Data processing method, system, electronic device and medium

Abstract

The present invention discloses a data processing method, system, electronic device and medium, the data processing method comprising: obtaining target processing data and at least one field name corresponding to the target processing data; obtaining processing instructions for the field names, parsing the processing instructions and obtaining data processing logic, the data processing logic being used to characterize specific operations on the target processing data; selecting a data processing model corresponding to the processing instructions based on the processing instructions, wherein the data processing model includes an objective function corresponding to the data processing logic; processing the target processing data based on the objective function, the field name and the data processing logic. The data processing method of the present invention realizes the selection of a corresponding data processing model according to the target processing data to be processed, realizes the adaptation of the target processing data and the data processing model, effectively meets the data processing needs of users, and improves the flexibility and processing efficiency of data processing.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a data processing method, system, electronic equipment and medium. Background Art

[0002] Currently, financial personnel mostly need to configure data processing logic through Excel (an office software) to process financial data when performing financial calculations. Different customers have different calculation requirements, so the calculation logic needs to be customized, and the communication time between the two parties is long. The existing calculation tools mainly configure data processing logic through Excel, but the data processing logic can only use the functions supported by Excel software through Excel configuration. There are fewer types of functions and custom functions cannot be implemented.

[0003] When using existing measurement tools to process data, only the measurement logic that comes with the measurement tool can be used. There are few types of measurement logic and it is not flexible enough to use. It cannot provide users with customized data processing logic and cannot effectively meet users' data processing needs, thus reducing the flexibility and efficiency of data processing. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the defect in the prior art that when using existing measurement tools to process data, only the measurement logic provided by the measurement tool can be used, the types of measurement logic are few, and the use is not flexible enough, and it is impossible to provide users with customized data processing logic, which cannot effectively meet the data processing needs of users, and reduces the flexibility and processing efficiency of data processing. A data processing method, system, electronic device and medium are provided.

[0005] The present invention solves the above technical problems through the following technical solutions:

[0006] In a first aspect, a data processing method is provided, the data processing method comprising:

[0007] Acquire target processing data and at least one field name corresponding to the target processing data;

[0008] Obtaining a processing instruction for the field name, parsing the processing instruction and obtaining a data processing logic, wherein the data processing logic is used to represent a specific operation on the target processing data;

[0009] Selecting a data processing model corresponding to the processing instruction based on the processing instruction, wherein the data processing model includes an objective function corresponding to the data processing logic;

[0010] The target processing data is processed based on the target function, the field name and the data processing logic.

[0011] The data processing method of the present invention obtains target processing data and at least one field name corresponding to the target processing data, obtains processing instructions for the field names, parses the processing instructions and obtains data processing logic, and selects a data processing model corresponding to the processing instructions based on the processing instructions, wherein the data processing model includes an objective function corresponding to the data processing logic, and processes the target processing data based on the objective function, the field name and the data processing logic, thereby realizing the selection of the corresponding data processing model according to the target processing data to be processed, realizing the adaptation of the target processing data and the data processing model, effectively meeting the data processing needs of users, and improving the flexibility and processing efficiency of data processing.

[0012] Preferably, the step of selecting a data processing model corresponding to the processing instruction based on the processing instruction specifically includes:

[0013] Acquire the data type of the target processing data;

[0014] Selecting a corresponding objective function from a data processing model based on the data type and the data processing logic;

[0015] The processable data type of the objective function is consistent with the data type of the target processing data.

[0016] The data processing method of the present invention obtains the data type of the target processing data; selects the corresponding target function from the data processing model based on the data type and the data processing logic; the processable data type of the target function is consistent with the data type of the target processing data, effectively verifies the processing instructions, eliminates erroneous processing instructions, and prevents data processing based on erroneous processing instructions, thereby reducing the time spent on data processing and further improving the efficiency of data processing.

[0017] Preferably, the data processing model includes multiple objective functions, multiple field names and multiple data processing logics, and each objective function, each field name and each data processing logic has a corresponding correspondence;

[0018] The data processing method constructs the data processing model through the following steps, specifically including:

[0019] Obtain any processing instruction, parse the processing instruction and obtain corresponding data processing logic;

[0020] Acquire an objective function corresponding to the data processing logic;

[0021] The correspondence between the field name, the data processing logic and the target function is obtained, and a data processing model for executing any one of the processing instructions is constructed based on the correspondence.

[0022] The data processing method of the present invention, relying on the constructed data processing model, realizes the construction of corresponding data processing models for different processing instructions. When a specific processing instruction is obtained, the data processing model corresponding to the processing instruction is selected, thereby realizing the operation and processing of data corresponding to different processing instructions, different processing data, and different field names, further meeting the user's data processing needs and further improving the flexibility of data processing.

[0023] Preferably, the processing instructions include historical processing instructions and current processing instructions;

[0024] The step of selecting a data processing model corresponding to the processing instruction based on the processing instruction further includes:

[0025] Acquire historical processing instructions and respective data processing models corresponding to respective historical processing instructions;

[0026] Encoding each of the data processing models to generate a model ID (Identification), wherein the model ID is used to characterize the corresponding relationship between each historical processing instruction and each data processing model;

[0027] Acquire new target processing data and the current processing instruction corresponding to the new target processing data;

[0028] Determining whether there is a target instruction matching the current processing instruction in the historical processing instructions;

[0029] If yes, then obtaining the target model ID corresponding to the target instruction, and processing the new target processing data based on the target data processing model corresponding to the target model ID;

[0030] If not, the new target processing data is processed based on the target function, the field name and the data processing logic.

[0031] The data processing method of the present invention encodes the data processing model corresponding to the historical processing instructions to obtain the model ID. When it is necessary to process the new target processing data according to the current processing instruction, it is determined whether there is a target instruction matching the current processing instruction in the historical processing instructions. If so, the target model ID corresponding to the target instruction is obtained, and the new target processing data is processed based on the target data processing model corresponding to the target model ID. There is no need to select the data processing model corresponding to the current processing instruction based on the current processing instruction, and the target processing data corresponding to the current processing instruction can be directly called for processing, which further improves the flexibility and efficiency of data processing.

[0032] In a second aspect, a data processing system is provided, the data processing system comprising:

[0033] A data acquisition module, used to acquire target processing data and at least one field name corresponding to the target processing data;

[0034] An instruction acquisition module, used to acquire a processing instruction for the field name, parse the processing instruction and obtain a data processing logic, wherein the data processing logic is used to represent a specific operation on the target processing data;

[0035] A screening module, configured to select a data processing model corresponding to the processing instruction based on the processing instruction, wherein the data processing model includes an objective function corresponding to the data processing logic;

[0036] A data processing module is used to process the target processing data based on the target function, the field name and the data processing logic.

[0037] Preferably, the screening module comprises:

[0038] A type acquisition unit, used to acquire the data type of the target processing data;

[0039] A function selection unit, configured to select a corresponding target function from a data processing model based on the data type and the data processing logic;

[0040] The processable data type of the objective function is consistent with the data type of the target processing data.

[0041] Preferably, the data processing model includes multiple objective functions, multiple field names and multiple data processing logics, and each objective function, each field name and each data processing logic has a corresponding correspondence;

[0042] The data processing model includes:

[0043] A first acquisition module, used to acquire any processing instruction, parse the processing instruction and obtain corresponding data processing logic;

[0044] A second acquisition module, used to acquire an objective function corresponding to the data processing logic;

[0045] The third acquisition module is used to obtain the correspondence between the field name, the data processing logic and the target function, and to construct a data processing model for executing any one of the processing instructions based on the correspondence.

[0046] Preferably, the processing instructions include historical processing instructions and current processing instructions;

[0047] The screening module also includes:

[0048] A model acquisition unit, used to acquire historical processing instructions and each data processing model corresponding to each of the historical processing instructions;

[0049] A model encoding unit, used for encoding each of the data processing models to generate a model ID, wherein the model ID is used to represent the corresponding relationship between each of the historical processing instructions and each of the data processing models;

[0050] The data acquisition module is also used to acquire new target processing data;

[0051] The instruction acquisition module is also used to acquire the current processing instruction corresponding to the new target processing data;

[0052] An instruction judging unit, used for judging whether there is a target instruction matching the current processing instruction in the historical processing instructions;

[0053] If yes, the data processing module is used to obtain the target model ID corresponding to the target instruction; and process the new target processing data based on the target data processing model corresponding to the target model ID;

[0054] If not, the data processing module is used to process the new target processing data based on the target function, the field name and the data processing logic.

[0055] The data processing system of the present invention, through the mutual cooperation between various modules and units, realizes the selection of the corresponding data processing model according to the target processing data to be processed, realizes the adaptation of the target processing data and the data processing model, effectively meets the data processing needs of users, and improves the flexibility and processing efficiency of data processing.

[0056] According to a third aspect, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any of the above-mentioned data processing methods when executing the computer program.

[0057] According to a fourth aspect, a computer-readable medium is provided, on which computer instructions are stored, and when the computer instructions are executed by a processor, any of the above-mentioned data processing methods is implemented.

[0058] The positive and progressive effects of the present invention are:

[0059] The data processing method of the present invention obtains target processing data and at least one field name corresponding to the target processing data; obtains processing instructions for the field names, parses the processing instructions and obtains data processing logic, wherein the data processing logic is used to characterize specific operations on the target processing data; selects a data processing model corresponding to the processing instructions based on the processing instructions, wherein the data processing model includes an objective function corresponding to the data processing logic; processes the target processing data based on the objective function, the field name and the data processing logic; realizes the selection of the corresponding data processing model according to the target processing data to be processed, realizes the adaptation of the target processing data and the data processing model, effectively meets the data processing needs of users, and improves the flexibility and processing efficiency of data processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 A flowchart of a data processing method provided in Example 1 of the present invention;

[0061] Figure 2 A schematic diagram of a flow chart of another data processing method provided in Embodiment 1 of the present invention;

[0062] Figure 3 A schematic diagram of a flow chart of another data processing method provided in Embodiment 1 of the present invention;

[0063] Figure 4 A schematic diagram of a flow chart of another data processing method provided in Embodiment 1 of the present invention;

[0064] Figure 5 A schematic diagram of the structure of a data processing system provided in Embodiment 2 of the present invention;

[0065] Figure 6 A schematic diagram of the structure of an electronic device provided in Example 3 of the present invention. DETAILED DESCRIPTION

[0066] The present invention is further described below by way of examples, but the present invention is not limited to the scope of the examples.

[0067] Example 1

[0068] This embodiment provides a data processing method. Figure 1 A flow chart of a data processing method provided in this embodiment is as follows: Figure 1 As shown, the data processing method of this embodiment includes:

[0069] Step 101: Obtain target processing data and at least one field name corresponding to the target processing data.

[0070] In this step, firstly, the target data to be processed by the user is obtained. The target data can be summarized table data, where the row title of each row or the column title of each column is called the field name, and the field name is used to characterize the data characteristics of the data content under the field name. There can be multiple corresponding field names in the target data.

[0071] Step 102: Get the processing instruction for the field name, parse the processing instruction and obtain the data processing logic.

[0072] The data processing logic is used to represent the specific operations on the target processing data.

[0073] In this step, the user's processing instructions based on the field name, that is, the processing instructions for the target data, are obtained, and the target processing instructions are parsed to obtain the data processing logic. The data processing logic is used to represent that the user wants to perform certain specific data calculation operations on the target data.

[0074] Step 103: Select a data processing model corresponding to the processing instruction based on the processing instruction.

[0075] The data processing model includes an objective function corresponding to the data processing logic.

[0076] In this step, since the target processing data corresponds to multiple field names, the processing instruction contains specific operation objects, that is, it includes data processing for a certain field name or all field names. Based on the field name information contained in the processing instruction, the data processing model corresponding to the field name is selected. The data processing model includes the objective function corresponding to the data processing logic, and the objective function is the functional expression of the data processing logic.

[0077] Step 104: Process the target processing data based on the target function, field name and data processing logic.

[0078] The data processing method in this embodiment obtains the target processing data and at least one field name corresponding to the target processing data, obtains the processing instructions for the field names, parses the processing instructions and obtains the data processing logic, and selects the data processing model corresponding to the processing instructions based on the processing instructions, wherein the data processing model includes the objective function corresponding to the data processing logic, and processes the target processing data based on the objective function, the field name and the data processing logic, thereby realizing the selection of the corresponding data processing model according to the target processing data to be processed, realizing the adaptation of the target processing data and the data processing model, effectively meeting the data processing needs of users, and improving the flexibility and processing efficiency of data processing.

[0079] In an alternative embodiment, Figure 2 A flow chart of a data processing method provided in this embodiment is as follows: Figure 2 As shown, the above step 103 specifically includes:

[0080] Step 1031: Obtain the data type of the target processing data.

[0081] Step 1032: Select a corresponding objective function from the data processing model based on the data type and data processing logic.

[0082] The processable data type of the target function is consistent with the data type of the target processing data.

[0083] In this step, the processable data type of the target function is consistent with the data type of the target processing data, for example, both are letter type, number type or string type. If the processable data type of the target function is inconsistent with the data type of the target processing data, it indicates that the target function cannot process the target processing data, and then the processing instructions are effectively verified, the wrong processing instructions are eliminated, and data processing is prevented according to the wrong processing instructions, which reduces the time spent on data processing and further improves the efficiency of data processing.

[0084] In an optional implementation, the data processing model includes multiple objective functions, multiple field names, and multiple data processing logics, and each objective function, each field name, and each data processing logic has a corresponding relationship; Figure 3 A method for constructing a data processing model provided in this embodiment, such as Figure 3 As shown, the method for constructing the data processing model of this embodiment specifically includes:

[0085] Step 201: Obtain any processing instruction, parse the processing instruction and obtain corresponding data processing logic.

[0086] In this step, the processing instruction includes the data processing logic for which field names.

[0087] Step 202: Obtain an objective function corresponding to the data processing logic;

[0088] In this step, the target function corresponding to the data processing logic is selected from the function library corresponding to the data processing model.

[0089] Step 203: Obtain the correspondence between the field name, data processing logic and the target function, and build a data processing model for executing any processing instruction based on the correspondence.

[0090] The data processing model includes multiple objective functions, multiple field names and multiple data processing logics. Each objective function, each field name and each data processing logic has a corresponding correspondence. Based on a field name, a data processing logic and a target function corresponding to a processing instruction obtained, the correspondence between the field name, the data processing logic and the objective function is determined, and based on the correspondence, a data processing model for executing the processing instruction is constructed.

[0091] The data processing method of this embodiment relies on the constructed data processing model to realize the construction of corresponding data processing models for different processing instructions. When the specific processing instructions are obtained, the data processing model corresponding to the processing instructions is selected, thereby realizing the operation and processing of data corresponding to different processing instructions, different processing data, and different field names, further meeting the user's data processing needs and further improving the flexibility of data processing.

[0092] In an alternative embodiment, Figure 4 A flowchart of a data processing method provided in this embodiment, wherein the processing instructions include historical processing instructions and current processing instructions; Figure 4 As shown, the above step 103 also includes:

[0093] Step 1033: Obtain historical processing instructions and each data processing model corresponding to each historical processing instruction.

[0094] In this step, the processing instructions include historical processing instructions and current processing instructions. There is a corresponding relationship between the processing instructions and the data models, and each data processing model corresponding to each historical processing instruction is obtained.

[0095] Step 1034: Encode each data processing model and generate a model ID.

[0096] The model ID is used to represent the corresponding relationship between each historical processing instruction and each data processing model.

[0097] In this step, each data processing model is encoded based on the correspondence between each historical processing instruction and each data processing model to generate a model ID.

[0098] Step 1035: Acquire new target processing data and current processing instructions corresponding to the new target processing data.

[0099] Step 1036: Determine whether there is a target instruction in the historical processing instructions that matches the current processing instruction.

[0100] If so, execute step 1037.

[0101] Step 1037: Obtain the target model ID corresponding to the target instruction, and process the new target processing data based on the target data processing model corresponding to the target model ID.

[0102] If not, execute step 1041.

[0103] Step 1041: Process new target processing data based on the target function, field name and data processing logic.

[0104] In this step, a target model ID matching the current processing instruction is selected from multiple data processing models, and new target processing data is processed based on the target data processing model corresponding to the target model ID.

[0105] The data processing method in this embodiment encodes the data processing model corresponding to the historical processing instructions to obtain the model ID. When it is necessary to process the new target processing data according to the current processing instruction, it is determined whether there is a target instruction matching the current processing instruction in the historical processing instructions. If so, the target model ID corresponding to the target instruction is obtained, and the new target processing data is processed based on the target data processing model corresponding to the target model ID. There is no need to select the data processing model corresponding to the current processing instruction based on the current processing instruction, and the target processing data corresponding to the current processing instruction can be directly called for processing, which further improves the flexibility and efficiency of data processing.

[0106] The data processing method of the present invention is further explained below in conjunction with specific application scenarios.

[0107] For example, the user's target processing data is air ticket related data, and the field names corresponding to the air ticket related data include order amount, average monthly transaction amount, service fee amount, service fee collection method, customer name, origin and destination, etc. If the processing instruction is "summarize the total amount of order amounts", then after parsing the processing instruction, it can be known that the corresponding data processing logic is a summation operation, and the corresponding processing object is the order amount. Then, the corresponding summation type data processing model A is selected. The data processing model A includes a "summation function", and the air ticket related data is processed based on the summation function, order amount, and summation operation.

[0108] The data type of the order amount is a numeric type, and the data type that the sum function can process is also a numeric type. When the data type of the order amount is consistent with the data type that the sum function can process, the sum function is selected to perform subsequent data processing operations. If a processing instruction is "sum the user names", after parsing the processing instruction, it can be known that the corresponding data processing logic is a sum operation, but the data type of the user name is a string, and the sum function cannot process string type data. Therefore, there is an error in the processing instruction, and an error prompt instruction can be output to prompt the user.

[0109] If a processing instruction includes multiple field names, such as the processing instruction is "summarize the order amount and service fee amount", the data corresponding to each field name will be processed.

[0110] If a processing instruction is "determine whether the order amount is greater than 500", after analyzing the processing instruction, it can be known that the corresponding data processing logic is a judgment operation, and when the order amount is greater than or equal to 500, the judgment result is qualified, and when the order amount is less than 500, the judgment result is unqualified. The corresponding processing object is the order amount, and the judgment type data processing model B is selected. The data processing model B includes the "IF function (i.e., judgment function)", and assigns "order amount greater than 500, qualified, unqualified" to the IF function, and implements the processing of the order amount based on the assigned IF function.

[0111] The processing instructions are aggregated to form historical processing instructions, and the data processing models corresponding to the historical processing instructions are encoded. For example, if the historical processing instruction a is "aggregate the total amount of order amounts", the data processing model corresponding to the instruction is encoded as A, and the historical processing instruction b is "determine whether the order amount is greater than 500", the data processing model corresponding to the instruction is encoded as B. If a user needs to process new target data such as the air ticket related data in January, and the current processing instruction is "aggregate the total amount of order amounts", it can be determined that there is a target processing instruction a corresponding to the current processing instruction in the historical processing instructions, and the data processing model A corresponding to the target processing instruction a is directly used to process the air ticket related data in January. If it is determined that there is no target processing instruction corresponding to the current processing instruction in the historical processing instructions, the new target processing data is processed based on the target function "summation function", the field name "order amount" and the data processing logic "aggregate the order amount in the air ticket related data in January".

[0112] The data processing model includes multiple objective functions, multiple field names and multiple data processing logics. Each objective function, each field name and each data processing logic has a corresponding correspondence. Based on a field name, a data processing logic and a target function corresponding to a processing instruction obtained, the correspondence between the field name, the data processing logic and the objective function is determined, and based on the correspondence, a data processing model for executing the processing instruction is constructed.

[0113] For example, the target functions include IF function, OR function (or function), AND function (and function), IFERROR function (error judgment function), MAX function (maximum function), MIN function (minimum function), SUM function (sum function), IFEMPTY function (blank judgment function), etc.

[0114] If the target data to be processed by the user corresponds to a new field name, and the new field name does not exist in the existing data model, you can create a new field name or directly create a new data processing model to meet user needs. The following will introduce how to create a new data processing model.

[0115] For example, if a target processing data is the train ticket data for February, the field names corresponding to the data include "order amount and insurance amount, etc.", the processing instruction is "summarize insurance amount", and the data processing logic is "sum operation", then the corresponding relationship between the field name, data processing logic and target function in the processing instruction is determined as: insurance amount-sum function-sum operation. In the new data processing model creation interface, click Add Model to enter the model editing interface, select the field name "insurance amount" in the editing interface and select the target function as the sum function from the function list, save the data processing model, and encode the data processing model corresponding to the processing instruction c "summarize insurance amount" as C. If there are other related data in the data processing logic, such as threshold data set for different functions or other related assignment data, the assignment operation is performed in the model editing interface. Each model editing interface includes a field name editing button that can be used to add, modify or delete field names.

[0116] Example 2

[0117] This embodiment provides a data processing system. Figure 5 A schematic diagram of the structure of a data processing system provided in this embodiment is shown in FIG. Figure 5 As shown, the data processing system includes:

[0118] A data acquisition module 1 is used to acquire target processing data and at least one field name corresponding to the target processing data; an instruction acquisition module 2 is used to acquire processing instructions for the field names, parse the processing instructions and obtain data processing logic, and the data processing logic is used to characterize specific operations on the target processing data; a screening module 3 is used to select a data processing model corresponding to the processing instructions based on the processing instructions, wherein the data processing model includes an objective function corresponding to the data processing logic; a data processing module 4 is used to process the target processing data based on the objective function, the field name and the data processing logic.

[0119] The screening module 3 includes: a type acquisition unit 31, used to obtain the data type of the target processing data; a function selection unit 32, used to select the corresponding target function from the data processing model based on the data type and data processing logic; wherein the processable data type of the target function is consistent with the data type of the target processing data.

[0120] The data processing model includes multiple objective functions, multiple field names and multiple data processing logics, and each objective function, each field name and each data processing logic has a corresponding correspondence; the data processing model specifically includes: a first acquisition module, used to acquire any processing instruction, parse the processing instruction and obtain the corresponding data processing logic; a second acquisition module, used to acquire the objective function corresponding to the data processing logic; a third acquisition module, used to acquire the correspondence between the field name, the data processing logic and the objective function, and construct a data processing model for executing any processing instruction based on the correspondence.

[0121] The processing instructions include historical processing instructions and current processing instructions; the screening module 3 also includes a model acquisition unit 33, which is used to acquire historical processing instructions and various data processing models corresponding to each historical processing instruction; a model encoding unit 34, which is used to encode each data processing model and generate a model ID, wherein the model ID is used to characterize the correspondence between each historical processing instruction and each data processing model; the data acquisition module 1 is also used to acquire new target processing data; the instruction acquisition module 2 is also used to acquire the current processing instruction corresponding to the new target processing data; the instruction judgment unit 35 is used to judge whether there is a target instruction matching the current processing instruction in the historical processing instructions; if so, the data processing module 4 is used to acquire the target model ID corresponding to the target instruction; and the new target processing data is processed based on the target data processing model corresponding to the target model ID; if not, the data processing module 4 is used to process the new target processing data based on the target function, field name and data processing logic.

[0122] The data processing system of this embodiment, through the mutual cooperation between various modules and units, realizes the selection of the corresponding data processing model according to the target processing data to be processed, realizes the adaptation of the target processing data and the data processing model, effectively meets the data processing needs of users, and improves the flexibility and efficiency of data processing.

[0123] Example 3

[0124] This embodiment provides an electronic device, Figure 6 This is a schematic diagram of the structure of an electronic device shown in this embodiment. The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the data processing method in the above-mentioned embodiment 1 is implemented. Figure 6 The electronic device 50 shown is only an example and should not limit the functions and scope of use of the embodiments of the present invention. Figure 6 As shown, the electronic device 50 may be in the form of a general-purpose computing device, for example, it may be a server device. The components of the electronic device 50 may include, but are not limited to: at least one processor 51, at least one memory 52, and a bus 53 connecting different system components (including the memory 52 and the processor 51).

[0125] The bus 53 includes a data bus, an address bus, and a control bus.

[0126] The memory 52 may include a volatile memory, such as a random access memory (RAM) 521 and / or a cache memory 522 , and may further include a read-only memory (ROM) 523 .

[0127] The memory 52 may also include a program tool 525 (or utility) having a set (at least one) of program modules 524, such program modules 524 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0128] The processor 51 executes various functional applications and data processing by running the computer programs stored in the memory 52, such as the data processing method in the above-mentioned embodiment 1.

[0129] The electronic device 50 may also communicate with one or more external devices 54. Such communication may be performed via an input / output (I / O) interface 55. Furthermore, the model generating electronic device 50 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 56. Figure 6As shown, the network adapter 56 communicates with other modules of the electronic device 50 via the bus 53. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device 50, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems, etc.

[0130] It should be noted that although several units / modules or sub-units / modules of the electronic device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided into multiple units / modules to be embodied.

[0131] Example 4

[0132] This embodiment provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the data processing method in the above-mentioned embodiment 1 is implemented.

[0133] The readable storage medium may include but is not limited to: a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device or any suitable combination of the above.

[0134] In a possible implementation manner, the present invention may also be implemented in the form of a program product, which includes program code. When the program product runs on a terminal device, the program code is used to enable the terminal device to execute the steps in the data processing method in the above-mentioned embodiment 1.

[0135] Among them, the program code for executing the present invention can be written in any combination of one or more programming languages, and the program code can be executed completely on the user device, partially on the user device, as an independent software package, partially on the user device and partially on a remote device, or completely on the remote device.

[0136] Although the specific embodiments of the present invention are described above, it should be understood by those skilled in the art that this is only for illustration and the protection scope of the present invention is defined by the appended claims. Those skilled in the art may make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but these changes and modifications all fall within the protection scope of the present invention.

Claims

1. A data processing method, characterized in that: The data processing method comprises: Acquire target processing data and at least one field name corresponding to the target processing data; Obtaining a processing instruction for the field name, parsing the processing instruction and obtaining a data processing logic, wherein the data processing logic is used to represent a specific operation on the target processing data; Selecting a data processing model corresponding to the processing instruction based on the processing instruction, wherein the data processing model includes an objective function corresponding to the data processing logic; Processing the target processing data based on the target function, the field name and the data processing logic; The data processing model includes multiple objective functions, multiple field names and multiple data processing logics, and each objective function, each field name and each data processing logic has a corresponding correspondence; The data processing method constructs the data processing model through the following steps, specifically including: Obtain any processing instruction, parse the processing instruction and obtain corresponding data processing logic; Acquire an objective function corresponding to the data processing logic; The correspondence between the field name, the data processing logic and the target function is obtained, and a data processing model for executing any one of the processing instructions is constructed based on the correspondence.

2. The data processing method according to claim 1, characterized in that: The step of selecting a data processing model corresponding to the processing instruction based on the processing instruction specifically includes: Acquire the data type of the target processing data; Selecting a corresponding objective function from a data processing model based on the data type and the data processing logic; The processable data type of the objective function is consistent with the data type of the target processing data.

3. The data processing method according to claim 1, characterized in that: The processing instructions include historical processing instructions and current processing instructions; The step of selecting a data processing model corresponding to the processing instruction based on the processing instruction further includes: Acquire historical processing instructions and respective data processing models corresponding to respective historical processing instructions; Encoding each of the data processing models to generate a model ID, wherein the model ID is used to characterize the corresponding relationship between each of the historical processing instructions and each of the data processing models; Acquire new target processing data and the current processing instruction corresponding to the new target processing data; Determining whether there is a target instruction matching the current processing instruction in the historical processing instructions; If yes, then obtaining the target model ID corresponding to the target instruction, and processing the new target processing data based on the target data processing model corresponding to the target model ID; If not, the new target processing data is processed based on the target function, the field name and the data processing logic.

4. A data processing system, characterized in that: The data processing system comprises: A data acquisition module, used to acquire target processing data and at least one field name corresponding to the target processing data; An instruction acquisition module, used to acquire a processing instruction for the field name, parse the processing instruction and obtain a data processing logic, wherein the data processing logic is used to represent a specific operation on the target processing data; A screening module, configured to select a data processing model corresponding to the processing instruction based on the processing instruction, wherein the data processing model includes an objective function corresponding to the data processing logic; A data processing module, used for processing the target processing data based on the target function, the field name and the data processing logic; The data processing model includes multiple objective functions, multiple field names and multiple data processing logics, and each objective function, each field name and each data processing logic has a corresponding correspondence; The data processing model includes: A first acquisition module, used to acquire any processing instruction, parse the processing instruction and obtain corresponding data processing logic; A second acquisition module, used to acquire an objective function corresponding to the data processing logic; The third acquisition module is used to obtain the correspondence between the field name, the data processing logic and the target function, and to construct a data processing model for executing any one of the processing instructions based on the correspondence.

5. The data processing system according to claim 4, characterized in that: The screening module comprises: A type acquisition unit, used to acquire the data type of the target processing data; A function selection unit, configured to select a corresponding target function from a data processing model based on the data type and the data processing logic; The processable data type of the objective function is consistent with the data type of the target processing data.

6. The data processing system according to claim 4, characterized in that: The processing instructions include historical processing instructions and current processing instructions; The screening module also includes: A model acquisition unit, used to acquire historical processing instructions and each data processing model corresponding to each of the historical processing instructions; A model encoding unit, used for encoding each of the data processing models to generate a model ID, wherein the model ID is used to represent the corresponding relationship between each of the historical processing instructions and each of the data processing models; The data acquisition module is also used to acquire new target processing data; The instruction acquisition module is also used to acquire the current processing instruction corresponding to the new target processing data; An instruction judging unit, used for judging whether there is a target instruction matching the current processing instruction in the historical processing instructions; If yes, the data processing module is used to obtain the target model ID corresponding to the target instruction; and process the new target processing data based on the target data processing model corresponding to the target model ID; If not, the data processing module is used to process the new target processing data based on the target function, the field name and the data processing logic.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the data processing method according to any one of claims 1 to 3 is implemented.

8. A computer readable medium having computer instructions stored thereon, characterized in that: When the computer instructions are executed by a processor, the data processing method according to any one of claims 1 to 3 is implemented.

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