A financial information system and operation method based on big data

Abstract

The present invention proposes a financial information system based on big data and a corresponding method, establishes a big data warehouse in the cloud, realizes the system's data set storage and big data utilization and interaction through the big data warehouse, and realizes the comprehensive management of the financial information system. The financial information system claimed for protection by the present invention simultaneously uses a comprehensive management server to manage multiple secondary servers and transaction nodes and block nodes in the blockchain, and adopts a transaction data interpolation server to perform transaction data interpolation storage. By utilizing the block differential storage properties, combining the transaction data interpolation of the transaction data interpolation server and the count accumulation value of the transaction data balancing server, block-based decentralized storage and multi-server collaborative management and regular updating of cloud big data are realized, making dynamic financial information analysis based on big data possible.

Description

Technical Field

[0001] The present invention belongs to the technical field of big data processing, and in particular relates to a financial information system based on big data and an operating method thereof. Background Art

[0002] As the information society gradually becomes established, more and more internet applications are generating more and more data redundancy. How to integrate and process this data into a powerful tool for social management and corporate decision-making is becoming an increasingly pressing issue in this information society.

[0003] Massive amounts of data, also known as big data, have emerged in the process of informatization. Big data is a product of the rapid development of internet technology. Big data refers to vast datasets collected from numerous sources in diverse formats, also known as massive data. Big data is characterized by large capacity, high velocity, diversity, and value. Large capacity refers to the vast amount of information in the database, with complex and varied content. Diversity refers to the diverse data types, including images, text, and audio, as well as the diverse data sources, both internal and external to the organization. High velocity refers to its rapid development and processing speed. Its value motivates us to research how to obtain valuable information.

[0004] Big data technology possesses many unique characteristics. First, it can process relatively large amounts of data. Second, it can handle diverse data types. Big data technology is not limited to processing large amounts of simple data, but can also handle complex data such as text, audio, and images. Furthermore, the application of big data technology offers the advantages of low density and high value. If the meaning of scattered and diverse data cannot be quickly analyzed, big data analysis can be used to unlock the hidden value within this information, enabling research and other applications, and making government affairs more convenient and comprehensive.

[0005] Large-Scale Data Storage, Management, Analysis, and Mining: Big data storage and management refers to storing collected data in memory, establishing corresponding databases, and managing and accessing them. Big data mining refers to the process of extracting hidden information and knowledge from large amounts of incomplete, noisy, ambiguous, and random real-world application data. This information and knowledge is potentially useful but unknown to humans. Big data analytics refers to the collection, storage, management, and analysis of large-scale data, focusing on how to compute the data required (HDFS, S3, HBase, Cassandra) and how to compute (Hadoop, Spark). This section contains more information, but some key points include: Hadoop: A general-purpose distributed system infrastructure with multiple components; the Hadoop ecosystem primarily consists of core components (such as HDFS, MapReduce, HBase, Zookeeper, Ozie, PIG, and Hive); Spark: Focuses on parallel data processing within a cluster and uses RDDs (Flexible Distributed Datasets) to process data in RAM. Storm: Continuously processes streams of data imported from a source and obtains incremental results at any time. HBase is a distributed, column-oriented open source database that can be considered a wrapper of HDFS. Its core function is data storage and a NoSQL database.

[0006] The application of big data in specific areas is booming. For example, in smart cities, big data is a key technology for achieving smart city success, impacting the overall performance of smart cities and the stability and reliability of observed events. The ultimate goal of vigorously developing the Internet of Things (IoT) in security, transportation, education, and healthcare is to enable more efficient and intelligent city management through the network. Leveraging big data technology, smart cities are making extensive use of big data in healthcare, transportation, and other areas. Big data is a modern internet-based technology. Leveraging the internet and big data, it enables continuous improvement of algorithms, resulting in increasingly sophisticated capabilities for incident and case analysis, as well as screening and search capabilities. Furthermore, the ultimate goal of vigorously developing big data is to enable more efficient and intelligent management of smart cities through the IoT. The massive volume of data generated necessitates a sophisticated big data computing system as a foundation. Smart city development requires an ever-increasing amount of data computation, and traditional hardware-based systems are struggling to meet daily data processing requirements. Combining IoT big data with smart cities will significantly improve the operational efficiency of the entire system.

[0007] In the financial information sector, the application of big data opens the door to the development of advanced financial analysis tools. The collection and analysis of massive amounts of data, along with the processing of this data, enables comprehensive analytical capabilities unattainable in traditional finance. However, current financial big data analysis systems rely solely on conventional massive data collection and analysis, failing to consider decentralized, multi-tiered services and management, as well as differentiated data analysis and storage. Consequently, these systems are poorly adaptable to user needs and cannot meet the demands of comprehensive blockchain-based system management.

[0008] The present invention proposes a financial information system based on big data and a corresponding method, establishes a big data warehouse in the cloud, realizes the system's data set storage and big data utilization and interaction through the big data warehouse, and realizes the comprehensive management of the financial information system. The financial information system claimed for protection by the present invention simultaneously uses a comprehensive management server to manage multiple secondary servers and transaction nodes and block nodes in the blockchain, and adopts a transaction data interpolation server to perform transaction data interpolation storage. By utilizing the block differential storage properties, combining the transaction data interpolation of the transaction data interpolation server and the count accumulation value of the transaction data balancing server, block-based decentralized storage and multi-server collaborative management and regular updating of cloud big data are realized, making dynamic financial information analysis based on big data possible. Summary of the Invention

[0009] The present invention aims to provide a financial information system and method based on big data that are superior to the existing technology.

[0010] In order to achieve the above object, the technical solution of the present invention is as follows:

[0011] A financial information system based on big data, comprising:

[0012] The integrated management server performs module stability analysis on the financial information system based on big data, determines a faulty module based on the module stability analysis, and performs module replacement;

[0013] The cloud-based big data warehouse receives query feedback from the transaction data interpolation server and stores the corresponding transaction data in the cloud-based big data warehouse for use by the system in performing big data analysis;

[0014] a plurality of IoT transaction nodes, each of the plurality of IoT transaction nodes being connected to a specific block, generating first financial transaction data corresponding to a transaction when a transaction occurs, and uploading the first financial transaction data to the connected block;

[0015] The Internet of Things transaction node records the corresponding relationship with the connected block, stores it as a first corresponding relationship, and sends the first corresponding relationship to the transaction relationship balancing server of the big data-based financial information system;

[0016] a transaction relationship balancing server, configured to store the first corresponding relationship and generate a first block transaction link table based on the first corresponding relationship;

[0017] The first block transaction link table at least includes: a block column for storing a block number; an IoT transaction node column for storing an IoT transaction node having a first corresponding relationship with a block having a specific block number; and a mapping quantity column for storing the number of IoT transaction nodes having a first corresponding relationship with a block having a specific block number.

[0018] a plurality of blocks, each block having a specific block number, each of the plurality of IoT transaction nodes being connected to a specific block, and the plurality of blocks receiving first financial transaction data uploaded by the connected IoT transaction node;

[0019] When a transaction occurs on the connected IoT transaction node, that is, when new first financial transaction data is generated, the block synchronizes the generated first financial transaction data to each block of the blockchain and sends the new first financial transaction data to the transaction data balancing server;

[0020] The block is further configured to send a first balance count to a transaction data balancing server when a transaction occurs at the connected IoT transaction node, i.e., when new first financial transaction data is generated, or when first financial transaction data synchronized with other blocks is received and local transaction data is updated and stored;

[0021] The block is further configured to send a second balancing count to a transaction data balancing server when receiving first financial transaction data synchronized with other blocks and when no local transaction data update storage is performed;

[0022] The block is further configured to generate transaction data interpolation and upload it to a transaction data interpolation server when receiving first financial transaction data synchronized with other blocks and when no local transaction data update and storage is performed;

[0023] The transaction data interpolation is used to represent the blocks and corresponding transactions for which local transaction data update storage is not performed when receiving the first financial transaction data synchronized with other blocks;

[0024] The transaction data balancing server is configured to receive a first balancing count sent by the block when a transaction occurs at a connected IoT transaction node, i.e., when new first financial transaction data is generated, or when the block receives first financial transaction data synchronized with other blocks and performs local transaction data update and storage, and receive a second balancing count sent by the block when the block receives first financial transaction data synchronized with other blocks and does not perform local transaction data update and storage;

[0025] The transaction data balancing server is further configured to accumulate the first and second balancing counts received during a data update process of a single transaction to obtain a count accumulation value, and to analyze the differentiated update storage of block transaction data in the big data-based financial information system based on the count accumulation value;

[0026] The transaction data balancing server is further configured to receive the first financial transaction data uploaded by each block and perform local storage, and obtain the transaction ID of this transaction;

[0027] A transaction data interpolation server, which is used to separately store the transaction data interpolation uploaded by each block;

[0028] The transaction data interpolation server is also used to receive queries from users of the financial analysis system, and comprehensively, based on the data stored in the transaction data balancing server and the first corresponding relationship stored in the transaction relationship balancing server, normalize the financial analysis results and feed them back to users whose queries have different weights.

[0029] Preferably, the first financial transaction data corresponding to the transaction at least includes the identifiers of the two parties to the transaction, the transaction time and amount of the transaction, and the transaction ID; and the transaction data interpolation at least includes the corresponding block number and transaction ID.

[0030] Preferably, after each new transaction arrives, after the transaction ID of the previous transaction is processed, the system's transaction ID is updated, and the next big data-based financial information system processing is performed based on the new transaction ID.

[0031] Preferably, the first balance count is a first unit count, and the second balance count is the first unit count+1.

[0032] Preferably, there are multiple IoT transaction nodes connected to a single block.

[0033] At the same time, the present invention discloses an operating method of a financial information system based on big data, the method comprising the following steps:

[0034] Step 1: operating the integrated management server to perform module stability analysis on the financial information system based on big data, and determining a faulty module based on the module stability analysis, and performing module replacement;

[0035] Step 2: Operate each of the plurality of IoT transaction nodes to connect to a specific block, generate first financial transaction data corresponding to the transaction when a transaction occurs, and upload the first financial transaction data to the connected block;

[0036] The IoT transaction node records the corresponding relationship with the connected block, stores it as a first corresponding relationship, and sends the first corresponding relationship to the transaction relationship balancing server of the big data-based financial information system;

[0037] Step 3: Operate the transaction relationship balancing server to store the first corresponding relationship, and generate a first block transaction link table based on the first corresponding relationship;

[0038] The first block transaction link table at least includes: a block column for storing a block number; an IoT transaction node column for storing an IoT transaction node having a first corresponding relationship with a block having a specific block number; and a mapping quantity column for storing the number of IoT transaction nodes having a first corresponding relationship with a block having a specific block number.

[0039] Step 4: operating each of the plurality of blocks, each of which has a specific block number, connecting each of the plurality of IoT transaction nodes to the specific block, and the plurality of blocks receiving the first financial transaction data uploaded by the connected IoT transaction node;

[0040] When a transaction occurs on the connected IoT transaction node, that is, when new first financial transaction data is generated, the block synchronizes the generated first financial transaction data to each block of the blockchain and sends the new first financial transaction data to the transaction data balancing server;

[0041] The block is further configured to send a first balance count to a transaction data balancing server when a transaction occurs at the connected IoT transaction node, i.e., when new first financial transaction data is generated, or when first financial transaction data synchronized with other blocks is received and local transaction data is updated and stored;

[0042] The block is further configured to send a second balancing count to a transaction data balancing server when receiving first financial transaction data synchronized with other blocks and when no local transaction data update storage is performed;

[0043] The block is further configured to generate transaction data interpolation and upload it to a transaction data interpolation server when receiving first financial transaction data synchronized with other blocks and when no local transaction data update and storage is performed;

[0044] The transaction data interpolation is used to represent the blocks and corresponding transactions for which local transaction data update storage is not performed when receiving the first financial transaction data synchronized with other blocks;

[0045] Step 5: Operate the transaction data balancing server to receive a first balancing count sent by the block when a transaction occurs at the connected IoT transaction node, i.e., when new first financial transaction data is generated, or when the block receives first financial transaction data synchronized with other blocks and performs local transaction data update and storage, and receive a second balancing count sent by the block when the block receives first financial transaction data synchronized with other blocks and does not perform local transaction data update and storage;

[0046] The transaction data balancing server is further configured to accumulate the first and second balancing counts received during a data update process of a single transaction to obtain a count accumulation value, and to analyze the differentiated update storage of block transaction data in the big data-based financial information system based on the count accumulation value;

[0047] The transaction data balancing server is further configured to receive the first financial transaction data uploaded by each block and perform local storage, and obtain the transaction ID of this transaction;

[0048] Step 6: Operate the transaction data interpolation server to separately store the transaction data interpolation uploaded by each block;

[0049] The transaction data interpolation server is further configured to receive queries from users of the financial analysis system, and based on the data stored in the transaction data balancing server and the first corresponding relationship stored in the transaction relationship balancing server, normalize the data and feed back the financial analysis results to users with different query weights.

[0050] Step 7: Operate the cloud-based big data warehouse to receive query feedback from the transaction data interpolation server, and store the corresponding transaction data in the cloud-based big data warehouse for the system to perform big data analysis.

[0051] Preferably, the first financial transaction data corresponding to the transaction at least includes the identifiers of the two parties to the transaction, the transaction time and amount of the transaction, and the transaction ID; and the transaction data interpolation at least includes the corresponding block number and transaction ID.

[0052] Preferably, after each new transaction arrives, after the transaction ID of the previous transaction is processed, the system's transaction ID is updated, and the next big data-based financial information system processing is performed based on the new transaction ID.

[0053] Preferably, the first balance count is a first unit count, and the second balance count is the first unit count+1.

[0054] Preferably, there are multiple IoT transaction nodes connected to a single block.

[0055] The present invention proposes a financial information system based on big data and a corresponding method, establishes a big data warehouse in the cloud, realizes the system's data set storage and big data utilization and interaction through the big data warehouse, and realizes the comprehensive management of the financial information system. The financial information system claimed for protection by the present invention simultaneously uses a comprehensive management server to manage multiple secondary servers and transaction nodes and block nodes in the blockchain, and adopts a transaction data interpolation server to perform transaction data interpolation storage. By utilizing the block differential storage properties, combining the transaction data interpolation of the transaction data interpolation server and the count accumulation value of the transaction data balancing server, block-based decentralized storage and multi-server collaborative management and regular updating of cloud big data are realized, making dynamic financial information analysis based on big data possible. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 This is a basic system structure diagram of a financial information system based on big data shown in the present invention;

[0057] Figure 2 This is a basic system structure diagram of a cloud-based big data warehouse in a big data-based financial information system shown in the present invention;

[0058] Figure 3 This is a basic system structure diagram of the interconnection between the integrated management server and the cloud-based big data warehouse in the financial information system based on big data shown in the present invention;

[0059] Figure 4 This is a preferred embodiment of the present invention showing the interconnection between blocks, corresponding transaction nodes, and transaction relationship balancing servers in a financial information system based on big data.

[0060] Figure 5 It is a schematic diagram of a preferred display embodiment of the financial information system operation method based on big data shown in the present invention. DETAILED DESCRIPTION

[0061] The following describes in detail several embodiments and beneficial effects of a big data-based financial information system claimed in the present invention to facilitate a more detailed review and analysis of the present invention.

[0062] In order to better understand the technical solution of the present invention, the embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0063] It should be understood that the embodiments described are only a portion 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 persons of ordinary skill in the art without creative work are within the scope of protection of the present invention.

[0064] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The singular forms "a", "an", "the" and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise.

[0065] It should be understood that the term "and / or" as used herein is merely a description of the relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0066] It should be understood that although the terms "first," "second," etc. may be used in embodiments of the present invention to describe the methods and corresponding apparatuses, these keywords should not be limited to these terms. These terms are merely used to distinguish keywords from one another. For example, without departing from the scope of embodiments of the present invention, a first balance count, a first block, etc. may also be referred to as a second balance count, a second block, and similarly, a second balance count, a second block, etc. may also be referred to as a first balance count, a first block.

[0067] The word "if," as used herein, may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)," depending on the context.

[0068] As the instruction manual Figure 1-4 As shown in the instruction manual, Figure 1-4 This is one embodiment of a financial information system based on big data and the interconnection relationship between its specific modules, which is claimed in the present invention. The system includes:

[0069] The integrated management server performs module stability analysis on the financial information system based on big data, determines a faulty module based on the module stability analysis, and performs module replacement;

[0070] As an embodiment that can be superimposed, the module stability analysis is performed on the financial information system based on big data, and the faulty module is determined based on the module stability analysis, and the module is replaced. Specifically,

[0071] The integrated management server sends stability analysis requests to each block, each transaction node, transaction data balancing server, transaction data interpolation server, and transaction relationship balancing server. Each transaction node collects its own operating data. The transaction data balancing server, transaction data interpolation server, and transaction relationship balancing server have their operating data collected uniformly by the transaction data interpolation server and uploaded to the integrated management server.

[0072] The integrated management server determines whether a module stability failure occurs based on the uploaded operation data of each module and the system's preset judgment threshold. If a module fails, the server will replace the module with its backup module or perform secondary initialization of the module.

[0073] The cloud-based big data warehouse receives query feedback from the transaction data interpolation server and stores the corresponding transaction data in the cloud-based big data warehouse for use by the system in performing big data analysis;

[0074] an Internet of Things transaction node, each of the plurality of Internet of Things transaction nodes being connected to a specific block, generating first financial transaction data corresponding to the transaction when a transaction occurs, and uploading the first financial transaction data to the connected block;

[0075] The Internet of Things transaction node records the corresponding relationship with the connected block, stores it as a first corresponding relationship, and sends the first corresponding relationship to the transaction relationship balancing server of the big data-based financial information system;

[0076] a transaction relationship balancing server, configured to store the first corresponding relationship and generate a first block transaction link table based on the first corresponding relationship;

[0077] The first block transaction link table at least includes: a block column for storing a block number; an IoT transaction node column for storing an IoT transaction node having a first corresponding relationship with a block having a specific block number; and a mapping quantity column for storing the number of IoT transaction nodes having a first corresponding relationship with a block having a specific block number.

[0078] a plurality of blocks, each block having a specific block number, each of the plurality of IoT transaction nodes being connected to a specific block, and the plurality of blocks receiving first financial transaction data uploaded by the connected IoT transaction node;

[0079] When a transaction occurs on the connected IoT transaction node, that is, when new first financial transaction data is generated, the block synchronizes the generated first financial transaction data to each block of the blockchain and sends the new first financial transaction data to the transaction data balancing server;

[0080] The block is further configured to send a first balance count to a transaction data balancing server when a transaction occurs at the connected IoT transaction node, i.e., when new first financial transaction data is generated, or when first financial transaction data synchronized with other blocks is received and local transaction data is updated and stored;

[0081] As an alternate embodiment, during the data update process for a single transaction, the first balance count represents the system's statistical count of storage updates performed when a transaction occurs on a connected transaction node, i.e., when new first financial transaction data is generated, or when first financial transaction data synchronized with other blocks is received and local transaction data storage is updated. The data update process for a single transaction, i.e., the process of uploading and updating data when a single transaction occurs on any transaction node in the blockchain system, only continues to upload and update data for the next transaction after the previous data upload and update is completed, is another alternate embodiment. The first balance count can be 1 or an integer multiple of 1. For example, if the big data-based financial information system has a blockchain with 200 blocks for storing data, then, when the first balance count is set to 1, after a transaction, if the other 199 blocks all receive the first financial transaction data synchronized by other blocks and perform local transaction data update storage, 200 first balance counts, that is, 200 "1" values, will be sent to the transaction data balance server. The transaction data balance server performs the first balance count accumulation, and the accumulated count value can be 200; when the first balance count is set to 2, after a transaction, if the other 199 blocks all receive the first financial transaction data synchronized by other blocks and perform local transaction data update storage, 200 first balance counts, that is, 200 "2" values, will be sent to the transaction data balance server. The transaction data balance server performs the first balance count accumulation, and the accumulated count value can be 400; note that as a superimposable embodiment, the single block in which the connected transaction node undergoes a transaction also uploads the first balance count.

[0082] The block is further configured to send a second balancing count to a transaction data balancing server when receiving first financial transaction data synchronized with other blocks and when no local transaction data update storage is performed;

[0083] As an overlapping embodiment, during the data update process of a single transaction, the second balance count represents the statistical count of the system's storage updates when receiving the first financial transaction data synchronized with other blocks and not performing local transaction data update storage. The data update process of a single transaction, that is, in the blockchain system, a single transaction occurs at any transaction node, and the data upload and update process is performed. After the previous data upload and update is completed, the data upload and update of the next transaction will continue. As another overlapping embodiment, the second balance count can be the first balance count + 1. For example, if the big data-based financial information system has a blockchain with 200 blocks for storing data, then when the first balance count is set to 1, the second balance count can be the first balance count + 1 = 2. After a transaction, if the other 197 blocks all receive the first financial transaction data synchronized by the other blocks and perform local transaction data updates and storage, while two blocks receive the first financial transaction data synchronized by the other blocks but do not perform local transaction data updates and storage, they will send 198 (197 + 1 (the connected block where the transaction occurred)) first balance counts, i.e., 198 "1" values, and two second balance counts, i.e., two "2" values, to the transaction data balancing server. The transaction data balancing server accumulates the first balance counts and the second balance counts, obtaining an accumulated count value of 202. At this point, based on the difference of 200 system blocks and the accumulated count value of 202, the transaction data balancing server can deduce that two blocks in the system received the first financial transaction data synchronized by the other blocks and did not perform local transaction data updates and storage. Therefore, these two blocks store historical, traceable transaction data for a specific period. Note that as an alternative embodiment, the single block where the transaction occurred on the connected transaction node also uploads the first balance count. By setting up statistical analysis of the first balance count and the second balance count on the transaction data balancing server, it is possible to achieve differentiated update and partial storage of block transaction data of the financial information system based on big data. At the same time, the transaction data balancing server can grasp the overall proportion data of differentiated storage of block transaction data of the entire financial analysis system while decentralizing storage.

[0084] The block is further configured to generate transaction data interpolation and upload it to a transaction data interpolation server when receiving first financial transaction data synchronized with other blocks and when no local transaction data update and storage is performed;

[0085] The transaction data interpolation is used to represent the blocks and corresponding transactions for which local transaction data update storage is not performed when receiving the first financial transaction data synchronized with other blocks;

[0086] As an overlapping embodiment, each transaction node generates a unique transaction ID to distinguish different transactions and circulates within the blockchain along with the first financial transaction data. The block is further configured to, upon receiving first financial transaction data synchronized with another block and without performing a local transaction data update and storage, generate and upload a transaction data interpolation to the transaction data interpolation server. This process includes at least recording the block's sequence number and the transaction ID from the received first financial transaction data within the transaction data interpolation, and uploading the transaction data interpolation to the transaction data interpolation server.

[0087] The transaction data balancing server is configured to receive a first balancing count sent by the block when a transaction occurs at a connected IoT transaction node, i.e., when new first financial transaction data is generated, or when the block receives first financial transaction data synchronized with other blocks and performs local transaction data update and storage, and receive a second balancing count sent by the block when the block receives first financial transaction data synchronized with other blocks and does not perform local transaction data update and storage;

[0088] The transaction data balancing server is further configured to accumulate the first and second balancing counts received during a data update process of a single transaction to obtain a count accumulation value, and to analyze the differentiated update storage of block transaction data in the big data-based financial information system based on the count accumulation value;

[0089] The transaction data balancing server is further configured to receive the first financial transaction data uploaded by each block and perform local storage, and obtain the transaction ID of this transaction;

[0090] A transaction data interpolation server, which is used to separately store the transaction data interpolation uploaded by each block;

[0091] The transaction data interpolation server is also used to receive queries from users of the financial analysis system, and comprehensively, based on the data stored in the transaction data balancing server and the first corresponding relationship stored in the transaction relationship balancing server, normalize the financial analysis results and feed them back to users whose queries have different weights.

[0092] As an alternate embodiment, the transaction data interpolation server is further configured to receive queries from users of the financial analysis system, normalize the data stored by the transaction data balancing server and the first correspondence stored by the transaction relationship balancing server, and then feed back the financial analysis results to the querying user. This process includes at least: determining the block number of a dodge block based on the accumulated count value of the transaction data balancing server and the transaction data interpolation performed by the transaction data interpolation server during a single transaction ID, extracting the transaction record of the specific dodge block as first transaction data and the transaction record of a specific block from other normal blocks as second transaction data, and sending a comparison of the first transaction data and the second transaction data as third transaction data to the user for display. For users with a first weight, only the first transaction data is displayed; for users with a second weight, only the second transaction data is displayed; and for users with a third weight, only the third transaction data is displayed. The dodge block is a block that, during the current transaction ID data update process, received first financial transaction data synchronized with other blocks but for which no local transaction data update was performed. Among them, the user with the first weight is a user who does not have the right to perform query or review operations on the latest transactions, the user with the second weight is a user who has the right to perform query or review operations on the latest transactions, and the user with the third weight is a system management user.

[0093] As a superimposable embodiment, the avoidance block is designated by the system, or is dynamically allocated by the system according to a specific election algorithm during each transaction ID processing.

[0094] As an overlayable embodiment, the first financial transaction data corresponding to the transaction includes at least the identifiers of the two parties to the transaction, the transaction time and transaction amount of the transaction, and the transaction ID; the transaction data interpolation includes at least the corresponding block number and transaction ID.

[0095] As another superimposable embodiment, after each new transaction arrives, after the transaction ID of the previous transaction is processed, the system's transaction ID is updated, and the next big data-based financial information system processing is performed based on the new transaction ID.

[0096] As another superimposable embodiment, the first balancing count is a first unit count, and the second balancing count is the first unit count+1.

[0097] As another superimposable embodiment, there are multiple IoT transaction nodes connected to a single block.

[0098] At the same time, as the instructions Figure 5 As shown in the instruction manual, Figure 5This is a schematic diagram showing a preferred embodiment of an operating method of a financial information system based on big data according to the present invention. The method includes the following steps:

[0099] As an embodiment that can be superimposed, the module stability analysis is performed on the financial information system based on big data, and the faulty module is determined based on the module stability analysis, and the module is replaced. Specifically,

[0100] S102: operating the integrated management server to perform module stability analysis on the financial information system based on big data, and determining a faulty module based on the module stability analysis, and performing module replacement;

[0101] As an embodiment that can be superimposed, the module stability analysis is performed on the financial information system based on big data, and the faulty module is determined based on the module stability analysis, and the module is replaced. Specifically,

[0102] The integrated management server sends stability analysis requests to each block, each transaction node, transaction data balancing server, transaction data interpolation server, and transaction relationship balancing server. Each transaction node collects its own operating data. The transaction data balancing server, transaction data interpolation server, and transaction relationship balancing server have their operating data collected uniformly by the transaction data interpolation server and uploaded to the integrated management server.

[0103] The integrated management server determines whether a module stability failure occurs based on the uploaded operation data of each module and the system's preset judgment threshold. If a module fails, the server will replace the module with its backup module or perform secondary initialization of the module.

[0104] S104: operating each of the plurality of IoT transaction nodes to connect to a specific block, generating first financial transaction data corresponding to the transaction when a transaction occurs, and uploading the first financial transaction data to the connected block;

[0105] The IoT transaction node records the corresponding relationship with the connected block, stores it as a first corresponding relationship, and sends the first corresponding relationship to the transaction relationship balancing server of the big data-based financial information system;

[0106] S106: operating the transaction relationship balancing server to store the first corresponding relationship, and generating a first block transaction link table based on the first corresponding relationship;

[0107] The first block transaction link table at least includes: a block column for storing a block number; an IoT transaction node column for storing an IoT transaction node having a first corresponding relationship with a block having a specific block number; and a mapping quantity column for storing the number of IoT transaction nodes having a first corresponding relationship with a block having a specific block number.

[0108] S108: operating each of a plurality of blocks, each of which has a specific block number, connecting each of a plurality of IoT transaction nodes to the specific block, and the plurality of blocks receiving first financial transaction data uploaded by the connected IoT transaction nodes;

[0109] When a transaction occurs on the connected IoT transaction node, that is, when new first financial transaction data is generated, the block synchronizes the generated first financial transaction data to each block of the blockchain and sends the new first financial transaction data to the transaction data balancing server;

[0110] The block is further configured to send a first balance count to a transaction data balancing server when a transaction occurs at the connected IoT transaction node, i.e., when new first financial transaction data is generated, or when first financial transaction data synchronized with other blocks is received and local transaction data is updated and stored;

[0111] The block is further configured to send a second balancing count to a transaction data balancing server when receiving first financial transaction data synchronized with other blocks and when no local transaction data update storage is performed;

[0112] The block is further configured to generate transaction data interpolation and upload it to a transaction data interpolation server when receiving first financial transaction data synchronized with other blocks and when no local transaction data update and storage is performed;

[0113] The transaction data interpolation is used to represent the blocks and corresponding transactions for which local transaction data update storage is not performed when receiving the first financial transaction data synchronized with other blocks;

[0114] S110: Operate the transaction data balancing server to receive a first balancing count sent by the block when a transaction occurs at the connected IoT transaction node, i.e., new first financial transaction data is generated, or when the block receives first financial transaction data synchronized with other blocks and performs local transaction data update and storage, and receive a second balancing count sent by the block when the block receives first financial transaction data synchronized with other blocks and does not perform local transaction data update and storage;

[0115] The transaction data balancing server is further configured to accumulate the first and second balancing counts received during a data update process of a single transaction to obtain a count accumulation value, and to analyze the differentiated update storage of block transaction data in the big data-based financial information system based on the count accumulation value;

[0116] The transaction data balancing server is further configured to receive the first financial transaction data uploaded by each block and perform local storage, and obtain the transaction ID of this transaction;

[0117] S112: Operate the transaction data interpolation server to separately store the transaction data interpolation uploaded by each block;

[0118] The transaction data interpolation server is also used to receive queries from users of the financial analysis system, and comprehensively, based on the data stored in the transaction data balancing server and the first corresponding relationship stored in the transaction relationship balancing server, normalize the financial analysis results and feed them back to users whose queries have different weights.

[0119] S114: Operate the cloud-based big data warehouse to receive query feedback from the transaction data interpolation server, and store the corresponding transaction data in the cloud-based big data warehouse for the system to perform big data analysis.

[0120] As an overlayable embodiment, the first financial transaction data corresponding to the transaction includes at least the identifiers of the two parties to the transaction, the transaction time and transaction amount of the transaction, and the transaction ID; the transaction data interpolation includes at least the corresponding block number and transaction ID.

[0121] As another superimposable embodiment, after each new transaction arrives, after the transaction ID of the previous transaction is processed, the system's transaction ID is updated, and the next big data-based financial information system processing is performed based on the new transaction ID.

[0122] As another superimposable embodiment, the first balancing count is a first unit count, and the second balancing count is the first unit count+1.

[0123] As another superimposable embodiment, there are multiple IoT transaction nodes connected to a single block.

[0124] The present invention proposes a financial information system based on big data and a corresponding method, establishes a big data warehouse in the cloud, realizes the system's data set storage and big data utilization and interaction through the big data warehouse, and realizes the comprehensive management of the financial information system. The financial information system claimed for protection by the present invention simultaneously uses a comprehensive management server to manage multiple secondary servers and transaction nodes and block nodes in the blockchain, and adopts a transaction data interpolation server to perform transaction data interpolation storage. By utilizing the block differential storage properties, combining the transaction data interpolation of the transaction data interpolation server and the count accumulation value of the transaction data balancing server, block-based decentralized storage and multi-server collaborative management and regular updating of cloud big data are realized, making dynamic financial information analysis based on big data possible.

[0125] In all the above embodiments, in order to achieve some special data transmission and read / write function requirements, the above method operation process and its corresponding device can add devices, modules, components, hardware, pin connections or memory, processor differences to expand functions.

[0126] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the methods, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0127] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the method steps is merely a logical or functional division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, which may be electrical, mechanical or other forms.

[0128] The units described as the various steps of the method and the separate components of the apparatus may or may not be logically or physically separate, and may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the objectives of this embodiment as needed.

[0129] In addition, the various method steps and their implementations, as well as the functional units in the various embodiments of the present invention, may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional units.

[0130] The above-mentioned methods and apparatuses can be implemented as integrated units in the form of software functional units, which can be stored in a computer-readable storage medium. The above-mentioned software functional units are stored in a storage medium and include instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) or a processor to perform some of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), NVRAM, a magnetic disk, or an optical disk.

[0131] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

[0132] It should be noted that the above embodiments are only used to more clearly explain and illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A financial information system based on big data, comprising: The integrated management server performs module stability analysis on the financial information system based on big data, determines a faulty module based on the module stability analysis, and performs module replacement; The cloud-based big data warehouse receives query feedback from the transaction data interpolation server and stores the corresponding transaction data in the cloud-based big data warehouse for use by the system in performing big data analysis; an Internet of Things transaction node, each of the plurality of Internet of Things transaction nodes being connected to a specific block, generating first financial transaction data corresponding to the transaction when a transaction occurs, and uploading the first financial transaction data to the connected block; The Internet of Things transaction node records the corresponding relationship with the connected block, stores it as a first corresponding relationship, and sends the first corresponding relationship to the transaction relationship balancing server of the big data-based financial information system; a transaction relationship balancing server, configured to store the first corresponding relationship and generate a first block transaction link table based on the first corresponding relationship; The first block transaction link table at least includes: a block column for storing a block number; an IoT transaction node column for storing an IoT transaction node having a first corresponding relationship with a block having a specific block number; and a mapping quantity column for storing the number of IoT transaction nodes having a first corresponding relationship with a block having a specific block number. a plurality of blocks, each block having a specific block number, each of the plurality of IoT transaction nodes being connected to a specific block, and the plurality of blocks receiving first financial transaction data uploaded by the connected IoT transaction node; When a transaction occurs on the connected IoT transaction node, that is, when new first financial transaction data is generated, the block synchronizes the generated first financial transaction data to each block of the blockchain and sends the new first financial transaction data to the transaction data balancing server; The block is further configured to send a first balance count to a transaction data balancing server when a transaction occurs at the connected IoT transaction node, i.e., when new first financial transaction data is generated, or when first financial transaction data synchronized with other blocks is received and local transaction data is updated and stored; The block is further configured to send a second balancing count to a transaction data balancing server when receiving first financial transaction data synchronized with other blocks and when no local transaction data update storage is performed; The block is further configured to generate transaction data interpolation and upload it to a transaction data interpolation server when receiving first financial transaction data synchronized with other blocks and when no local transaction data update and storage is performed; The transaction data interpolation is used to represent the blocks and corresponding transactions for which local transaction data update storage is not performed when receiving the first financial transaction data synchronized with other blocks; The transaction data balancing server is configured to receive a first balancing count sent by the block when a transaction occurs at a connected IoT transaction node, i.e., when new first financial transaction data is generated, or when the block receives first financial transaction data synchronized with other blocks and performs local transaction data update and storage, and receive a second balancing count sent by the block when the block receives first financial transaction data synchronized with other blocks and does not perform local transaction data update and storage; The transaction data balancing server is further configured to accumulate the first and second balancing counts received during a data update process of a single transaction to obtain an accumulated count value, and analyze the differentiated update storage of block transaction data in the big data-based financial information system based on the accumulated count value; The transaction data balancing server is further configured to receive the first financial transaction data uploaded by each block and perform local storage, and obtain the transaction ID of this transaction; A transaction data interpolation server, which is used to separately store the transaction data interpolation uploaded by each block; The transaction data interpolation server is also used to receive queries from users of the financial analysis system. Comprehensively, based on the data stored in the transaction data balancing server and the first corresponding relationship stored in the transaction relationship balancing server, the financial analysis results are normalized according to the weight settings of different users and fed back to users with different weights to enable users to perform queries.

2. A financial information system based on big data as claimed in claim 1, wherein: The first financial transaction data corresponding to the transaction at least includes the identifiers of the two parties to the transaction, the transaction time and amount of the transaction, and the transaction ID; the transaction data interpolation at least includes the corresponding block number and transaction ID.

3. A financial information system based on big data as claimed in claim 2, wherein: After each new transaction arrives, after the transaction ID of the previous transaction is processed, the system's transaction ID is updated, and the next big data-based financial information system processing is performed based on the new transaction ID.

4. The big data-based financial information system according to claim 1, characterized in that: The first balance count is a first unit count, and the second balance count is the first unit count+1.

5. The big data-based financial information system according to claim 4, characterized in that: There are multiple IoT transaction nodes connected to a single block.

6. A method for operating a financial information system based on big data, the method comprising the following steps: Step 1: operating the integrated management server to perform module stability analysis on the financial information system based on big data, and determining a faulty module based on the module stability analysis, and performing module replacement; Step 2: Operate each of the plurality of IoT transaction nodes to connect to a specific block, generate first financial transaction data corresponding to the transaction when a transaction occurs, and upload the first financial transaction data to the connected block; in, The Internet of Things transaction node records the corresponding relationship with the connected block, stores it as a first corresponding relationship, and sends the first corresponding relationship to the transaction relationship balancing server of the big data-based financial information system; Step 3: Operate the transaction relationship balancing server to store the first corresponding relationship, and generate a first block transaction link table based on the first corresponding relationship; The first block transaction link table at least includes: a block column for storing a block number; an IoT transaction node column for storing an IoT transaction node having a first corresponding relationship with a block having a specific block number; and a mapping quantity column for storing the number of IoT transaction nodes having a first corresponding relationship with a block having a specific block number. Step 4: operating each of the plurality of blocks, each of which has a specific block number, connecting each of the plurality of IoT transaction nodes to the specific block, and the plurality of blocks receiving the first financial transaction data uploaded by the connected IoT transaction node; When a transaction occurs on the connected IoT transaction node, that is, when new first financial transaction data is generated, the block synchronizes the generated first financial transaction data to each block of the blockchain and sends the new first financial transaction data to the transaction data balancing server; The block is further configured to send a first balance count to a transaction data balancing server when a transaction occurs at the connected IoT transaction node, i.e., when new first financial transaction data is generated, or when first financial transaction data synchronized with other blocks is received and local transaction data is updated and stored; The block is further configured to send a second balancing count to a transaction data balancing server when receiving first financial transaction data synchronized with other blocks and when no local transaction data update storage is performed; The block is further configured to generate transaction data interpolation and upload it to a transaction data interpolation server when receiving first financial transaction data synchronized with other blocks and when no local transaction data update and storage is performed; The transaction data interpolation is used to represent the blocks and corresponding transactions for which local transaction data update storage is not performed when receiving the first financial transaction data synchronized with other blocks; Step 5: Operate the transaction data balancing server to receive a first balancing count sent by the block when a transaction occurs at the connected IoT transaction node, i.e., when new first financial transaction data is generated, or when the block receives first financial transaction data synchronized with other blocks and performs local transaction data update and storage, and receive a second balancing count sent by the block when the block receives first financial transaction data synchronized with other blocks and does not perform local transaction data update and storage; The transaction data balancing server is further configured to accumulate the first and second balancing counts received during a data update process of a single transaction to obtain an accumulated count value, and analyze the differentiated update storage of block transaction data in the big data-based financial information system based on the accumulated count value; The transaction data balancing server is further configured to receive the first financial transaction data uploaded by each block and perform local storage, and obtain the transaction ID of this transaction; Step 6: Operate the transaction data interpolation server to separately store the transaction data interpolation uploaded by each block; The transaction data interpolation server is further configured to receive queries from users of the financial analysis system, and based on the data stored in the transaction data balancing server and the first corresponding relationship stored in the transaction relationship balancing server, normalize the financial analysis results according to the weights set for different users, and feed them back to users with different weights to enable the users to perform queries; Step 7: Operate the cloud-based big data warehouse to receive query feedback from the transaction data interpolation server, and store the corresponding transaction data in the cloud-based big data warehouse for the system to perform big data analysis.

7. The method for operating a financial information system based on big data as claimed in claim 6, wherein: The first financial transaction data corresponding to the transaction at least includes the identifiers of the two parties to the transaction, the transaction time and amount of the transaction, and the transaction ID; the transaction data interpolation at least includes the corresponding block number and transaction ID.

8. The method for operating a financial information system based on big data as claimed in claim 7, wherein: After each new transaction arrives, after the transaction ID of the previous transaction is processed, the system's transaction ID is updated, and the next big data-based financial information system processing is performed based on the new transaction ID.

9. The method for operating a financial information system based on big data according to claim 6, characterized in that: The first balance count is a first unit count, and the second balance count is the first unit count+1.

10. The method for operating a financial information system based on big data according to claim 9, characterized in that: There are multiple IoT transaction nodes connected to a single block.

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