Data processing method and apparatus

Abstract

The application discloses a data processing method and device, and relates to the technical field of big data analysis. A specific embodiment of the method comprises the following steps: receiving a data processing request, determining a target object and a business type corresponding to the data processing request; acquiring a data source and at least one measurement index corresponding to the business type; locating a description statement of the target object from the data source; calling an extraction component corresponding to each measurement index to extract the value of each measurement index from the description statement; determining processing information corresponding to the data processing request according to the value of the measurement index, and performing business data processing on the target object according to the processing information. The embodiment can reduce the repetition and coupling degree between codes, and is beneficial to the upgrading and operation and maintenance of an information system.

Description

Technical Field

[0001] This invention relates to the field of big data data analysis technology, and in particular to a data processing method and apparatus. Background Technology

[0002] Information systems often aggregate data from multiple data sources and then process this data according to business needs to facilitate specific workflows for relevant personnel. Data processing is a crucial task in information systems. Different business scenarios require different data processing methods. Generally, different data processing programs need to be written according to business requirements to perform different functionalities. This approach leads to high redundancy and tight coupling between code segments, hindering system upgrades and maintenance. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide a data processing method and apparatus that can reduce code redundancy and coupling, which is beneficial to the upgrading and maintenance of information systems.

[0004] In a first aspect, embodiments of the present invention provide a data processing method, including:

[0005] Receive a data processing request and determine the target object and business type corresponding to the data processing request;

[0006] Obtain the data source and at least one metric corresponding to the business type;

[0007] From the data source, locate the description statement of the target object;

[0008] Call the extraction component corresponding to each of the aforementioned metrics to extract the value of each of the aforementioned metrics from the description statement;

[0009] Based on the value of the measurement index, the processing information corresponding to the data processing request is determined, and based on the processing information, business data processing is performed on the target object.

[0010] Optionally, the step of calling the extraction component corresponding to each of the measurement indicators to extract the value of each of the measurement indicators from the description statement includes:

[0011] The description statement is segmented into words to obtain multiple words of the description statement;

[0012] The extraction component corresponding to the measurement metric is invoked to determine the target word that matches the extraction information corresponding to the measurement metric from the multiple word segments, and the target word is used as the value of the measurement metric.

[0013] Optionally, determining the processing information corresponding to the data processing request based on the value of the measurement indicator includes:

[0014] Determine at least one verification piece corresponding to the business type;

[0015] Using the values ​​of the aforementioned metrics, the matching results between the target object and each of the aforementioned verification information are determined;

[0016] Based on the matching results between the target object and each of the verification information, the processing information corresponding to the data processing request is determined.

[0017] Optionally, determining the matching result between the target object and each of the verification information using the values ​​of the measurement indicators includes:

[0018] Determine at least one verification condition corresponding to the verification information;

[0019] Using the values ​​of the aforementioned metrics, the verification results of each verification condition for the target object are determined;

[0020] Based on the verification results corresponding to each of the verification conditions, the matching result between the target object and the verification information is determined.

[0021] Optionally, the at least one verification condition includes: a first type of condition, which corresponds to a single measurement metric;

[0022] The step of determining the verification result of each verification condition for the target object using the values ​​of the measurement indicators includes:

[0023] From the at least one measurement index, determine the target index corresponding to the first type of condition;

[0024] Determine the indicator parameters and parameter operations corresponding to the first type of condition;

[0025] Based on the value of the target indicator, the indicator parameters, and the parameter operations, the verification result of the first type of conditions for the target object is determined.

[0026] Optionally, the at least one verification condition includes: a second type of condition, which corresponds to multiple measurement indicators;

[0027] The step of determining the verification result of each verification condition for the target object using the values ​​of the measurement indicators includes:

[0028] From the at least one measurement index, determine multiple target indicators corresponding to the second type of condition;

[0029] For each target indicator, determine the indicator parameters and parameter operations corresponding to the target indicator under the second type of condition; based on the value of the target indicator, the indicator parameters and the parameter operations, determine the verification result corresponding to the target indicator;

[0030] Based on the verification results corresponding to each of the target indicators, the verification results of the second type of conditions for the target object are determined.

[0031] Optionally, determining the verification result of the second type of condition for the target object based on the verification results corresponding to each of the target indicators includes:

[0032] Determine the combination information corresponding to the second type of conditions;

[0033] Based on the combined information, the verification results corresponding to each of the target indicators are combined to generate a rule expression corresponding to the second type of condition;

[0034] The calculation result of the rule expression is determined, and the calculation result is determined as the verification result of the second type of condition for the target object.

[0035] Optionally, the step of performing business data processing on the target object based on the processing information includes:

[0036] Determine the target table, target fields, and processing method corresponding to the processing information;

[0037] The data of the target object corresponding to the target field in the target table is processed in the manner described above.

[0038] Secondly, embodiments of the present invention provide a data processing apparatus, comprising:

[0039] The request receiving module is used to receive data processing requests and determine the target object and business type corresponding to the data processing request.

[0040] The metric acquisition module is used to acquire the data source and at least one measurement metric corresponding to the business type.

[0041] The statement locating module is used to locate the description statement of the target object from the data source;

[0042] The value extraction module is used to call the extraction component corresponding to each of the measurement indicators to extract the value of each of the measurement indicators from the description statement.

[0043] The processing module is used to determine the processing information corresponding to the data processing request based on the value of the measurement indicator, and to perform business data processing on the target object based on the processing information.

[0044] Optionally, the value extraction module is specifically used for:

[0045] The description statement is segmented into words to obtain multiple words of the description statement;

[0046] The extraction component corresponding to the measurement metric is invoked to determine the target word that matches the extraction information corresponding to the measurement metric from the multiple word segments, and the target word is used as the value of the measurement metric.

[0047] Optionally, the processing module is specifically used for:

[0048] Determine at least one verification piece corresponding to the business type;

[0049] Using the values ​​of the aforementioned metrics, the matching results between the target object and each of the aforementioned verification information are determined;

[0050] Based on the matching results between the target object and each of the verification information, the processing information of the target object corresponding to the data processing request is determined.

[0051] Optionally, the processing module is specifically used for:

[0052] Determine at least one verification condition corresponding to the verification information;

[0053] Using the values ​​of the aforementioned metrics, the verification results of each verification condition for the target object are determined;

[0054] Based on the verification results corresponding to each of the verification conditions, the matching result between the target object and the verification information is determined.

[0055] Thirdly, embodiments of the present invention provide an electronic device, including:

[0056] One or more processors;

[0057] Storage device for storing one or more programs.

[0058] When the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any of the above embodiments.

[0059] Fourthly, embodiments of the present invention provide a computer-readable medium having a computer program stored thereon, which, when executed by a processor, implements the methods described in any of the above embodiments.

[0060] Fifthly, embodiments of the present invention provide a computer program product, including a computer program that, when executed by a processor, implements the methods described in any of the above embodiments.

[0061] One embodiment of the above invention has the following advantages or beneficial effects: Upon receiving a data processing request, the system determines the target object and business type corresponding to the data processing request; based on the target object and business type, it determines the processing information corresponding to the data processing request and completes the data processing corresponding to the data processing request. The system can directly use the processing information for data processing, or it can call the data processing program corresponding to the processing information for data processing. Multiple business requirements can share the same processing information, eliminating the need to write separate data processing programs for different business requirements, reducing code redundancy and coupling, and facilitating the upgrade and maintenance of the information system.

[0062] The further effects of the aforementioned unconventional alternative methods will be explained below in conjunction with specific implementation methods. Attached Figure Description

[0063] The accompanying drawings are provided to better understand the invention and are not intended to unduly limit the scope of the invention. Wherein:

[0064] Figure 1 This is a flowchart illustrating a data processing method provided in the first embodiment of the present invention;

[0065] Figure 2 This is a flowchart illustrating a data processing method provided in the second embodiment of the present invention;

[0066] Figure 3 This is a flowchart illustrating a data processing method provided in the third embodiment of the present invention;

[0067] Figure 4 This is a schematic diagram of the structure of a data processing device provided in an embodiment of the present invention;

[0068] Figure 5 This is a schematic diagram of the structure of a computer system suitable for implementing terminal devices or servers of the present invention. Detailed Implementation

[0069] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of the present invention, including various details to aid understanding. These details should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0070] It should be noted that the collection, analysis, use, transmission, and storage of user personal information involved in the technical solution of this invention all comply with relevant laws and regulations, are used for legitimate and reasonable purposes, and are not shared, disclosed, or sold outside of these legitimate uses, and are subject to supervision and management by regulatory authorities. Necessary measures should be taken to prevent unauthorized access to such personal information data, ensure that personnel authorized to access personal information data comply with relevant laws and regulations, and ensure the security of user personal information. Once this user personal information data is no longer needed, the risk should be minimized by restricting or even prohibiting data collection and / or deleting the data.

[0071] Figure 1 This is a flowchart illustrating a data processing method provided in the first embodiment of the present invention, as shown below. Figure 1 As shown, the method includes:

[0072] Step 101: Receive data processing request and determine the target object and business type corresponding to the data processing request.

[0073] The target object can be set according to business needs and application scenarios. Target objects can be: users, companies, goods, financial products, etc. For example, if the data to be filtered or processed is user data, then users can be the target object. If the data to be filtered or processed is user data for a target region, then users for that region can be the target object. If the data to be filtered or processed is item data, then the items can be the target object. If the data to be filtered or processed is textile item data, then the textile items can be the target object.

[0074] The business type can be set according to business needs and application scenarios. For example, if the target object is a user, the business type could be to add a user level or modify user permissions. If the target object is an item, the business type could be to modify the item's value attribute or modify the item's inventory.

[0075] Step 102: Obtain the data source corresponding to the business type and at least one metric; locate the description statement of the target object from the data source.

[0076] A description statement is a statement used to describe information about a target object. Description statements can have a fixed format, meaning they can consist of fixed fields. For example, if the fixed fields are identifier, place of origin, weight, and inventory, the description statement could be: 001-Beijing-50-1000. Description statements can also lack a fixed format; these can be obtained from data sources such as contracts or web pages.

[0077] Metrics can be set according to business needs and application scenarios. Metrics are used to describe parameters of the target object, such as unit price, clicks, impressions, number of purchases, and product categories. In the following text, quantifiable metrics like unit price will be referred to as range-based metrics, and categorizable metrics like product categories will be referred to as aggregate-based metrics.

[0078] The system can preset the mapping relationship between business types and metrics, and obtain the corresponding metrics for each business type based on the mapping relationship.

[0079] The system can also pre-define the mapping relationship between business types and data sources, and retrieve the data source corresponding to the business type based on this mapping relationship. Data sources may include: file path, file name, network link, database name, table name, etc.

[0080] There are many ways to locate the descriptive statements of a target object. For example, the descriptive text can be obtained directly through the file path or network link corresponding to the data source, and the content of the descriptive text can be used as the descriptive statement. Alternatively, the descriptive statement can be obtained from a table in the database corresponding to the data source.

[0081] When the data source is a file path, and multiple text files exist within that file path, the text name is determined based on the target object's object information. The text file with that name is then used as the target object's description text, and its content is used as the description statement. For example, if various contracts are stored in the same path, with contract names corresponding to target object numbers, the data source can be set to that path. The contract text corresponding to the target object is then located using the object number, and the description statement of the target object is found within the contract text.

[0082] Step 103: Call the extraction component corresponding to each metric to extract the value of each metric from the description statement.

[0083] The description statement contains different fields, each corresponding to a different metric. Fields can be categorized as descriptive, range-based, and aggregate-based. Descriptive fields are typically text-based and unformatted. Range-based and aggregate-based fields can be mapped to specific metrics according to their business meaning.

[0084] It can parse descriptive statements to obtain parsing results. Extracted information includes the correspondence between the parsing results and the fields. Using the parsing results, fact objects in an object-oriented language are generated, and then the values ​​of the metrics are determined by the field values.

[0085] In one embodiment of the present invention, the description statement can also be segmented in the following manner to obtain multiple segments of the description statement; the extraction component corresponding to the measurement index is called to determine the target segment that matches the extraction information corresponding to the measurement index from the multiple segments, and the target segment is used as the value of the measurement index.

[0086] The extraction component can include the correspondence between metrics and extraction rules. Extraction rules can be in the form of regular expressions. Using the extraction component, the values ​​of the metrics are matched from multiple tokens in the description statement.

[0087] For example, if the metric is the ID card number, the extraction rule can be: "^[1-9]\\d{5}(18|19|20|21)\\d{2}((0[1-9])|(10|11|12))(([0-2][1-9])|10|20|30|31)\\d{3}[0-9Xx]$". Then, the extraction component will determine the target word from multiple word segments using the above extraction rule, and use it as the value of the ID card number.

[0088] Step 104: Based on the values ​​of the metrics, determine the processing information corresponding to the data processing request, and based on the processing information, perform business data processing on the target object.

[0089] The processing information corresponding to a data processing request can be determined in the following ways: determine at least one verification information corresponding to the business type; determine the matching result between the target object and each verification information by using the value of the metric; and determine the processing information corresponding to the data processing request based on the matching result between the target object and each verification information.

[0090] Validation information can be set according to business needs and application scenarios. Validation information can include validation conditions, actions, and orchestration-related attributes. Orchestration-related attributes include: whether it is exclusive, whether it is repeatable, priority, etc.

[0091] To facilitate the application and management of verification information, a verification information set can be set up. The verification information set contains a group of verification information, and each verification information in the set can be stored in key-value pairs.

[0092] Validation information can be created based on one or more metrics. The value of the validation information is determined by the values ​​of each metric. Specifically, if the value of the validation information is true or 1, the matching result between the target object and the validation information is true or 1. If the value of the validation information is false or 0, the matching result between the target object and the validation information is false or 0.

[0093] After constructing the validation information, a rule engine is typically needed to execute the validation. The rule engine includes a context and a rule executor. The context may include fact objects, accept validation information, reject validation information, accept results, end controls, and some context variables.

[0094] Step 104: Based on the values ​​of the metrics, determine the processing information corresponding to the data processing request, and based on the processing information, perform business data processing on the target object.

[0095] The processing information can be set according to business needs and application scenarios. It can be used to perform operations such as summing, averaging, finding the maximum and minimum values ​​of target fields within a target object. It can also modify the target field of a target object to a target value. Furthermore, it can be used to select all target objects whose matching results with each validation setting are true.

[0096] In one embodiment of the present invention, the processing information includes: a target table, target fields, and a processing method. Based on the processing information, business data processing is performed on the target object, including: determining the target table, target fields, and processing method corresponding to the processing information; and processing the data of the target object corresponding to the target field of the target table according to the processing method.

[0097] The processing methods can include: summation, averaging, finding the maximum or minimum value, multiplying by a correlation coefficient, etc. Processing methods can also include setting a target value, thereby modifying the target field of the target object to the target value. Specifically, based on the object information of the target object, the target record is retrieved from the target table, and the data in the target field of the target record is processed using this method. Object information may include: object identifier, object attribute values, etc.

[0098] In this embodiment of the invention, upon receiving a data processing request, the target object and business type corresponding to the data processing request are determined. Based on the target object and business type, the processing information corresponding to the data processing request is determined, and the data processing corresponding to the data processing request is completed. Multiple business requirements can share the same processing information, eliminating the need to write separate data processing programs for different business requirements. This reduces code redundancy and coupling, and is beneficial for information system upgrades and maintenance.

[0099] Figure 2 This is a flowchart illustrating a data processing method provided in the second embodiment of the present invention, as shown below. Figure 2 As shown, the method includes:

[0100] Step 201: Receive data processing request and determine the target object and business type corresponding to the data processing request.

[0101] Step 202: Obtain the data source corresponding to the business type and at least one metric; locate the description statement of the target object from the data source.

[0102] Step 203: Call the extraction component corresponding to each metric to extract the value of each metric from the description statement.

[0103] Step 204: Determine at least one verification information corresponding to the business type, and determine at least one verification condition corresponding to each verification information.

[0104] Validation criteria can be set according to business needs and application scenarios. Validation criteria can be created based on one or more metrics.

[0105] Step 205: Using the values ​​of the measurement indicators, determine the verification results of each verification condition for the target object.

[0106] For each metric, the validation conditions correspond to metric parameters and parameter operations. Metric parameters are preset value values ​​for a specific metric. Metric parameters can be a set or a range of values. For range-based metrics, parameter operations include: `belongs to`, `greater than`, `greater than or equal to`, `less than`, `less than or equal to`, and `equal to`. For set-based metrics, parameter operations include: `equivalent to`, `contains in`, and `not contained in`. Validation conditions are used to validate the relevant data of the target object using the preset metric parameters and parameter operations, and return a Boolean result.

[0107] Step 206: Determine the matching result between the target object and the verification information based on the verification results corresponding to each verification condition.

[0108] The matching result between the target object and the verification information can be determined according to preset matching rules. For example, if the verification result corresponding to all verification conditions in the verification information is true, then the matching result between the target object and the verification information is determined to be true. Alternatively, as long as there is a verification result corresponding to any verification condition that is true, then the matching result between the target object and the verification information is determined to be true, and so on.

[0109] Step 207: Based on the matching results between the target object and each verification information, determine the processing information corresponding to the data processing request, and perform business data processing on the target object based on the processing information.

[0110] A tree structure can be constructed within the system, comprising a verification information set, verification information, verification conditions, indicator parameters, and target objects. The verification information set contains multiple verification information entries, and each entry contains multiple verification conditions. When verification conditions are constructed based on a single metric, each verification condition corresponds to an indicator parameter and extracted information.

[0111] Extracting information is used to extract the values ​​of metrics from the input description statement. During the construction process, the extracted information can be mapped to fields in the description statement, completing the mapping between extracted information and extracted metrics. After defining a target object, reflection is used to associate the extracted information corresponding to the metric with the metric and integrate it into the condition evaluator, completing the mapping between fields in the description statement and extracted information. Extracted information may include: extraction methods, extraction rules, etc.

[0112] In this embodiment of the invention, multiple verification conditions can be set according to the business scenario, and then one or more verification conditions can be combined into a single verification information. During data processing, the verification results corresponding to each verification condition are first obtained based on the values ​​of each metric. Then, based on the verification results corresponding to each verification condition, the matching results between the target object and each verification information are obtained, thereby determining the processing information for the target object.

[0113] In one embodiment of the present invention, at least one verification condition includes: a first type of condition, which corresponds to a single measurement index; determining the verification result of each verification condition for the target object using the value of the measurement index includes: determining the target index corresponding to the first type of condition from at least one measurement index; determining the index parameter and parameter operation corresponding to the first type of condition; and determining the verification result of the first type of condition for the target object based on the value of the target index, the index parameter and parameter operation.

[0114] The first type of condition corresponds to a single metric and is a simple condition. It corresponds to a preset metric parameter and provides an evaluator. The evaluator is used to obtain the value of the metric corresponding to the first type of condition based on the input description. The first type of condition can perform calculations between the obtained metric value and the preset metric parameter and return a Boolean result.

[0115] For example, the first type of condition is used to filter products with a profit value greater than 1000. The target object is the product, the corresponding metric for this validation condition is product profit, the metric parameter is 1000, and the parameter operation is "greater than". Using the metric parameter and parameter operation, it is possible to determine whether the profit value of the target object is greater than 1000, thereby filtering out a list of products with a profit value greater than 1000.

[0116] For example, the first type of condition is used to determine whether the current transaction is an investment transaction. The target object is the transaction itself, the corresponding metric for the verification condition is the transaction type, and the metric parameters are a set including: wealth management, deposit, fund, and stock categories. The parameter operation is inclusion. Using the metric parameters and parameter operations, it is possible to determine whether the target object is an investment transaction.

[0117] In one embodiment of the present invention, at least one verification condition includes: a second type of condition, which corresponds to multiple metrics; determining the verification result of each verification condition for the target object using the values ​​of the metrics includes: determining multiple target metrics corresponding to the second type of condition from at least one metric; determining the metric parameters and parameter operations of the target metrics corresponding to the second type of condition for each target metric; determining the verification result corresponding to the target metric based on the values ​​of the target metrics, the metric parameters, and the parameter operations; and determining the verification result of the second type of condition for the target object based on the verification results corresponding to each target metric.

[0118] The second type of condition corresponds to multiple metrics and is considered a complex condition. It represents more complex logical relationships and allows for more intricate logical processing. Each target metric corresponding to a second type of condition corresponds to a first type of condition. The metric parameters and operations corresponding to a target metric can be viewed as the metric parameters and operations corresponding to a first type of condition.

[0119] The second type of condition is a combination of multiple first type conditions using a Boolean operation. Multiple first type conditions can be combined into a single second type condition expression using Boolean operations such as logical AND and logical OR. For example, second type condition A = first type condition 1 AND first type condition 2 OR first type condition 3.

[0120] Based on the verification results corresponding to each target indicator, determine the verification results of the second type of condition for the target object, including: determining the combination information corresponding to the second type of condition; combining the verification results corresponding to each target indicator based on the combination information to generate the rule expression corresponding to the second type of condition; determining the calculation result of the rule expression, and determining the calculation result as the verification result of the second type of condition for the target object.

[0121] The combination information may include the execution order, operation type, and priority of each target indicator. Operation types may include logical AND, logical OR, etc. Each target indicator corresponds to a first-type condition. Based on the priority in the second-type condition expression, the operation order of each first-type condition can be combined to generate the rule expression corresponding to the second-type condition.

[0122] For example, if the target is a transaction, the second type of condition corresponds to two metrics: transaction amount and transaction type. The first criterion for transaction amount is used to filter transactions with an amount greater than 100. The second criterion for transaction type is used to determine whether the current transaction is an investment transaction.

[0123] If the combination of the verification results corresponding to the two target indicators is a logical AND, then this second type of condition is used to determine whether the transaction amount is greater than 100 and the transaction type is an investment transaction. If the combination of the verification results corresponding to the two target indicators is a logical OR, then this second type of condition is used to determine whether the transaction amount of the target object is greater than 100, or whether the transaction type is an investment transaction.

[0124] The rule expression corresponding to the second type of condition can be converted into a conditional linked list of AND operations. The combination of two adjacent nodes in the conditional linked list of AND operations is an AND operation. The nodes in the conditional linked list of AND operations include: the conditional linked list of OR operations, the verification results corresponding to the first type of condition, etc. Specifically, the combination of two adjacent nodes in the conditional linked list of OR operations is an OR operation. The nodes in the conditional linked list of OR operations include: the verification results corresponding to the first type of condition, etc.

[0125] For example: Condition A of type 2 = Condition 1 of type 1 and Condition 2 of type 1 or Condition 3 of type 1. Here, Condition A of type 2 is the rule expression corresponding to the condition of type 2. Condition 1 of type 1, Condition 2 of type 1, and Condition 3 of type 1 are the verification results corresponding to the target indicator.

[0126] Then the second type of condition A can be transformed into: orConditions = [first type of condition 2, first type of condition 3], andConditions = [[first type of condition 1], orConditions]. Where, orConditions is the condition list for the OR operation, and andConditions is the condition list for the AND operation.

[0127] The rule expression corresponding to the transformed second type of condition can be quickly evaluated using the condition list evaluation rules of AND operation and OR operation.

[0128] The conditional list evaluation rule for AND operations is as follows: if the regular expression is of the form TRUE and FALSE and TRUE…, when the operation reaches the second node False, it directly returns False without evaluating the values ​​after False.

[0129] The conditional list evaluation rule for OR operation is as follows: if the regular expression is in the form of TRUE and FALSE and TRUE..., when the first node TRUE is evaluated, TRUE is returned directly without evaluating the values ​​after TRUE.

[0130] The process of constructing a validation information set can include the following four steps: defining fact objects; defining an indicator library; extracting configured validation information and condition parameters; and constructing the validation information set. These steps effectively organize complex validation information and utilize a unique expression language to evaluate rule expressions. Furthermore, the storage methods for the conditional linked lists of OR and AND operations, combined with a fast evaluation mechanism, can effectively improve the computational efficiency of rule expressions corresponding to the second type of conditions.

[0131] Figure 3 This is a flowchart illustrating a data processing method provided in the third embodiment of the present invention, as shown below. Figure 3 As shown, the method includes:

[0132] Step 301: Receive data processing request and determine the target object and business type corresponding to the data processing request.

[0133] Step 302: Obtain the data source corresponding to the business type and at least one metric; locate the description statement of the target object from the data source.

[0134] Step 303: Call the extraction component corresponding to each metric to extract the value of each metric from the description statement.

[0135] Step 304: Use the values ​​of the metrics to determine the matching results between the target object and each verification information.

[0136] Step 305: Obtain the preset strategy mapping relationship.

[0137] The strategy mapping relationship is used to store the correspondence between matching results and processing information. A matching result corresponds to one or more verification messages. For example, if the matching result for verification message 1 is true, the matching result for verification message 2 is true, and the matching result for verification message 3 is true, then it corresponds to processing message 3. If the matching result for verification message 1 is true, the matching result for verification message 2 is true, and the matching result for verification message 3 is false, then it corresponds to processing message 2, and so on.

[0138] Step 306: Based on the matching results between the target object and each verification information, find the processing information corresponding to the target object in the policy mapping relationship.

[0139] Generally, based on the matching results of each verification message, one and only one corresponding processing message can be found in the policy mapping relationship. If no processing message is found, or if multiple processing messages are found, an alarm is issued.

[0140] Step 307: Based on the found processing information, perform business data processing on the target object.

[0141] The processing information can be set according to business needs and application scenarios. Processing information can represent summing, averaging, finding the maximum, or finding the minimum value of a target field within a target object. It can also represent modifying a target field of a target object to a target value. Furthermore, it can represent selecting all target objects whose matching results with each validation message are true.

[0142] In this embodiment of the invention, the system presets a strategy mapping relationship. Based on the matching results between the target object and each verification information, it searches for the processing information corresponding to the target object in the strategy mapping relationship. Multiple business requirements can share the same processing information, which can reduce the coupling between codes and reduce the difficulty and workload of system development when requirements change or the system is redesigned.

[0143] Figure 4 This is a schematic diagram of the structure of a data processing device provided in one embodiment of the present invention, as shown below. Figure 4 As shown, the device includes:

[0144] The request receiving module 401 is used to receive a data processing request and determine the target object and business type corresponding to the data processing request.

[0145] The indicator acquisition module 402 is used to acquire the data source and at least one measurement indicator corresponding to the business type.

[0146] The statement locating module 403 is used to locate the description statement of the target object from the data source;

[0147] The value extraction module 404 is used to call the extraction component corresponding to each of the measurement indicators to extract the value of each of the measurement indicators from the description statement.

[0148] The processing module 405 is used to determine the processing information corresponding to the data processing request based on the value of the measurement index, and to perform business data processing on the target object based on the processing information.

[0149] Optionally, the value extraction module 404 is specifically used for:

[0150] The description statement is segmented into words to obtain multiple words of the description statement;

[0151] The extraction component corresponding to the measurement metric is invoked to determine the target word that matches the extraction information corresponding to the measurement metric from the multiple word segments, and the target word is used as the value of the measurement metric.

[0152] Optionally, the processing module 405 is specifically used for:

[0153] Determine at least one verification piece corresponding to the business type;

[0154] Using the values ​​of the aforementioned metrics, the matching results between the target object and each of the aforementioned verification information are determined;

[0155] Based on the matching results between the target object and each of the verification information, the processing information of the target object corresponding to the data processing request is determined.

[0156] Optionally, the processing module 405 is specifically used for:

[0157] Determine at least one verification condition corresponding to the verification information;

[0158] Using the values ​​of the aforementioned metrics, the verification results of each verification condition for the target object are determined;

[0159] Based on the verification results corresponding to each of the verification conditions, the matching result between the target object and the verification information is determined.

[0160] Optionally, the at least one verification condition includes: a first type of condition, which corresponds to a single measurement metric;

[0161] The processing module 405 is specifically used for:

[0162] From the at least one measurement index, determine the target index corresponding to the first type of condition;

[0163] Determine the indicator parameters and parameter operations corresponding to the first type of condition;

[0164] Based on the value of the target indicator, the indicator parameters, and the parameter operations, the verification result of the first type of conditions for the target object is determined.

[0165] Optionally, the at least one verification condition includes: a second type of condition, which corresponds to multiple measurement indicators;

[0166] The processing module 405 is specifically used for:

[0167] From the at least one measurement index, determine multiple target indicators corresponding to the second type of condition;

[0168] For each target indicator, determine the indicator parameters and parameter operations corresponding to the target indicator under the second type of condition; based on the value of the target indicator, the indicator parameters and the parameter operations, determine the verification result corresponding to the target indicator;

[0169] Based on the verification results corresponding to each of the target indicators, the verification results of the second type of conditions for the target object are determined.

[0170] Optionally, the processing module 405 is specifically used for:

[0171] Determine the combination information corresponding to the second type of conditions;

[0172] Based on the combined information, the verification results corresponding to each of the target indicators are combined to generate a rule expression corresponding to the second type of condition;

[0173] The calculation result of the rule expression is determined, and the calculation result is determined as the verification result of the second type of condition for the target object.

[0174] Optionally, the processing module 405 is specifically used for:

[0175] Determine the target table, target fields, and processing method corresponding to the processing information;

[0176] The data of the target object corresponding to the target field in the target table is processed in the manner described above.

[0177] This invention provides an electronic device, comprising:

[0178] One or more processors;

[0179] Storage device for storing one or more programs.

[0180] When one or more programs are executed by one or more processors, the one or more processors implement the methods of any of the above embodiments.

[0181] This invention provides a computer program product, including a computer program that, when executed by a processor, implements the enterprise risk assessment method of this invention.

[0182] The following is for reference. Figure 5 It shows a schematic diagram of the structure of a computer system 500 suitable for implementing a terminal device of the present invention. Figure 5 The terminal device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0183] like Figure 5As shown, the computer system 500 includes a central processing unit (CPU) 501, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 502 or programs loaded from storage section 508 into random access memory (RAM) 503. The RAM 503 also stores various programs and data required for the operation of the system 500. The CPU 501, ROM 502, and RAM 503 are interconnected via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0184] The following components are connected to I / O interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to I / O interface 505 as needed. A removable medium 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 510 as needed so that computer programs read from it can be installed into storage section 508 as needed.

[0185] In particular, according to the embodiments disclosed in this invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by central processing unit (CPU) 501, it performs the functions defined above in the system of this invention.

[0186] It should be noted that the computer-readable medium shown in this invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0187] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0188] The modules described in the embodiments of the present invention can be implemented in software or hardware. The described modules can also be housed in a processor, and for example, can be described as: a request receiving module, an indicator acquisition module, a statement location module, a value extraction module, and a processing module. The names of these modules do not necessarily limit the module itself; for example, the request receiving module can also be described as "a module that receives data processing requests and determines the target object and business type corresponding to the data processing request."

[0189] In another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiments; or it may exist independently and not assembled into the device. The computer-readable medium carries one or more programs, which, when executed by the device, cause the device to include:

[0190] Receive a data processing request and determine the target object and business type corresponding to the data processing request;

[0191] Obtain the data source and at least one metric corresponding to the business type;

[0192] From the data source, locate the description statement of the target object;

[0193] Call the extraction component corresponding to each of the aforementioned metrics to extract the value of each of the aforementioned metrics from the description statement;

[0194] Based on the value of the measurement index, the processing information corresponding to the data processing request is determined, and based on the processing information, business data processing is performed on the target object.

[0195] According to the technical solution of this embodiment of the invention, upon receiving a data processing request, the target object and business type corresponding to the data processing request are determined. Based on the target object and business type, the processing information corresponding to the data processing request is determined, and the data processing corresponding to the data processing request is completed. Multiple business requirements can share the same processing information, eliminating the need to write separate data processing programs for different business requirements. This reduces code redundancy and coupling, and is beneficial for information system upgrades and maintenance.

[0196] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A data processing method, characterized in that, include: Receive a data processing request and determine the target object and business type corresponding to the data processing request; Obtain the data source and at least one metric corresponding to the business type; wherein the data source corresponds to a file path or network link; the metric is used to describe the parameters of the target object; From the data source, locate the description statement of the target object; wherein, the description statement is a statement used to describe the information of the target object; Call the extraction component corresponding to each of the aforementioned metrics to extract the value of each of the aforementioned metrics from the description statement; The step of calling the extraction component corresponding to each of the measurement indicators to extract the value of each of the measurement indicators from the description statement includes: performing word segmentation on the description statement to obtain multiple word segments of the description statement; calling the extraction component corresponding to the measurement indicator to determine the target word segment that matches the extracted information corresponding to the measurement indicator from the multiple word segments, and using the target word segment as the value of the measurement indicator. Based on the value of the measurement index, the processing information corresponding to the data processing request is determined, and based on the processing information, business data processing is performed on the target object.

2. The method according to claim 1, characterized in that, The step of determining the processing information corresponding to the data processing request based on the value of the measurement indicator includes: Determine at least one verification piece corresponding to the business type; Using the values ​​of the aforementioned metrics, the matching results between the target object and each of the aforementioned verification information are determined; Based on the matching results between the target object and each of the verification information, the processing information corresponding to the data processing request is determined.

3. The method according to claim 2, characterized in that, The step of determining the matching result between the target object and each of the verification information using the values ​​of the measurement indicators includes: Determine at least one verification condition corresponding to the verification information; Using the values ​​of the aforementioned metrics, the verification results of each verification condition for the target object are determined; Based on the verification results corresponding to each of the verification conditions, the matching result between the target object and the verification information is determined.

4. The method according to claim 3, characterized in that, The at least one verification condition includes: a first type of condition, which corresponds to a single measurement indicator; The step of determining the verification result of each verification condition for the target object using the values ​​of the measurement indicators includes: From the at least one measurement index, determine the target index corresponding to the first type of condition; Determine the indicator parameters and parameter operations corresponding to the first type of condition; Based on the value of the target indicator, the indicator parameters, and the parameter operations, the verification result of the first type of conditions for the target object is determined.

5. The method according to claim 3, characterized in that, The at least one verification condition includes: a second type of condition, which corresponds to multiple measurement indicators; The step of determining the verification result of each verification condition for the target object using the values ​​of the measurement indicators includes: From the at least one measurement index, determine multiple target indicators corresponding to the second type of condition; For each target indicator, determine the indicator parameters and parameter operations corresponding to the target indicator under the second type of condition; based on the value of the target indicator, the indicator parameters and the parameter operations, determine the verification result corresponding to the target indicator; Based on the verification results corresponding to each of the target indicators, the verification results of the second type of conditions for the target object are determined.

6. The method according to claim 5, characterized in that, The step of determining the verification result of the second type of condition for the target object based on the verification results corresponding to each of the target indicators includes: Determine the combination information corresponding to the second type of conditions; Based on the combined information, the verification results corresponding to each of the target indicators are combined to generate a rule expression corresponding to the second type of condition; The calculation result of the rule expression is determined, and the calculation result is determined as the verification result of the second type of condition for the target object.

7. The method according to claim 1, characterized in that, The step of processing business data on the target object based on the processing information includes: Determine the target table, target fields, and processing method corresponding to the processing information; The data of the target object corresponding to the target field in the target table is processed in the manner described above.

8. A data processing apparatus, characterized in that, include: The request receiving module is used to receive data processing requests and determine the target object and business type corresponding to the data processing request. The metric acquisition module is used to acquire the data source and at least one metric corresponding to the business type; wherein, the data source corresponds to a file path or network link; and the metric is used to describe the parameters of the target object. The statement locating module is used to locate the descriptive statement of the target object from the data source; wherein the descriptive statement is a statement used to describe the information of the target object; The value extraction module is used to call the extraction component corresponding to each of the measurement indicators to extract the value of each of the measurement indicators from the description statement. The value extraction module is specifically used for: performing word segmentation on the description statement to obtain multiple word segments of the description statement; calling the extraction component corresponding to the measurement indicator to determine the target word segment that matches the extraction information corresponding to the measurement indicator from the multiple word segments, and using the target word segment as the value of the measurement indicator; The processing module is used to determine the processing information corresponding to the data processing request based on the value of the measurement indicator, and to perform business data processing on the target object based on the processing information.

9. The apparatus according to claim 8, characterized in that, The processing module is specifically used for: Determine at least one verification piece corresponding to the business type; Using the values ​​of the aforementioned metrics, the matching results between the target object and each of the aforementioned verification information are determined; Based on the matching results between the target object and each of the verification information, the processing information of the target object corresponding to the data processing request is determined.

10. The apparatus according to claim 9, characterized in that, The processing module is specifically used for: Determine at least one verification condition corresponding to the verification information; Using the values ​​of the aforementioned metrics, the verification results of each verification condition for the target object are determined; Based on the verification results corresponding to each of the verification conditions, the matching result between the target object and the verification information is determined.

11. An electronic device, characterized in that, include: One or more processors; 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 implement the method as described in any one of claims 1-7.

12. A computer-readable medium having a computer program stored thereon, characterized in that... When the program is executed by the processor, it implements the method as described in any one of claims 1-7.

13. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-7.

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