Points file processing method, device, equipment, medium and program product

Abstract

The present disclosure provides a points file processing method, including: obtaining points files of M channels among N channels, the N channels include channels for handling services for users, the points files include user data generated in response to the services handled by the users; based on a preset configuration file, processing the points file of each of the M channels, each of the channels corresponds to at least one of the configuration files, the configuration files include processing logic for the user data; obtaining the user points according to the processing results corresponding to each of the channels, the processing results are obtained by executing the processing logic on the user data in the points file. The present disclosure also provides a points file processing apparatus, device, storage medium and program product.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing, and more specifically to a point file processing method, device, equipment, medium and program product. Background Art

[0002] Some companies can accumulate points based on user data, allowing users to use the accumulated points as a redemption carrier to redeem rights and interests, thereby achieving the purpose of giving back to users and enhancing user stickiness. In the process of calculating user points, user data may involve different points activities, and points activities may involve different points calculation rules. Therefore, user data is usually matched with corresponding points calculation conditions to calculate user points, where the points calculation conditions include the processing logic of user data.

[0003] In related technologies, the processing logic of user data may be directly embedded in the program, for example, the relevant variables are directly replaced with fixed calculation rules in the source code of the program, which cannot be changed at will. However, the points activities of various companies are diverse and the business scenarios are numerous, resulting in complex and diverse user data content and formats. The user data processing logic is also dynamic and complex due to changes or interrelationships in points activities and business scenarios. Therefore, how to dynamically and scalably configure the processing logic and efficiently process complex user data in multiple business scenarios is a problem that needs to be solved urgently. Summary of the invention

[0004] In view of the above problems, the present disclosure provides an integral file processing method, apparatus, device, medium and program product that can dynamically and scalably configure processing logic through abstraction, centralization and configuration.

[0005] One aspect of an embodiment of the present disclosure provides a points file processing method, comprising: obtaining points files of M channels out of N channels, wherein the N channels include a channel for handling business for a user, the points file includes user data generated in response to the business handled by the user, N and M are integers greater than or equal to 1, respectively, and M is less than or equal to N; based on a preset configuration file, processing the points file of each channel out of the M channels, wherein each channel corresponds to at least one of the configuration files, and the configuration files include processing logic for the user data; obtaining the user points according to the processing results corresponding to each channel, wherein the processing results are obtained by executing the processing logic on the user data in the points file.

[0006] According to an embodiment of the present disclosure, the configuration file includes a parsing configuration file, the processing logic includes a parsing logic, and the processing of the points file of each of the M channels based on the preset configuration file includes: determining the corresponding parsing configuration file based on the channel identifier of each channel; executing the parsing logic in the parsing configuration file to parse the points file of each channel, wherein the parsing logic is used to convert the user data into user data in a predetermined format.

[0007] According to an embodiment of the present disclosure, the parsing configuration file includes X parsing units, and the execution of the parsing logic in the parsing configuration file and parsing the points file of each channel includes executing the X parsing units, which specifically includes: determining X first target fields from the user data, wherein X is an integer greater than or equal to 1; mapping the values ​​of the X first target fields to X columns in a first database table, wherein the mapped X columns include the user data in the predetermined format, and the X parsing units include X types of parsing logic corresponding to the X columns.

[0008] According to an embodiment of the present disclosure, the method further includes: executing a preset storage process to merge at least two of the first database tables having an association relationship into a second database table, wherein the association relationship is determined by a relationship between channels in the N channels.

[0009] According to an embodiment of the present disclosure, the configuration file includes a process configuration file, the processing logic includes process logic, and the processing of the points file of each of the M channels based on the preset configuration file also includes: determining the corresponding process configuration file based on the channel identifier of each channel; executing the process logic in the process configuration file to process the parsed points file of each channel, wherein the process logic is used to process the user data in the predetermined format to obtain a processing result.

[0010] According to an embodiment of the present disclosure, the process configuration file includes Y process unit sets, and the execution of the process logic in the process configuration file and the processing of the parsed points file of each channel include: based on the preset order of the Y process unit sets, executing each process unit set in the Y process unit sets in sequence, wherein each process unit set corresponds to each processing flow for obtaining the processing result; wherein each process unit set includes Z process units, each process unit in the Z process units corresponds to each sub-processing flow in each processing flow, and each process unit includes at least one of the process logics, and Y and Z are integers greater than or equal to 1 respectively.

[0011] According to an embodiment of the present disclosure, obtaining the user points according to the processing results corresponding to each channel includes: determining a second target field from the parsed points file of each channel; querying the corresponding configuration conditions based on the second target field, wherein the configuration conditions are used to determine the calculation conditions for obtaining the user points; and obtaining the user points according to the configuration conditions and the processing results.

[0012] According to an embodiment of the present disclosure, before querying the corresponding configuration condition based on the second target field, it also includes presetting the configuration condition, specifically including: presetting at least one parameter identifier in the third database table; and presetting at least one scenario field corresponding to each parameter identifier in the at least one parameter identifier in the fourth database table.

[0013] According to an embodiment of the present disclosure, the configuration condition corresponding to the query based on the second target field includes: determining a target parameter identifier based on the at least one parameter identifier in the third database table; determining at least one scenario field corresponding to the target parameter identifier from the fourth database table; matching the second target field with the at least one scenario field to obtain a matching result; and determining the corresponding configuration condition based on the matching result.

[0014] According to an embodiment of the present disclosure, it also includes: assigning N channel identifiers to the N channels; setting a file storage path corresponding to each channel identifier, and a points file identifier; wherein obtaining the points files of M channels out of the N channels includes: scanning the file storage path corresponding to each channel identifier to obtain at least one storage file; based on the points file identifier, determining the points file from the at least one storage file.

[0015] Another aspect of an embodiment of the present disclosure provides a points file processing device, including: a file acquisition module, used to acquire points files of M channels out of N channels, wherein the N channels include a channel for handling business for users, and the points file includes user data generated in response to the business handled by the user, and N and M are integers greater than or equal to 1 respectively; a file processing module, used to process the points file of each channel out of the M channels based on a preset configuration file, wherein each channel corresponds to at least one of the configuration files, and the configuration file includes processing logic for the user data; a points acquisition module, used to obtain the user points according to the processing results corresponding to each channel, wherein the processing results are obtained by executing the processing logic on the user data in the points file.

[0016] Another aspect of an embodiment of the present disclosure provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the method as described above.

[0017] Another aspect of the embodiments of the present disclosure further provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the method as described above.

[0018] Another aspect of the embodiments of the present disclosure further provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0019] One or more of the above embodiments have the following beneficial effects: first, the steps or objects to be processed are abstracted according to the characteristics of each of the N channels to form a processing logic adapted to each channel. Then, the configuration files of the N channels are centrally managed in a centralized manner, so that each channel corresponds to at least one configuration file. In the form of configuration files, a configurable design of the processing logic adapted to the N channels is implemented. Thus, by operating the configuration files, dynamic changes and scalable effects of the processing logic can be achieved, such as being able to execute the processing logic in the corresponding configuration file for the points files of M channels to process the user data in the points files. Finally, the user points are obtained based on the processing results. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The above contents and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0021] Figure 1 The following schematically shows an architecture diagram of a user points processing system according to an embodiment of the present disclosure;

[0022] Figure 2 A flowchart of a points file processing method according to an embodiment of the present disclosure is schematically shown;

[0023] Figure 3 Schematically shows a flow chart of processing a points file according to an embodiment of the present disclosure;

[0024] Figure 4 Schematically shows a flow chart of parsing a score file according to an embodiment of the present disclosure;

[0025] Figure 5 Schematically shows a flowchart of processing a points file according to another embodiment of the present disclosure;

[0026] Figure 6A flowchart of obtaining user points according to an embodiment of the present disclosure is schematically shown;

[0027] Figure 7 A flowchart schematically shows the configuration conditions preset according to an embodiment of the present disclosure;

[0028] Figure 8 A flowchart schematically shows a query configuration condition according to an embodiment of the present disclosure;

[0029] Fig. 9 A flowchart of obtaining a points file according to an embodiment of the present disclosure is schematically shown;

[0030] Fig.10 The structure block diagram of the points file processing device according to the embodiment of the present disclosure is schematically shown;

[0031] Fig.11 A block diagram of an electronic device suitable for implementing a points file processing method according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0032] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0033] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0034] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0035] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0036] The relevant terms involved in the embodiments of the present disclosure have the following meanings:

[0037] Channel: used to distinguish the types of business handled by users, the source of business provided, data source, user behavior, business scenarios and other factors. For example, the data generated by users using credit cards for consumption can be considered to belong to the credit card channel, and the data generated by users using debit cards for consumption can be considered to belong to the debit card channel. This disclosure does not impose specific restrictions on channels, as long as they can achieve the purpose of distinction.

[0038] Processing logic: The data processing process that completes one or more processing behaviors according to specific needs. For example, based on the preset program execution logic and execution conditions, one or more program statements are executed according to the content of user data.

[0039] Database table: An object used to store data in a database, which is a collection of structured data.

[0040] Stored procedure: A set of SQL statements to perform specific functions, which are compiled and stored in the database. It is called and executed by specifying the name of the stored procedure and giving parameters (if the stored procedure has parameters).

[0041] In the technical solution of the present disclosure, the acquisition, collection, storage, use, processing, transmission, provision, disclosure and application of user data are all carried out with the user's permission, comply with the relevant laws and regulations, take necessary confidentiality measures, and do not violate public order and good morals.

[0042] Figure 1 The following schematically shows an architecture diagram of a user points processing system according to an embodiment of the present disclosure.

[0043] like Figure 1 As shown, the user points processing system 100 according to this embodiment may include a data source 110, a first cluster 120, a second cluster 130, a third cluster 140, a rule engine 150, a fourth cluster 160, a message middleware 170, a fifth cluster 180 and a sixth cluster 190. Among them, the data source 110 may include a static data source 111 and a real-time data source 112. Among them, the first cluster 120, the second cluster 130, the third cluster 140, the fourth cluster 160, the fifth cluster 180 and the sixth cluster 190 may be distributed clusters respectively. The message middleware 170 may be a message cluster for providing message queue services.

[0044] The data source 110 is used to receive a static data source, such as first user data generated according to a first behavior of a user, and can also be used to receive a real-time data source, such as second user data generated according to a second behavior. The points file may include a static points file and a dynamic points file, and the corresponding points file includes the first user data or the second user data.

[0045] The first cluster 120 may include multiple server clusters, wherein each server cluster may include several servers. The first cluster 120 may be used to pre-process static data.

[0046] The second cluster 130 may include a Hadoop cluster, which is used to receive the pre-processed data from the first cluster 120 and further process and calculate the pre-processed data. The Hadoop cluster is a platform suitable for distributed storage and distributed computing of massive data, which may include a distributed storage framework HDFS component, a distributed computing framework MapReduce component, and a resource scheduling platform yarn component.

[0047] The third cluster 140 may include a Spark cluster, which is used to read the files processed by the second cluster 130 and perform concurrent processing one by one. Specifically, rule matching may be performed one by one, and integral calculation may be performed according to the matched rules. The Spark cluster may be used as a caller for resource allocation, wherein the Spark applications running in the Spark cluster run independently and are isolated from each other to a certain extent.

[0048] The rule engine 150 may be used to call one or more scoring rules, and in response to the call of the third cluster 140 , screen the scoring rules and return matching scoring rules.

[0049] The fourth cluster 160 may include a plurality of online application clusters for providing the first online service.

[0050] The message middleware 170 may include a Kafka message cluster for providing message queue services. The Kafka message cluster can classify messages according to topics when saving them. Each topic can be divided into multiple partion groups, and each partion is an ordered queue. Each message in a partion is assigned an ordered id.

[0051] The fifth cluster 180 may include a stream computing Storm cluster, which is used to monitor messages in the Kafka message cluster and perform stream processing.

[0052] The sixth cluster 190 may include a plurality of online application clusters for providing a second online service.

[0053] The user point processing system 100 can be used to implement the user point processing method of the embodiment of the present disclosure, and can also be used to deploy the user point processing device of the embodiment of the present disclosure.

[0054] The following will be based on Figure 1 The user points processing system described in the present invention takes the user points processing of a financial institution as an example, and obtains a static points file from a static data source. Figure 2 to Figure 9 The user points processing method of the embodiment of the present disclosure is described in detail.

[0055] Figure 2 The flowchart of the points file processing method according to an embodiment of the present disclosure is schematically shown.

[0056] like Figure 2 As shown, the points file processing method of this embodiment may include operations S210 to S230.

[0057] In operation S210, points files of M channels out of N channels are obtained, wherein the N channels include channels for handling services for users, and the points files include user data generated in response to the services handled by users, and N and M are integers greater than or equal to 1, respectively, and M is less than or equal to N.

[0058] Taking a bank as an example, the channels may include credit card channels, debit card channels, and target activity channels. For example, a credit card channel may provide credit card consumption services to users and generate user data in response to a user's credit card consumption behavior. A debit card channel may provide debit card consumption services to users and generate user data in response to a user's debit card consumption behavior. A target activity channel may provide services such as activity entrance and activity description to users in response to a user's participation in an activity and generate user data.

[0059] The points file may include user data of one or more users within a period of time. For example, a credit card points file may include credit card consumption flow information of multiple users within a period of time. A debit card points file may include debit card consumption flow information of multiple users within a period of time. A standard record points file may include standard record information of multiple users within a period of time.

[0060] Reference Figure 1 After the user handles business in M ​​channels, a points file will be generated and pushed to the static data source. The static data source may include a storage device for storing static points files. The points file can be scanned out from the storage device at regular intervals. Because, during the regular scanning process, the points file of each channel may not have been pushed to the static data source, so the points files of M channels are obtained.

[0061] In operation S220, based on a preset configuration file, a score file of each of the M channels is processed, wherein each channel corresponds to at least one configuration file, and the configuration file includes a processing logic for user data.

[0062] The score files generated by each channel may have different formats, such as file formats, or the same value in each file may correspond to different fields. Therefore, at least one configuration file may be set for each channel to process the data in the score file.

[0063] Since different channels may use different data generation processes, the content and format of the points files received from each channel are different, and points cannot be calculated through a unified processing logic. Therefore, using the configuration file corresponding to each channel can achieve targeted processing. Among them, we can first abstract part of the data of each channel into the object to be processed based on the characteristics of each channel and the conditions required to obtain user points. Based on the need to process the above part of the data into the target data content or data format, determine the processing logic for the object to be processed.

[0064] Due to the abstraction, a certain processing logic can be generalized and applied to multiple channels with corresponding requirements, that is, part of the processing logic between one or more channels can be shared (for example, the common logic can be written in each configuration file, or a configuration file shared by the channels can be set). In addition, through the adapted configuration file, the processing logic unique to each channel can also be written into the configuration file.

[0065] In operation S230, the user points are obtained according to the processing results corresponding to each channel, wherein the processing results are obtained by executing processing logic on the user data in the points file.

[0066] According to the embodiments of the present disclosure, firstly, the steps or objects to be processed are abstracted according to the characteristics of each channel in the N channels to form a processing logic adapted to each channel. Then, the configuration files of the N channels are centrally managed in a centralized manner, so that each channel corresponds to at least one configuration file. In the form of configuration files, a configurable design of the processing logic adapted to the N channels is realized. Thus, the dynamic change and scalability effect of the user processing logic can be realized by operating the configuration files. For the points files of M channels, the processing logic in the corresponding configuration files can be executed to process the user data in the points files. Finally, the user points are obtained according to the processing results. Thus, the problems of processing numerous business scenarios and complex and diverse data formats can be partially solved.

[0067] Figure 3 The flowchart of processing the points file in operation S220 according to an embodiment of the present disclosure is schematically shown.

[0068] like Figure 3 As shown, in operation S220, based on a preset configuration file, processing the score file of each channel in the M channels may include operations S310 to S320. The configuration file includes a parsing configuration file, and the processing logic includes a parsing logic.

[0069] In operation S310 , a corresponding parsing configuration file is determined based on the channel identifier of each channel.

[0070] In some embodiments, a channel identifier may be assigned to each channel in advance, and the parsing configuration file may have a parsing identifier corresponding to the channel identifier, for example, the name of the parsing configuration file is named after the channel identifier, and the name is the parsing identifier. Alternatively, the channel identifier may be written into the parsing configuration file as the parsing identifier.

[0071] In operation S320, the parsing logic in the parsing configuration file is executed to parse the points file of each channel, wherein the parsing logic is used to convert the user data into user data in a predetermined format.

[0072] Reference Figure 1 , the first cluster 120 can run batch application 1, batch application 2, batch application 3, ... batch application N. Each batch application can be connected to a corresponding channel, and after determining the parsing configuration file, execute the parsing logic to process the user data.

[0073] The predetermined format may refer to a user data format that complies with a unified specification. For example, the fields representing the same value in different points files are not the same, that is, they are considered to have different formats, and the above values ​​can be mapped to the same field. For example, the type of user data in different points files is integer or floating point, etc., that is, it is considered to have different formats, and the format can be unified as a string type. For example, different points files have values ​​with the same business meaning in different units, that is, they are considered to have different formats, and the units can be unified, such as US dollars, Japanese yen or euros are all converted into RMB.

[0074] One of the functions of the parsing logic is to pre-process the points file in the static data source to facilitate the subsequent unified operation of the pre-processed user data. For example, a user can use a credit card to consume in the mobile banking client of Bank A, or in applications such as WeChat, Alipay, and UnionPay. Although the points file generated in the above process can be defined as a credit card channel, different merchants and applications for credit card consumption are different, which will generate different user data formats. Through pre-processing, user data in different formats can be converted into user data in a predetermined format.

[0075] You can use the Format expression in XML format to perform formatting configuration, use the channel identifier as the identifier of the configuration segment, and use the parsing unit as the node to configure the parsing logic for each line of user data in the points file.

[0076] Figure 4 The flowchart of parsing the score file in operation S320 according to an embodiment of the present disclosure is schematically shown.

[0077] like Figure 4 As shown, in operation S320, the parsing logic in the parsing configuration file is executed, and parsing the score file of each channel may include executing the X parsing units, specifically including operations S410 to S420. The parsing configuration file includes X parsing units.

[0078] In operation S410 , X first target fields are determined from user data, where X is an integer greater than or equal to 1.

[0079] For example, in the points file of the credit card channel, each line of user data is a consumption flow of a user. Among them, each line of user data can include user identification User ID, credit card number Card Number, transaction serial number Serials Number, etc. (only as an example). The parsing configuration unit may include three parsing units A, B, and C corresponding to user identification User ID, credit card number Card Number, and transaction serial number Serials Number, respectively. For example, parsing unit A is used to determine the first target field User ID, and the other two parsing units B and C are used to determine Card Number and Serials Number.

[0080] In operation S420, the values ​​of the X first target fields are mapped to X columns in the first database table, wherein the mapped X columns include user data in a predetermined format, and the X parsing units include X types of parsing logic corresponding to the X columns.

[0081] For example, parsing unit A traverses each row of user data and first determines the first target field User ID. Then, the value corresponding to User ID is filled into the column corresponding to the user ID in the first database table, such as the UserNumber column. Parsing units B and C have similar parsing processes as above, which will not be repeated here.

[0082] The role of the X types of parsing logic is, on the one hand, to fill the data that meets the requirements into the corresponding columns, so as to facilitate the files in the static data source to be entered into the database for subsequent processing. In addition, by mapping the value of the User ID to the UserNumber column, the data format of the front end (user-oriented) can be converted into a format that is convenient for the back end (points processing background) to process. On the other hand, configuring the parsing logic in units of parsing units is conducive to clear and standardized processing steps of user data. In some embodiments, each parsing logic can be composed of multiple program statements, such as statements for functions such as data cleaning, field matching, and traversal.

[0083] According to an embodiment of the present disclosure, after executing operation S420, it also includes executing a preset stored procedure to merge at least two first database tables with an association relationship into a second database table, wherein the association relationship is determined by the relationship between channels in the N channels.

[0084] Reference Figure 1 After the first database table is obtained in the first cluster 120, the first database table can be unloaded to the second cluster 130 through a stored procedure. The first database table obtained by preprocessing using the parsing configuration file in the first cluster 120 can be a temporary table, and then the first database table is further processed and merged to obtain a target table in the second cluster 130.

[0085] The relationship between channels can be obtained by connecting the user data of each channel. For example, the credit card channel can include the credit card A channel, the credit card B channel and the credit card C channel. Among them, the credit card A channel can generate a transaction serial number under the credit card, and the corresponding points file can include the transaction serial number and the user ID to indicate that the user has a credit card transaction behavior, and the transaction serial number and user ID are used to prevent duplicate transactions. The credit card B channel is used to process the transaction details information of the bank scene. For example, the points file can include the transaction serial number, as well as the corresponding merchant information, whether the contract is signed, the transaction amount, the transaction type and other information. The credit card C channel is used to process the transaction details information of the bank scene, such as the transaction details information of the user in WeChat, Alipay, UnionPay and other applications. For example, the points file can include the transaction serial number, as well as the corresponding merchant information, whether the contract is signed, the transaction amount, the transaction type and other information.

[0086] After executing operations S410 to S420, the credit card A channel, the credit card B channel, and the credit card C channel correspond to the first database table respectively. To calculate the user points of the credit card channel, all the data of the three first database tables of the three channels can be processed uniformly. Therefore, based on the stored procedure, the first database tables of the three channels can be merged into a second database table (i.e., the target table) based on the transaction serial number.

[0087] Figure 5 A flowchart of processing a points file in operation S220 according to another embodiment of the present disclosure is schematically shown.

[0088] like Figure 5 As shown, in operation S220, based on a preset configuration file, processing the score file of each channel in the M channels may include operations S510 to S520. Operations S510 to S520 may be performed after operation S320. The configuration file includes a parsing configuration file, and the processing logic includes a parsing logic.

[0089] In operation S510 , a corresponding process configuration file is determined based on the channel identification of each channel.

[0090] The configuration method of the process configuration file is similar to that of the analysis configuration file. The process configuration file can be assigned an identifier corresponding to the channel identifier to facilitate identification.

[0091] In operation S520, the process logic in the process configuration file is executed to process the parsed score file of each channel, wherein the process logic is used to process the user data in a predetermined format to obtain the processing result.

[0092] The parsed points file of each channel may be the first database table of each channel. For example, when there is an association relationship between the credit card channel A, the credit card channel B, and the credit card channel C, the parsed points files of the three channels may all correspond to the same second database table. Similarly, the three channels may also correspond to the same process configuration file, for example, determined by the channel identifier of the credit card channel A.

[0093] According to an embodiment of the present disclosure, the process configuration file includes Y process unit sets, and operation S520 includes: based on the preset order of the Y process unit sets, sequentially executing each process unit set in the Y process unit sets, wherein each process unit set corresponds to each processing flow for obtaining a processing result. Each process unit set includes Z process units, each process unit in the Z process units corresponds to each sub-process flow in each processing flow, each process unit includes at least one process logic, and Y and Z are integers greater than or equal to 1 respectively.

[0094] Reference Figure 1 The third cluster 140 can be used to retrieve the parsed score file of each channel from the second cluster 130, and after determining the process configuration file, each process unit set therein is executed in sequence.

[0095] For example, in the third cluster 140, the statement "Card01 = Filter1, Check1, Check2, Deal1" can be configured in the properties type file of the JAVA project. Among them, "Card01" is the channel identifier of the credit card A channel, and "Filter1", "Check1", "Check2", and "Deal1" are respectively variable variables used to call the process unit set corresponding to each processing flow. Based on the preset order in the above statements, "Filter1", "Check1", "Check2", and "Deal1" are executed in sequence during the execution process. For example, the role of executing "Filter1" is to filter out invalid data in user data, the role of executing "Check1" is to check whether the merchant ID of the current user data is in the merchant blacklist, the role of executing "Check2" is to check whether the user ID of the current user data is in the user blacklist, and the role of executing "Deal1" is to calculate the points to obtain the processing result. At the same time or after executing "Deal1", the rule engine can be called to calculate the processing result. The processing result may include the accumulated points value of each user data.

[0096] Taking the execution of "Filter1" as an example, the process unit set called by it can include several process units, and the process of executing the process unit is the process of completing the sub-process flow. For example, the process unit used to filter the first type of invalid data (such as null value), the process unit used to filter the second type of invalid data (such as garbled characters), etc.

[0097] It should be noted that the process logic in the process configuration file is different from the rules that can be called by the rule engine 150. The user data content processed by the execution of the process logic is different from that processed by the execution of the rules. For example, "Check1" is used to execute the corresponding process logic to check whether the merchant ID is in the merchant blacklist, so the merchant ID check can be performed without configuring the rule.

[0098] Figure 6 The flowchart of obtaining user points in operation S230 according to an embodiment of the present disclosure is schematically shown.

[0099] like Figure 6 As shown, obtaining user points according to the processing results corresponding to each channel in operation S230 may include operations S610 to S630.

[0100] Reference Figure 1After the third cluster 140 processes the parsed points file to obtain the processing result, the processing result can be pushed to the message middleware 170, and the processing result can be encapsulated into a corresponding message. Specifically, the third cluster 140 can calculate one or more processing results in response to one or more activities involved in each transaction flow data, and encapsulate them into one or more messages.

[0101] The sixth cluster 190 may perform operations S610 to S630 to obtain user points. For example, the sixth cluster 190 may include a router or a gateway, an online application 1, an online application 2, an online application 3, ..., an online application N, and a database. Among them, the online applications 1 to N may provide online services, and the online services may respond to the request generated by the consumption message from the fifth cluster 180 to update the user points in units of user point accounts.

[0102] In operation S610 , a second target field is determined from the parsed score file of each channel.

[0103] An optional implementation is that each message includes a second target field, and each message can be considered as a parsed points file.

[0104] Another optional implementation is to include the Serials Number, User ID and the integral value in each message. The fifth cluster 180 may obtain a second database table from the database, and determine the second target field based on the Serials Number.

[0105] In operation S620, a corresponding configuration condition is queried based on the second target field, wherein the configuration condition is used to determine a calculation condition for obtaining user points.

[0106] In operation S630, user points are obtained according to the configuration conditions and the processing results.

[0107] For example, first, the online service calls the current accumulated points according to the User ID. Then, the row data of a Serials Number corresponding to the User ID in the second database table is accessed, and the corresponding points activity field in the points activity column is determined as the second target field. Then, the corresponding configuration conditions are queried, such as whether there is a maximum limit on the points that can be accumulated by the points activity. If so, it is further determined based on the current accumulated points value whether the accumulated points under the points activity exceed the maximum value. If not, the accumulation continues directly on the basis of the current accumulated points.

[0108] Figure 7 The flowchart schematically shows the preset configuration conditions according to the embodiment of the present disclosure.

[0109] Before executing operation S620, configuration conditions may also be preset, such as Figure 7 As shown, the preset configuration condition may include operations S710 to S720.

[0110] In operation S710, at least one parameter identifier is preset in a third database table.

[0111] The parameter identifier may refer to configuring the calculation condition in a parameterized manner. Each calculation condition may be assigned a corresponding parameter identifier.

[0112] In operation S720, at least one scenario field corresponding to each parameter identifier in at least one parameter identifier is preset in a fourth database table.

[0113] The scenario field may refer to the detailed scenario information specifically related to the user data, such as fields corresponding to a number of point activities, point star ratings, consumption amount, merchant name, and other information.

[0114] The third database table can be used as a parameter identifier set definition table to define parameter identifiers (such as names, numbers, etc.) and types. The fourth database table can be used as a parameter identifier specific value table to define enumeration values ​​of parameter identifiers, namely, scenario fields.

[0115] According to the embodiments of the present disclosure, on the one hand, parameterized configuration is implemented in the form of a database table, and dynamically adjustable parameter identifiers can be stored through a database wide table design. Compared with the configuration file method, the database table method is more flexible and specific, takes effect faster, and centralized configuration is more efficient. On the other hand, parameterized configuration is implemented by combining the third database table and the fourth database table, which can facilitate the management of a variety of computing conditions. Whether in programming or condition update, operating in accordance with management specifications can improve efficiency.

[0116] Figure 8 The flowchart of querying configuration conditions in operation S620 according to an embodiment of the present disclosure is schematically shown.

[0117] like Figure 8 As shown, querying the corresponding configuration condition based on the second target field in operation S620 may include operations S810 to S840.

[0118] In operation S810, a target parameter identifier is determined based on at least one parameter identifier in a third database table.

[0119] Each parameter identifier may be determined as a target parameter identifier in sequence according to the order in the third database table.

[0120] In operation S820, at least one scenario field corresponding to the target parameter identifier is determined from the fourth database table.

[0121] In operation S830, the second target field is matched with at least one scenario field to obtain a matching result.

[0122] In some embodiments, the parsed points file can be a second database table. Each row of data in the second database table can be used as a processing unit to determine whether a column field in each row of data meets which calculation condition. For example, first, a column field is used as the second target field, such as the points activity Activity A. Then, the target parameter identifier is determined from the third database table, such as the maximum limit of the accumulated points Max_jifen. Next, at least one scene field corresponding to Max_jifen is determined from the fourth database table. Activity A is matched with at least one scene field to obtain a matching result.

[0123] According to the embodiments of the present disclosure, in order to avoid frequent queries of the third and fourth database tables, which may lead to system pressure caused by multiple database accesses, the third and fourth database tables may be uniformly stored in redis cache, and cache updates may be triggered when parameter identifiers or scene fields are changed, thereby achieving the effect of clustering effectiveness.

[0124] In operation S840, a corresponding configuration condition is determined based on the matching result.

[0125] An optional implementation is to use the point activity with a maximum point accumulation limit as a scene field, corresponding to Max_jifen in the fourth database table. If Activity A can match the corresponding scene field ActivityA, the matching result is successful, and the configuration condition is that Activity A sets a maximum point accumulation limit. If no match is found, the matching result is failed, and the configuration condition is that Activity A does not set a maximum point accumulation limit.

[0126] Another optional implementation is to use all the points activities as scene fields, corresponding to Max_jifen in the fourth database table, and set the flag to 1 for the activities that set the maximum limit of points accumulation, and set the flag to 0 for the activities that do not set the maximum limit of points accumulation. Therefore, you can first match the corresponding scene field Activity A based on Activity A, and then query the flag. If it is 1, the matching result is turned on, and the configuration condition is that Activity A sets the maximum limit of points accumulation. If it is 0, the matching result is turned off, and the configuration condition is that Activity A does not set the maximum limit of points accumulation.

[0127] Fig. 9 The flowchart of obtaining a points file according to an embodiment of the present disclosure is schematically shown.

[0128] like Fig. 9 As shown, obtaining the points file in this embodiment may include operations S910 to S940, wherein operation S210 may include operations S930 to S940.

[0129] In operation S910, N channel identifiers are allocated to N channels.

[0130] In operation S920, a file storage path corresponding to each channel identifier and a points file identifier are set.

[0131] A monitoring configuration table can be preset to assign channel IDs, set file storage paths, and point file IDs. The monitoring configuration table can be an Excel table or a database table.

[0132] Table 1 schematically shows monitoring configuration contents in some embodiments.

[0133] Table 1

[0134] Channel ID File storage path Points file identifier Card01 / home / ap / nas / file1 Card01_***_%DATEyyyyMMdd%.dat Card02 / home / ap / nas / file2 Card02_***_%DATEyyyyMMdd%.dat

[0135] The points file identifier may be in the form of, for example, "channel identifier_write serial number_write date", and the file of each channel may use the points file identifier as the file name.

[0136] In operation S930, the file storage path corresponding to each channel identifier is scanned to obtain at least one storage file.

[0137] In operation S940, a points file is determined from at least one storage file based on the points file identifier.

[0138] The NFT script can be pushed to each monitoring application server for batch update through the FTP script deployment machine, without restarting the monitoring application server. For example, the NFT script can be read by the Linux system on the monitoring server and take effect immediately. Among them, the NFT script can be called to execute the monitoring process. Referring to Table 1, the NFT script can be called at regular intervals to scan whether there are resolvable storage files in the file storage path corresponding to each channel identifier. In the case of a storage file, the file name is identified again. If the file name meets the points file identifier, it is determined to be a points file.

[0139] Based on the above-mentioned points file processing method, the present disclosure also provides a points file processing device. Fig.10 The device is described in detail.

[0140] Fig.10 The structural block diagram of the points file processing device according to an embodiment of the present disclosure is schematically shown.

[0141] like Fig.10 As shown, the points file processing device 1000 of this embodiment includes a file acquisition module 1010, a file processing module 1020 and a points acquisition module 1030.

[0142] The file acquisition module 1010 can execute operation S210 to obtain the points files of M channels out of N channels, wherein the N channels include channels for handling business for users, and the points files include user data generated in response to the business handled by the users, and N and M are integers greater than or equal to 1 respectively.

[0143] The file acquisition module 1010 may further perform operations S910 to S940, which will not be described in detail herein.

[0144] The file processing module 1020 may perform operation S220 to process the score file of each of the M channels based on a preset configuration file, wherein each channel corresponds to at least one configuration file, and the configuration file includes processing logic for user data.

[0145] The file processing module 1020 may further perform operations S310 to S320, operations S410 to S420, and operations S510 to S520, which will not be described in detail herein.

[0146] The points acquisition module 1030 may perform operation S230 to obtain user points according to the processing result corresponding to each channel, wherein the processing result is obtained by executing processing logic on the user data in the points file.

[0147] The points acquisition module 1030 may also perform operations S610 to S630 and operations S810 to S840, which are not described in detail herein.

[0148] The points file processing device 1000 can monitor the file storage path and storage file name corresponding to the channel identifier through file monitoring configuration, and trigger the parsing process when it is determined that the points file has arrived. Then, the parsing task reads the parsing configuration file to disassemble the rows and columns. Then, after the parsing is completed, the process configuration file is triggered, and the configuration steps in the process unit set are processed in sequence. Finally, combined with the corresponding parameters of the database table, it is determined whether the record meets the conditions and finally the target state result set is obtained to obtain the user points. Through the configurable design, it is possible to efficiently handle complex format problems in multiple scenarios.

[0149] According to an embodiment of the present disclosure, any multiple modules among the file acquisition module 1010, the file processing module 1020 and the score acquisition module 1030 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module.

[0150] According to an embodiment of the present disclosure, at least one of the file acquisition module 1010, the file processing module 1020, and the integral acquisition module 1030 may be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or may be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or by any one of the three implementation methods of software, hardware, and firmware, or by an appropriate combination of any of them. Alternatively, at least one of the file acquisition module 1010, the file processing module 1020, and the integral acquisition module 1030 may be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding function may be executed.

[0151] Fig.11 A block diagram of an electronic device suitable for implementing a points file processing method according to an embodiment of the present disclosure is schematically shown.

[0152] like Fig.11 As shown, the electronic device 1100 according to an embodiment of the present disclosure includes a processor 1101, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1102 or a program loaded from a storage part 1108 to a random access memory (RAM) 1103. The processor 1101 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 1101 may also include an onboard memory for caching purposes. The processor 1101 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0153] In RAM 1103, various programs and data required for the operation of electronic device 1100 are stored. Processor 1101, ROM 1102 and RAM 1103 are connected to each other via bus 1104. Processor 1101 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 1102 and / or RAM 1103. It should be noted that the program can also be stored in one or more memories other than ROM 1102 and RAM 1103. Processor 1101 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in one or more memories.

[0154] According to an embodiment of the present disclosure, the electronic device 1100 may further include an input / output (I / O) interface 1105, which is also connected to the bus 1104. The electronic device 1100 may further include one or more of the following components connected to the I / O interface 1105: an input portion 1106 including a keyboard, a mouse, etc. An output portion 1107 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc. A storage portion 1108 including a hard disk, etc. And a communication portion 1109 including a network interface card such as a LAN card, a modem, etc. The communication portion 1109 performs communication processing via a network such as the Internet. A drive 1110 is also connected to the I / O interface 1105 as needed. A removable medium 1111, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1110 as needed, so that the computer program read therefrom is installed into the storage portion 1108 as needed.

[0155] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0156] According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus, or a device. For example, according to an embodiment of the present disclosure, a computer-readable storage medium may include the ROM 1102 and / or RAM 1103 described above and / or one or more memories other than ROM 1102 and RAM 1103.

[0157] The embodiment of the present disclosure also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the item recommendation method provided by the embodiment of the present disclosure.

[0158] The above functions defined in the system / device of the embodiment of the present disclosure are performed when the computer program is executed by the processor 1101. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0159] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 1109, and / or installed from a removable medium 1111. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0160] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 1109, and / or installed from the removable medium 1111. When the computer program is executed by the processor 1101, the above functions defined in the system of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the system, device, means, module, unit, etc. described above can be implemented by a computer program module.

[0161] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0162] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0163] It will be appreciated by those skilled in the art that the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways, even if such combinations and / or combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways without departing from the spirit and teachings of the present disclosure. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0164] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. The scope of the present disclosure is defined by the attached claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A points file processing method, comprising: Obtaining score files of M channels among N channels, wherein the N channels include channels for handling services for users, and the score files include user data generated in response to the services handled by the users, N and M are integers greater than or equal to 1, respectively, and M is less than or equal to N; Based on a preset configuration file, processing the score file of each channel in the M channels, wherein each channel corresponds to at least one of the configuration files, and the configuration file includes a processing logic for the user data; Obtaining user points according to the processing results corresponding to each channel, wherein the processing results are obtained by executing the processing logic on the user data in the points file; The configuration file includes a process configuration file, the processing logic includes a process logic, and the processing of the score file of each channel in the M channels based on the preset configuration file includes: Based on the channel identifier of each channel, determining the corresponding process configuration file; Execute the process logic in the process configuration file to process the parsed points file of each channel, wherein the process logic is used to process the user data in a predetermined format to obtain the processing result; The process configuration file includes Y process unit sets, and the process logic in the process configuration file is executed, and the score file of each channel after processing and parsing includes: Based on a preset order of the Y process unit sets, sequentially executing each process unit set in the Y process unit sets, wherein each process unit set corresponds to each processing flow for obtaining the processing result; Among them, each process unit set includes Z process units, each process unit in the Z process units corresponds to each sub-processing process in each processing process, and each process unit includes at least one of the process logics, and Y and Z are integers greater than or equal to 1 respectively.

2. The method according to claim 1, wherein: The configuration file includes a parsing configuration file, the processing logic includes a parsing logic, and the processing of the score file of each channel in the M channels based on the preset configuration file includes: Based on the channel identifier of each channel, determining the corresponding parsing configuration file; The parsing logic in the parsing configuration file is executed to parse the points file of each channel, wherein the parsing logic is used to convert the user data into the user data in the predetermined format.

3. The method according to claim 2, wherein: The parsing configuration file includes X parsing units, and executing the parsing logic in the parsing configuration file to parse the points file of each channel includes executing the X parsing units, specifically including: Determine X first target fields from the user data, where X is an integer greater than or equal to 1; The values ​​of the X first target fields are mapped to X columns in the first database table, wherein the mapped X columns include the user data in the predetermined format, and the X parsing units include X types of parsing logic corresponding to the X columns.

4. The method according to claim 3, wherein: The method further comprises: A preset stored procedure is executed to merge at least two of the first database tables having an association relationship into a second database table, wherein the association relationship is determined by a relationship between channels in the N channels.

5. The method according to claim 1, wherein: The obtaining of the user points according to the processing result corresponding to each channel includes: Determine a second target field from the parsed score file of each channel; Querying a corresponding configuration condition based on the second target field, wherein the configuration condition is used to determine a calculation condition for obtaining the user points; The user points are obtained according to the configuration conditions and the processing results.

6. The method according to claim 5, wherein: Before querying the corresponding configuration condition based on the second target field, the configuration condition is also preset, specifically including: Preset at least one parameter identifier in the third database table; At least one scenario field corresponding to each parameter identifier in the at least one parameter identifier is preset in the fourth database table.

7. The method according to claim 6, wherein: The configuration condition corresponding to the query based on the second target field includes: Determining a target parameter identifier based on the at least one parameter identifier in the third database table; Determine at least one scenario field corresponding to the target parameter identifier from the fourth database table; Matching the second target field with the at least one scenario field to obtain a matching result; A corresponding configuration condition is determined based on the matching result.

8. The method according to claim 1, wherein: include: Allocating N channel identifiers to the N channels; Set the file storage path corresponding to each channel ID and the points file ID; The step of obtaining the score files of M channels among N channels includes: Scan the file storage path corresponding to each channel identifier to obtain at least one storage file; Based on the points file identifier, the points file is determined from the at least one storage file.

9. A points file processing device, comprising: A file acquisition module, used to acquire score files of M channels among N channels, wherein the N channels include channels for handling services for users, and the score files include user data generated in response to the services handled by the users, and N and M are integers greater than or equal to 1 respectively; A file processing module, used for processing the score file of each channel in the M channels based on a preset configuration file, wherein each channel corresponds to at least one of the configuration files, and the configuration file includes a processing logic for the user data; A points acquisition module, used to obtain user points according to the processing results corresponding to each channel, wherein the processing results are obtained by executing the processing logic on the user data in the points file; The configuration file includes a process configuration file, the processing logic includes a process logic, and the processing of the score file of each channel in the M channels based on the preset configuration file includes: Based on the channel identifier of each channel, determining the corresponding process configuration file; Execute the process logic in the process configuration file to process the parsed points file of each channel, wherein the process logic is used to process the user data in a predetermined format to obtain the processing result; The process configuration file includes Y process unit sets, and the process logic in the process configuration file is executed, and the score file of each channel after processing and parsing includes: Based on a preset order of the Y process unit sets, sequentially executing each process unit set in the Y process unit sets, wherein each process unit set corresponds to each processing flow for obtaining the processing result; Among them, each process unit set includes Z process units, each process unit in the Z process units corresponds to each sub-processing process in each processing process, and each process unit includes at least one of the process logics, and Y and Z are integers greater than or equal to 1 respectively.

10. An electronic device comprising: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors execute the method according to any one of claims 1 to 8.

11. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the method according to any one of claims 1 to 8.

12. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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