1359results about "File system types" patented technology

The invention provides an intelligent agent tool calling knowledge optimization method based on empirical path graph evolution, which comprises the following steps: when an intelligent agent successfully completes a task for the first time, recording an intelligent agent tool calling sequence, input and output parameters and an execution result, generating a structured calling log, the calling log is converted into a standardized calling path knowledge unit; performing structured representation and semantic representation on the calling path knowledge unit, storing the structured representation in a graph database, and storing the semantic representation in a vector database; task intentions, tool entities and calling paths are used as heterogeneous nodes, an experience path knowledge graph is constructed, the experience path knowledge graph is used for recording the multi-dimensional relation among tasks, paths and tools, execution performance attributes and feedback attributes are added to path nodes in the graph, and agent tool calling knowledge optimization is completed. And the purpose of improving the tool calling efficiency and robustness of the intelligent agent in the multi-task environment is achieved.

The invention discloses a retrieval enhancement generated document screening system and method fusing a verification mechanism, and relates to the technical field of document screening, the system comprises a user input and query analysis module for extracting key information through natural language processing, and converting the key information into a high-dimensional semantic vector, a meta-tag and a keyword set; the multi-source document retrieval module is used for obtaining documents from multiple data sources through mixed retrieval and generating a candidate set through preliminary screening and sorting; the credibility evaluation and security verification module is used for generating scores and labels after multi-dimensional evaluation and screening qualified documents; the document consistency detection module is used for detecting document conflicts, processing and sequencing, and ensuring logic consistency; the document acquisition and generation module is used for inputting qualified documents into a generation model and generating answers with references; and the result output and tracing module is used for outputting answers and recording whole-process data to ensure traceability. The invention aims to ensure the accuracy and credibility of the generated content through a multi-dimensional verification mechanism.

The invention discloses an intelligent log retrieval and analysis system based on a model context protocol MCP, and relates to the technical field of log analysis. The system comprises an MCP log semantic conversion and retrieval engine, a log format irrelevant feature extraction and indexer, a dynamic log format recognition and context enhancement system, a real-time retrieval analysis and aggregation controller and a multi-level semantic retrieval and visualization engine. According to the context enhancement system, unknown formats can be identified, semantic tags can be complemented, and semantic consistency and behavior tracking capability can be improved. The retrieval analysis controller supports semantic expression analysis, strategy generation and feedback closed loop, and strategy scheduling and multi-dimensional aggregation analysis are achieved. And finally, outputting a structured semantic result by the system, and visually displaying the structured semantic result through components such as a semantic composition device and a context expander. All the modules are managed in a unified mode through a capability registration mechanism, dynamic arrangement and upstream and downstream closed-loop linkage are supported, and a log intelligent analysis framework with high semantic driving and a clear structure is formed.

The invention relates to the technical field of distributed system transaction management, and discloses an inventory consistency management method and device based on distributed transactions, and the method comprises the following steps: pre-occupying an inventory, and recording the state information of the inventory to a Redis hash structure; after the inventory is pre-occupied successfully, generating a pre-deducted snapshot, generating a compensation identifier, and writing the pre-deducted snapshot and the compensation identifier into a MySQL transaction log together; verifying the uniqueness of the compensation identifier, and submitting the current database transaction after the uniqueness of the compensation identifier is confirmed; when the submission of the current database transaction fails, executing a compensation operation on the current database transaction; and after the compensation operation is executed, performing data consistency verification on the MySQL transaction log and the Redis hash structure. According to the method and the system, the consistency of inventory management during distributed transaction processing is highly guaranteed.

A snapshot of metadata of a file system on a source storage system is stored in one or more of storage devices of a target storage system. A request to access data stored in the file system is received. A portion of the metadata including identification information of the data is identified. The data stored in the file system is retrieved by providing the source storage system with the identification information of the data.

The invention relates to the technical field of computer data processing, and discloses an automatic format conversion and incremental synchronization method for cross-platform heterogeneous document data. The method comprises the following steps: capturing an atomic data change event from a source system transaction log; aggregating into logic transaction units according to the transaction identifiers; converting into a unified intermediate normal form; generating a target system operation instruction set based on the metadata mapping rule; the synchronization sites are executed and persisted in a transactional manner. According to the method, through log-level capture and transactional synchronization, data integrity, sequence and high consistency are ensured, and efficient and reliable data synchronization between heterogeneous systems is supported.

The invention relates to the technical field of data processing, and provides a BMC fault recording method and device, computer equipment and a storage medium, and the method comprises the steps: responding to a kernel fault of a target operating system of a target BMC, and printing fault log information; obtaining a pre-configured memory technology device partition; transmitting the fault log information to an annular fault cache region to form cache log data; storing the cached log data in a memory technical equipment partition, and generating a fault log file; and in response to a user reading instruction, reading and outputting the fault log file of the memory technical equipment partition. According to the technical scheme provided by one or more embodiments of the invention, the fault log can be effectively recorded, maintenance personnel can timely and accurately know the fault position and the fault reason, and BMC fault diagnosis and repair can be efficiently completed.

Techniques are described for performing different types of restart operations for a file storage replication between a source file system and a target file system in different cloud infrastructure regions. In certain embodiments, the disclosed techniques perform a restart operation to terminate a current cross-region replication by synchronizing resource cleanup operations in the source file system and the target file system, respectively. In other embodiments, disclosed techniques perform a restart operation to allow a customer to reuse the source file system by identifying a restartable base snapshot in the source file system without dependency on the target file system.

The invention provides a system abnormity intelligent diagnosis and recovery method and system fusing time sequence logs, and relates to the field of distributed system operation and maintaining.The method comprises the steps that operation logs are collected from a plurality of service nodes of a distributed system, time sequence alignment is conducted, and calling relation and performance measurement data are extracted; time sequence change features are calculated in the sliding time window, dynamic feature vectors are generated through fusion coding, and a cross-service time sequence association graph is constructed; identifying an abnormal service node and matching the abnormal service node with historical fault data to obtain a historical propagation path and a feature vector; calculating a propagation convergence coefficient and a characteristic deviation degree based on a historical propagation path to obtain a causal intensity score; and identifying a fault influence degree according to the score, and adaptively adjusting a resource isolation and flow scheduling strategy. According to the invention, accurate diagnosis and efficient recovery of distributed system faults are realized.

The invention belongs to the technical field of system operation and maintenance monitoring, and particularly discloses a system health degree assessment method and system, a terminal and a medium. Comprising the following steps: collecting log stream data of a target system and a heterogeneous subsystem to obtain log feature data; inputting the log feature data into an exception detection engine of a preset training model, and performing exception judgment on the log feature data based on the exception detection engine to obtain an exception detection result; according to the anomaly detection result and the operation index of the target system, performing multi-dimensional comprehensive calculation on the operation index to obtain a system health degree score; and performing processing calculation according to the log feature data, the anomaly detection result and the system health degree score, and outputting a system operation state analysis result. By introducing the anomaly detection model based on the support vector data description and the improved grey wolf optimization algorithm, efficient analysis and anomaly recognition of complex heterogeneous system logs are realized, and the system stability and the operation and maintenance efficiency can be improved.

The invention discloses a file metadata multi-version storage management method and device, computer equipment and a storage medium. The method comprises the steps of obtaining file metadata; in response to the received generation instruction, generating a snapshot version for the file metadata to obtain a snapshot version set; extracting a first snapshot version and a second snapshot version from the snapshot version set, updating the snapshot version set, and storing the snapshot version set in a memory area; packaging the file metadata, the first snapshot version and the second snapshot version to obtain a coded data structure, and storing the coded data structure in a memory area; storing the updated snapshot version set and the coded data structure in a storage device; querying the memory area according to the query instruction, querying the storage device if the query fails, and returning a query result; by means of the method, decoupling storage of multiple versions of file metadata can be achieved, and the system memory utilization rate and the snapshot version management efficiency can be improved.

The invention discloses a cross-platform file transfer method in the mine field, which comprises the following steps: S1, mine file source identification and fluidization: docking an industrial internet platform, reading an original file generated by a specific business scene, and converting the original file into a file stream; s2, intelligent unified transcoding for the mining terminal: performing unified transcoding on the file stream through an intelligent transcoding engine; s3, encryption based on the mine data security level: carrying out encryption processing on the transcoded file; and S4, safe unloading driven by the mine service: receiving the encrypted transcoding file, and decrypting and decoding the encrypted transcoding file at a target mine terminal or a mine appointed storage node. According to the method, safe and efficient cross-platform transmission among mine multi-service systems is realized, the problem of mine terminal file compatibility is thoroughly solved, the file transmission and access efficiency in a mine weak network environment is remarkably improved, and a mine-level data security protection system is constructed.

The invention discloses a kernel probe generation method and device, computer equipment and a storage medium, and relates to the technical field of operating system kernel monitoring, and the kernel probe generation method comprises the steps of obtaining a target metadata file corresponding to a current operating system kernel in response to a kernel probe generation request; determining a target declarative strategy file; and determining a target program logic file corresponding to the target declarative strategy file, and generating a probe code according to the target program logic file and the target metadata file to obtain a kernel probe program. The probe program source code adaptive to the current kernel version can be dynamically generated in combination with the target metadata file and the target declarative strategy file, kernel probe development logic and underlying kernel knowledge can be decoupled through the source code generation function, and developers do not need to deeply understand kernel internal data structures and version differences; the development threshold is lower, a specific operating system or probe type is supported, and a universal Linux kernel and multiple probe types are also supported.

The invention provides a log data reading method and device, equipment, a medium and a program product, and relates to the field of big data. Obtaining a mapping relationship between a plurality of timeline identifiers in a database and corresponding start log serial numbers; the timeline identifier is an identifier generated when the main database and the standby database are switched, whether the log data cross different timeline identifiers or not is judged according to the mapping relation and the starting log serial number and the ending log serial number of the log data, and under the condition that the log data cross different timeline identifiers, the log data cross different timeline identifiers. Reconstructing a log reading process according to a start log serial number of a new timeline identifier, wherein the new timeline identifier is different from the plurality of timeline identifiers; according to the method, automatic reconstruction of the log reading process after main and standby switching is achieved, the problems of low efficiency and poor real-time performance caused by manual operation are avoided, and continuity and consistency of data synchronization of the source end and the target end are guaranteed.

The invention relates to the technical field of cloud storage, can be applied to business system platforms of financial science and technology, medical treatment and health and the like, and discloses a hierarchical storage method, device and equipment for data files and a medium, and the method comprises the following steps: acquiring the data files in a storage unit, and extracting data characteristic parameters in the data files; performing multi-dimensional quantitative analysis on the data feature parameters to obtain a dimensional feature analysis value; identifying a dynamic weight of the data feature parameter, and performing weighted calculation on the data feature parameter according to the dimension feature analysis value and the dynamic weight to obtain a dynamic storage analysis value; identifying a data storage type label according to the dynamic storage analysis value; matching the data storage type label with strategies in a storage strategy library to obtain a target storage strategy; determining a storage hierarchy according to the target storage strategy; a storage address of the data file in the storage hierarchy is identified and the data file is stored in the storage address. The accuracy of hierarchical storage of the data files can be improved.

The invention discloses a confidential evaluation compliance document automatic generation system and method based on strategic data management and control and full-link verification, and aims at solving the problems that traditional confidential evaluation document generation is low in efficiency, insufficient in safety protection, poor in expansibility and the like. According to the method, hard coding logic is replaced by a strategy engine center, a scene-template-strategy association mechanism is constructed, and full-process automatic generation of secret evaluation documents is achieved through scene configuration, intelligent template matching, parameter analysis, multi-dimensional data cleaning and desensitization, national secret standard automatic signing and full-process log management and control. The generation efficiency is remarkably improved, a sensitive data'identification-processing-protection 'safety closed loop is formed, the tamper-proof and auditing requirements of secret evaluation are met, a newly-added scene can be quickly accessed through strategy configuration, and the expansibility and reusability are excellent.

The invention relates to the technical field of electric power construction management, in particular to a full-chain-number intelligent construction collaborative management method and system based on electric power production. The method comprises the following steps: constructing a construction actual measurement parameter reverse mapping path, and reversely synchronizing a construction actual measurement data set to a design platform; structuring the change information in the debugging event log into measuring point mapping change data, and constructing a debugging change information reverse synchronization path based on a point construction loop three-way binding structure; constructing a dynamic transformer area operation portrait, introducing a transformer area deviation attribution identification model to compare the dynamic transformer area operation portrait with the static archive data to generate a transformer area operation deviation matrix, and dynamically adjusting a reactive power compensation control strategy and a load prediction model parameter; and performing unified archiving on the construction actual measurement data set, the measurement point mapping change data and the dynamic court operation portrait in real time. According to the invention, the reverse closed-loop collaborative management method for the whole life cycle of power production and construction is realized.

The invention discloses a coal storage and transportation intelligent management method and system, relates to the technical field of intelligent management systems, and aims to solve the problems of lack of environment monitoring, scheduling decision lag, extensive safety response and serious data island in the prior art. The method comprises the following steps: collecting the physical state, environmental parameters and operation behavior data of a coal storage yard in real time through a distributed sensor network; constructing a three-dimensional dynamic digital twinborn model and inputting the model into a time sequence neural network to predict the risk of spontaneous combustion, collapse or dust explosion in the future; and generating a dynamic scheduling instruction in combination with the task priority and the equipment state, and triggering a multi-level security response mechanism. The system comprises a sensor network module, a data fusion modeling module, a risk prediction module, a scheduling optimization module, and a closed-loop control and safety response module. According to the scheme, safety early warning preposition, scheduling decision intelligent optimization and resource energy efficiency collaborative improvement in the storage and transportation process are achieved, and the response capability and operation reliability of the coal supply chain are remarkably enhanced.

The invention relates to an inventory data synchronization and consistency verification system supporting network disconnection fault tolerance, and discloses an inventory data synchronization and consistency verification system which realizes continuous recording of inventory operation during a network disconnection period through network state detection and local cache, performs batch transmission after network recovery through a synchronous uploading and verification mechanism, and ensures data integrity. According to the inventory data synchronization and consistency verification system supporting network disconnection fault tolerance, data conflicts are automatically solved through a conflict detection and strategy processing module, a difference report is generated through consistency verification, and secondary synchronization is executed, so that safe synchronization and final consistency guarantee of inventory data are achieved, and it is ensured that the service process is continuous and stable. The system is characterized by comprising a network state detection module, a local cache module, a transaction log management module, a synchronous uploading module, a conflict detection module, a conflict resolution strategy module, a consistency verification module and an abnormity alarm and manual intervention interface module.

The invention discloses a big data governance method and system based on a rule engine, belongs to the technical field of big data processing, and aims to solve the technical problems of low efficiency, slow response and rule stiffness in the current data governance process. Comprising a data access layer used for collecting data from each data source; the metadata management module is used for constructing a knowledge graph based on the metadata; the rule engine module is used for constructing a rule base; the data quality evaluation module is used for analyzing and evaluating the multi-source heterogeneous data based on the rule base; the authority control and compliance auditing module is used for performing authority control and performing compliance analysis on data operation through a preset compliance scale board based on an auditing log; the governance engine module is used for carrying out governance operation on the multi-source heterogeneous data based on the data quality analysis result to form a data governance execution result; and the feedback optimization module is used for optimizing the AI large model based on the data governance execution result.

The invention discloses an MCP-based log data interactive retrieval visualization and report generation system, and relates to the technical field of log visualization. The system comprises a semantic analysis engine, an intelligent visualization engine, a structured report generation engine, an intelligent filing engine and an adaptive optimization system. Each module constructs a closed loop through a data stream driven by context semantics and a feedback path, and supports the whole process from original log analysis, visual analysis and semantic report generation to archiving management and strategy iteration. The system has a context-enhanced semantic modeling capability, an interactive multi-view linkage mechanism, an automatic report arrangement structure and a feedback-driven optimization capability, improves the structural property, interpretability and adaptability of log analysis compared with a traditional scheme, and is particularly suitable for complex scenes such as troubleshooting, security audit and system situation awareness.

The invention provides a data processing method and device based on code logs, equipment and a storage medium, and relates to the technical field of big data. The method comprises the following steps: acquiring a code file set, and acquiring log information output by each code file in the code file set; wherein a plurality of preset log codes are inserted into the code file, and the preset log codes are used for outputting log information; the log information represents the operation condition of the code file; determining the total data amount of the log information of all the code files, and if the total data amount meets a preset condition, deleting at least one preset log code from the at least one code file to obtain a new code file set; and obtaining new log information output by each code file in the new code file set. According to the method, the data processing efficiency of the code log information is improved.

The invention provides a storage device, a storage method and a storage access method based on lake and warehouse integration. The storage device comprises a storage management unit, a unified metadata management unit and a federal query engine unit, the storage management unit is used for realizing hybrid storage and dynamic hierarchical storage; the unified metadata management unit is used for metadata atlas construction, concurrency control and GDPR compliance support; the federal query engine is used for intelligent routing decision, SQL dialect unification and intelligent push-down optimization; based on a lake and warehouse integrated storage device and an access technology thereof, unified management of structured and unstructured data is supported, the problem of data islands is avoided, and cross-engine data visibility is realized through unified metadata management; according to the lake and warehouse integrated storage device and the access method, technologies such as a dynamic hierarchical storage strategy, intelligent routing decision, intelligent push-down optimization and the like are fused, and the storage and access efficiency and the robustness of the system are greatly improved.

The invention particularly relates to a distributed time series data cross-node atomic writing and transaction management method. According to the distributed time series data cross-node atomic writing and transaction management method, a coordination node receives a time series writing request, generates a unique TID and issues the unique TID; the storage node writes the data into a pre-write log WAL, marks the data as pending, and establishes mapping between the TID and log entries; the cooperative node sends a pre-submission instruction, and the node responds after being ready; and if verification is passed, broadcasting submission is carried out, a formal storage update version is written, otherwise, rollback is carried out, operation is cancelled according to WAL, and finally associated logs and states are cleared. According to the distributed time series data cross-node atomic write-in and transaction management method, end-to-end atomicity, consistency, low delay and rapid recovery of cross-node time series data write-in are achieved, a write-in path only needs one-time WAL write-in, synchronous blocking is avoided, and the concurrent throughput performance is remarkably improved; and the scheme does not invade an upper-layer application interface, and can be reused in any distributed storage system supporting the WAL.

The invention discloses a semantic unification and anomaly traceability analysis method and system for heterogeneous program logs, and the method comprises the steps: firstly collecting original logs in various formats, and packaging the original logs into standard objects in a unified manner; thirdly, identifying fields through a rule and a semantic model, uniformly mapping and labeling semantic tags, eliminating semantic differences, and constructing log data with uniform semantics; automatically constructing a cross-system call chain based on the request identifier and the like; secondly, extracting log features and comparing the log features with a normal behavior model to carry out anomaly detection, and generating an abnormal event; combining time, calling and dependency to construct an anomaly propagation path, and reversely backtracking and positioning an anomaly source; abnormal priority scores are calculated according to the propagation range, the influence degree and the like, and sorting and visual display are carried out; through unified semantic modeling and automatic association analysis of heterogeneous logs, accurate tracing and intelligent positioning of cross-service link anomalies are realized, the operation and maintenance efficiency is effectively improved, and the dependence on artificial experience is reduced.

The invention provides a construction log generation method based on an intelligent agent and a large model. The method comprises the following steps: 1, constructing a multi-source heterogeneous data acquisition layer: automatically acquiring required original data from a built-in interface, an external application programming interface, Internet of Things equipment and a manual input channel through the intelligent agent; 2, establishing a data preprocessing and structuring layer: processing unstructured data by using an AI technology, extracting key information, and packaging the key information into a standardized data unit; 3, constructing a domain model of precise construction terms and log styles; 4, generating a log first draft by the large model; 5, man-machine collaboration auditing and optimizing, wherein a man-machine collaboration interface is provided for engineers to audit, correct and confirm the generated log first draft; and 6, based on manual feedback, establishing an optimization closed loop, and carrying out continuous iterative optimization on data acquisition, a preprocessing rule, a cue word template or a large model. According to the method, full-automatic acquisition is realized, various data sources are automatically docked through the intelligent agent, and manpower is thoroughly liberated.

The invention relates to the technical field of data acquisition and treatment, and discloses a multimodal compatible global real-time full-amount active data acquisition and treatment method, which comprises the following steps: acquiring data source connection information of a regional medical platform, identifying potential data sources in a region, and constructing a feature portrait; matching an acquisition strategy for each data source and generating an acquisition task configuration; data acquisition is carried out, data of different data forms are analyzed, and data formats are unified; performing data cleaning, standardization and quality verification; carrying out sensitive field identification, and carrying out desensitization and encryption processing on sensitive information; performing association key extraction and entity recognition disambiguation; performing multi-source data intelligent association integration; matching the classified storage strategy and carrying out persistence processing, recording a processing process and carrying out interface development; according to the method, data cleaning, standardization, quality verification and privacy desensitization are pre-embedded into an acquisition process through a streaming collaborative governance mechanism, so that integrated processing of acquisition and governance is realized.

The invention discloses a correlation analysis engine method, system and device based on multi-source heterogeneous data and a storage medium, and belongs to the technical field of information security and log analysis.The method comprises the steps that a unified field model oriented to the multi-source heterogeneous data is constructed, and standardization is conducted to generate standardized log data; the standardized log data are input into a data processing module, and normalization, cleaning, label generation and structured storage operations are completed; based on a preset rule set, inputting the processed standardized log data into a correlation analysis engine, executing matching according to a rule type, and generating a task instruction containing action configuration when matching succeeds; and the action execution module generates structured alarm data according to the task instruction and outputs a security event record containing multiple fields. The problems that in the prior art, due to the fact that log sources are diversified, field formats are not uniform, a rule matching mechanism is single and cannot meet various analysis requirements, and the alarm generation process depends on manual configuration and lacks structured output are solved.

The present storage solution provides an order of operations of a computer-implemented method for performing transient failure handling with an improved application I / O resumption time for a symmetric distributed storage system; an order of operations of a computer-implemented method for performing persistent failure handling with an improved application I / O resumption time for a symmetric distributed storage system; an order of operations of a computer-implemented method for performing transient failure handling with an improved application I / O resumption time to maintain dependent write order consistency for a symmetric distributed storage system; an order of operations of a computer-implemented method for performing secondary side write Op handling to maintain dependent write order consistency for a symmetric distributed storage system; and an order of operations of a computer-implemented method for performing secondary side read Op handling to maintain dependent write order consistency for a symmetric distributed storage system in accordance with some embodiments.

A data processing architecture controls data processing arbitration in a high performance computing system that includes one or more premises. Individual premises can include one or more server computers executing an instance of a local file system and including one or more temporary data storage devices. Individual instances of the local file system can access files stored in objects of a primary data store. Individual objects of the primary data store can be accessed using a common identifier indicating a storage location of the individual objects in the primary data store.