Accounting data storage method and device, data reporting method and device and medium

Abstract

The invention discloses a responsibility judgment data storage method and device and a data reporting method and device, and the method comprises the steps: obtaining service data from at least two pieces of service equipment, and the service data of each piece of service equipment comprises an evidence chain identifier which is used for identifying an evidence chain of a target order; extracting the service data according to a preset responsibility judgment rule to obtain responsibility judgment data of the at least two service devices, the responsibility judgment data of each service device comprising the evidence chain identifier; and storing the responsibility judgment data. Therefore, the responsibility judgment data of the target order is diversified, systematic evidence storage of the responsibility judgment data of the target order is realized, and improvement of the responsibility judgment accuracy of a driver is facilitated.

Description

Technical Field

[0001] The present invention relates to the field of the freight industry, and particularly to a method for storing liability judgment data, a method for reporting data, a device, and a medium. Background Art

[0002] With the rapid development of the freight industry, in order to improve service quality and user experience, a freight platform needs to judge the liability of freight drivers, so as to impose corresponding penalties or rewards on the drivers. In this process, it involves the evidence storage and collection of specific driver behaviors, providing a basis for liability judgment for operation personnel or customer service personnel.

[0003] Currently, the freight platform stores liability judgment evidence, and the freight platform can judge the liability of the driver through the liability judgment evidence. However, the liability judgment evidence stored by the freight platform is relatively single. For example, the liability judgment evidence is the evidence collected under a certain specific service. As a result, the accuracy of driver liability judgment is relatively low. Summary of the Invention

[0004] Based on this, in view of the above technical problems, it is necessary to provide a method for storing liability judgment data, a method for reporting data, a device, and a medium to solve at least one of the above problems.

[0005] The present invention provides a method for storing liability judgment data, including:

[0006] Obtaining service data from at least two service devices, each service data including: an evidence chain identifier for identifying an evidence chain of a target order;

[0007] Extracting the service data according to a preset liability judgment rule to obtain liability judgment data of the at least two service devices, each liability judgment data of the service device including the evidence chain identifier;

[0008] Storing the liability judgment data.

[0009] Optionally, before extracting the service data according to the preset liability judgment rule to obtain the liability judgment data of the at least two service devices, the method further includes:

[0010] Checking the integrity and legality of the service data.

[0011] Optionally, the preset liability judgment rule includes data types to be excluded and data fields to be retained in the service data.

[0012] Optionally, before storing the liability judgment data, the method further includes:

[0013] Creating a target database for storing the liability judgment data;

[0014] Create at least one table structure according to the data type and data format of the liability judgment data;

[0015] The storing of the liability judgment data includes:

[0016] Store the liability judgment data into the target database according to the at least one table structure.

[0017] Optionally, synchronize the liability judgment data stored in the target database to a third-party database.

[0018] The present invention also provides a data reporting method, including:

[0019] Obtain service data;

[0020] Obtain an evidence chain identifier, which is used to identify the evidence chain of a target order;

[0021] Send service data to a liability judgment data storage device, where the service data is used for the liability judgment data storage device to extract liability judgment data, and the service data includes: the service data and the evidence chain identifier.

[0022] Optionally, the obtaining of the evidence chain identifier includes:

[0023] Generate the evidence chain identifier according to a service identifier, the creation time of the target order, and a random number.

[0024] Optionally, the obtaining of the evidence chain identifier includes:

[0025] Obtain an evidence chain identifier from a first service device, where the first service device provides a first service for the target order.

[0026] The present invention also provides a liability judgment storage device, including:

[0027] An obtaining module, configured to obtain service data from at least two service devices, and each service data includes: an evidence chain identifier, which is used to identify the evidence chain of a target order;

[0028] An extracting module, configured to extract the service data according to a preset liability judgment rule to obtain the liability judgment data of the at least two service devices, and the liability judgment data of each service device includes the evidence chain identifier;

[0029] A storing module, configured to store the liability judgment data.

[0030] The present invention also provides one or more readable storage media storing computer-readable instructions, and when the computer-readable instructions are executed by a processor, the method for storing liability judgment data as described above is implemented, or the method for data reporting as described above is implemented.

[0031] The present invention provides a computer device, including a memory, a processor, and computer-readable instructions stored on the memory and running on the processor. It is characterized in that when the processor executes the computer-readable instructions, the method for storing liability determination data as described above is implemented, or the method for reporting data as described above is implemented.

[0032] The present invention provides a method for storing liability determination data, a method for reporting data, a device, and a medium, including: obtaining service data from at least two service devices, each service data including: an evidence chain identifier, which is used to identify the evidence chain of a target order; extracting the service data according to a preset liability determination rule to obtain the liability determination data of the at least two service devices, and the liability determination data of each service device includes the evidence chain identifier; storing the liability determination data. By obtaining service data from multiple service devices and extracting the liability determination data from the service data of multiple service devices according to a preset liability determination rule, and each liability determination data includes the evidence chain identifier of the target order. Therefore, the liability determination data of the target order is diversified, and systematic evidence storage of the liability determination data of the target order is realized, which is beneficial to improving the accuracy of driver liability determination. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments of the present invention. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0034] Figure 1 is one of the schematic flowcharts of the method for storing liability determination data in an embodiment of the present invention;

[0035] Figure 2 is the second schematic flowchart of the method for storing liability determination data in an embodiment of the present invention;

[0036] Figure 3 is the third schematic flowchart of the method for storing liability determination data in an embodiment of the present invention;

[0037] Figure 4 is a schematic diagram of at least one time period included in the life cycle of a target order in an embodiment of the present invention;

[0038] Figure 5 is the fourth schematic flowchart of the method for storing liability determination data in an embodiment of the present invention;

[0039] Figure 6 is one of the schematic flowcharts of the method for reporting data in an embodiment of the present invention;

[0040] Figure 7 It is a schematic diagram of threads corresponding to multiple services in an embodiment of the present invention;

[0041] Figure 8 It is the second schematic diagram of the process of the data reporting method in an embodiment of the present invention;

[0042] Figure 9 It is the third schematic diagram of the process of the data reporting method in an embodiment of the present invention;

[0043] Figure 10 It is the fourth schematic diagram of the process of the data reporting method in an embodiment of the present invention;

[0044] Figure 11 It is a schematic structural diagram of a liability judgment data storage device in an embodiment of the present invention;

[0045] Figure 12 It is a schematic structural diagram of a data reporting device in an embodiment of the present invention;

[0046] Figure 13 It is a schematic diagram of a computer device in an embodiment of the present invention. Detailed implementation manners

[0047] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0048] In one embodiment, as Figure 1 shown, Figure 1 It is the first schematic diagram of the process of the liability judgment data storage method in an embodiment of the present invention. The embodiment of the present invention provides a liability judgment data storage method, which specifically includes the following steps:

[0049] S101. Obtain service data from at least two service devices.

[0050] The service data of each service device is the service data generated when the service device provides corresponding services for the target order. The service data of each service device includes: an evidence chain identifier, which is used to identify the evidence chain of the target order. For example, Service Device A provides the service of creating an order for the target order. That is, Service Device A reports the service data related to creating the target order to the liability judgment data storage device. The service data includes the order number of the target order, the creation time of the target order, and the evidence chain identifier of the target order. Service Device B provides the service of voice call for the target order. That is, Service Device B reports the service data related to the voice call of the target order to the liability judgment data storage device. The service data includes: an evidence chain identifier and voice call information.

[0051] It should be noted that the service device can report the service data of the target order to the liability judgment data storage device through a distributed stream processing platform. The distributed stream processing platform can be Apache Kafka, or other distributed stream processing platforms. This application does not limit this. For example, the service device can use Apache Kafka to report the service data of the target order to the liability judgment data storage device. The liability judgment data storage device can configure Kafka to ensure that it can read the service data reported by each service device in order. For example, the liability judgment data storage device configures the maximum number of messages to pull and the timing of adjusting the commit offset. To save the bandwidth required when the service device reports service data, the service device first compresses the service data to be reported to obtain the compressed service data. This method effectively improves the transmission efficiency of service data. The service device can use Snappy compression, or other compression methods. This application does not limit this. It should be noted that Snappy is a toolkit for compression or decompression.

[0052] It should be noted that the service device can report data through a software development kit (SDK). The SDK is provided by the liability judgment data storage device and deployed in the company's internal code repository. For example, developers build a data reporting SDK and publish it to the company's internal Maven repository. Each business system development team introduces the data reporting SDK package in the build file of its project and configures it according to the interface document provided by the data reporting SDK. The data reporting SDK package is integrated on each service device, and the service data is reported to the liability judgment data storage device through the data reporting SDK package

[0053] S102. Extract the liability judgment data of at least two service devices according to a preset liability judgment rule.

[0054] The liability judgment data of at least two service devices is used to judge the liability of the driver responsible for the target order. The liability judgment data of each service device includes an evidence chain identifier. It should be noted that the service data of these at least two service devices may not all be used to judge the liability of the driver. Therefore, the liability judgment data storage device needs to extract the service data of these at least two service devices according to the preset liability judgment rules to retain the liability judgment data of these at least two service devices. When extracting, the liability judgment data storage device needs to perform data integrity check and data legality check on the service data of at least two service devices. For example, the service data of each service device must carry the identifier of the service provided by the service device for the target order and the evidence chain identifier. If the service data reported by a certain service device lacks the evidence chain identifier, it means that the service data is illegal. Another example is that for a specific service, such as the order creation service, if the service data corresponding to the order creation service does not carry the order number, it means that the service data is incomplete. For illegal service data or incomplete service data, the liability judgment data storage device can discard the service data. The preset liability judgment rules are set by the liability judgment data storage device according to the order liability judgment experience of the operation personnel. In addition, if the liability judgment data storage device receives compressed service data, the liability judgment data storage device needs to first perform a decompression operation on the service data and then perform the operation of extracting the liability judgment data.

[0055] S103. Store the liability judgment data.

[0056] The liability judgment data storage device stores the liability judgment data of at least two service devices into the local database. The database can be MySQL or other types of databases. MySQL is the name of a database. The present application does not limit this. The liability judgment data storage device uses the (java database connectivity, JDBC) connection technology to batch insert the liability judgment data into the MySQL database to ensure the persistent storage of the liability judgment data.

[0057] Refer to Figure 2 , Figure 2 is the second flow diagram of the liability judgment data storage method in an embodiment of the present invention; in an embodiment of the present invention, before S102, the method further includes:

[0058] S201. Check the integrity and legality of the service data.

[0059] In an embodiment of the present invention, the preset liability judgment rules include extraction rules corresponding to each of at least two service devices, and the extraction rules corresponding to each service device include: data types to be excluded and data fields to be retained in the service data.

[0060] It should be noted that each service device provides at least one service for a target order. Each service corresponds to an extraction rule. Each extraction rule is a data cleaning rule script written by a developer according to business requirements. This script defines the data fields to be excluded and the data fields to be retained. For example, for the a service data reported by the A service device, the a service data includes: order number field, creation time field, and order price field. The liability judgment data storage device can, through the data cleaning rule script of the service corresponding to the a service data, exclude the order price field in the a service data and only retain the order number field and the creation time field. The liability judgment data storage device can also exclude redundant log information and temporary cache data in the reported service data through preset liability judgment rules.

[0061] Refer to Figure 3 , Figure 3 is the third schematic diagram of the process of the liability judgment data storage method in an embodiment of the present invention; in an embodiment of the present invention, when storing the liability judgment data, the liability judgment data storage method further includes:

[0062] S301. Create a target database.

[0063] The target database is used to store the liability judgment data of at least two service devices. The liability judgment data storage device can create a target database on a MySQL database server.

[0064] S302. Create at least one table structure according to the data type and data format of the liability judgment data.

[0065] It should be noted that refer to Figure 4 , Figure 4 is the schematic diagram of the evidence chain of the target order in an embodiment of the present invention; the liability judgment data storage device needs to collect the liability judgment data corresponding to the target order at different time periods. As Figure 4 shown, the life cycle of this target order includes five time periods, namely the time period from the start of the order to the order placement, the time period from the order placement to the order acceptance, the time period from the order acceptance to before transportation, the time period from before transportation to during transportation, and the time period from during transportation to the bill. Each time period corresponds to a table structure. The table structure of each time period is used to indicate the data type and data format of the liability judgment data corresponding to that time period. For example, in the time period from during transportation to the bill, the A service device provides liability judgment data for the target order: A1: "111", A2: 22, A3: "aaa"; the B service device provides liability judgment data for the target order: B1: 22, B2: "22", B3: 23. Thus, as shown in Table 1, the table structure corresponding to the time period from during transportation to the bill includes at least the fields in Table 1. The data type of each field is defined in Table 1.

[0066] Table 1

[0067]

[0068]

[0069] It should be noted that the table structure for each time period includes an evidence chain identifier and a service identifier. The service identifier is used to identify the service of the service device. The liability judgment data corresponding to each time period is associated through the evidence chain identifier to form the complete evidence chain data of the target order. Optionally, the liability judgment data corresponding to each time period can be provided by at least one service device. Each service device can provide at least one service. Each service provides service data for the target order. For example, as can be seen from Table 1 above, the liability judgment data corresponding to the time period from in transit to billing includes the liability judgment data of Service Device A and the liability judgment data of Service Device B.

[0070] In one embodiment, storing the liability judgment data includes:

[0071] Storing the liability judgment data into the target database according to at least one table structure.

[0072] It should be noted that the liability judgment data storage device stores the liability judgment data corresponding to each time period into the target database according to the table structure of each time period. For example, the table structure corresponding to the time period from in transit to billing is Table 1. The liability judgment data storage device stores the liability judgment data of Service Device A and the liability judgment data of Service Device B into the target database according to the data types of each field defined in Table 1. For example, the liability judgment data of Service Device A stored in the target database includes: A1: "111", A2: 22, A3: "aaa". The liability judgment data of Service Device B stored in the target database includes: B1: 22, B2: "22", B3: 23.

[0073] It should be noted that the liability judgment data storage adopts a transaction processing mechanism during the process of storing the liability judgment data to ensure data consistency and integrity. If an error occurs during the storage process, for example, when a connection failure occurs or a data insertion fails, the target database rolls back the inserted data transaction and records the error information in the log file. At the same time, the liability judgment data storage notifies relevant personnel for processing through an alarm mechanism. For example, the liability judgment data storage can notify relevant personnel by email or text message.

[0074] In an embodiment of the present invention, the liability judgment data storage device may query a target database according to the evidence chain identifier of the obtained liability judgment data to obtain the existing liability judgment data. Then, the liability judgment data storage device may associate and integrate the existing liability judgment data with the newly obtained liability judgment data to obtain the complete evidence chain data of the target order, and store it in the memory of the liability judgment data storage device. Optionally, the liability judgment data storage device may use a linked list or a tree-like data structure to store the complete evidence chain data of the target order.

[0075] Refer to Figure 5 , Figure 5 FIG. 4 is a schematic flowchart of a liability judgment data storage method in an embodiment of the present invention; in an embodiment of the present invention, the liability judgment data storage method further includes:

[0076] S501. Synchronize the liability judgment data stored in the target database to a third-party database.

[0077] It should be noted that when the amount of stored liability judgment data is large, the liability judgment data storage device cannot meet the high-concurrency query requirements of users. Therefore, the liability judgment data storage device will regularly synchronize the stored liability judgment data to a third-party database. For example, the target database is a MySQL database, and the third-party database is a Hive big data warehouse. Specifically, due to the high performance of the Hive big data warehouse, the liability judgment data storage device can use the LOAD DATA statement or other data import tools of the Hive big data warehouse to import the liability judgment data from the MySQL database in the liability judgment data storage device into the Hive big data warehouse.

[0078] Optionally, in the Hive big data warehouse, business personnel perform data analysis using computing engines such as MapReduce or Spark structured query language (SQL) according to pre-defined business metric calculation logics, generating corresponding business metric data and business intelligence (BI) chart data. For example, first, business personnel set up the environment of the Hive big data warehouse and configure the data synchronization connection between the Hive big data warehouse and the MySQL database. Then, business personnel write a script for liability determination data synchronization to synchronize the liability determination data in the MySQL database to the Hive big data warehouse regularly (e.g., every day at midnight). Next, business personnel define different business metric calculation logics according to business requirements. Business personnel obtain corresponding source data from a third-party database (the Hive big data warehouse) according to this business metric calculation logic and calculate the obtained source data to get the corresponding business metrics. For example, the business metric can be the number of violation behaviors of a driver within a specific time period or the average processing duration of business orders. Business personnel can use the built-in functions and SQL query statements of the Hive big data warehouse to obtain source data from the Hive big data warehouse and analyze this source data. Business personnel export the analysis results into a data format that can be used to generate BI charts. For example, the data format of a CSV file. Business personnel can also directly obtain data from the Hive big data warehouse through visualization tools and display it. For example, front-end developers use a popular front-end framework to design the corresponding page layout and components according to the requirements of the driver dimension. The front-end framework can be the Vue framework or the React framework. Developers obtain data through the RESTful API provided by the back-end service and use the data binding function of the front-end framework to dynamically display the data on the page. Then, back-end developers use back-end development frameworks such as SpringBoot to build the back-end service of the interface display module. That is, back-end developers develop application programming interfaces (APIs) that interact with the data processing module and the database. Common API interfaces include an interface for obtaining the complete evidence chain data of a driver according to the driver ID and an interface for filtering business data according to user query conditions. The back-end service connects to the MySQL database through connection pool technology, executes query operations according to business requirements, and returns the results to the front-end in JSON format. At the same time, the back-end service is also responsible for integrating the BI chart data generated by the data analysis module and passing the reference address or data content of this BI chart data to the front-end page for display on the corresponding page. Finally, users access the front-end page of the interface display module through a browser. When the front-end page is loaded, the front-end service sends a request to the back-end service to obtain the corresponding data.For example, when the driver dimension page is loaded, the front-end service sends the driver ID to the back-end service. The back-end service queries the complete evidence chain data of the driver from the Hive big data warehouse or the local MySQL database based on the driver ID and returns the result to the front-end service. The complete evidence chain data includes driving behavior data, order data, and violation record data. The front-end service uses a data rendering component to display the data on the page.

[0079] In addition, users can perform interactive operations on the interface, such as clicking to view detailed information, filtering data, and exporting data. When the user clicks to view detailed information, the front-end service sends a request to the back-end service. The back-end service queries more detailed evidence data from the database based on the request parameters and returns it to the front-end service for pop-up display or page jump display. When the user performs a data filtering operation, the front-end service passes the filtering conditions to the back-end service. The back-end service queries the database according to the filtering conditions and returns the filtered result to the front-end service for page update display. When the user clicks the export data button, the back-end service queries the corresponding data from the database according to the user's permissions and data scope, converts the queried data into a file in a format such as Excel or Portable Document Format (PDF), and provides it for the user to download through the browser download function.

[0080] The present invention provides a liability judgment data storage method, including: obtaining service data from at least two service devices, where the service data of each service device includes: an evidence chain identifier for identifying an evidence chain of a target order; extracting the service data according to a preset liability judgment rule to obtain liability judgment data of the at least two service devices, where the liability judgment data of each service device includes the evidence chain identifier; and storing the liability judgment data. By obtaining service data from multiple service devices and extracting liability judgment data from the service data of multiple service devices according to a preset liability judgment rule, and each liability judgment data includes an evidence chain identifier of a target order. Therefore, the liability judgment data of the target order is diversified, and systematic evidence storage of the liability judgment data of the target order is realized, which is beneficial to improving the accuracy of driver liability judgment.

[0081] Refer to Figure 6 , Figure 6 is one of the schematic flowcharts of the data reporting method in an embodiment of the present invention; an embodiment of the present invention provides a data reporting method, which specifically includes the following steps:

[0082] S601. Obtain service data.

[0083] The service data is the service data generated when the first service device provides corresponding services for the target order. In the complete order process of the target order, the service device needs to report the service data at the key nodes of the order. For example, the order key nodes include: the order creation completion node, the driver receiving the order node, the driver canceling the order node, and / or the voice passing node. Of course, there are other key nodes, and this application does not limit them. For example, when the order is created and completed, the service device needs to first obtain service data such as the order number and order time, and then report the service data to the liability judgment data storage device through the SDK.

[0084] It should be noted that the service data may include the system log link trace ID and the service ID. The system log link trace ID is used to track the log data related to the target order. When performing operation and maintenance, the operation and maintenance personnel can view the log data related to the target order according to the system log link trace ID.

[0085] Refer to Figure 7 , Figure 7 is a schematic diagram of one of the threads corresponding to multiple services in an embodiment of the present invention. In each service device, each thread corresponds to an evidence chain information. That is, within one service device, each thread binds to one order, and there are no two threads binding to the same order at the same time. Therefore, by binding the thread to the evidence chain identifier, it is beneficial to isolate the corresponding evidence chain information.

[0086] S602. Obtain the evidence chain identifier;

[0087] The evidence chain identifier is used to identify the evidence chain of the target order.

[0088] S603. Send the service data to the liability judgment data storage device.

[0089] It should be noted that the service data is used for the liability judgment data storage device to extract the liability judgment data, and the service data includes: the service data and the evidence chain identifier. Through the evidence chain identifier, the liability judgment data storage device can associate the service data reported from at least one service device.

[0090] Refer to Figure 8 , Figure 8 is the second schematic diagram of the process of the data reporting method in an embodiment of the present invention; in an embodiment of the present invention, step S602 is further refined, including:

[0091] S801. Generate the evidence chain identifier according to the service identifier, the creation time of the target order, and the random number.

[0092] It should be noted that the service device determines the generation rule of the evidence chain identifier according to the initialization setting requirements of the SDK. The service device generates the evidence chain identifier based on the creation time of the target order, the business system identifier, and the random number.

[0093] Refer to Figure 9 , Figure 9 which is the second schematic flowchart of the data reporting method in an embodiment of the present invention; in an embodiment of the present invention, step S602 is further refined, including:

[0094] S901. Obtain the evidence chain identifier from the first service device.

[0095] It should be noted that the first service device provides the first service for the target order, and the second service device provides the second service for the target order. The first service and the second service are two consecutive services and the second service is before the first service. For example, the target order requires three service devices to provide service data. These three service devices include the A service device, the B service device, and the C service device. The A service device provides service 1, the B service device provides service 2, and the C service device provides service 3. The arrangement order of service 1, service 2, and service 3 is: service 2 - service 1 - service 3. The above-mentioned first service is service 1 and the second service is service 2. Therefore, the A service device can obtain the evidence chain identifier from the B service device. Then, the A service device sends the evidence chain identifier and service data to the liability determination data storage device. It should be noted that the arrangement order relationship between multiple services corresponding to the target order can be pre-configured. Further, the order of provision between different services determines the sorting order relationship between different services. For example, the service for creating the target order must be ranked after the language call service of the target order.

[0096] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The order of execution of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0097] In an embodiment, a liability determination data storage device is provided, and this liability determination data storage device corresponds one-to-one with the liability determination data storage method in the above embodiment. As Figure 11 shown Figure 11 is a schematic structural diagram of a liability determination data storage device in an embodiment of the present invention. The liability determination data storage device includes:

[0098] An acquisition module 1101, configured to acquire service data from at least two service devices, and each service data includes: an evidence chain identifier, where the evidence chain identifier is used to identify the evidence chain of the target order;

[0099] An extraction module 1102, configured to extract the service data according to a preset liability determination rule to obtain the liability determination data of the at least two service devices, and the liability determination data of each service device includes the evidence chain identifier;

[0100] A storage module 1103 for storing the liability judgment data.

[0101] Optionally, the liability judgment data storage device further includes:

[0102] An inspection module 1104 for inspecting the integrity and legality of the service data;

[0103] Optionally, the preset liability judgment rules include the data types to be excluded and the data fields to be retained in the service data.

[0104] The obtaining module 1101 is specifically configured to:

[0105] Create a target database for storing the liability judgment data;

[0106] Create at least one table structure according to the data type and data format of the liability judgment data;

[0107] Store the liability judgment data into the target database according to the at least one table structure.

[0108] Optionally, the liability judgment data storage device further includes:

[0109] A synchronization module 1105 for synchronizing the liability judgment data stored in the target database to a third-party database.

[0110] For the specific limitations of the liability judgment data storage device, reference can be made to the limitations on the liability judgment data storage method in the foregoing text, which will not be elaborated here. Each module in the above liability judgment data storage device can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above modules.

[0111] In one embodiment, a data reporting device is provided, and the data reporting device corresponds one-to-one to the data reporting method in the above embodiment. As Figure 12 shown, Figure 12 is a schematic structural diagram of a data reporting device in an embodiment of the present invention. The data reporting device includes:

[0112] An obtaining module 1201 for obtaining service data and an evidence chain identifier, where the evidence chain identifier is used to identify the evidence chain of the target order;

[0113] A sending module 1202 for sending service data to the liability judgment data storage device, where the service data is used for the liability judgment data storage device to extract liability judgment data, and the service data includes: the service data and the evidence chain identifier.

[0114] Optionally, the obtaining module 1201 is specifically configured to: generate the evidence chain identifier according to the service identifier, the creation time of the target order, and a random number.

[0115] Optionally, the obtaining module 1201 is specifically configured to: obtain the evidence chain identifier from a first service device that provides a first service for the target order.

[0116] For the specific definition of the data reporting device, reference may be made to the definition of the data reporting method in the foregoing text, which will not be elaborated herein. Each module in the foregoing data reporting device may be implemented in whole or in part by software, hardware, and their combination. The foregoing modules may be embedded in or independent of a processor in a computer device in the form of hardware, or stored in a memory in the computer device in the form of software, so as to facilitate the processor to call and execute the operations corresponding to the foregoing modules.

[0117] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as Figure 13 shown. Figure 13 FIG. is a schematic diagram of a computer device in an embodiment of the present invention. The computer device includes a processor, a memory, a network interface, and a database connected through a device bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a readable storage medium and an internal memory. The readable storage medium stores an operating device, computer-readable instructions, and a database. The internal memory provides an environment for the operation of the operating device and computer-readable instructions in the readable storage medium. The database of the computer device is used to store data involved in the liability determination data storage method. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer-readable instructions are executed by the processor, the liability determination data storage method or the data reporting method described above is implemented. The readable storage medium provided in this embodiment includes a non-volatile readable storage medium and a volatile readable storage medium.

[0118] In one embodiment, a computer device is provided. The computer device may be a terminal device, and its internal structure diagram may be as Figure 13 shown. The computer device includes a processor, a memory, and a network interface connected through a device bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a readable storage medium. The readable storage medium stores computer-readable instructions. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer-readable instructions are executed by the processor, the liability determination data storage method or the data reporting method described above is implemented. The readable storage medium provided in this embodiment includes a non-volatile readable storage medium and a volatile readable storage medium.

[0119] In one embodiment, a computer device is provided, including a memory, a processor, and computer-readable instructions stored in the memory and executable on the processor. When the processor executes the computer-readable instructions, the steps of the above-mentioned liability determination data storage method or the steps of the above-mentioned data reporting method are implemented.

[0120] In one embodiment, a readable storage medium is provided. The readable storage medium stores computer-readable instructions. When the computer-readable instructions are executed by a processor, the method steps of the above-mentioned charging platform device docking with a third-party platform are implemented. Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing relevant hardware through computer-readable instructions. The computer-readable instructions can be stored in a non-volatile readable storage medium or a volatile readable storage medium. When the computer-readable instructions are executed, they can include the processes of the above-mentioned method embodiments. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in this application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0121] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above-mentioned division of each functional unit and module is used for illustration. In actual applications, the above-mentioned functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above.

[0122] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for storing judgment data, characterized in that: include: Acquire service data from at least two service devices, each service data including: an evidence chain identifier, the evidence chain identifier being used to identify an evidence chain for a target order; Extracting the service data according to a preset accountability rule to obtain accountability data of the at least two service devices, wherein the accountability data of each service device includes the evidence chain identifier; The determination data is stored.

2. The method according to claim 1, characterized in that: Before extracting the service data according to the preset accountability rule to obtain the accountability data of the at least two service devices, the method further includes: Check the integrity and legitimacy of the service data.

3. The method according to claim 1 or 2, characterized in that: The preset judgment rules include data types to be removed and data fields to be retained in the service data.

4. The method according to claim 1 or 2, characterized in that: Before storing the judgment data, the method further comprises: Creating a target database, wherein the target database is used to store the judgment data; Create at least one table structure according to the data type and data format of the judgment data; The storing of the judgment data comprises: The judgment data is stored in the target database according to the at least one table structure.

5. The method according to claim 4, characterized in that: The method further comprises: The judgment data stored in the target database is synchronized to a third-party database.

6. A data reporting method, characterized in that: The method comprises: Get business data; Obtaining an evidence chain identifier, where the evidence chain identifier is used to identify the evidence chain of the target order; Sending service data to a judgment data storage device, the service data is used by the judgment data storage device to extract the judgment data, the service data including: the business data and the evidence chain identifier.

7. The method according to claim 6, characterized in that: The obtaining of the evidence chain identifier includes: The evidence chain identifier is generated according to the service identifier, the creation time of the target order and a random number.

8. The method according to claim 6, characterized in that: The obtaining of the evidence chain identifier includes: An evidence chain identifier is obtained from a first service device, where the first service device provides a first service for the target order.

9. A judgment storage device, characterized in that: include: An acquisition module, used to acquire service data from at least two service devices, each service data includes: an evidence chain identifier, the evidence chain identifier is used to identify the evidence chain of the target order; An extraction module, configured to extract the service data according to a preset accountability rule to obtain accountability data of the at least two service devices, wherein the accountability data of each service device includes the evidence chain identifier; A storage module is used to store the judgment data.

10. A readable storage medium having computer readable instructions stored thereon, characterized in that: The computer readable instructions are executed by a processor to implement the method according to any one of claims 1 to 5 or 6 to 7.

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