for maintaining transactional consistency, and a catalog API for external system coordination.

Among other techniques, techniques for dynamic survivorship, cross-tenant matching, and lineage entity identifier (EID) promotion are described. A system utilizing these techniques can include an EID assignment engine, a progressive stitching engine, and a data item update engine. The progressive stitching engine can be at least conceptually characterized as comprising a data point onboarding subengine, a data point registration subengine, a data point matching subengine, and a data point merging subengine. A method utilizing these techniques can include assigning a data item EID to a data item, onboarding a data point, assigning a data point EID to the data point, matching the data point with the data item in a multitenant EID lineage-persistent relational database management system (RDBMS), merging the data point with the data item to create a merged data item, and changing the data item, triggering survivorship and lineage EID promotion rules.

A method and apparatus for optimizing a query in a relational database management system (RDBMS) when a predicate on a data column in the query has a correlation to a partitioning attribute of a partitioning column in data retrieved from a cloud-based store, wherein the optimizing uses the correlation between the data column in the query to the partitioning column in the data retrieved from the cloud-based store for data elimination when processing the query. The correlation is defined in a formula or lookup data structure that maps or range-maps from the data column to the partitioning column.

The application discloses a crowd subscription method and system based on kafka, a terminal and a storage medium. The method comprises the following steps: acquiring crowd data of different crowds, controlling a crowd production program to send the crowd data to kafka, receiving state data returned by the kafka, and storing the state data into a relational database management system; when a request sent by a subscription page is received, the state data is displayed on the subscription page, and a crowd is subscribed in the subscription page; based on the crowd, target state data corresponding to the crowd in the relational database management system is acquired, and the target state data is sent to the kafka for consumption, so as to complete the subscription of the crowd. When each team uses the user portrait system, the required crowd can be acquired for data extraction in a subscription mode, and the subscription can be performed before or after the crowd is executed.

The embodiment of the invention provides a database establishment method and device, equipment, a storage medium and a program product, and relates to the field of financial science and technology. Comprising the following steps: acquiring administrator information, target object information, evaluation mechanism information, evaluation result information and weight information of a target object, and creating an instruction based on a table in a relational database management system MySQL, and creating a corresponding administrator information table, a target object information table, an evaluation mechanism information table, an evaluation result information table and a warrant information table of the target object according to the information. And based on the association instruction in the MySQL, establishing an association relationship between an evaluation result information table and a target object information table as well as between a warrant information table and the target object information table, establishing an association relationship between an administrator information table and an evaluation mechanism information table, and establishing an association relationship between the administrator information table and the target object information table, so as to obtain a database. According to the method, the intelligent degree of data query is improved.

The invention discloses a data backup method and device, electronic equipment and a readable storage medium, which are used for solving the technical problems that the data backup process is difficult to monitor and manage, the occupied storage space is large, and an effective compression mechanism is lacked. The method comprises the steps that when a to-be-executed task created by a user for identity authentication service data is detected in a preset database, the backup type of the to-be-executed task is determined; determining a database table and a file directory of the to-be-executed task according to the backup type; when the backup type is a person-certificate record, exporting the database table as a first comma separation value file by using a COPY command of a relational database management system; compressing the first comma separation value file by using a zstd compression algorithm to obtain first backup data; and backing up the file directory by using a command line program to obtain second backup data.

A system includes a relational database management system component and a column-oriented data processing component. The relational database system component stores database information in a row format. The column-oriented data processing component stores the database information in a column format. In response to a database update request, the relational database management system component updates the database information stored in the row format; the relational database management system component notifies the column-oriented data processing component of the database update request; and the column-oriented data processing component updates the database information stored in the column format. In response to a query request, the column-oriented data processing component generates a query response based on the database information stored in the column format. In this manner, the system is able to generate up-to-date reports without the need for extraction, translation and loading procedures.