Financial business data processing method, device, electronic equipment and storage medium

Abstract

The present invention relates to the field of big data technology, and provides a data processing method, device, electronic device and storage medium for financial services, the method comprising: collecting real-time account information corresponding to the financial services to be processed; using a preset routing decision module to route the fund transaction data table of each account from the real-time account information; identifying the fund type of each fund in the fund transaction data table of each account; dividing the fund transaction data table corresponding to at least one account according to the fund type to obtain multiple sub-account data tables; executing the data processing task in the data processing request, extracting data from multiple sub-account data tables, and obtaining data processing results. The present invention can process the same type of fund data in the same sub-account data table without processing other sub-account data tables, thereby improving data processing efficiency.

Description

Technical Field

[0001] The present invention relates to the field of big data technology, and in particular to a data processing method, device, electronic device and storage medium for financial services. Background Art

[0002] With the continuous expansion of financial business, fund types continue to increase. The existing technology stores all fund type data in a financial account summary table, and summarizes the end-of-day share data of each account in the financial account summary table.

[0003] However, in the process of summarizing the daily end-of-day share data, it is necessary to process the daily data of each account to obtain the daily end-of-day share data. Since the data in the financial account summary table is large and complex, the processing process is slow, causing delays in the feedback of data processing results, resulting in low data processing efficiency.

[0004] Therefore, it is necessary to propose a method that can process data quickly and accurately. Summary of the invention

[0005] In view of the above, it is necessary to propose a data processing method, device, electronic device and storage medium for financial business, which can process the same type of fund data in the same sub-account data table without processing other sub-account data tables, thereby improving data processing efficiency.

[0006] A first aspect of the present invention provides a method for processing financial business data, the method comprising:

[0007] Parsing the received data processing request, collecting real-time account information corresponding to the financial business to be processed, wherein the real-time account information includes at least one account;

[0008] Using a preset routing decision module to route out a fund transaction data table of each account from the real-time account information;

[0009] Identify the fund type of each fund in the fund transaction data table of each account, wherein the fund transaction data table of each account contains at least one fund;

[0010] Dividing the fund transaction data table corresponding to the at least one account according to the fund type to obtain a plurality of sub-account data tables;

[0011] Execute the data processing task in the data processing request, extract data from the multiple sub-account data tables, and obtain data processing results.

[0012] Optionally, the using a preset routing decision module to route the fund transaction data table of each account from the real-time account information includes:

[0013] Obtaining preset multiple dimensions and fund transaction storage templates corresponding to the financial business to be processed;

[0014] Identify a routing node corresponding to each dimension of each account in the real-time account information;

[0015] Based on the routing nodes corresponding to each dimension of each account, a preset routing decision module is used to route the dimension information corresponding to each dimension from the real-time account information;

[0016] The multiple dimensional information corresponding to the multiple dimensions of each account is mapped to the corresponding fund transaction storage template to obtain a fund transaction data table for each account.

[0017] Optionally, the identifying the fund type of each fund in the fund transaction data table of each account includes:

[0018] Extract the fund code of each fund from the fund transaction data table of each account;

[0019] The fund type of each fund is determined based on the fund code of each fund.

[0020] Optionally, dividing the fund transaction data table corresponding to the at least one account according to the fund type to obtain a plurality of sub-account data tables includes:

[0021] For each fund transaction data table of each account, the fund transaction data of the same type of funds are recorded in the same sub-data table using a preset grouping aggregation function according to the fund type, and each sub-data table is bound to the corresponding user account;

[0022] According to the fund type, multiple sub-data tables bound to the user account are classified to obtain multiple sub-account data tables, wherein each sub-account data table contains multiple sub-data tables of the same type of funds.

[0023] Optionally, the multiple sub-data tables bound to the user accounts are classified according to the fund type to obtain multiple sub-account data tables including:

[0024] Multiple sub-data tables of the same type of funds are merged according to the preset table-merging rules to obtain the corresponding sub-account data table for each fund type.

[0025] Optionally, executing the data processing task in the data processing request, extracting data from the multiple sub-account data tables, and obtaining the data processing results includes:

[0026] Analyze the data processing task and obtain data processing conditions;

[0027] Convert the data processing conditions into database query statements according to preset conversion rules;

[0028] Execute the database query statement, traverse the multiple sub-account data tables, and obtain data processing results.

[0029] Optionally, parsing the received data processing request and collecting real-time account information corresponding to the financial business to be processed includes:

[0030] Parsing the message of the data processing request to obtain the message information carried by the message;

[0031] Obtaining a block identification code of the blockchain from the message information;

[0032] Acquire a preset application layer interface according to the block identification code of the blockchain;

[0033] Obtaining the encryption key of the financial service device node to be processed according to the application layer interface;

[0034] The encryption key is used to encrypt the real-time data collected from the financial service device to be processed using an encryption algorithm, and the encrypted real-time data is output through the application layer interface to obtain the real-time account information corresponding to the financial service to be processed.

[0035] A second aspect of the present invention provides a data processing device for financial services, the device comprising:

[0036] A parsing and collecting module, used to parse the received data processing request and collect real-time account information corresponding to the financial business to be processed, wherein the real-time account information includes at least one account;

[0037] A routing module, used to route the fund transaction data table of each account from the real-time account information using a preset routing decision module;

[0038] an identification module, used to identify the fund type of each fund in the fund transaction data table of each account, wherein the fund transaction data table of each account contains at least one fund;

[0039] a division module, configured to divide the fund transaction data table corresponding to the at least one account according to the fund type to obtain a plurality of sub-account data tables;

[0040] The extraction module is used to execute the data processing task in the data processing request, extract data from the multiple sub-account data tables, and obtain data processing results.

[0041] A third aspect of the present invention provides an electronic device, comprising a processor and a memory, wherein the processor is configured to implement the data processing method for financial services when executing a computer program stored in the memory.

[0042] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, and the computer program, when executed by a processor, implements the data processing method for financial services.

[0043] In summary, the data processing method, device, electronic device and storage medium of the financial business described in the present invention use a preset routing decision module to route the fund transaction data table of each account from the real-time account information, which is convenient for the subsequent unified management of the fund transaction data table of each account, and improves the management efficiency of fund transaction data. Identify the fund type of each fund in the fund transaction data table of each account, divide the corresponding fund transaction data table of the at least one account according to the fund type, obtain multiple sub-account data tables, determine the same type of fund as a sub-account data table, and process the same type of fund data in the same sub-account data table during subsequent data processing, without processing other sub-account data tables, thereby improving data processing efficiency. Execute the data processing task in the data processing request, and directly extract the data processing results from the multiple sub-account data tables, thereby improving the timeliness of obtaining the data processing results. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a flow chart of a data processing method for financial services provided in Embodiment 1 of the present invention.

[0045] Figure 2 It is a structural diagram of a data processing device for financial services provided in Embodiment 2 of the present invention.

[0046] Figure 3 It is a schematic diagram of the structure of an electronic device provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0047] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict.

[0048] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0049] Embodiment 1

[0050] Figure 1 It is a flow chart of a data processing method for financial services provided in Embodiment 1 of the present invention.

[0051] In this embodiment, the financial business data processing method can be applied to electronic devices. For electronic devices that need to perform financial business data processing, the financial business data processing function provided by the method of the present invention can be directly integrated into the electronic device, or run in the electronic device in the form of a software development kit (SDK).

[0052] like Figure 1 As shown, the data processing method for financial services specifically includes the following steps. According to different requirements, the order of the steps in the flowchart can be changed, and some can be omitted.

[0053] S11, parsing the received data processing request, and collecting real-time account information corresponding to the financial business to be processed, wherein the real-time account information includes at least one account.

[0054] In this embodiment, for the financial field, when performing data processing of financial business, a data processing request is initiated to the server through the client. Specifically, the client can be a smart phone, IPAD or other existing smart devices, and the server can be a data processing subsystem. During the data processing process, the client can send a data processing request to the data processing subsystem.

[0055] In this embodiment, when the data processing request subsystem receives a data processing request, it parses the data processing request and obtains real-time account information of the financial business to be processed, wherein the real-time account information includes user information, transaction flow information, transaction time, transaction amount, fund code, fund type and other account-related information, wherein the real-time account information includes at least one account.

[0056] In an optional embodiment, parsing the received data processing request and collecting real-time account information corresponding to the financial business to be processed includes:

[0057] Parsing the message of the data processing request to obtain the message information carried by the message;

[0058] Obtaining a block identification code of the blockchain from the message information;

[0059] Acquire a preset application layer interface according to the block identification code of the blockchain;

[0060] Obtaining the encryption key of the financial service device node to be processed according to the application layer interface;

[0061] The encryption key is used to encrypt the real-time data collected from the financial service device to be processed using an encryption algorithm, and the encrypted real-time data is output through the application layer interface to obtain the real-time account information corresponding to the financial service to be processed.

[0062] In this embodiment, the block identification code of the blockchain is used to uniquely identify the identity information of the block in the blockchain. Specifically, the identity information refers to identifying the application layer interface in the block.

[0063] In this embodiment, different pending financial services correspond to different pending service device nodes, and an application layer interface is pre-set for each pending service device node, wherein the application layer interface is set in a block of the blockchain, and the encryption key of the corresponding pending financial service device node is stored in the application layer interface. The blockchain does not rely on a third party and transmits real-time account information through its own distributed nodes, which can prevent the leakage of real-time account information and thereby improve the security of real-time account information.

[0064] In this embodiment, when real-time account information is collected, the real-time data collected by the financial business equipment to be processed is encrypted, and the real-time data is output through the application layer interface pre-set in the blockchain block to obtain real-time account information, thereby improving the security of the real-time account information.

[0065] S12, using a preset routing decision module to route out a fund transaction data table of each account from the real-time account information.

[0066] In this embodiment, the fund transaction data table includes account information of each account. For example, account A includes user information, business information, time information and other account-related information.

[0067] In an optional embodiment, the method of routing the fund transaction data table of each account from the real-time account information using a preset routing decision module includes:

[0068] Obtaining preset multiple dimensions and fund transaction storage templates corresponding to the financial business to be processed;

[0069] Identify a routing node corresponding to each dimension of each account in the real-time account information;

[0070] Based on the routing nodes corresponding to each dimension of each account, a preset routing decision module is used to route the dimension information corresponding to each dimension from the real-time account information;

[0071] The multiple dimensional information corresponding to the multiple dimensions of each account is mapped to the corresponding fund transaction storage template to obtain a fund transaction data table for each account.

[0072] In this embodiment, since the data processing logic in the account information corresponding to different financial services is different, multiple dimensions and fund transaction data storage templates can be pre-set for each financial service based on historical data, which facilitates the subsequent unified management of the fund transaction data table of each account and improves the management efficiency of fund transaction data.

[0073] Specifically, the preset multiple dimensions may include a user dimension, a fund dimension and a time dimension, wherein the user dimension includes user information such as user account, user basic information, user attributes, etc., and the user attributes refer to the account level of the user account and the risk preference for purchasing funds. For example, risk preferences include conservative, stable, balanced, active and aggressive; the fund dimension includes fund information such as fund number and fund type, and the time dimension includes time information such as fund purchase time and account risk assessment time.

[0074] In this embodiment, the fund transaction data table includes account information of each account, for example, user information, type of fund purchased, time of fund purchase, amount of fund purchase, and other account information.

[0075] S13, identifying the fund type of each fund in the fund transaction data table of each account, wherein the fund transaction data table of each account contains at least one fund.

[0076] In this embodiment, each account contains at least one fund, wherein each fund corresponds to a fund type. Specifically, the fund type includes multiple types. For example, the fund type can be divided into open-end funds and closed-end funds according to the fund units; it can be divided into growth funds, income funds and balanced funds according to the investment risks and returns; it can also be divided into four categories of bond funds, stock funds, money market funds and mixed funds according to the investment objects. This embodiment does not make any restrictions here.

[0077] In an optional embodiment, the identifying the fund type of each fund in the fund transaction data table of each account includes:

[0078] Extract the fund code of each fund from the fund transaction data table of each account;

[0079] The fund type of each fund is determined based on the fund code of each fund.

[0080] In this embodiment, the fund code is used to uniquely identify the fund type.

[0081] S14, dividing the fund transaction data table corresponding to the at least one account according to the fund type to obtain a plurality of sub-account data tables.

[0082] In an optional embodiment, the dividing the fund transaction data table corresponding to the at least one account according to the fund type to obtain a plurality of sub-account data tables includes:

[0083] For each fund transaction data table of each account, the fund transaction data of the same type of funds are recorded in the same sub-data table using a preset grouping aggregation function according to the fund type, and each sub-data table is bound to the corresponding user account;

[0084] According to the fund type, multiple sub-data tables bound to the user account are classified to obtain multiple sub-account data tables, wherein each sub-account data table contains multiple sub-data tables of the same type of funds.

[0085] In this embodiment, a grouping aggregation function may be preset, and the grouping aggregation function may be an aggregation function or a grouping SELECT.

[0086] Furthermore, the multiple sub-data tables bound to the user accounts are classified according to the fund type to obtain multiple sub-account data tables including:

[0087] Multiple sub-data tables of the same type of funds are merged according to the preset table-merging rules to obtain the corresponding sub-account data table for each fund type.

[0088] Specifically, the preset table entry rule can be to table entry according to users, for example, all funds of the same user are sorted in sequence and table entry; it can also be to table entry according to the chronological order of purchase time of multiple funds of the same type; it can also be to table entry according to the frequency of use of funds of the same type of funds, for example, funds of the same type of funds are sorted in descending order according to the frequency of use of each fund, and the funds are tabled in the corresponding sub-account data table in sequence according to the descending sorting results.

[0089] In this embodiment, since the grouping aggregation function can group the real-time account information corresponding to the same type of funds in each fund transaction data table of each account, and aggregate the real-time account information corresponding to each fund in the real-time account information corresponding to the same type of funds, it is ensured that only one data is recorded for each fund of each fund type in each account, thereby reducing the amount of data in each sub-data table, and further reducing the amount of data in each sub-account data table. When performing subsequent data processing of financial services, the data in each sub-account data table is taken into account, thereby improving data processing efficiency.

[0090] In other optional embodiments, the method further includes:

[0091] Identify the fund code of each fund in the fund transaction data table of each account;

[0092] The fund transaction data table corresponding to the at least one account is divided according to the fund code to obtain a sub-account data table for each fund.

[0093] In this embodiment, for the current business in the financial field, due to the needs of the business model, a large part of the income of the fund business is reflected in the asset size of the user. In order to provide users with more and better asset allocation, the business often needs to connect to multiple funds and manage the asset data of tens of millions of users at the same time. For the needs of user experience and capital loss prevention and control, the end-of-day share file of each fund is calculated every day. Due to the large number of fund types, the huge amount of data, and the large number of user asset account movement operations, it takes a long time to calculate the end-of-day share file of each fund every day, which cannot meet the timeliness requirements. At the same time, the massive data reading and writing operations also bring huge pressure to the database.

[0094] In this embodiment, by dividing the corresponding fund transaction data table of the at least one account, the same type of funds are determined as a sub-account data table or each fund is individually determined as a sub-account data table. When the data processing task is subsequently executed, there is no need to perform data processing, and the data processing results are directly extracted from the multiple sub-account data tables, which solves the problem that the timeliness requirements cannot be met in the prior art and improves the timeliness of obtaining data processing results.

[0095] In this embodiment, the same fund is separately identified as a sub-account data table. When a new fund type or account information corresponding to a new fund is received, only a new sub-account data table needs to be recreated without processing the original sub-account data table. This realizes the horizontal expansion of the fund account, reduces the amount of data in the existing financial account master table, adopts the idea of ​​multiple processing of a small amount of data, improves the overall efficiency of inserting new fund account information, and thus improves data processing efficiency.

[0096] S15, executing the data processing task in the data processing request, extracting data from the multiple sub-account data tables, and obtaining data processing results.

[0097] In this embodiment, the data in the sub-account data table is result data. When executing a data processing task, data is extracted from the multiple sub-account data tables according to the data processing conditions in the data processing task, without the need for processing, thereby improving data processing efficiency.

[0098] In an optional embodiment, executing the data processing task in the data processing request, extracting data from the multiple sub-account data tables, and obtaining the data processing results includes:

[0099] Analyze the data processing task and obtain data processing conditions;

[0100] Convert the data processing conditions into database query statements according to preset conversion rules;

[0101] Execute the database query statement, traverse the multiple sub-account data tables, and obtain data processing results.

[0102] Exemplarily, the data processing conditions in the processing task are: extracting the current share of the M fund of the target account, converting the extracted current share of the M fund of the target account into a database query statement, wherein the database query statement can be an SQL query statement: querying the data corresponding to the fund code of the M fund, executing the SQL query statement, traversing the multiple sub-account data tables, querying the data corresponding to the fund code of the M fund, and extracting to obtain the data processing result.

[0103] In this embodiment, since the data in each sub-account data table are real-time account information classified based on the fund type field, when a data processing request is subsequently received, data is extracted from multiple sub-account data tables corresponding to the target account according to the data processing conditions to obtain the data processing result corresponding to the target account. The data processing result is the cumulative result of the real-time account information. At the same time, the data processing result does not need to be calculated separately, instead of the prior art that generates the user's final share data by aggregating the user's daily transaction records, thereby improving the timeliness of the data processing results.

[0104] In summary, the data processing method for financial services described in this embodiment routes the fund transaction data table of each account from the real-time account information by using a preset routing decision module, which facilitates the subsequent unified management of the fund transaction data table of each account and improves the management efficiency of fund transaction data. The fund type of each fund in the fund transaction data table of each account is identified, and the corresponding fund transaction data table of the at least one account is divided according to the fund type to obtain multiple sub-account data tables, and the same type of fund is determined as a sub-account data table. When the data is subsequently processed, the same type of fund data is processed in the same sub-account data table, and there is no need to process other sub-account data tables, thereby improving the data processing efficiency. The data processing task in the data processing request is executed, and the data processing results are directly extracted from the multiple sub-account data tables, thereby improving the timeliness of obtaining the data processing results.

[0105] Embodiment 2

[0106] Figure 2 It is a structural diagram of a data processing device for financial services provided in Embodiment 2 of the present invention.

[0107] In some embodiments, the financial service data processing device 20 may include a plurality of functional modules composed of program code segments. The program code of each program segment in the financial service data processing device 20 may be stored in the memory of the electronic device and executed by the at least one processor to execute (see Figure 1 Description) The function of data processing for financial business.

[0108] In this embodiment, the data processing device 20 for financial services can be divided into multiple functional modules according to the functions it performs. The functional modules may include: a parsing and acquisition module 201, a routing module 202, an identification module 203, a division module 204, and an extraction module 205. The module referred to in the present invention refers to a series of computer-readable instruction segments that can be executed by at least one processor and can complete fixed functions, which are stored in a memory. In this embodiment, the functions of each module will be described in detail in subsequent embodiments.

[0109] The parsing and collecting module 201 is used to parse the received data processing request and collect the real-time account information corresponding to the financial business to be processed, wherein the real-time account information includes at least one account.

[0110] In this embodiment, for the financial field, when performing data processing of financial business, a data processing request is initiated to the server through the client. Specifically, the client can be a smart phone, IPAD or other existing smart devices, and the server can be a data processing subsystem. During the data processing process, the client can send a data processing request to the data processing subsystem.

[0111] In this embodiment, when the data processing request subsystem receives a data processing request, it parses the data processing request and obtains real-time account information of the financial business to be processed, wherein the real-time account information includes user information, transaction flow information, transaction time, transaction amount, fund code, fund type and other account-related information, wherein the real-time account information includes at least one account.

[0112] In an optional embodiment, the parsing and collecting module 201 parses the received data processing request and collects the real-time account information corresponding to the financial business to be processed, including:

[0113] Parsing the message of the data processing request to obtain the message information carried by the message;

[0114] Obtaining a block identification code of the blockchain from the message information;

[0115] Acquire a preset application layer interface according to the block identification code of the blockchain;

[0116] Obtaining the encryption key of the financial service device node to be processed according to the application layer interface;

[0117] The encryption key is used to encrypt the real-time data collected from the financial service device to be processed using an encryption algorithm, and the encrypted real-time data is output through the application layer interface to obtain the real-time account information corresponding to the financial service to be processed.

[0118] In this embodiment, the block identification code of the blockchain is used to uniquely identify the identity information of the block in the blockchain. Specifically, the identity information refers to identifying the application layer interface in the block.

[0119] In this embodiment, different pending financial services correspond to different pending service device nodes, and an application layer interface is pre-set for each pending service device node, wherein the application layer interface is set in a block of the blockchain, and the encryption key of the corresponding pending financial service device node is stored in the application layer interface. The blockchain does not rely on a third party and transmits real-time account information through its own distributed nodes, which can prevent the leakage of real-time account information and thereby improve the security of real-time account information.

[0120] In this embodiment, when real-time account information is collected, the real-time data collected by the financial business equipment to be processed is encrypted, and the real-time data is output through the application layer interface pre-set in the blockchain block to obtain real-time account information, thereby improving the security of the real-time account information.

[0121] The routing module 202 is used to route the fund transaction data table of each account from the real-time account information using a preset routing decision module.

[0122] In this embodiment, the fund transaction data table includes account information of each account. For example, account A includes user information, business information, time information and other account-related information.

[0123] In an optional embodiment, the routing module 202 uses a preset routing decision module to route the fund transaction data table of each account from the real-time account information, including:

[0124] Obtaining preset multiple dimensions and fund transaction storage templates corresponding to the financial business to be processed;

[0125] Identify a routing node corresponding to each dimension of each account in the real-time account information;

[0126] Based on the routing nodes corresponding to each dimension of each account, a preset routing decision module is used to route the dimension information corresponding to each dimension from the real-time account information;

[0127] The multiple dimensional information corresponding to the multiple dimensions of each account is mapped to the corresponding fund transaction storage template to obtain a fund transaction data table for each account.

[0128] In this embodiment, since the data processing logic in the account information corresponding to different financial services is different, multiple dimensions and fund transaction data storage templates can be pre-set for each financial service based on historical data, which facilitates the subsequent unified management of the fund transaction data table of each account and improves the management efficiency of fund transaction data.

[0129] Specifically, the preset multiple dimensions may include a user dimension, a fund dimension and a time dimension, wherein the user dimension includes user information such as user account, user basic information, user attributes, etc., and the user attributes refer to the account level of the user account and the risk preference for purchasing funds. For example, risk preferences include conservative, stable, balanced, active and aggressive; the fund dimension includes fund information such as fund number and fund type, and the time dimension includes time information such as fund purchase time and account risk assessment time.

[0130] In this embodiment, the fund transaction data table includes account information of each account, for example, user information, type of fund purchased, time of fund purchase, amount of fund purchase, and other account information.

[0131] The identification module 203 is used to identify the fund type of each fund in the fund transaction data table of each account, wherein the fund transaction data table of each account contains at least one fund.

[0132] In this embodiment, each account contains at least one fund, wherein each fund corresponds to a fund type. Specifically, the fund type includes multiple types. For example, the fund type can be divided into open-end funds and closed-end funds according to the fund units; it can be divided into growth funds, income funds and balanced funds according to the investment risks and returns; it can also be divided into four categories of bond funds, stock funds, money market funds and mixed funds according to the investment objects. This embodiment does not make any restrictions here.

[0133] In an optional embodiment, the identification module 203 identifies the fund type of each fund in the fund transaction data table of each account including:

[0134] Extract the fund code of each fund from the fund transaction data table of each account;

[0135] The fund type of each fund is determined based on the fund code of each fund.

[0136] In this embodiment, the fund code is used to uniquely identify the fund type.

[0137] The division module 204 is used to divide the fund transaction data table corresponding to the at least one account according to the fund type to obtain multiple sub-account data tables.

[0138] In an optional embodiment, the division module 204 divides the fund transaction data table corresponding to the at least one account according to the fund type, and obtains multiple sub-account data tables including:

[0139] For each fund transaction data table of each account, the fund transaction data of the same type of funds are recorded in the same sub-data table using a preset grouping aggregation function according to the fund type, and each sub-data table is bound to the corresponding user account;

[0140] According to the fund type, multiple sub-data tables bound to the user account are classified to obtain multiple sub-account data tables, wherein each sub-account data table contains multiple sub-data tables of the same type of funds.

[0141] In this embodiment, a grouping aggregation function may be preset, and the grouping aggregation function may be an aggregation function or a grouping SELECT.

[0142] Furthermore, the multiple sub-data tables bound to the user accounts are classified according to the fund type to obtain multiple sub-account data tables including:

[0143] Multiple sub-data tables of the same type of funds are merged according to the preset table-merging rules to obtain the corresponding sub-account data table for each fund type.

[0144] Specifically, the preset table entry rule can be to table entry according to users, for example, all funds of the same user are sorted in sequence and table entry; it can also be to table entry according to the chronological order of purchase time of multiple funds of the same type; it can also be to table entry according to the frequency of use of funds of the same type of funds, for example, funds of the same type of funds are sorted in descending order according to the frequency of use of each fund, and the funds are tabled in the corresponding sub-account data table in sequence according to the descending sorting results.

[0145] In this embodiment, since the grouping aggregation function can group the real-time account information corresponding to the same type of funds in each fund transaction data table of each account, and aggregate the real-time account information corresponding to each fund in the real-time account information corresponding to the same type of funds, it is ensured that only one data is recorded for each fund of each fund type in each account, thereby reducing the amount of data in each sub-data table, and further reducing the amount of data in each sub-account data table. When performing subsequent data processing of financial services, the data in each sub-account data table is taken into account, thereby improving data processing efficiency.

[0146] In other optional embodiments, the fund code of each fund in the fund transaction data table of each account is identified; the corresponding fund transaction data table of the at least one account is divided according to the fund code to obtain a sub-account data table for each fund.

[0147] In this embodiment, for the current business in the financial field, due to the needs of the business model, a large part of the income of the fund business is reflected in the asset size of the user. In order to provide users with more and better asset allocation, the business often needs to connect to multiple funds and manage the asset data of tens of millions of users at the same time. For the needs of user experience and capital loss prevention and control, the end-of-day share file of each fund is calculated every day. Due to the large number of fund types, the huge amount of data, and the large number of user asset account movement operations, it takes a long time to calculate the end-of-day share file of each fund every day, which cannot meet the timeliness requirements. At the same time, the massive data reading and writing operations also bring huge pressure to the database.

[0148] In this embodiment, by dividing the corresponding fund transaction data table of the at least one account, the same type of funds are determined as a sub-account data table or each fund is individually determined as a sub-account data table. When the data processing task is subsequently executed, there is no need to perform data processing, and the data processing results are directly extracted from the multiple sub-account data tables, which solves the problem that the timeliness requirements cannot be met in the prior art and improves the timeliness of obtaining data processing results.

[0149] In this embodiment, the same fund is separately identified as a sub-account data table. When a new fund type or account information corresponding to a new fund is received, only a new sub-account data table needs to be recreated without processing the original sub-account data table. This realizes the horizontal expansion of the fund account, reduces the amount of data in the existing financial account master table, adopts the idea of ​​multiple processing of a small amount of data, improves the overall efficiency of inserting new fund account information, and thus improves data processing efficiency.

[0150] The extraction module 205 is used to execute the data processing task in the data processing request, extract data from the multiple sub-account data tables, and obtain data processing results.

[0151] In this embodiment, the data in the sub-account data table is result data. When executing a data processing task, data is extracted from the multiple sub-account data tables according to the data processing conditions in the data processing task, without the need for processing, thereby improving data processing efficiency.

[0152] In an optional embodiment, the extraction module 205 executes the data processing task in the data processing request, extracts data from the multiple sub-account data tables, and obtains data processing results including:

[0153] Analyze the data processing task and obtain data processing conditions;

[0154] Convert the data processing conditions into database query statements according to preset conversion rules;

[0155] Execute the database query statement, traverse the multiple sub-account data tables, and obtain data processing results.

[0156] Exemplarily, the data processing conditions in the processing task are: extracting the current share of the M fund of the target account, converting the extracted current share of the M fund of the target account into a database query statement, wherein the database query statement can be an SQL query statement: querying the data corresponding to the fund code of the M fund, executing the SQL query statement, traversing the multiple sub-account data tables, querying the data corresponding to the fund code of the M fund, and extracting to obtain the data processing result.

[0157] In this embodiment, since the data in each sub-account data table are real-time account information classified based on the fund type field, when a data processing request is subsequently received, data is extracted from multiple sub-account data tables corresponding to the target account according to the data processing conditions to obtain the data processing result corresponding to the target account. The data processing result is the cumulative result of the real-time account information. At the same time, the data processing result does not need to be calculated separately, instead of the prior art that generates the user's final share data by aggregating the user's daily transaction records, thereby improving the timeliness of the data processing results.

[0158] In summary, the data processing device for financial services described in this embodiment routes the fund transaction data table of each account from the real-time account information by using a preset routing decision module, which facilitates the subsequent unified management of the fund transaction data table of each account and improves the management efficiency of fund transaction data. The fund type of each fund in the fund transaction data table of each account is identified, and the corresponding fund transaction data table of the at least one account is divided according to the fund type to obtain multiple sub-account data tables, and the same type of fund is determined as a sub-account data table. When the data is subsequently processed, the same type of fund data is processed in the same sub-account data table, and there is no need to process other sub-account data tables, thereby improving the data processing efficiency. The data processing task in the data processing request is executed, and the data processing results are directly extracted from the multiple sub-account data tables, thereby improving the timeliness of obtaining the data processing results.

[0159] Embodiment 3

[0160] See also Figure 3 FIG. 2 is a schematic diagram of the structure of an electronic device provided in Embodiment 3 of the present invention. In a preferred embodiment of the present invention, the electronic device 3 includes a memory 31 , at least one processor 32 , at least one communication bus 33 and a transceiver 34 .

[0161] Those skilled in the art should understand that Figure 3 The structure of the electronic device shown does not constitute a limitation of the embodiments of the present invention, and may be a bus structure or a star structure. The electronic device 3 may also include more or less other hardware or software than shown in the figure, or a different component arrangement.

[0162] In some embodiments, the electronic device 3 is an electronic device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application-specific integrated circuits, programmable gate arrays, digital processors, and embedded devices. The electronic device 3 may also include client devices, which include but are not limited to any electronic product that can interact with a client through a keyboard, mouse, remote control, touchpad, or voice-controlled device, such as a personal computer, tablet computer, smart phone, digital camera, etc.

[0163] It should be noted that the electronic device 3 is only an example, and other existing or future electronic products that are suitable for the present invention should also be included in the protection scope of the present invention and included here by reference.

[0164] In some embodiments, the memory 31 is used to store program codes and various data, such as the data processing device 20 of financial services installed in the electronic device 3, and to achieve high-speed and automatic access to programs or data during the operation of the electronic device 3. The memory 31 includes a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable programmable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0165] In some embodiments, the at least one processor 32 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips, etc. The at least one processor 32 is the control core (Control Unit) of the electronic device 3, and uses various interfaces and lines to connect various components of the entire electronic device 3, and executes various functions and processes data of the electronic device 3 by running or executing programs or modules stored in the memory 31, and calling data stored in the memory 31.

[0166] In some embodiments, the at least one communication bus 33 is configured to implement connection and communication between the memory 31 and the at least one processor 32, etc.

[0167] Although not shown, the electronic device 3 may also include a power source (such as a battery) for supplying power to each component. Optionally, the power source may be logically connected to the at least one processor 32 through a power management device, so that the power management device can manage charging, discharging, and power consumption management. The power source may also include one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 3 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0168] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0169] The above-mentioned integrated unit implemented in the form of a software function module can be stored in a computer-readable storage medium. The above-mentioned software function module is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, electronic device, or network device, etc.) or a processor to execute a part of the method described in each embodiment of the present invention.

[0170] In a further embodiment, in combination Figure 2 The at least one processor 32 can execute the operating device of the electronic device 3 and various installed application programs (such as the data processing device 20 for financial services), program codes, etc., for example, the above-mentioned modules.

[0171] The memory 31 stores program codes, and the at least one processor 32 can call the program codes stored in the memory 31 to execute related functions. For example, Figure 2 The modules described are program codes stored in the memory 31 and are executed by the at least one processor 32, thereby realizing the functions of the modules to achieve the purpose of data processing of financial services.

[0172] Exemplarily, the program code may be divided into one or more modules / units, which are stored in the memory 31 and executed by the processor 32 to complete the present application. The one or more modules / units may be a series of computer-readable instruction segments capable of completing specific functions, which are used to describe the execution process of the program code in the electronic device 3. For example, the program code may be divided into a parsing and acquisition module 201, a routing module 202, an identification module 203, a division module 204, and an extraction module 205.

[0173] In one embodiment of the present invention, the memory 31 stores a plurality of computer-readable instructions, and the plurality of computer-readable instructions are executed by the at least one processor 32 to implement the function of data processing of financial services.

[0174] Specifically, the specific implementation method of the at least one processor 32 for the above instructions can refer to Figure 1 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0175] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0176] Furthermore, the computer-readable storage medium may be non-volatile or volatile.

[0177] Furthermore, the computer-readable storage medium may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function, etc.; the data storage area may store data created according to the use of the blockchain node, etc.

[0178] The blockchain referred to in this application is a new application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, encryption algorithm, etc. Blockchain is essentially a decentralized database, a string of data blocks generated by cryptographic methods. Each data block contains a batch of network transaction information, which is used to verify the validity of its information (anti-counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, platform product service layer, and application service layer.

[0179] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0180] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0181] It is obvious to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential features of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the present invention is defined by the appended claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any figure mark in the claims should not be regarded as limiting the claims involved. In addition, it is obvious that the word "including" does not exclude other units or, and the singular does not exclude the plural. The multiple units or devices stated in the present invention can also be implemented by one unit or device through software or hardware. The words first, second, etc. are used to indicate names, and do not indicate any particular order.

[0182] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A data processing method for financial services, characterized in that: The method comprises: Parsing the received data processing request and collecting real-time account information corresponding to the financial business to be processed, including: parsing the message of the data processing request to obtain the message information carried by the message; obtaining the block identification code of the blockchain from the message information; obtaining a preset application layer interface according to the block identification code of the blockchain; obtaining the encryption key of the device node of the financial business to be processed according to the application layer interface; using the encryption key, encrypting the real-time data collected from the financial business device to be processed using an encryption algorithm, and outputting the encrypted real-time data through the application layer interface to obtain the real-time account information corresponding to the financial business to be processed, wherein the real-time account information includes at least one account, the application layer interface is set in the block of the blockchain, and the encryption key of the corresponding device node of the financial business to be processed is stored in the application layer interface; The method uses a preset routing decision module to route out a fund transaction data table of each account from the real-time account information, including: obtaining preset multiple dimensions and a fund transaction storage template corresponding to the financial business to be processed; identifying a routing node corresponding to each dimension of each account in the real-time account information; based on the routing node corresponding to each dimension of each account, using a preset routing decision module to route out dimension information corresponding to each dimension from the real-time account information; mapping the multiple dimension information corresponding to the multiple dimensions of each account to the corresponding fund transaction storage template to obtain a fund transaction data table for each account; Identify the fund type of each fund in the fund transaction data table of each account, wherein the fund transaction data table of each account contains at least one fund; The fund transaction data table corresponding to the at least one account is divided according to the fund type to obtain a plurality of sub-account data tables, including: for each fund transaction data table of each account, the fund transaction data corresponding to each fund in the fund transaction data of the same type of funds is aggregated and calculated using a preset grouping aggregation function according to the fund type to obtain result data, and the result data is recorded in the same sub-data table, and each sub-data table is bound to a corresponding user account; the plurality of sub-data tables bound to the user account are classified according to the fund type to obtain a plurality of sub-account data tables, wherein each sub-account data table contains a plurality of sub-data tables of the same type of funds, and the data in each of the sub-account data tables is the result data; Execute the data processing task in the data processing request, extract data from the multiple sub-account data tables, and obtain data processing results.

2. The data processing method for financial services according to claim 1, characterized in that: The fund type of each fund in the fund transaction data table identifying each account includes: Extract the fund code of each fund from the fund transaction data table of each account; The fund type of each fund is determined based on the fund code of each fund.

3. The data processing method for financial services according to claim 2, characterized in that: The multiple sub-data tables bound to the user accounts are classified according to the fund type to obtain multiple sub-account data tables including: Multiple sub-data tables of the same type of funds are merged according to the preset table-merging rules to obtain the corresponding sub-account data table for each fund type.

4. The data processing method for financial services according to claim 1, characterized in that: The executing the data processing task in the data processing request, extracting data from the multiple sub-account data tables, and obtaining the data processing results comprises: Analyze the data processing task and obtain data processing conditions; Convert the data processing conditions into database query statements according to preset conversion rules; Execute the database query statement, traverse the multiple sub-account data tables, and obtain data processing results.

5. A data processing device for financial services, characterized in that: The device is used to implement the data processing method for financial services according to any one of claims 1 to 4, and the device includes: A parsing and collecting module, used to parse the received data processing request and collect real-time account information corresponding to the financial business to be processed, wherein the real-time account information includes at least one account; A routing module, used to route the fund transaction data table of each account from the real-time account information using a preset routing decision module; an identification module, used to identify the fund type of each fund in the fund transaction data table of each account, wherein the fund transaction data table of each account contains at least one fund; a division module, configured to divide the fund transaction data table corresponding to the at least one account according to the fund type to obtain a plurality of sub-account data tables; The extraction module is used to execute the data processing task in the data processing request, extract data from the multiple sub-account data tables, and obtain data processing results.

6. An electronic device, characterized in that: The electronic device includes a processor and a memory, and the processor is used to implement the data processing method for financial services as described in any one of claims 1 to 4 when executing the computer program stored in the memory.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the data processing method for financial services as described in any one of claims 1 to 4 is implemented.

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