Distributed log storage system and query analysis method

Abstract

The invention provides a log distributed data warehouse storage system and a query analysis method, and relates to the technical field of data warehouse storage. Comprising a local financial infrastructure digital intelligent fusion platform constructed around two major directions of local financial basic service and digital service, an agile aggregation platform constructed based on a middle platform, and a business application platform for providing different scene solutions for various scenes of the financial industry. The method has the advantages that by constructing a local financial infrastructure digital-intelligent fusion platform, offline is gradually migrated to online by applying information technologies such as the Internet, so that financial infrastructures are constructed, interconnection and basic sharing among different market subjects are realized, and the economic benefit is improved. Therefore, financial services are provided for market institutions and the public more effectively, and on one hand, the big data collection, arrangement and analysis capability and the settlement, risk control and intelligent operation capability of financial infrastructures of local financial institutions can be improved.

Description

Technical Field

[0001] The present invention relates to the field of data warehouse storage technology, and specifically to a log distributed data warehouse storage system and a query analysis method. Background Art

[0002] The fourth industrial revolution, with digitalization as its main feature, is rapidly promoting the rapid development of the digital economy. The era of digital intelligence, with the main features of the interconnection of all things, the perception of all things, and the intelligence of all things, is coming. As an important hub of the economy, local financial institutions have taken the lead in promoting digital transformation, working hard in the field of digitalization, and striving to create a smart financial ecology with intelligence, ecology, and scenario as its main features. In order to better support the construction of the local smart financial ecology and quickly meet the needs of agile and intelligent financial services, research on the construction of a digital and intelligent integration platform for local financial infrastructure is carried out. Focusing on the two major directions of local financial basic services and digital services, through the integration and innovation of new generation information technologies such as big data, cloud computing, and artificial intelligence with financial technology, the basic service capabilities of the business field are integrated, refined, and abstracted, and the componentization, modularization, and flexibility of services in related business fields are promoted, tens of thousands of basic business components are formed, and a rapid configuration, generation, and verification mechanism for product diversification is established, and financial products are agilely developed and innovated. After the platform is completed, it will mainly serve local financial institutions, government agencies, industrial institutions, etc., which will help further enrich the diversified development of local financial formats and create a one-stop solution for the digital transformation of local finance.

[0003] Based on industry needs, we provide a "1+1+N" local financial service system architecture, build platform-based financial business interconnection, data sharing and circulation, financial service scenario construction and other financial ecological service capabilities, and support the construction of a local financial characteristic industrial and financial ecosystem.

[0004] To solve the above problems, a log distributed data warehouse storage system and query analysis method are proposed. Summary of the invention

[0005] 1. Technical issues to be resolved In view of the shortcomings of the existing technology, the present invention provides a log distributed data warehouse storage system and a query and analysis method, which has the advantages of improving the security of local financial services and enhancing scalability, and solves the problems of low security and difficult management of financial services.

[0006] (II) Technical solution To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a log distributed data warehouse storage system, comprising a local financial infrastructure digital-intelligence fusion platform built around the two major directions of local financial basic services and digital services, an agile aggregation platform built based on the middle platform, and a business application platform that provides different scenario-based solutions for various scenarios in the financial industry. The local financial infrastructure digital-intelligence fusion platform serves as a database, the agile aggregation platform serves as a processing unit, and the business application platform serves as a front-end operation unit. The local financial infrastructure digital-intelligence fusion platform and the agile aggregation platform are signal-connected, and the agile aggregation platform and the business application platform are signal-connected. The agile aggregation platform is internally provided with a financial risk intelligentization module based on a knowledge graph, wherein The financial risk intelligent module based on knowledge graph performs full-process visualization operations on structured data, including ontology construction, entity extraction, index construction and retrieval result display. From bottom to top, it can be divided into a data source layer, a graph and index construction layer, and an external application layer. The financial risk intelligent module based on knowledge graph is internally provided with a financial institution knowledge graph and a risk event graph. The signal connection of the financial risk intelligent module based on knowledge graph includes an adaptive cloud resource scheduling model based on an improved ant colony algorithm, a heterogeneous network fusion architecture of a hierarchical and domain-based SDN, and a data efficient storage and access unit based on a time series database. The heterogeneous network fusion architecture of a hierarchical and domain-based SDN is divided into a main control layer, a domain control layer, and a data transmission layer. The data transmission layer signal connection includes a heterogeneous access network terminal.

[0007] The data structure is constructed through knowledge graph nodes and edges. Nodes are used to represent financial entities, and edges are used to represent the relationship between financial entities, so that customer identity information, financial transaction processes, and settlement processes can be accurately recorded. At the same time, the scope of use of financial information is expanded through the description of related relationships, which solves the problem of financial information asymmetry. At the same time, the pertinence in financial risk management and the effectiveness of risk prevention are enhanced. Through the use of deep learning, natural language processing and other technologies to portray the subject of systemically important financial institutions (SIFIs), analyze risk information such as news and announcements, and respectively construct knowledge graphs and risk event graphs of systemically important financial institutions, monitor and warn systemically important financial institutions, so as to achieve monitoring and early warning of systemic financial risks. Information crawling is carried out on news, announcements and other Internet information related to the subject of systemically important financial institutions through web crawler technology, and the crawled Internet information is written into the risk event graph as an input vector using natural language processing and other technologies. At the same time, the knowledge graph of the subject of systemically important financial institutions is associated with the output of risk monitoring and early warning information for systemically important financial institutions through the deep learning model, thereby achieving monitoring and early warning of systemic financial risks.

[0008] Preferably, the local financial infrastructure digital and intelligent integration platform includes a front-end application layer, a middle-end capability layer and a back-end basic layer. The middle-end capability layer is internally provided with a business middle-end, a data middle-end and an intelligent middle-end. By building a local financial infrastructure digital and intelligent integration platform, it helps local financial institutions to achieve independent innovation, full business platform support and full life cycle management from a strategic and global perspective, and empower local finance with digital technology to promote high-quality development.

[0009] Preferably, the agile aggregation platform includes a business capability level, a technical capability level and a data capability level. The financial risk intelligence module based on the knowledge graph is located at the business capability level. The business application platform provides users with scenario business applications such as financial business management solutions, financial funds clearing and settlement solutions, financial comprehensive wealth management solutions, and financial asset trading solutions. The agile aggregation platform built on the middle platform is oriented to financial industry customers, drives enterprise digital changes with data intelligence, realizes omni-channel connection of financial institutions' businesses and digital operations of customers, and aims to help financial institutions with strategic transformation and business development, decouple traditional financial core systems, and create a smart middle platform with clear hierarchy, efficient operation, security and reliability.

[0010] Preferably, the adaptive cloud resource scheduling model based on the improved ant colony algorithm improves the traditional ant colony algorithm by increasing the load balancing adaptive factor in the cloud computing resource scheduling process, reasonably optimizes the cloud computing resource scheduling model, thereby improving resource utilization and reducing resource energy consumption costs. It can maximize the scheduling of cloud computing resources, allocate tasks to the most suitable cloud virtual resource nodes, and complete the best matching of tasks and virtual machines, thereby achieving the goals of relatively low virtual resource consumption, relatively short task execution time, and maintaining load balancing of the entire cloud system. At the same time, it enhances the search ability for the global optimal solution, so that the improved ant colony optimization algorithm has a stronger ability to explore unknown paths, thereby breaking the state of stagnant search after falling into a local optimal solution, enhancing the probability of solving the global optimal solution, and effectively shortening the time required for large-scale data processing.

[0011] Preferably, the access network terminal adopts different access methods (such as Wi-Fi, Bluetooth and Zigbee, etc.), supports the integration of communication networks with different systems of IP protocol and non-IP protocol, and the access network terminal forwards the flow information to the core network. The domain controller is responsible for controlling the domain switch, and the main controller processes cross-domain data packets.

[0012] Preferably, the data efficient storage and access unit based on the time series database selects the Elasticsearch database as the financial transaction data storage database, and applies MySQL to store other application data.

[0013] A query analysis method for a log distributed data warehouse storage system, the query analysis method for a log distributed data warehouse storage system comprising: Integrate local financial information and user information into a data warehouse storage database; Users enter customer information and query items on the business application platform, and the user information is input into the financial risk intelligent module based on the knowledge graph; Profiling the subjects who need to query items within the system, analyzing the items that need to be queried, crawling information related to systemically important financial institutions through web crawler technology, writing the crawled information as input vectors into the knowledge graph using natural language processing and other technologies, and delivering the information to the business application platform; Users obtain query information on the business application platform.

[0014] Preferably, by increasing the load balancing adaptive factor in the cloud computing resource scheduling process, the traditional ant colony algorithm is improved, and the improved algorithm can maximize the scheduling of cloud computing resources and enable tasks to be allocated to the most suitable cloud virtual resource nodes; SDN technology is applied to heterogeneous converged network management and control. By separating the control plane and the data plane, a unified programming interface is introduced to perform logical centralized management of all network devices. The main domain control layer sends flow tables based on flow information to guide the SDN switches in the core network to complete flow forwarding, thereby achieving the convergence and interoperability of heterogeneous access networks. The control plane of the heterogeneous network convergence architecture of layered and domain SDN includes the main controller and the domain controller.

[0015] (III) Beneficial effects Compared with the prior art, the present invention provides a log distributed data warehouse storage system and query analysis method, which has the following beneficial effects: This log distributed data warehouse storage system and query and analysis method, by building a digital and intelligent integration platform for local financial infrastructure, is conducive to gradually migrating offline to online through the use of information technologies such as the Internet, so as to build financial infrastructure and achieve interconnection and basic sharing among different market players, thereby more effectively providing financial services to market institutions and the general public. On the one hand, it can enhance the big data collection, organization and analysis capabilities of the financial infrastructure of local financial institutions, as well as the clearing and settlement, risk control and intelligent operation capabilities; on the other hand, it can provide strong technical support for the stable operation and efficient development of the Internet financial service system.

[0016] This log distributed data warehouse storage system and query analysis method builds an agile aggregation platform for financial industry customers, drives enterprise digital change with data intelligence, realizes omni-channel connection of financial institutions' business and digital operation of customers, and aims to help financial institutions with strategic transformation and business development, decouple traditional financial core systems, and create a clear-layered, efficient, safe and reliable smart middle platform to quickly respond to scenario-based and ecological financial business needs, support rapid innovation and development of business, and improve user service capabilities and operational efficiency.

[0017] This log distributed data warehouse storage system and query analysis method realizes the monitoring and early warning of the entire process of financial services based on the knowledge graph, which enhances the pertinence in financial risk management and the effectiveness of risk prevention. By studying the adaptive cloud resource scheduling model based on the improved ant colony algorithm, by increasing the load balancing adaptive factor in the cloud computing resource scheduling process, the traditional ant colony algorithm is improved, the cloud computing resource scheduling model is reasonably optimized, the cloud computing resource allocation and scheduling efficiency is improved, and the platform system is stably maintained in a load balancing state. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is the overall architecture diagram of the local financial infrastructure digital intelligence integration platform proposed by the present invention; Figure 2 This is the architecture diagram of the agile aggregation platform based on the middle platform proposed by the present invention; Figure 3 The knowledge graph data retrieval and visualization method system architecture proposed in this invention; Figure 4 This is a flow chart of the intelligent early warning technology for financial risks based on knowledge graph proposed by the present invention; Figure 5 This is a diagram of the heterogeneous network fusion architecture of the layered and domain-based SDN proposed in the present invention. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] See also Figure 1-5, a log distributed data warehouse storage system, including a local financial infrastructure digital intelligence fusion platform built around the two major directions of local financial basic services and digital services, an agile aggregation platform built based on the middle platform, and a business application platform that provides different scenario-based solutions for various scenarios in the financial industry. The local financial infrastructure digital intelligence fusion platform serves as a database, the agile aggregation platform serves as a processing unit, and the business application platform serves as a front-end operation unit. The local financial infrastructure digital intelligence fusion platform and the agile aggregation platform are signal-connected, and the agile aggregation platform and the business application platform are signal-connected. The agile aggregation platform is internally equipped with a financial risk intelligence module based on a knowledge graph, among which the financial risk intelligence module based on the knowledge graph The energy module performs full-process visualization operations on structured data, including ontology construction, entity extraction, index construction and retrieval result display. From bottom to top, it can be divided into data source layer, graph and index construction layer and external application layer. The financial risk intelligent module based on knowledge graph is internally equipped with financial institution knowledge graph and risk event graph. The signal connections of the financial risk intelligent module based on knowledge graph include adaptive cloud resource scheduling model based on improved ant colony algorithm, heterogeneous network fusion architecture of layered and domain SDN and efficient data storage and access unit based on time series database. The heterogeneous network fusion architecture of layered and domain SDN is divided into main control layer, domain control layer and data transmission layer. The signal connection of data transmission layer includes heterogeneous access network terminals.

[0021] like Figure 1 As shown in the figure, the data structure is constructed by knowledge graph nodes and edges, nodes are used to represent financial entities, and edges are used to represent the relationship between financial entities, so that customer identity information, financial transaction process, and settlement process can be accurately recorded. At the same time, the scope of use of financial information is expanded through the description of related relationships, which solves the problem of financial information asymmetry. At the same time, the pertinence in financial risk management and the effectiveness of risk prevention are enhanced. Through the use of deep learning, natural language processing and other technologies to portray the subject of systemically important financial institutions (SIFIs), analyze risk information such as news and announcements, respectively construct knowledge graphs and risk event graphs of systemically important financial institutions, and monitor and warn systemically important financial institutions, so as to achieve monitoring and early warning of systemic financial risks. Through web crawler technology, information crawling is carried out on the Internet such as news and announcements related to the subject of systemically important financial institutions, and the crawled Internet information is written into the risk event graph as an input vector using natural language processing and other technologies. At the same time, the knowledge graph of the subject of systemically important financial institutions is associated with the deep learning model to output risk monitoring and early warning information for systemically important financial institutions, thereby achieving monitoring and early warning of systemic financial risks.

[0022] The digital and intelligent integration platform of local financial infrastructure includes the front-end application layer, the middle-office capability layer and the back-end basic layer. The middle-office capability layer is internally equipped with the business middle-office, data middle-office and intelligent middle-office. By building a digital and intelligent integration platform for local financial infrastructure, it will help local financial institutions to achieve independent innovation, full-business platform support and full-life cycle management from a strategic and overall perspective, and empower local finance with digital technology to achieve high-quality development.

[0023] like Figure 2 As shown, the agile aggregation platform includes business capability level, technical capability level and data capability level. The financial risk intelligence module based on knowledge graph is located at the business capability level. The business application platform provides users with scenario business applications such as financial business management solutions, financial funds clearing and settlement solutions, financial comprehensive wealth management solutions, and financial asset trading solutions. The agile aggregation platform built on the middle platform is aimed at financial industry customers, using data intelligence to drive enterprise digital changes, realize omni-channel connection of financial institutions' businesses and digital operations of customers, and aims to help financial institutions with strategic transformation and business development, decouple traditional financial core systems, and create a smart middle platform with clear hierarchy, efficient operation, security and reliability.

[0024] Among them, the financial business management solution customizes the design and development of business management systems for local trading venues, banks, funds, small loans, factoring, leasing and other institutions, achieves seamless connection between business management systems and business production systems, improves business risk management capabilities, helps enterprises develop efficiently and in compliance with regulations, and realizes the digital transformation and upgrading of the financial industry; Financial clearing and settlement solutions provide infrastructure construction for local financial institutions and regulatory agencies in the financial industry, and provide clearing and settlement system construction services for clearing and settlement companies, e-commerce platforms, supply chain platforms, 7+4 financial institutions, etc. By building business platforms and clearing and settlement systems, we can achieve automated processing of fund clearing and settlement, and promote the construction of local financial infrastructure systems; Financial comprehensive wealth management solutions provide professional and comprehensive wealth system construction, help financial institutions establish comprehensive wealth management capabilities, and provide high-quality financial planning, cross-selling tools, wealth operations, transaction services, information services, wealth monitoring and reporting services around wealth management customer service processes and wealth management professional models. They provide customers with diversified and hierarchical wealth management application design and development, and help financial institutions establish comprehensive wealth management capabilities; Financial asset trading solutions In the filing, registration, and trading of financial assets, land property rights, and other equity transactions, according to business needs, the information on filing and trading is publicized through the trading system, which fully promotes online, process-based, and standardized business, improves transaction efficiency, and promotes the liquidity of financial assets and property rights markets; The asset-liability management system helps group companies or companies in a certain scale to improve their debt management capabilities. The system covers liquidity loans, trade financing, project loans and bonds, etc. Through the full life cycle management of corporate debt products, it allows companies to fully control financing business and make statistical analysis of debt risks possible. At the same time, it meets the regulatory requirements of regulators and realizes the online digitization and visualization of corporate assets.

[0025] like Figure 5 As shown in the figure, the adaptive cloud resource scheduling model based on the improved ant colony algorithm improves the traditional ant colony algorithm by increasing the load balancing adaptive factor in the cloud computing resource scheduling process, and reasonably optimizes the cloud computing resource scheduling model, thereby improving resource utilization and reducing resource energy consumption costs. It can maximize the scheduling of cloud computing resources, allocate tasks to the most suitable cloud virtual resource nodes, and complete the best matching of tasks and virtual machines, achieving the goals of relatively low virtual resource consumption, relatively short task execution time, and maintaining load balance of the entire cloud system. At the same time, it enhances the search ability for the global optimal solution, so that the improved ant colony optimization algorithm has a stronger ability to explore unknown paths, thereby breaking the state of stagnant search after falling into the local optimal solution, enhancing the probability of solving the global optimal solution, and effectively shortening the time required for large-scale data processing.

[0026] The access network terminal adopts different access methods (such as Wi-Fi, Bluetooth and Zigbee, etc.), supports the integration of communication networks with different IP protocols and non-IP protocols, and forwards the flow information to the core network. The domain controller is responsible for controlling the domain switch, and the main controller processes cross-domain data packets.

[0027] The data efficient storage and access unit based on the time series database selects the Elasticsearch database as the financial transaction data storage database, and uses MySQL to store other application data.

[0028] A query analysis method for a log distributed data warehouse storage system, the query analysis method for a log distributed data warehouse storage system comprising: Integrate local financial information and user information into a data warehouse storage database; Users enter customer information and query items on the business application platform, and the user information is input into the financial risk intelligent module based on the knowledge graph; Profiling the subjects who need to query items within the system, analyzing the items that need to be queried, crawling information related to systemically important financial institutions through web crawler technology, writing the crawled information as input vectors into the knowledge graph using natural language processing and other technologies, and delivering the information to the business application platform; Users obtain query information on the business application platform.

[0029] By increasing the load balancing adaptive factor in the cloud computing resource scheduling process, the traditional ant colony algorithm is improved. The improved algorithm can maximize the scheduling of cloud computing resources and enable tasks to be allocated to the most suitable cloud virtual resource nodes. SDN technology is applied to heterogeneous converged network management and control. By separating the control plane and the data plane, a unified programming interface is introduced to perform logical centralized management of all network devices. The main domain control layer sends flow tables based on flow information to guide the SDN switches in the core network to complete flow forwarding, thereby achieving the convergence and interoperability of heterogeneous access networks. The control plane of the heterogeneous network convergence architecture of layered and domain SDN includes the main controller and the domain controller.

[0030] To sum up, this log distributed data warehouse storage system and query and analysis method, the local financial infrastructure digital intelligence integration platform mainly faces the financial business of local financial institutions, and has very high requirements for data security. The system design target users are local financial institutions, government agencies, industrial institutions, etc. There are a large amount of capital data flows concentrated in the system, requiring the system to handle properly, and the confidentiality goals start from data confidentiality, transaction confidentiality and other aspects. Transactions need to be encrypted, sometimes hardware encryption, sometimes software encryption. According to the MVC design concept, the control layer, model layer, and view layer are strictly layered for development, and different process modules in the class are encapsulated and annotated differently. The development log is configured, and complex problems are simplified into a collection of different methods or classes. Use a concise main process code style, and strive to have good scalability in the architecture. In the future, local financial development may occur and respond to personalized needs and customization among different users. The system can meet changes at a relatively low cost, requiring the development of low coupling and high cohesion of each component. On the basis of meeting user needs, the system achieves good responsiveness and improves user experience.

[0031] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise one" do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0032] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A log distributed data warehouse storage system, characterized by: It includes a local financial infrastructure digital-intelligence fusion platform built around the two major directions of local financial basic services and digital services, an agile aggregation platform built based on the middle platform, and a business application platform that provides different scenario-based solutions for various scenarios in the financial industry. The local financial infrastructure digital-intelligence fusion platform serves as a database, the agile aggregation platform serves as a processing unit, and the business application platform serves as a front-end operation unit. The local financial infrastructure digital-intelligence fusion platform and the agile aggregation platform are signal-connected, and the agile aggregation platform and the business application platform are signal-connected. The agile aggregation platform is internally equipped with a financial risk intelligentization module based on a knowledge graph, wherein the financial risk intelligentization module based on the knowledge graph is used for The whole process visualization operation of ontology construction, entity extraction, index construction and retrieval result display of structured data can be divided into data source layer, graph and index construction layer and external application layer from bottom to top. The financial risk intelligent module based on knowledge graph is internally provided with financial institution knowledge graph and risk event graph. The signal connection of the financial risk intelligent module based on knowledge graph includes adaptive cloud resource scheduling model based on improved ant colony algorithm, heterogeneous network fusion architecture of layered and domain SDN and data efficient storage and access unit based on time series database. The heterogeneous network fusion architecture of layered and domain SDN is divided into main control layer, domain control layer and data transmission layer. The signal connection of data transmission layer includes heterogeneous access network terminal.

2. A log distributed data warehouse storage system as claimed in claim 1, characterized in that: The local financial infrastructure digital and intelligent integration platform includes a front-end application layer, a middle-end capability layer and a back-end basic layer. The middle-end capability layer is internally equipped with a business middle-end, a data middle-end and an intelligent middle-end.

3. A log distributed data warehouse storage system as claimed in claim 2, characterized in that: The agile aggregation platform includes business capability level, technical capability level and data capability level. The financial risk intelligent module based on knowledge graph is located at the business capability level. The business application platform provides users with financial business management solutions, financial funds clearing and settlement solutions and financial comprehensive wealth management solutions.

4. A log distributed data warehouse storage system as claimed in claim 3, characterized in that: The adaptive cloud resource scheduling model based on the improved ant colony algorithm improves the traditional ant colony algorithm by increasing the load balancing adaptive factor in the cloud computing resource scheduling process, and can maximize the scheduling of cloud computing resources, so that tasks are allocated to the most suitable cloud virtual resource nodes, and achieve the best matching of tasks and virtual machines.

5. A log distributed data warehouse storage system and query analysis method as claimed in claim 4, characterized in that: The access network terminal adopts different access modes and supports the integration of communication networks with different systems of IP protocol and non-IP protocol. The access network terminal forwards the flow information to the core network, the domain controller is responsible for controlling the domain switch, and the main controller processes cross-domain data packets.

6. A log distributed data warehouse storage system as claimed in claim 5, characterized in that: The data efficient storage and access unit based on the time series database selects the Elasticsearch database as the financial transaction data storage database, and uses MySQL to store other application data.

7. A query analysis method for a log distributed data warehouse storage system, characterized in that: The query analysis method of the log distributed data warehouse storage system includes: Integrate local financial information and user information into a data warehouse storage database; Users enter customer information and query items in the business application platform, and the user information is input into the financial risk intelligent module based on the knowledge graph; Profiling the subjects who need to query items within the system, analyzing the items that need to be queried, crawling information related to systemically important financial institutions through web crawler technology, writing the crawled information as input vectors into the knowledge graph using natural language processing and other technologies, and delivering the information to the business application platform; Users obtain query information on the business application platform.

8. A query and analysis method for a log distributed data warehouse storage system according to claim 7, characterized in that: By increasing the load balancing adaptive factor in the cloud computing resource scheduling process, the traditional ant colony algorithm is improved. The improved algorithm can maximize the scheduling of cloud computing resources and enable tasks to be allocated to the most suitable cloud virtual resource nodes. SDN technology is applied to heterogeneous converged network management and control. By separating the control plane and the data plane, a unified programming interface is introduced to perform logical centralized management of all network devices. The main domain control layer sends flow tables based on flow information to guide the SDN switches in the core network to complete flow forwarding, thereby achieving the convergence and interoperability of heterogeneous access networks. The control plane of the heterogeneous network convergence architecture of layered and domain SDN includes the main controller and the domain controller.

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