1247 results about "Data consistency" patented technology

The invention relates to the technical field of cable operation state detection, and particularly discloses a multi-source data driven cable operation state comprehensive evaluation method, which comprises the following steps of S1, adopting a layered distributed sensing network architecture, and deploying three types of core sensors at key nodes of a cable, through space-time calibration of the multi-source heterogeneous sensor, data consistency is improved, fusion deviation is eliminated, the problem of data islands of a traditional system is solved, and a precise evaluation foundation is laid; noise suppression and dynamic correlation modeling are adopted, environmental interference is stripped, a vibration and displacement coupling relation is quantified, limitation of a single parameter is broken through, heterogeneous fault features are captured, and evaluation comprehensiveness and sensitivity are improved; a self-adaptive threshold mechanism is constructed based on environment weight and historical data, the bottleneck of a fixed threshold is broken through, an evaluation standard is corrected along with equipment aging and environment change, misjudgment is avoided, and diagnosis robustness in different scenes is enhanced.

The invention relates to the technical field of offshore area monitoring, in particular to an offshore area pollutant diffusion real-time tracking and traceability monitoring system. The method comprises the following steps: a data perception and fusion unit collects and preprocesses data, carries out space-time calibration and multi-source fusion, and outputs a standardized fusion space-time sequence; the pollutant diffusion simulation and prediction unit calculates a flow velocity field, simulates a diffusion process and predicts a trend; the pollutant traceability positioning unit tracks a pollution path and inverts pollution source parameters; the emergency decision support unit determines a risk level and generates an emergency plan. And through a space-time alignment algorithm and a multi-source fusion mechanism, the data consistency and reliability are improved, a high-quality data basis is provided for subsequent processing, and the monitoring accuracy is guaranteed.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as financial science and technology and medical health, and discloses a processing environment switching and recovery method, device, equipment and medium. The method comprises the steps that multi-source heterogeneous data in a main processing environment and a standby processing environment are acquired, and the system fault probability is obtained through multi-model collaborative prediction; a dynamic threshold value is generated in combination with a historical service period mode and a real-time service load, when the fault probability exceeds the threshold value, a switching strategy is generated based on the fault scene knowledge base and the service priority, and flow scheduling between the main processing environment and the standby processing environment is executed; and monitoring the business index of the standby processing environment during the scheduling period, and triggering the fusing rollback when the business index is lower than the health standard. According to the method, the fault identification precision is improved through multi-source data fusion and multi-model prediction, adaptive scheduling is realized in combination with a dynamic threshold and a switching strategy, and fusing rollback is triggered to guarantee high availability and data consistency, so that the continuity and stability of key services are enhanced.

The invention relates to the technical field of application state diagnosis, in particular to an application state dynamic diagnosis and automatic repair method and system.The method comprises the steps that multi-source heterogeneous logs are collected and standardized in real time, key fields are extracted, context information is injected, and structured log data are generated; inputting the structured log data into a dynamic anomaly detection model, constructing a dual-path detection mechanism based on LSTM time sequence analysis and a graph neural network, identifying an abnormal mode and positioning a fault root cause; according to the output of the anomaly detection model, a repair action is triggered in a grading manner through an intelligent repair strategy engine; in the repairing process, system state changes are stored and recorded through a pre-writing type redundancy log, automatic rollback during abnormity is achieved on the basis of check point information, and data consistency and system stability are guaranteed. The problem of service interruption or data inconsistency possibly caused by traditional automatic repair is avoided, and the reliability of automatic operation and maintenance is improved.

The invention discloses a distributed computing task non-perception migration method and system under optical fiber network interruption. The distributed computing task non-perception migration method comprises the following steps: constructing a distributed task migration system and an output system architecture; collecting network state indexes, constructing a network topological graph, and analyzing the state of an optical fiber link for fault prediction; obtaining a calculation task operation state, establishing a sub-task mapping relation, constructing a directed dependency graph, and generating a state snapshot; analyzing resource requirements, reserving standby resources, and deploying a distributed cache system; analyzing a fault influence range, extracting an influenced calculation sub-graph, and selecting a migration target node; in a target node preloading environment, reconstructing an execution context, and redirecting a communication path; and setting a data change capture mechanism, synchronizing incremental data and executing consistency verification. According to the method, non-perception migration of the computing tasks is realized, task continuity and data consistency are guaranteed, and the reliability of the distributed computing system in an optical fiber network fault scene is improved.

The invention relates to the technical field of data processing, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a data processing and analysis method, device, equipment and medium, and the method comprises the steps: obtaining a data source set, and registering a source label and field mapping relation; executing extraction, cleaning, conversion and loading in the data processing assembly line based on the data source set, the source label and the field mapping relation to generate a processing table set; performing quality verification and exception handling on the processing table set to generate a verified processing table set; generating an index cloud based on the verified processing table set and the configuration strategy; the index cloud is pushed to the analysis tool set through the interface transmission channel, and the analysis tool set generates analysis output according to the index cloud. According to the method, through unified data registration, standardized processing and quality verification, the index cloud is generated in combination with the configuration strategy and pushed to the analysis tool set, the analysis result is generated and transmitted, the data consistency is ensured, and the real-time performance is improved.

The invention discloses an intelligent optimization method and system for territorial space planning based on multi-source data fusion, and belongs to the technical field of territorial space planning. Constructing a data consistency evaluation model, and generating a confidence weight matrix; local sensitivity analysis is carried out, and space conflict units are identified; generating a minimum disturbance path and a feasibility sequence based on the neighborhood stability and the historical change frequency; searching an optimal path combination through a multi-objective optimization algorithm; and identifying a high-sensitivity area as a key planning weak-sensitivity area, executing a dynamic fine tuning strategy, and finally outputting an optimized territorial space layout result. The method can effectively improve the scientificity and adaptability of space planning, and has good practical application value.

The invention discloses a home page multi-component parallel prefetching and rendering first screen acceleration method and device and a storage medium, and the method comprises the following steps: constructing a global dependency relationship model based on the metadata and dependency relationship of each component of a home page, and calculating the priority for each component according to a predefined priority evaluation strategy, generating a component scheduling sequence constrained by the priority and the dependency relationship; controlling a concurrency control strategy of the component; preferentially rendering a visual placeholder structure, and smoothly replacing the real content to a user visible area through a progressive rendering replacement strategy; when the variable quantity of the component data exceeds a preset threshold value, triggering an increment updating strategy based on the difference content; generating a cache identifier according to component granularity, reading and writing data in a multi-level cache structure based on the cache identifier, and ensuring data consistency by adopting a background asynchronous verification strategy; and collecting performance indexes in a page rendering process, and adjusting the priority evaluation strategy, the concurrency control strategy and the increment updating strategy according to the performance indexes.

The invention relates to an enterprise data operation multi-source data virtualization access and index automatic management and control method and system, belongs to the technical field of computers, and aims to solve the problems of index definition fragmentation, frequent logic conflicts, dependency static management and verification rule rigid coupling in the prior art. Comprising the following steps: constructing a unified virtualized data access layer to integrate heterogeneous data sources; the indexes are disassembled into semantic atoms capable of being managed in a versioning mode and registered to an atom knowledge base; dynamically constructing an index dependency relation directed acyclic graph based on semantic atom combination; dynamically binding the data quality rules with semantic atoms; and analyzing an index request through a virtualized query engine, reversely traversing atlas aggregation dependency and rules, generating and executing local query, and automatically checking result data quality at the same time. According to the method, unified index definition, dependence on automatic conduction, quality embedded verification and multi-source transparent access are realized, and the data consistency, the treatment efficiency and the system flexibility are remarkably improved.

The invention discloses an ERP (Enterprise Resource Planning) data intelligent supervision method based on the Internet of Things, which relates to the technical field of enterprise informatization, and comprises the following steps: constructing a time sequence integrity observation layer in an Internet of Things data acquisition link, embedding a mirror image time anchor in each sensor sampling point, recording electromagnetic interference, time service offset and queuing delay, generating a phase fingerprint time baseline, and obtaining a phase fingerprint time baseline; constructing a unified time reference framework; operating a causal coherent analysis mechanism based on a unified time reference frame, comparing instantaneous offsets of a mirror time anchor and a real-time timestamp, identifying a phase inversion region, extracting information of a corresponding sampling node, a production line position and an energy consumption unit, generating a high-risk time slice list, and determining a time correction boundary. According to the method, a time sequence observation layer and a time reference frame are constructed, phase abnormity is identified, a data trend is reconstructed, a regulation and control instruction draft is generated, sampling time sequence recovery and scheduling convergence are realized through time inversion control, data consistency and decision accuracy are improved, and a closed-loop control system is constructed.

The invention discloses a system and method for ensuring data consistency of a low-voltage power distribution network, and the method comprises the following steps: obtaining multi-source operation data uploaded by all collection devices in the low-voltage power distribution network, and converging the multi-source operation data to a unified processing channel; a timestamp dynamic alignment and mapping mechanism is adopted, sampling frequency and time offset are detected and corrected, and a unified time axis is generated; executing unit conversion and field unification operation according to the data type label, and constructing a standard field structure; carrying out prediction compensation on missing data by adopting a time sequence sliding window interpolation model; a sliding window anomaly rate detection strategy is applied to identify numerical value abrupt change and execute anomaly replacement; and performing structured output on the data set subjected to the consistency processing. According to the method, fine alignment, standardized processing and high-reliability correction of multi-source heterogeneous data can be realized, and the data consistency level and decision support capability of the low-voltage power distribution network in operation monitoring, analysis and control scenes are improved.

The invention discloses a load balancing optimization method and device, electronic equipment and a storage medium, and relates to the technical field of load balancing optimization, and the method comprises the steps: carrying out the differentiation processing of a data migration task according to a file storage threshold value, and combining a migration performance index and server resource occupation information collected in real time, the task allocation strategy is adjusted through the dynamic task allocation algorithm, so that the reasonable allocation of the files with different sizes and the dynamic load optimization in the migration process are realized. The technical problems that in the prior art, server overload and resource idling coexist due to a single migration server or a static task allocation strategy, high delay and data inconsistency risks are generated due to network congestion and uneven task allocation in the migration process, and the overall performance and reliability of a system are affected can be solved. The technical effects of optimizing the load balance degree, reducing overload and idle conditions of the server, reducing migration delay, ensuring data consistency and improving the overall performance and reliability of the system are achieved.

The invention provides a gait analysis method and an early warning system based on multi-source data fusion, three types of original signals are collected through a wearable inertial sensor, a plantar pressure insole and an edge calculation camera, and multi-dimensional motion characteristic parameters are fused through wavelet denoising, low-pass filtering, interpolation alignment and data consistency correction, so that the gait analysis method based on multi-source data fusion is realized. And constructing a user individualized gait feature prototype library. The method further adopts a dynamic causal graph network to model a motion relation between joints, determines an abnormal coupling mode based on causal weight and historical reference, and combines activity context and Bayesian rules to generate a dynamic threshold value to realize risk grading early warning, so that heterogeneous data collaborative analysis precision and abnormal gait detection sensitivity are improved, and the method is suitable for large-scale popularization and application. And support is provided for gait health monitoring and personalized risk management and control under multiple scenes.

The invention discloses a casting surface defect automatic detection method, which comprises the following steps of: synchronously acquiring multi-moment surface images and morphology data of a casting through multiple channels, automatically partitioning and extracting texture attributes, and realizing accurate space-time indexing; a denoising and brightness normalization algorithm is adopted to improve the consistency of basic data; in combination with a deep learning segmentation model and feature analysis, time sequence space defect matching, affine mapping, pseudo label generation and self-supervision consistency training are completed step by step, and fine-grained optimization is performed on dynamic change of a segmentation boundary. Therefore, the accuracy of defect detection is improved, and high-quality data support is provided for production process improvement and defect traceability.

The invention relates to the technical field of multi-agent collaboration, in particular to a multi-agent collaboration method and system based on shared memory data exchange, and the method comprises the steps: creating and initializing a shared data area which is mapped and accessed by a plurality of agent processes in a physical memory; constructing an annular buffer structure on the shared data area, and realizing a lock-free read-write pointer propulsion mechanism based on atomic operation and a memory barrier so as to support a plurality of intelligent agents to perform data read-write concurrently; asynchronous notification of data updating is carried out between agent processes through a lightweight event notification mechanism; and each agent performs autonomous decision making and task scheduling based on the shared data so as to realize distributed collaboration. A data block version control and verification mechanism is introduced into the annular buffer structure, and when it is detected that the agents are abnormal, resources of the abnormal agents are automatically recycled, and a data consistency recovery process is triggered. Multiple times of data copying between a kernel mode and a user mode are eliminated, and communication delay is reduced.

The invention provides a ship-based unified storage and management design data method, which comprises the following steps that: an operation end generates and sends an editing request with a node identifier, an editing type, a timestamp and a digital signature, and a WEB front end receives and verifies the legality of the request through an encryption channel; the storage service generates an intention lock based on the permission table and version number matching, and concurrent access control is achieved. Then, the WEB front end carries out content definition partitioning (CDC) and Hash fingerprint calculation on a design file stream, the storage service realizes partitioning duplicate removal and incremental storage according to a fingerprint matching result, and a Merkle tree is utilized to construct a file version integrity Hash root; on this basis, the system analyzes model differences, constructs a semantic difference chart, and calls a rule engine to perform automatic pre-check. According to the method, efficient storage, collaborative editing, security and credibility and hierarchical scheduling management of ship design data are realized, and the method has the technical advantages of high data consistency, high resource utilization rate, traceability auditing and the like.

The invention provides a regional wind field multi-source heterogeneous work order data fast structuring system fused with a large language model, which comprises a plurality of modules, and is characterized in that a data input module receives various work order images; the OCR layout recognition module comprehensively recognizes the data, extracts key information, determines a spatial position and outputs text fragments with coordinates and layout anchor point information, and the rule field extraction module recognizes format category fields from the text fragments and calculates rule matching confidence; the semantic field recognition module recognizes descriptive fields from unstructured content and outputs related confidence information, the fusion decision module calculates final confidence of field candidates according to a predetermined function and judges output or complementation according to a threshold value, and the data consistency verification module is connected with an asset database to verify key information. The data complementation module generates complementation candidates and confidence coefficients, the man-machine collaborative closed-loop module pushes suggestions and receives feedback, and the result output module outputs standardized data. According to the method, the multi-source heterogeneous work order data can be effectively processed.

The invention provides a Hadoop cluster incremental backup recovery method based on data block optimization, and relates to the technical field of data management, and the method comprises the following steps: obtaining distribution state information and historical change records of data blocks in a distributed file system, extracting space-time correlation characteristics, and constructing a data block dependency graph containing dependency direction and dependency intensity; identifying the changed data blocks, performing topological sorting, and identifying key path data blocks and independent data block clusters; calculating a distribution entropy value according to a copy distribution position, and determining a backup granularity type; a backup execution sequence is generated according to a topological sorting result, key path data blocks are backed up preferentially, independent data block clusters are backed up in parallel, and backup metadata containing dependency relationship identifiers and distribution entropy values are generated; and performing dependency consistency verification after recovery based on the dependency relationship identifier. According to the method, the backup recovery efficiency is improved, the data consistency is guaranteed, and the storage overhead is reduced.

The invention relates to a three-dimensional reconstruction-oriented Gaussian point cloud lossless coding and decoding method, a product and a storage medium. The method comprises the following steps: extracting a first Gaussian point cloud corresponding to anhor data in a numpy array format at a coding side; converting the first Gaussian point cloud in the numpy array format into a first Gaussian point cloud in a ply format; meanwhile, through a Morton code-based spatial sorting method, performing Morton code sorting on geometric data and attribute data of the first Gaussian point cloud in the numpy array format, and generating a Morton sequence index table; and carrying out AVS coding on the first Gaussian point cloud in the ply format to obtain compressed data in a binary code stream form. On the decoding side, AVS decoding is carried out when the compressed data in the binary code stream form and the Morton sequence index table are received, and a second Gaussian point cloud in the ply format is obtained through reduction; performing format conversion on the second Gaussian point cloud in the ply format to obtain a second Gaussian point cloud in a numpy array format; and rearranging the attribute data and the geometric data based on the Morton sequence index table to realize one-to-one correspondence of the geometric data and the attribute data between the first Gaussian point cloud and the second Gaussian point cloud before and after coding and decoding. Compared with an existing method, the data consistency before and after coding is improved.

The invention relates to the technical field of hard disks, in particular to a data protection method of a solid state disk and the solid state disk, the method comprises the steps that a flash memory medium is divided into a data block area, a log block area and a metadata area, and the metadata area comprises a mapping directory, a mapping block and a check point block; a block mapping table and a log page mapping table are established in a volatile memory, and dbMSN and lbMSN are stored. Adding write-in data to a log block page, updating a log page mapping table, and generating check points according to full writing of a log area. When no free page exists, the damaged log blocks are selected in a rotating mode to be combined, new data block migration pages are distributed, mapping is updated, the MSN is progressively increased, changes are written into the mapping blocks, and the mapping catalogue is updated when the mapping blocks are addressed. After restarting, positioning a mapping block by a mapping directory to recover block mapping, reading check points in a reverse order, and traversing an uncovered log area to reconstruct log page mapping; and comparing the dbMSN with the lbMSN, setting inconsistent log pages to be invalid, establishing consistent access and shielding invalid pages. According to the method and the device, the problems of data consistency and availability caused by metadata loss, uncertain merging state and low recovery efficiency of the hybrid mapping FTL in a crash scene can be solved.

The invention discloses a high arch dam global deformation analysis method and system fusing InSAR and measuring point data, particularly relates to the technical field of radar interference deformation monitoring, and is used for solving the problem of inaccurate shielding failure compensation. According to the method, data stability is guaranteed by obtaining InSAR image data and extracting sight line direction displacement in combination with coherence indexes, a key measuring point deformation sequence is collected, an InSAR result is calibrated based on stable reference points, data consistency is improved, a projection correction coefficient is constructed by using a dam body three-dimensional structure model, the sight line displacement is inversely solved into structural normal displacement, and the accuracy of the dam body three-dimensional structure model is improved. Obtaining an initial deformation value of the real structure meaning; according to the method, a spatial coupling map of measuring points and InSAR pixels is constructed for a shielding failure area, deformation compensation of the failure area is completed based on an edge weight, finally the deformation compensation result is remapped to a three-dimensional structure model, measuring point data restoration is performed on a high arch dam, and structural plane-level deformation visualization and trend analysis are realized more quickly and more accurately.

The invention relates to a security management and control method and system for a mobile terminal of a visitor in a secret-related area and a medium, and the security management and control method comprises the steps: obtaining visitor identity information inputted by the mobile terminal, and generating a session ID and a first dynamic two-dimensional code; in response to the reading of the code scanning verification device on the first dynamic two-dimensional code, the server verifies the legality of the session ID, and issues a preset management and control strategy after the verification is passed; when the mobile terminal is in the controlled state, monitoring violation operation violating the control strategy and generating a violation log containing violation operation information; generating a second dynamic two-dimensional code in response to a leaving instruction of the mobile terminal; in response to the reading of the code scanning verification device on the second dynamic two-dimensional code, triggering the mobile terminal to upload the violation log to the server; and after confirming that the summary information is consistent with the data of the violation log, the server sends a control releasing instruction to the mobile terminal, so that the mobile terminal is recovered to a normal state. According to the invention, the information protection capability of the secret-related place is improved.

Techniques are described for maintaining data consistency when failure events occur during file storage replications between file systems in different cloud infrastructure regions. In certain embodiments, two generation numbers (or different identifications) are assigned to two groups of processed B-tree key-value pairs, one before and one after a failure event, within a key range. In some embodiments, the two generation numbers are assigned to a group of B-tree key-value pairs processed by a failed thread and another group of B-tree key-value pairs processed by a substitute thread taking over the failed thread to avoid potential data corruption.

The invention discloses an asynchronous processing method and device for business process data, and belongs to a distributed system data processing technology, and the method comprises the following steps: S101, receiving a business request message, and persistently storing the business request message in a main message queue; s102, acquiring a to-be-processed message from the main message queue, and locking an associated target data record before executing processing; s103, verifying data consistency based on the version number recorded by the target data, if the version number is matched, executing processing and updating the version number, and otherwise, discarding the message; s104, after successful processing, sending a confirmation instruction deletion message to the main message queue; through persistent storage of the main message queue, a version number verification mechanism and management of the dead message queue, the problem of data inconsistency caused by concurrent operation is effectively prevented, reliable transmission of messages is ensured, loss of service data is avoided, dead message processing efficiency is optimized, and the method has the advantages of ensuring data consistency, preventing message loss and improving system reliability.

The invention relates to the technical field of anti-interference of intelligent monitoring data acquisition of a new energy power station, in particular to a self-adaptive anti-interference system for data acquisition of an intelligent auxiliary monitoring system. A windowing judgment mechanism is formed based on cross-node stage consistency; thirdly, defining participation paths of the data units with different stage attributes in cross-node association analysis, and aligning and screening multi-node data through data consistency management; when the stage consistency window meets a release condition, controlled stage regression processing is performed on the data unit in the unstable stage, so that the data acquisition node gradually enters a unified stage attribute; according to the method, the instantaneous abnormal processing of the interference influence is converted into staged and structured management, and the continuity, consistency and reliability of data acquisition and analysis in a complex power monitoring scene are greatly improved.

The invention discloses a data processing method and system for a dynamic knowledge graph, particularly relates to the technical field of knowledge graph data processing, and is used for solving the problem of park multi-source data consistency. The method is oriented to a park, system records are standardized as park event frames carrying object identifiers, event types and time information, association is achieved through a unified object identifier set, sub-graph templates are inquired according to the event types, object nodes are positioned, the sub-graphs are expanded according to template paths, affected sub-graphs are limited, and incremental updating is executed only within the range. The method comprises the steps of recording and writing effective time, failure time and a source event identifier, constructing a time version chain, generating a current state in combination with conflict detection of a preset time window and a source priority decision, constructing a current view and a historical view, adding a time filtering condition to query, and realizing time sequence retrieval of scenes such as equipment operation and lease change. And the updating efficiency and the data consistency of the park knowledge graph are improved.

Systems and methods for dynamically evaluating metadata consistency and data reliability in a data management system are disclosed herein. The system may retrieve first metadata and second metadata. The system may retrieve a metadata ruleset. Based on the metadata ruleset, the system may generate a first metadata consistency metric indicating a first measure of consistency. The system may determine to process each record of the first metadata as a batch. The system may generate a second metadata consistency metric indicating a second measure of consistency. The system may determine to process each record of the second metadata independently.

The invention provides a cross-equipment circulation and collaborative operation and maintenance method for a gap atomization service, relates to the technical field of computer system operation and maintenance, is applied to complex scenes such as a smart park, and aims to solve the problems that services among different gap terminals cannot be seamlessly coordinated and the operation and maintenance efficiency is low. According to the method, granularity self-adaptive splitting and standardized packaging are carried out on atomization services by constructing a swan gap terminal cluster; a cross-device circulation scheduling center is established based on the Gawan distributed soft bus, and dynamic migration of the service sub-modules among the terminals is realized through a circulation decision algorithm; meanwhile, a collaborative operation and maintenance system is constructed, operation and maintenance data are integrated, and intelligent early warning and batch operation and maintenance are achieved through a fault prediction model; and the data consistency before and after service circulation is guaranteed by combining a distributed incremental synchronization mechanism. According to the method, through deep fusion of seamless circulation of atomization services and collaborative operation and maintenance, the multi-terminal service collaborative efficiency in a complex scene is improved, the resource utilization rate is optimized, and the operation and maintenance cost is reduced.

The invention discloses an electronic medical record intelligent writing and structured processing system based on AIGC, and relates to the technical field of medical information processing and artificial intelligence application, and the system comprises a medical record information extraction and analysis module which extracts diagnosis records, medication schemes and treatment plan data of a patient in different departments and time points from an electronic medical record system, and obtains a medical record information analysis module; analyzing semantic content and format differences of the data by adopting a natural language processing algorithm to obtain a standardized medical information set; the diagnosis and treatment map construction module is used for constructing a patient diagnosis and treatment map according to the standardized medical information set and determining potential heterogeneous data connection points in the map; according to the electronic medical record intelligent writing and structured processing system based on AIGC, medical record data consistency checking and conflict automatic coordination are achieved, and the cross-department diagnosis and treatment cooperation efficiency and the safety and accuracy of a patient treatment scheme are remarkably improved.

The invention provides a data decoupling centralized query method and system based on MQ message triggering, and relates to the technical field of data query, and the method comprises the steps of receiving a message queue data change message, constructing a field, dividing check nodes by depending on a directed acyclic graph, carrying out data consistency verification, and pushing a transaction identifier to carry out concurrent operation scheduling. And collecting hotspot information by adopting a Bloom filter to adjust data fragmentation and cache distribution, generating a distributed query routing table, and distributing query requests according to the routing table. According to the method, the data consistency is improved, and the query performance is optimized.