80 results about "Database query" patented technology

Follow ups to user queries are generated in text-to-database query conversion services based on context provided by generated database queries and / or database query execution results. A query generation service extracts an entity type(s) from a database query generated from a user query and, if applicable, from the execution results. The query generation service retrieves a user query template(s) and corresponding database query template(s) for a same table of a target database as the database query and have parameters of the same types as the extracted entity type(s). The query generation service populates the parameter(s) of each user query template and database query template with an entity name(s) that correspond to the entity type(s) and were extracted from the database query and / or database query execution result. The populated user query templates are provided in response to the user query as follow up queries.

The application discloses a kind of based on graph structure's power grid voltage stability margin online prediction method, comprising the following steps: constructing power grid attribute graph model in graph database, and establishing event-driven mechanism to realize the incremental update of topological change;Based on parameterized graph query template, dynamically generate graph database query statement, obtain the node feature matrix and adjacency matrix of prediction time, and convert to sparse tensor format;Constructing spatio-temporal graph convolution network prediction model;Through the incremental update of topological change driven by event-driven mechanism, to drive spatio-temporal graph convolution network prediction model;The prediction result and model intermediate layer node embedding vector are written back to graph database as attribute.This application realizes the millisecond level online prediction of power grid voltage stability margin, meets the real-time, accuracy and adaptability requirements of power system online safety analysis.

The application belongs to the technical field of databases, and specifically discloses a database query optimization method and system based on metric learning and correlation correction. The method comprises the following steps: constructing a training set based on data in a database table, training a metric learning model based on the training set to learn correlation information between columns, and storing the correlation information as extended statistical metadata; responding to and analyzing a query statement, obtaining single-column statistical information of relevant columns and statistical information of multi-column correlation from the extended statistical metadata; calculating an initial selection rate based on the column independence assumption, correcting the initial selection rate based on the multi-column correlation to obtain a final multi-column selection rate after correction; and estimating query cost based on the final multi-column selection rate, and selecting an execution path according to the estimation result to generate a final execution plan. Through the application, the accuracy of multi-column selection rate estimation can be improved.

This application provides a database sharding and virtual table query method based on SQL interceptors, relating to the field of data sharding technology. This application requires only one lightweight SQL interceptor component to be introduced into the microservice, without modifying the data source configuration; sharding rules are centrally managed in the configuration center, and changes are pushed to each service interceptor in real time without restarting any microservices, achieving true dynamic configuration refresh and greatly improving system flexibility and maintainability; by introducing the "virtual table" abstraction, the natural inheritance relationship in the business model is mapped to the database query layer; business code does not need to care about which sub-table the data is actually stored in, and can perform global queries based on common fields, greatly simplifying complex query business code and reducing development complexity.

The present application belongs to the field of database query optimization task, and relates to an uncertainty quantification query cost estimation method under generalization of cross-database. The uncertainty of cost estimation can be quantified, and the method can be accurately and effectively generalized to the database which has not been learned. The method mainly comprises a cross-database representation module CDR and an uncertainty cost estimation module CEU. The CDR module encodes the minimum set of cross-database query plan features, and uses Tree-LSTM to ignore the database-specific features. Then, the CEU module estimates the cost of a given set of query plans in the database and outputs the estimated uncertainty. Compared with the traditional cost estimation, the method can quantify the uncertainty of cost estimation, and can be accurately and effectively generalized to the database which has not been learned.

The present application relates to the technical field of anti-counterfeiting traceability, in particular to an anti-counterfeiting traceability system for production date based on font encryption, which hides and embeds a traceability code into the font structure of the production date through a font encoding module. The production date, as a mandatory information on the package, is difficult to remove. By using the font variant embedding code method, anti-counterfeiting information can be embedded without changing the reading content, thereby enhancing the anti-damage and security of the traceability code. The system generates a font encoding table based on the daily production date as a seed parameter, ensuring that the same traceability code corresponds to different font sequences on different dates, and has unpredictability and non-reusability. The image recognition decoding module adopts a date and font separation identification structure to realize high-precision extraction of font identification ID, and restores the traceability code in combination with the encoding table of the day. Finally, the product batch, source and authenticity information are verified through database query, effectively improving the security and tamper resistance of the anti-counterfeiting traceability on the product package.

This invention relates to the field of data processing technology and discloses a map-related question-answering system and method based on a multi-agent approach. The system uses a fine-tuned BERT model to extract intent and slot information from user questions and passes this information to a supervisor agent controlled by a large language model. The supervisor agent assigns this information to a database interaction agent, which performs a database query and returns the query results to the supervisor agent. If the current result directly answers the user's question, the supervisor agent replies with the answer. Otherwise, the supervisor agent passes the user's question, intent, slot information, and latitude and longitude information obtained from the database query to a map reasoning agent, which performs a map query. When the user's question involves reasoning, this agent performs the final reasoning and returns the reasoned answer to the supervisor agent, which then returns it to the user. This invention utilizes multiple agents to perform the task of answering questions, greatly improving the accuracy of question answers.

The application discloses a database range filter design method and device based on a binary decision tree, and belongs to the technical field of database query. The method considers that data sets to be processed in a database are not uniform in most application scenarios, and an initial binary decision tree is constructed offline according to the distribution characteristics of the data sets. Each node of the initial binary decision tree is a range, and a root node represents a range interval of keys in the entire data set. Simulated online query is performed by using the initial binary decision tree, and pruning is performed according to the access frequencies of leaf nodes. Finally, compression coding is performed to obtain a database range filter. In the process of constructing the binary decision tree, the binary tree is grown according to data density and skew degree, so that the problem of high false positive rate in the case of uneven data distribution can be solved. The pruning operation of the binary tree according to the access frequency can reduce the space occupation. Finally, the database range filter can efficiently process data in the case of uneven data.

This invention discloses a visualization report analysis method based on task discrimination and query generation. It receives user queries, generates a sequence of subtasks through task planning using a large language model, and evaluates and optimizes the subtask sequence using a task planning discriminator. For each subtask, after vectorization, similarity calculation is performed with a tool description vector library to obtain the top K tool descriptions, and the large language model further refines the selection to N tools. When a subtask involves a database query, similarity matching is performed based on a query example library to obtain query examples, which are then combined with table structure information to generate and execute a query statement. Finally, a visualization report is generated based on the subtask processing results. This invention effectively improves the accuracy of the large model in task decomposition, tool invocation, and query statement generation by introducing a task planning discriminator, vectorized tool recommendation technology, and dynamic query statement suggestion technology, thereby enhancing the execution effect of complex data queries.

This invention provides a deep learning-based crowdsourced database query optimization and trusted data processing system, relating to system software and database fields. It includes a query optimization engine module, a task allocation module, a data trust assurance module, and a trusted blockchain center module. The query optimization engine module generates an optimization execution plan and enables online model evolution through asynchronous incremental training triggered on demand by a verification submodule. The task allocation module achieves accurate task distribution through graph model task modeling and iterative matching. The data trust assurance module adopts an on-chain and off-chain collaborative architecture, detects data tampering through hash consistency comparison, and completes database recovery based on time-slice replicas and legitimate transaction replay. The trusted blockchain center module provides privacy computing and automatic verification and evidence storage services for multi-stream data. This invention effectively solves the problems of low query efficiency, inaccurate task matching, and data tamper-proofing and compliance self-verification in high-concurrency environments in crowdsourced database scenarios.

This invention provides a method, medium, and system for managing production basic data based on a scalable data model, belonging to the field of production basic data management technology. This invention achieves separate storage of core fixed attributes and dynamically extended attributes by establishing a hybrid storage architecture, constructing a material genealogy database to support batch traceability queries, deploying a distributed inventory management system to ensure the atomicity of inventory operations, establishing a streaming data processing platform to predict production cycle time, utilizing an AI-based production data fusion model to optimize data model configuration schemes and material distribution plans, and establishing an anomaly detection and adaptive adjustment mechanism to cope with system performance fluctuations. This solves the technical problems of low cross-database query efficiency and difficulty in ensuring data consistency after separating the dynamic extended attributes and fixed attributes of production basic data.

This invention discloses a database query plan selection method driven by teaching effectiveness, comprising: obtaining an exponential plan space based on SQL; and a processing method based on incremental TIPS, in the first... i It's my turn i The first candidate program space in the round, according to the first round i The first candidate program space of the round and the second i The first candidate program set in round -1 yielded the... i The first set of candidate plans in the round, based on the i The first candidate plan set is used to obtain the final first candidate plan set, or, based on the batch TIPS processing method, the second candidate plan space is obtained. The second candidate plan set is then updated according to the second candidate plan space and the execution plans in the second candidate plan set to obtain the final second candidate plan set. This invention can quickly obtain other candidate plans considered by the query optimizer during the decision-making process for the query the user wants to query.

A computer-implemented method for sharing access to a database of records relating to clinical trial investigators amongst a number of users is disclosed. Each record includes a number of data fields associated with a clinical trial investigator and has associated metadata indicating a record owner. The method comprises: a) receiving a database query from a first user; b) resolving the query using a first subset of the records in the database including only those records for which the associated metadata indicates that the record owner is the first user and those records for which the associated metadata indicates that the record owner is another user which has registered a sharing rule in respect of the first user, whereby the first user is granted permission to access its records; and c) generating a result set including only those records used to resolve the query that satisfy the query.

A method for query optimization may include capturing a proposed database query input into a user interface. The method may further include providing the proposed database query to a machine-learning model. The machine-learning model may have been trained, using one or more gathered and / or simulated sets of query execution overhead data and one or more gathered and / or simulated sets of database queries, to determine a potential execution overhead of a database query and output a query execution score. The method may further include outputting, by the machine-learning model, the query execution score based on the proposed database query. The method may further include determining that the query execution score exceeds a query execution score threshold. The method may further include triggering a corrective action based on the query execution score exceeding the query execution score threshold.

A computing network provides a database service and implements a caching mechanism for processing database queries. The database services are provided using a primary replica of data and computing resources, and a secondary replica of the data and computing resources. The primary and secondary replicas are synchronized so that the secondary replica can provide the database services in place of the primary replica in response to a failover from the primary replica to the secondary replica. In response to initiating, by the database service, a failover from the primary replica to the secondary replica, the cached plans compiled by the secondary replica are used to process matching query batches by the secondary replica. The secondary replica processes the matching query batches without accessing plans compiled by the primary replica.

The application discloses a database query method and device, a storage medium and a computer program product, and belongs to the technical field of databases. The method comprises the following steps: determining a logical plan tree based on a database query request; converting the logical plan tree into a physical plan tree, wherein the execution environment of a physical plan node is TEE or REE; determining a TEE plan and a REE plan according to the physical plan tree; and obtaining a database query result by executing the TEE plan through a database executor in TEE and executing the REE plan through a database executor in REE by using a first memory. The TEE and the REE both contain the database executor, the execution environment does not need to be switched, the environment switching overhead is eliminated, there is no calling relationship between the TEE executor and the REE executor, and the scheduling overhead is eliminated. The first memory of the REE is shared by the TEE and the REE to exchange data, so that the TEE and the REE efficiently cooperate, and the database query efficiency is improved.

A method of controlling a function of an analysis system (110) is disclosed. The method comprises: a. providing at least one container (114) containing at least one control fluid, the container (114) comprising at least one identifier (124), wherein the identifier (124) comprises at least one identification number of the container (114); b. reading the identifier (124) of the container (114) by using at least one reading device (113) of the analysis system (110); and c. performing a database query in a database (116) of the analysis system (110), the database (116) containing database entries (130) for a plurality of known containers (114), the database entries comprising identification numbers of the known containers (114) and assigned expiration information for the respective known container (114), the database query comprising checking whether the container (114) already has a database entry (130) in the database (116). Further, an analysis system (110) is disclosed, comprising at least one analysis device (112) for determining a concentration of an analyte in a sample of a body fluid.

Evaluating stored query results including generating a database query using a state specification of a graphical user interface, wherein the database query is composed to retrieve a current query result from a cloud-based data warehouse; searching a cache local to the query execution engine for the current query result, wherein the cache comprises a first previous query result from the cloud-based data warehouse; determining, based on the searching, that the current query result may be generated using the first previous query result from the cache; and creating the current query result using at least a portion of the first previous query result from the cache.

The application provides a data query method, device and equipment and program product. It relates to the technical field of big data processing, comprising receiving a data query request sent by a client; when it is determined that the request parameter matches the cache generation rule, the target data is obtained by directly performing cache query in the cache area according to the request parameter; when it is determined that the request parameter does not match the cache generation rule, the target data is obtained by performing database query in the supplier database; and the target data is sent to the client to respond to the data query request. By matching the request parameter with the cache generation rule in advance, it is determined that the cache area contains the cache data corresponding to the request parameter when the matching is successful, otherwise it does not contain. In the case of no matching, the cache area does not need to be queried, but the database on the supplier side is directly queried, the time occupied by invalid query in the cache area is saved, and the efficiency of data query is improved.

The application provides a multi-table data query method, system, device and medium based on JPA combination, belonging to the technical field of data processing. The method comprises the following steps: in response to the front-end display requirement, determining the data tables to be queried and the association relationship between the data tables; using JPA entity to define the structure of the data tables and the association relationship between the data tables; respectively executing queries on each data table, using Java streaming interface to perform data processing and combination on each query result in the memory; and integrating the combined query result into a data structure that can be parsed by the front end and returning it. Through step-by-step query and data processing, the application reduces the number of database queries, avoids complex multi-table association, improves query efficiency, uses Java streaming interface for data processing and combination, improves the efficiency of data processing, disassembles the query logic, facilitates extension, combines and optimizes multi-table data through JPA, reduces the number of database queries, and shortens the query time.

One embodiment of the present invention sets forth a technique for processing a query of a life cycle assessment (LCA) database. The technique includes searching one or more hierarchical structures included in the LCA database for data nodes that match a set of parameters that is (i) included in the query and (ii) specifies one or more properties of an entity. The technique also includes upon determining that a data node includes an unknown consumption or an unknown emission, matching a second set of parameters associated with the data node to an entry in a cache and computing one or more environmental impacts based on a functional unit that is (i) included in the entry and (ii) includes a quantity associated with the unknown consumption or the unknown emission. The technique further includes causing the one or more environmental impacts to be outputted in a response to the query.

This invention provides a database query optimization method and related products. The query optimization method includes: obtaining a query statement containing aggregation sorting instructions; determining whether the query statement contains multiple instructions with sorting operations; if so, obtaining the compatibility of the sorting operations among the multiple instructions, where compatibility indicates whether there is an inclusion relationship between any two sorting keys in the sorting direction; and determining the target sorting path for the query statement based on the compatibility. This query optimization method dynamically optimizes the query based on the compatibility of multiple sorting operations, thereby determining the optimal target sorting path, avoiding redundant sorting, and achieving the goal of improving database query efficiency and reducing resource consumption.

This application relates to a method, apparatus, electronic device, and storage medium for generating materialized views. The method involves: filtering target query patterns from database query logs; generating candidate materialized view creation statements corresponding to the target query patterns; creating candidate materialized views based on these statements in a resource-isolated sandbox environment and quantitatively evaluating the candidate materialized views; deciding whether to approve and deploy the candidate materialized views; and conducting a health assessment of deployed materialized views, performing corresponding optimization operations based on the assessment results. This achieves automated and precise selection of high-value optimization targets, reducing reliance on senior experts. Quantitative evaluation of candidate materialized views ensures that deployed materialized views provide clear benefits. Furthermore, multi-dimensional health assessments of deployed materialized views automatically identify and eliminate inefficient materialized views, enabling continuous and automated optimization and recycling of computing and storage resources.

This invention relates to the field of information retrieval, specifically to a database query method based on a graph structure. The method includes collecting all data tables in the database, multiple query statement-data table pairs, and establishing an enterprise knowledge base; modeling a database graph structure based on all data tables; enhancing the input natural language query using RAG to obtain an enhanced query statement; selecting initial nodes from the graph structure based on the enhanced query statement and completing graph initial node matching; generating a target node set based on each initial node; generating an SQL statement corresponding to the enhanced query statement based on the target node set to achieve SQL statement conversion; and executing the SQL statement to query the database and obtain the query results. Existing NL2SQL suffers from insufficient semantic understanding and poor interpretability. The database query method based on a graph structure provided by this invention has better semantic understanding and interpretability.

This invention provides a database query optimization method and related products. The method includes: obtaining an SQL query statement containing a result set constraint clause; identifying whether the initial query execution plan of the SQL query statement contains a pushdown node; if the pushdown node is present, generating candidate query paths that push down the result set constraint clause to the pushdown node; and selecting a target query execution plan from the initial query execution plan of the SQL query statement and multiple query execution plans of the candidate query paths based on cost evaluation of each candidate query path, to execute the SQL query statement. This invention achieves dynamic pushdown of row count constraint operations in the execution plan, overcoming the limitations of traditional static execution plans in optimizers. By identifying scenarios such as outer joins, set operations, parallel execution, and Cartesian products, it can pre-prune data volume in the early stages of data processing, significantly reducing the burden of query operations.

Techniques are disclosed that relate to capturing and replaying database queries to assess the impacts of updates to a database system. A system may receive a plurality of queries from a set of users to execute against a database that stores data. The system identifies one or more of the queries that are deemed relevant to updates being made to the database system. The system executes the received queries and captures query execution information for the one or more identified queries. The system replays, based on the execution information, the one or more queries using the database system with the one or more updates enabled to determine a first performance of the database system. The system may generate a report indicating whether the first performance represents a reduction in performance relative to a second performance of the database system with the one or more updates disabled.

This invention discloses a barcode scanning fault-tolerant identification method and system based on a phased notification mechanism, applied to the WeChat Mini Program runtime environment. The barcode string obtained by scanning undergoes a progressive multi-layer format verification (pure number verification → length verification → country code matching → verification bit calculation), terminating if the previous layer fails. When verification fails, the module-level closure variable retry counter increments: if the maximum threshold is not reached, a progress indicator is displayed via `wx.showToast`, and after a preset delay, `wx.scanCode` is called again to initiate a new scanning operation; if the threshold is reached, a three-step phase switch driven by the UI layer alternation rules of the WeChat Mini Program API is executed: ① resetting the counter, ② `wx.hideToast()` actively closes any potentially still-displayed toasts to avoid rendering conflicts with `wx.showModal`, ③ a confirmation dialog box pops up for the user to choose between using the current result or rescanning. When verification passes or the user selects "use this result," a local product database query is executed, and the result is passed to the calling page via a callback function. This invention also discloses an independent implementation of dual-mode barcode scanning on the cashier page—manual scanning and continuous camera scanning modes employ differentiated "pause → resume" retry strategies. This invention resolves the UI-level conflict between the two system notification APIs in WeChat Mini Programs by mandating the sequential operation of `wx.hideToast()` → `wx.showModal()`, and ensures the correctness of the recursive retry state and the continuity of the retry state across short-lifecycle pages through a module-level closure counter.

A system / method includes a processor configured to: generate, via a first machine learning (ML) model, a database query for chargeback dispute resolution for a financial transaction between a customer account and a merchant account; retrieve, using the database query, an account behavior description for one or both of the customer account or the merchant account; generate a dispute resolution prompt based on the account behavior description; submit the dispute resolution prompt to a second ML model comprising an LLM to generate a resolution recommendation; and approve or deny a chargeback corresponding to the financial transaction based on the resolution recommendation.

The application provides a power scientific research data semantic retrieval method and system fused with a knowledge graph, and relates to the technical field of semantic retrieval.The method comprises the following steps: performing associated label identification on incremental power scientific research data to obtain a plurality of associated label sets; performing topological relationship reconstruction by taking a predefined knowledge associated attribute as an associated rule to generate a power scientific research knowledge graph; performing semantic analysis to generate explicit retrieval requirements and implicit retrieval requirements; performing extension associated indexing after executing bidirectional dynamic weighted screening to locate core entity nodes to obtain a primary retrieval result set; performing expansion correction to output a plurality of expansion associated results; generating a retrieval display priority sequence; and performing progressive visual screen display feedback.The application solves the technical problem that power scientific research data management and retrieval in the prior art mostly depend on traditional keyword retrieval and database query-based modes, cross-field comprehensive query is difficult to implement, and retrieval results are inaccurate.

A system / method includes a processor configured to: generate, via a first machine learning (ML) model, a database query for real-time authorization of a transaction authorization request, the transaction authorization request including a customer account identifier and a merchant identifier; retrieve, using the database query, an account behavior description for a customer account identified by the customer account identifier; generate a transaction authorization prompt based on the account behavior description; submit the transaction authorization prompt to a second ML model comprising an LLM to generate an authorization recommendation; transmit the authorization recommendation and the transaction authorization request to an issuer of the customer account; receive a response to the transaction authorization request from the issuer; and approve or deny a transaction corresponding to the transaction authorization request based on the response.