Data Processing Method, Apparatus, Electronic Device and Computer-Readable Storage Medium

Abstract

The present invention discloses a data processing method, apparatus, electronic device, and computer-readable storage medium. Among them, the method includes: determining a first data volume used by a target object once when executing a target task according to the behavior data of the target object and the target task; determining a second data volume allocated to the target object by a server; determining a third data volume used by the target object when executing the target task within a predetermined time period according to the first data volume used by the target object once when executing the target task; subtracting the third data volume from the second data volume to obtain a data volume difference; and restricting the number of times the target object executes the target task within the predetermined time period when the data volume difference is greater than a predetermined threshold. The present invention solves the technical problem that in the related art, when performing frequency limiting processing, the processing method is too simple, and the obtained processing result does not meet the user's expectations.

Description

Technical Field

[0001] The present invention relates to the field of computers, and in particular, to a data processing method, apparatus, electronic device, and computer-readable storage medium. Background Art

[0002] Traditional request frequency limiting methods include caching, degradation, token bucket algorithms, etc. However, these methods all perform request limiting operations on the client side, which is too single and not flexible enough.

[0003] In response to the above problems, no effective solution has been proposed yet. Summary of the Invention

[0004] Embodiments of the present invention provide a data processing method, apparatus, electronic device, and computer-readable storage medium to at least solve the technical problem that in the related art, when performing frequency limiting processing, the processing method is too simple and the obtained processing result does not meet the user's expectations.

[0005] According to one aspect of the embodiments of the present invention, a data processing method is provided, including: determining a first data amount used by the target object for each execution of the target task according to the behavior data of the target object and the target task; determining a second data amount allocated by the server to the target object; determining a third data amount used by the target object for executing the target task within a predetermined time period according to the first data amount used by the target object for each execution of the target task; calculating the difference between the third data amount and the second data amount to obtain a data amount difference; and restricting the number of times the target object executes the target task within the predetermined time period when the data amount difference is greater than a predetermined threshold.

[0006] Optionally, the determining a first data amount used by the target object for each execution of the target task according to the behavior data of the target object and the target task includes: determining the activity level of the target object according to the behavior data of the target object; determining the importance level of the target task according to the target task; and determining the first data amount used by the target object for each execution of the target task according to the activity level of the target object and the importance level of the target task.

[0007] Optionally, the determining a second data amount allocated by the server to the target object includes: obtaining the total data amount of the server; determining an allocation ratio according to the total data amount of the server, the activity level of the target object, the importance level of the target task, and the first data amount used by the target object for each execution of the target task; and determining the second data amount allocated by the server to the target object according to the allocation ratio.

[0008] Optionally, determining the allocation ratio according to the total amount of data of the server, the activity level of the target object, the importance level of the target task, and the first data amount used by the target object each time when executing the target task includes: determining the ratio of the first data amount used by the target object each time when executing the target task to the total amount of data of the server; allocating weight values corresponding to the activity level of the target object and the importance level of the target task; and determining the allocation ratio according to the ratio, the activity level of the target object after allocating the weight values, and the importance level of the target task.

[0009] Optionally, determining the third data amount used by the target object when executing the target task within a predetermined time period according to the first data amount used by the target object each time when executing the target task includes: determining the number of times the target object executes the target task within the predetermined time period; and when the number of times is not zero, determining the product of the first data amount used by the target object each time when executing the target task and the number of times the target object executes the target task within the predetermined time period as the third data amount used by the target object when executing the target task within the predetermined time period.

[0010] Optionally, it further includes: when the data amount difference is less than or equal to the predetermined threshold, incrementing the number of times the target object executes the target task within the predetermined time period by one, and re-determining the third data amount used by the target object when executing the target task within the predetermined time period.

[0011] According to one aspect of an embodiment of the present invention, there is provided a data processing apparatus, including: a first determination module, configured to determine the first data amount used by the target object each time when executing the target task according to the behavior data of the target object and the target task; a second determination module, configured to determine the second data amount allocated by the server to the target object; a third determination module, configured to determine the third data amount used by the target object when executing the target task within a predetermined time period according to the first data amount used by the target object each time when executing the target task; a difference-making module, configured to make a difference between the third data amount and the second data amount to obtain a data amount difference; and a restriction module, configured to restrict the number of times the target object executes the target task within the predetermined time period when the data amount difference is greater than the predetermined threshold.

[0012] According to one aspect of an embodiment of the present invention, there is provided an electronic device, including: a processor; and a memory for storing instructions executable by the processor; wherein, the processor is configured to execute the instructions to implement the data processing method described in any one of the above.

[0013] According to one aspect of an embodiment of the present invention, there is provided a computer-readable storage medium, which enables an electronic device to execute the data processing method described in any one of the above when the instructions in the computer-readable storage medium are executed by a processor of the electronic device.

[0014] According to one aspect of an embodiment of the present invention, there is provided a computer program product including a computer program, which implements the data processing method described in any one of the above when executed by a processor.

[0015] In an embodiment of the present invention, based on the behavior data of a target object and a target task, a first data volume used by the target object for a single execution of the target task is determined, and a second data volume allocated to the target object by a server is determined. Based on the first data volume used by the target object for a single execution of the target task, a third data volume used by the target object for executing the target task within a predetermined time period is determined. Then, the difference between the third data volume and the second data volume is calculated to obtain a data volume difference. When the data volume difference is greater than a predetermined threshold, the number of times the target object executes the target task within the predetermined time period is restricted. Since the frequency limit determination is made based on the data volume difference, that is, determined according to the behavior data of the target object and the target task, it is jointly determined according to a specific target object and a specific target task, which is targeted. It not only considers the business requirements but also the behavior of the target object, meets the expectations of the target object, and solves the technical problem in the related art that when performing frequency limit processing, the processing method is too simple and the processing result does not meet the user's expectations. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present invention, form a part of this application, and the schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0017] Figure 1 is a flowchart of the data processing method according to an embodiment of the present invention;

[0018] Figure 2 is a schematic diagram of the frequency limit method provided by an alternative embodiment of the present invention;

[0019] Figure 3 is a flowchart of the frequency limit method provided by an alternative embodiment of the present invention;

[0020] Figure 4 is a block diagram of the structure of the data processing device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] To enable those skilled in the art to better understand the solution of the present invention, the following will clearly and completely describe the technical solution in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned accompanying drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such data used in appropriate cases can be interchanged so that the embodiments of the present invention described herein can be implemented in an order different from those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0023] Embodiment 1

[0024] According to an embodiment of the present invention, an embodiment of a data processing method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order from that here.

[0025] Figure 1 is a flowchart of the data processing method according to an embodiment of the present invention. As Figure 1 shown, the method includes the following steps:

[0026] Step S102, determine the first data volume used once by the target object when executing the target task according to the behavior data of the target object and the target task;

[0027] Step S104, determine the second data volume allocated by the server to the target object;

[0028] Step S106, determine the third data volume used by the target object when executing the target task within a predetermined time period according to the first data volume used once by the target object when executing the target task;

[0029] Step S108, subtract the second data volume from the third data volume to obtain a data volume difference;

[0030] Step S110, when the data volume difference is greater than a predetermined threshold, limit the number of times the target object performs the target task within a predetermined time period.

[0031] Through the above steps, based on the behavior data of the target object and the target task, determine the first data volume used by the target object for each single execution of the target task, and determine the second data volume allocated by the server to the target object. Based on the first data volume used by the target object for each single execution of the target task, determine the third data volume used by the target object for performing the target task within a predetermined time period. Then, subtract the third data volume from the second data volume to obtain the data volume difference. When the data volume difference is greater than the predetermined threshold, limit the number of times the target object performs the target task within a predetermined time period. Since the frequency limit judgment is based on the data volume difference, that is, determined according to the behavior data of the target object and the target task, therefore, it is jointly determined by a specific target object and a specific target task, which is targeted. It not only considers the business requirements but also the behavior of the target object, meets the expectations of the target object, and solves the technical problem that in the related art, when performing frequency limit processing, the processing method is too simple and the processing result does not meet the user's expectations.

[0032] As an optional embodiment, based on the behavior data of the target object and the target task, determine the first data volume used by the target object for each single execution of the target task. Among them, the target task can be multiple types. For example, it can be an access request to the server without distinguishing the accessed data and operations; it can also be a certain type of access request to the server, that is, the accessed data and operations are restricted. It can be set customarily according to the actual application and scenario. When determining the first data volume used by the target object for each single execution of the target task based on the behavior data of the target object and the target task, first determine the activity level of the target object based on the behavior data of the target object, and determine the importance level of the target task based on the target task. Generally speaking, the higher the activity level of the target object, the smaller the first data volume set for each single use, that is, it can provide convenience for active target objects. The more important the target task, the smaller the first data volume set for each single use, that is, for important tasks, they can be completed in a shorter time, or with less data volume, thus accelerating the execution of the tasks. Determine the first data volume used by the target object for each single execution of the target task based on the activity level of the target object and the importance level of the target task. Make the determined first data volume used by the target object for each single execution of the target task reasonable and considered from multiple aspects, which is more in line with the expectations of the target object.

[0033] As an alternative embodiment, determine the second data volume allocated by the server to the target object. Since the server can allocate data volumes to multiple terminal devices and the total data volume of the server is fixed, it is necessary to determine the second data volume allocated by the server to the target object according to the actual situation for subsequent operations. There are various ways to determine the second data volume allocated by the server to the target object. For example, it can be done in the following way: First, obtain the total data volume of the server for allocation. Then, based on the total data volume of the server, the activity level of the target object, the importance level of the target task, and the first data volume used by the target object each time when performing the target task, determine the allocation ratio. When determining the allocation ratio, the ratio of the first data volume used by the target object each time when performing the target task to the total data volume of the server can be determined. That is, determine the ratio of the data volume used by the target object when performing the target task once to the total data volume. Then, assign corresponding weight values to the activity level of the target object and the importance level of the target task determined above. Based on the ratio, the activity level of the target object after assigning the weight value, and the importance level of the target task, determine the allocation ratio. Based on the allocation ratio, determine the second data volume allocated by the server to the target object. By determining the allocation ratio for allocation, the server can allocate the data volume more appropriately, ensuring that the data volumes received by multiple terminal devices are fair and suitable for each terminal device.

[0034] As an alternative embodiment, based on the first data volume used by the target object each time when performing the target task, determine the third data volume used by the target object when performing the target task within a predetermined time period. It can be determined by determining the number of times the target object performs the target task within the predetermined time period. When the number is not zero, determine the product of the first data volume used by the target object each time when performing the target task and the number of times the target object performs the target task within the predetermined time period as the third data volume used by the target object when performing the target task within the predetermined time period. That is, determine the third data volume used by the target object when performing the target task within the predetermined time period by determining the number of times the target object performs the target task within the predetermined time period. When the number is zero, allow the target object to perform the target task. It can be understood that the more times the target object performs the target task within the predetermined time period, the more data volume is occupied. Therefore, it is necessary to determine whether the second data volume provided by the server can meet the third data volume used by the target object. Based on this, determine whether to perform a frequency limiting operation.

[0035] As an alternative embodiment, when determining whether the second data volume provided by the server can meet the third data volume used by the target object, the third data volume can be subtracted from the second data volume to obtain a data volume difference. When the data volume difference is greater than a predetermined threshold, the number of times the target object executes the target task within a predetermined time period is restricted. When the data volume difference is less than or equal to the predetermined threshold, the number of times the target object executes the target task within the predetermined time period is incremented by one, and the third data volume used by the target object to execute the target task within the predetermined time period is re-determined. That is, when the target object executes the target task once, a judgment is made once. When the second data volume provided by the server cannot meet the third data volume used by the target object, the number of times the target object executes the target task within a predetermined time period is restricted. This is to utilize resources reasonably and effectively.

[0036] Based on the above embodiments and alternative embodiments, an alternative implementation manner is provided, which is specifically described below.

[0037] In an alternative implementation manner of the present invention, a frequency limiting method based on the photoelectric effect equation is provided. By applying the photoelectric effect equation (Ek = hv - W0) and using the principle of the photoelectric effect: in the photoelectric effect, electrons in a metal need to do work to overcome the attraction of the atomic nucleus when flying out of the metal surface, and the amount of work done also varies depending on the electrons and the type of metal. The remaining kinetic energy is calculated. Applying this effect to the frequency limiting method enables frequency limiting of server resources for different levels of users. That is, the remaining kinetic energy of the users carried by the current server is calculated, and when the remaining kinetic energy carried by the current server after user access is insufficient, a frequency limiting operation is automatically performed. Figure 2 is the schematic diagram of the frequency limiting method provided by the alternative implementation manner of the present invention, Figure 3 is the flowchart of the frequency limiting method provided by the alternative implementation manner of the present invention, as Figure 2 、 3 shown. The alternative implementation manner of the present invention is introduced in detail below:

[0038] S1. The user executes the target task, where the target task may refer to a request sent by the terminal side used by the user to the server;

[0039] S2. Query the number of times the user executes the target task, where the executed target task can be represented by key: v + user ID + request name + IP;

[0040] S3. When the number of times of executing the target task is empty, that is, the target task has not been executed, the first execution is allowed, and it jumps to step S6;

[0041] S4. When the number of times of executing the target task is not empty, that is, the target task has been executed, the photoelectric effect equation is applied to calculate Ek. The steps of applying the photoelectric effect are as follows;

[0042] S4.1, Calculate the first data volume used by the user for a single execution of the target task, where the first data volume is represented by h;

[0043] h is the size of the data volume used by the user for one execution of the target task, which is a constant. Depending on the different behavioral data of the user and the different services executed by the target task, calculate the first data volume used by the user for each execution of the target task and assign it to the user, which can be used as h in the photoelectric effect equation;

[0044] It should be noted that the higher the user level or activity, the less data volume the user uses for each execution of the target task, enabling active users to achieve the purpose of executing the target task by consuming less data volume. In the photoelectric effect equation, it can be understood that the less kinetic energy is consumed to break free from the metal each time, so the higher the accessible frequency.

[0045] S4.2, Calculate the second data volume allocated by the server to the user, where the data volume allocated by the server is represented by W0;

[0046] Estimate the total data volume allocated by the server to the user for executing the target task based on the resource configuration of the server currently carrying the target task, the user level, or the activity level. In the photoelectric effect equation, it can be understood as the total kinetic energy, which is used as W0 in the photoelectric effect equation.

[0047] S4.3, Determine the third data volume used by the user for executing the target task within a predetermined time period, where this data volume is represented by hv;

[0048] v is the number of times the user executes the target task, which is stored in the cache and an expiration time is set. Query the number of times v that the user executes the target task in the current server in the cache. If it is not empty, obtain the data volume h used by the user for executing the target task and calculate the data volume used by the user for executing the target task within the predetermined time period. In the photoelectric effect equation, it can be understood as the consumed kinetic energy hv. If v is empty, the user can directly execute the target task without frequency limiting operations.

[0049] S4.4, Application of the photoelectric effect equation;

[0050] Apply the photoelectric effect equation (Ek = hv - W0). After the user executes the target task in the server, calculate the remaining data volume borne by the server for this user. In the photoelectric effect equation, it can be understood as the remaining kinetic energy Ek.

[0051] S5, Frequency Limiting Judgment. According to the result (Ek) calculated in S4, if the result is greater than 0, it is considered that the remaining kinetic energy is insufficient, which means that after the user executes the target task on the current server, the total amount of data allocated by the server for the user to execute the target task is insufficient. Therefore, a frequency limiting operation is performed on this user, that is, the number of times of executing the target task is too many, and access is restricted in order to effectively utilize resources.

[0052] S6, Frequency Limiting Judgment. According to the result (Ek) calculated in S4, if the result is less than or equal to 0, it is considered that the remaining kinetic energy is sufficient, then no processing is performed, and the number of times v of the user executing the target task in the cache is incremented by 1, and the response key: v + user ID + request name + IP is set with an expiration time.

[0053] Through the above optional implementation manners, at least the following beneficial effects can be achieved:

[0054] (1) For specific users, the frequency is dynamically adjusted according to user level, user activity, etc., and the upper limit of executing the target task within a predetermined time is restricted, that is, the frequency and traffic of the user executing the target task are dynamically restricted, improving the flexibility of frequency limiting.

[0055] (2) In the face of a large number of users, equation calculation is used for management and frequency limiting, making the management and maintenance of frequency limiting simpler.

[0056] (3) Effectively protects the stability of the server and terminal devices.

[0057] (4) Comprehensively improves the utilization rate of resources.

[0058] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0059] Through the description of the above implementation manners, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is a better implementation manner. Based on such an understanding, the technical solution of the present invention, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disc), and includes several instructions for causing a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods of the various embodiments of the present invention.

[0060] Example 2

[0061] According to an embodiment of the present invention, there is also provided an apparatus for implementing the above data processing method. Figure 4 It is a structural block diagram of a data processing apparatus according to an embodiment of the present invention, as Figure 4 shown. The apparatus includes: a first determination module 402, a second determination module 404, a third determination module 406, a difference calculation module 408, and a restriction module 410. The following provides a detailed description of the apparatus.

[0062] The first determination module 402 is configured to determine a first data volume used by the target object once when executing the target task according to the behavior data of the target object and the target task; the second determination module 404 is connected to the first determination module 402 and is configured to determine a second data volume allocated by the server to the target object; the third determination module 406 is connected to the second determination module 404 and is configured to determine a third data volume used by the target object when executing the target task within a predetermined time period according to the first data volume used by the target object once when executing the target task; the difference calculation module 408 is connected to the third determination module 406 and is configured to subtract the second data volume from the third data volume to obtain a data volume difference; the restriction module 410 is connected to the difference calculation module 408 and is configured to restrict the number of times the target object executes the target task within a predetermined time period when the data volume difference is greater than a predetermined threshold.

[0063] It should be noted here that the above first determination module 402, second determination module 404, third determination module 406, difference calculation module 408, and restriction module 410 correspond to steps S102 to S110 in the implementation of the data processing method. The instances and application scenarios implemented by multiple modules and the corresponding steps are the same, but are not limited to the content disclosed in the above Example 1.

[0064] Example 3

[0065] According to another aspect of an embodiment of the present invention, there is also provided an electronic device, including: a processor; a memory for storing processor-executable instructions, wherein the processor is configured to execute the instructions to implement the data processing method of any one of the above.

[0066] Example 4

[0067] According to another aspect of an embodiment of the present invention, there is also provided a computer-readable storage medium. When the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device can execute the data processing method of any one of the above.

[0068] Example 5

[0069] According to another aspect of the embodiments of the present invention, there is also provided a computer program product, including a computer program, characterized in that when the computer program is executed by a processor, it implements the data processing method described in any one of the above.

[0070] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments.

[0071] In the above embodiments of the present invention, the descriptions of the respective embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0072] In the several embodiments provided in the present application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only illustrative. For example, the division of the units can be a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the units or modules can be in electrical or other forms.

[0073] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0074] In addition, in each embodiment of the present invention, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0075] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, read-only memories (ROMs), random access memories (RAMs), mobile hard disks, magnetic disks, or optical discs.

[0076] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A data processing method, characterized in that, comprising: determining a first data volume used by the target object once when executing the target task according to the behavior data of the target object and the target task; determining a second data volume allocated to the target object by the server; determining a third data volume used by the target object when executing the target task within a predetermined time period according to the first data volume used by the target object once when executing the target task; subtracting the third data volume from the second data volume to obtain a data volume difference; when the data volume difference is greater than a predetermined threshold, restricting the number of times the target object executes the target task within the predetermined time period; wherein, determining the second data volume allocated to the target object by the server includes: obtaining the total data volume of the server; determining an allocation ratio according to the total data volume of the server, the activity level of the target object, the importance level of the target task, and the first data volume used by the target object once when executing the target task; determining the second data volume allocated to the target object by the server according to the allocation ratio.

2. The method according to claim 1, characterized in that, the determining a first data volume used by the target object once when executing the target task according to the behavior data of the target object and the target task includes: determining the activity level of the target object according to the behavior data of the target object; determining the importance level of the target task according to the target task; determining a first data volume used by the target object once when executing the target task according to the activity level of the target object and the importance level of the target task.

3. The method according to claim 1, characterized in that, the determining an allocation ratio according to the total data volume of the server, the activity level of the target object, the importance level of the target task, and the first data volume used by the target object once when executing the target task includes: determining the ratio of the first data volume used by the target object once when executing the target task to the total data volume of the server; allocating weight values corresponding to the activity level of the target object and the importance level of the target task; determining the allocation ratio according to the ratio, the activity level of the target object after allocating the weight value, and the importance level of the target task.

4. The method according to claim 1, characterized in that, the determining a third data volume used by the target object when executing the target task within a predetermined time period according to the first data volume used by the target object once when executing the target task includes: determining the number of times the target object executes the target task within a predetermined time period; when the number is not zero, determining the product of the first data volume used by the target object once when executing the target task and the number of times the target object executes the target task within a predetermined time period as the third data volume used by the target object when executing the target task within a predetermined time period.

5. The method according to claim 4, wherein, it further comprises: when the data volume difference is less than or equal to the predetermined threshold, incrementing the number of times the target object executes the target task within a predetermined time period by one, and re-determining the third data volume used by the target object to execute the target task within the predetermined time period.

6. A data processing apparatus, wherein, it comprises: a first determination module, configured to determine a first data volume used per time by the target object when executing the target task according to the behavior data of the target object and the target task; a second determination module, configured to determine a second data volume allocated by the server to the target object; a third determination module, configured to determine a third data volume used by the target object to execute the target task within a predetermined time period according to the first data volume used per time by the target object when executing the target task; a difference-making module, configured to make a difference between the third data volume and the second data volume to obtain a data volume difference; a restriction module, configured to restrict the number of times the target object executes the target task within the predetermined time period when the data volume difference is greater than a predetermined threshold; wherein, the second determination module is further configured to obtain the total data volume of the server; determine an allocation ratio according to the total data volume of the server, the activity level of the target object, the importance level of the target task, and the first data volume used per time by the target object when executing the target task; and determine the second data volume allocated by the server to the target object according to the allocation ratio.

7. An electronic device, wherein, it comprises: a processor; a memory for storing instructions executable by the processor; wherein, the processor is configured to execute the instructions to implement the data processing method according to any one of claims 1 to 5.

8. A computer-readable storage medium, wherein, when the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the data processing method according to any one of claims 1 to 5.

9. A computer program product, comprising a computer program, wherein, when the computer program is executed by a processor, it implements the data processing method according to any one of claims 1 to 5.

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