WO2019095669A1 - Salary calculation data processing method, application server, and computer readable storage medium - Google Patents

Abstract

Disclosed in the present application is a salary calculation data processing method. The method comprises: collecting, within a preset time period, statistics about data of which a use frequency in a salary calculation process is greater than a preset value; delimiting a memory space of a preset size, and caching the data of which the use frequency is greater than the preset value into the memory space; setting an access interface for accessing the memory space; monitoring the salary calculation process, and obtaining data required in the salary calculation process; determining whether the data required in the salary calculation process is data from the memory space; and performing salary calculation according to the determination result. The present application also provides an application server and a computer readable storage medium. According to the salary calculation data processing method, the application server, and the computer readable storage medium provided in the present application, memory read and write becomes faster, salary calculation is greatly accelerated, and compared with conventional processing modes, an overall operational speed is significantly improved.

Description

Data processing method for salary calculation, application server and computer readable storage medium

This application claims the priority of the Chinese Patent Application filed on November 17, 2017, the Chinese Patent Office, the application number is 201711141746.4, and the invention is entitled "data processing method for salary calculation, application server and computer readable storage medium". The content is incorporated into the application by reference.

Technical field

The present application relates to the field of communications technologies, and in particular, to a data processing method for salary calculation, an application server, and a computer readable storage medium.

Background technique

With the development of enterprises, various channel organizations have become more complicated, and the salary calculation of corresponding channels has become complicated, and the reading and processing of data has become more and more complicated. In particular, the calculation of many commissions involved in the salary calculation process will repeatedly read many data from the database. According to the current database mechanism, the data may need to be read from the hard disk when reading data, so that many data need to be repeatedly imported from the hard disk. Into the memory, further processing of the memory data, which not only causes the hard disk to be read and written to affect the life of the hard disk, but also because of repeated data read and write repeatedly resulting in inefficiency of the entire salary calculation process.

Summary of the invention

In view of this, the present application proposes a data processing method for salary calculation, an application server, and a computer readable storage medium, which can make the memory read and write speed faster, greatly improve the salary calculation speed, and the overall operation speed is compared with the conventional processing method. Great improvement.

First, in order to achieve the above object, the present application provides an application server, which includes a memory, a processor, and a data processing program for storing salary calculations executable on the processor, the salary The computed data processing program is implemented by the processor to implement the following steps:

Data used in a salary calculation process that is greater than a preset value during a preset time period;

Delimiting a memory space of a preset size, and buffering the data whose usage frequency is greater than a preset value into the memory space;

Setting an access interface for accessing the memory space;

Monitoring the salary calculation process to obtain data required for the salary calculation process;

Determining whether data required by the salary calculation process belongs to data in the memory space;

If the data required by the salary calculation process belongs to the data in the memory space, the data required in the salary calculation process is retrieved from the memory space through the access interface; and

The salary calculation is performed based on the data required during the salary calculation process.

In addition, in order to achieve the above object, the present application further provides a data processing method for salary calculation, which is applied to an application server, and the method includes the following steps:

Data used in a salary calculation process that is greater than a preset value during a preset time period;

Delimiting a memory space of a preset size, and buffering the data whose usage frequency is greater than a preset value into the memory space;

Setting an access interface for accessing the memory space;

Monitoring the salary calculation process to obtain data required for the salary calculation process;

Determining whether data required by the salary calculation process belongs to data in the memory space;

If the data required by the salary calculation process belongs to the data in the memory space, the data required in the salary calculation process is retrieved from the memory space through the access interface; and

The salary calculation is performed based on the data required during the salary calculation process.

Further, in order to achieve the above object, the present application further provides a computer readable storage medium storing a data processing program of salary calculation, the data processing program of the salary calculation may be at least one processor Executing, in order for the at least one processor to perform the steps of the data processing method of the salary calculation as described above.

Compared with the prior art, the application server, the data processing method of the salary calculation, and the computer readable storage medium proposed by the present application firstly use data whose frequency is greater than a preset value in the statistical salary calculation process in a preset time period; Then, delimiting a memory space of a preset size, and buffering the data whose usage frequency is greater than a preset value into the memory space; secondly, setting an access interface for accessing the memory space; and again, monitoring a salary calculation process to obtain Data required by the salary calculation process; thereafter, determining whether data required by the salary calculation process belongs to data in the memory space; and when data required by the salary calculation process belongs to data in the memory space, Then, the data required in the salary calculation process is retrieved from the memory space through the access interface; finally, the salary calculation is performed according to the data required in the salary calculation process. In this way, it can avoid the repeated reading and writing of the hard disk data in the prior art and affect the service life of the hard disk, and also cause the inefficiency of the entire salary calculation process due to repeated data read and write, which can make the memory read and write. The speed is faster, the salary calculation speed is greatly improved, and the overall operation speed is greatly improved compared with the conventional processing method.

DRAWINGS

1 is a schematic diagram of an optional hardware architecture of an application server in the present application;

2 is a block diagram showing the program of the first embodiment of the data processing program of the salary calculation of the present application;

Figure 3 is a block diagram showing the program of the second embodiment of the data processing program of the salary calculation of the present application;

4 is a program block diagram of a third embodiment of a data processing program for salary calculation of the present application;

5 is a flowchart of a first embodiment of a data processing method for salary calculation of the present application;

6 is a flowchart of a second embodiment of a data processing method for salary calculation of the present application;

FIG. 7 is a flowchart of a third embodiment of a data processing method for salary calculation of the present application.

The implementation, functional features and advantages of the present application will be further described with reference to the accompanying drawings.

Detailed ways

In order to make the objects, technical solutions, and advantages of the present application more comprehensible, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It is understood that the specific embodiments described herein are merely illustrative of the application and are not intended to be limiting. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present application without departing from the inventive scope are the scope of the present application.

It should be noted that the descriptions of "first", "second" and the like in the present application are for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. . Thus, features defining "first" or "second" may include at least one of the features, either explicitly or implicitly. In addition, the technical solutions between the various embodiments may be combined with each other, but must be based on the realization of those skilled in the art, and when the combination of the technical solutions is contradictory or impossible to implement, it should be considered that the combination of the technical solutions does not exist. Nor is it within the scope of protection required by this application.

Referring to FIG. 1, it is a schematic diagram of an optional hardware architecture of the application server 1.

The application server 1 may be a computing device such as a rack server, a blade server, a tower server, or a rack server. The application server 1 may be a stand-alone server or a server cluster composed of multiple servers.

In this embodiment, the application server 1 may include, but is not limited to, the memory 11, the processor 12, and the network interface 13 being communicably connected to each other through a system bus.

The application server 1 connects to the network through the network interface 13 to obtain information. The network may be an intranet, an Internet, a Global System of Mobile communication (GSM), a Wideband Code Division Multiple Access (WCDMA), a 4G network, or a 5G network. Wireless or wired networks such as networks, Bluetooth, Wi-Fi, and call networks.

It is pointed out that Figure 1 only shows the application server 1 with components 11-13, but it should be understood that not all illustrated components may be implemented, and more or fewer components may be implemented instead.

The memory 11 includes at least one type of readable storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (eg, SD or DX memory, etc.), and a random access memory (RAM). , static random access memory (SRAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), programmable read only memory (PROM), magnetic memory, magnetic disk, optical disk, and the like. In some embodiments, the memory 11 may be an internal storage unit of the application server 1, such as a hard disk or memory of the application server 1. In other embodiments, the memory 11 may also be an external storage device of the application server 1, such as a plug-in hard disk equipped with the application server 1, a smart memory card (SMC), and a secure digital ( Secure Digital, SD) cards, flash cards, etc. Of course, the memory 11 can also include both the internal storage unit of the application server 1 and its external storage device. In this embodiment, the memory 11 is generally used to store an operating system installed in the application server 1 and various types of application software, such as program code of the data processing program 200 of the salary calculation. Further, the memory 11 can also be used to temporarily store various types of data that have been output or are to be output.

The processor 12 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data processing chip in some embodiments. The processor 12 is typically used to control the overall operation of the application server 1, such as performing data interaction or communication related control and processing, and the like. In this embodiment, the processor 12 is configured to run program code or processing data stored in the memory 11, such as the data processing program 200 that runs the salary calculation.

The network interface 13 may comprise a wireless network interface or a wired network interface, which is typically used to establish a communication connection between the application server 1 and other electronic devices.

In this embodiment, the application server 1 installs and runs a data processing program 200 with salary calculation. When the data processing program 200 of the salary calculation is run, the application server 2 calculates the salary calculation for a preset time period. The process uses a data whose frequency is greater than a preset value; delimits a memory space of a preset size, and caches the data whose usage frequency is greater than a preset value into the memory space; sets an access interface for accessing the memory space; and monitors a salary calculation process, obtaining data required by the salary calculation process; determining whether data required by the salary calculation process belongs to data in the memory space; and data required by the salary calculation process belongs to data in the memory space At the time, the data required in the salary calculation process is retrieved from the memory space through the access interface; and the salary calculation is performed according to the data required in the salary calculation process. In this way, it can avoid the repeated reading and writing of the hard disk data in the prior art and affect the service life of the hard disk, and also cause the inefficiency of the entire salary calculation process due to repeated data read and write, which can make the memory read and write. The speed is faster, the salary calculation speed is greatly improved, and the overall operation speed is greatly improved compared with the conventional processing method.

So far, the application environment of the various embodiments of the present application and the hardware structure and functions of related devices have been described in detail. Hereinafter, various embodiments of the present application will be proposed based on the above-described application environment and related devices.

First, the present application proposes a data processing program 200 for salary calculation.

Referring to FIG. 2, it is a program block diagram of the first embodiment of the data processing program 200 of the salary calculation of the present application.

In this embodiment, the salary calculation data processing program 200 includes a series of computer program instructions stored in the memory 11, and when the computer program instructions are executed by the processor 12, the salary of the embodiments of the present application can be implemented. Calculated data processing operations. In some embodiments, the salary calculation data processing program 200 can be divided into one or more modules based on the particular operations implemented by the various portions of the computer program instructions. For example, in FIG. 2, the salary calculation data processing program 200 can be divided into a statistics module 201, a cache module 202, a setting module 203, an acquisition module 204, a determination module 205, and a calculation module 206. among them:

The statistic module 201 is configured to use data whose frequency is greater than a preset value in a statistical salary calculation process in a preset time period. In this embodiment, the preset time and the preset value are set by the administrator according to requirements, and the specific range of the preset time and the preset value is not limited in the present application. For example, if the manager wants to know the data used in the salary calculation process for more than 50 times in a week, the preset time is set to 1 week and the preset value is set to 50.

In addition, for the convenience of statistics, the statistics module 201 adds identification information to the data whose usage frequency is greater than a preset value.

The statistic module 201 is further configured to: obtain the identification information of the data used by the salary calculation process, and read the identification information from the hard disk by using the identifier information to collect the data that is used in the salary calculation process. The number of times the data is represented.

The cache module 202 is configured to delimit a memory space of a preset size, and cache the data whose usage frequency is greater than a preset value into the memory space. Specifically, the preset size is set by the administrator according to the number of employees and the calculation period. For example, when the number of employees is small and the calculation period is short, the memory space can be set to be relatively small, for example, 1G memory. Conversely, when the number of employees is large and the calculation period is long, the memory space can be set relatively large. For example, 10G memory. In this embodiment, the data whose usage frequency is greater than the preset value is cached into the memory space, which can implement data sharing of multiple calculation processes, reduce data read and write times, improve computing performance, and maintain data consistency.

The setting module 203 is configured to set an access interface for accessing the memory space. In this embodiment, the access interface supports data reading in the k/v mode and the list mode.

The obtaining module 204 is configured to monitor a salary calculation process and obtain data required by the salary calculation process.

Specifically, in order to obtain data required by the salary calculation process, the obtaining module 204 is further configured to intercept a data retrieval command generated by the salary calculation process; and parse the data retrieval command to obtain the required Identification information of the data.

The determining module 205 is configured to determine whether data required by the salary calculation process belongs to data in the memory space. Further, the determining module 205 is further configured to compare whether the identification information of the required data and the identification information of the data in the memory space are consistent. If yes, the determining module 205 determines that the data required by the salary calculation process belongs to the data in the memory space whose usage frequency is greater than a preset value.

The calculating module 206 is configured to retrieve data required in the salary calculation process from the memory space through the access interface when data required by the salary calculation process belongs to data in the memory space.

The calculation module 206 is further configured to perform salary calculation according to the data required in the salary calculation process that is retrieved. Further, the salary calculation result may be displayed by the mobile terminal. In this embodiment, the mobile terminal may be a mobile phone, a smart phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a navigation device, and a car. A mobile device such as a device, and a fixed terminal such as a digital TV, a desktop computer, a notebook, a server, and the like.

Further, based on the above-described first embodiment of the data processing program 200 of the salary calculation of the present application, a second embodiment of the present application (shown in FIG. 3) is proposed. In this embodiment, the salary calculation data processing program 200 further includes a clearing module 207, where:

The clearing module 207 is configured to erase data of the memory space after the salary calculation ends.

Further, based on the above-described first embodiment of the data processing program 200 of the salary calculation of the present application, a third embodiment of the present application (shown in FIG. 4) is proposed. In this embodiment, the salary calculation data processing program 200 further includes a backup module 208, wherein:

The backup module 208 is configured to back up data of the memory space to the cloud.

In this embodiment, the data of the memory space is backed up to the cloud, and on the one hand, the data is not lost after the disk is damaged. On the other hand, through the backup storage of the memory data, the intermediate calculation process data can also be saved, which is convenient for verifying the correctness of the salary calculation process.

In addition, the present application also proposes a data processing method for salary calculation.

Referring to FIG. 5, it is a schematic flowchart of the implementation of the first embodiment of the data processing method of the salary calculation of the present application. In this embodiment, the order of execution of the steps in the flowchart shown in FIG. 5 may be changed according to different requirements, and some steps may be omitted.

In step S501, the data whose frequency is greater than the preset value is used in the statistical salary calculation process in the preset time period. In this embodiment, the preset time and the preset value are set by the administrator according to requirements, and the specific range of the preset time and the preset value is not limited in the present application. For example, if the manager wants to know the data used more than 50 times during the salary calculation in 1 week, set the preset time to 1 week and the preset value to 50. The application server 1 collects data with a preset time period using a frequency greater than a preset value in the salary calculation process by:

The application server 1 obtains identification information of data used in the salary calculation process, and counts the number of times the data represented by the identification information is read from the hard disk by using the identification information.

In addition, for convenience statistics, the application server 1 adds identification information to the data whose usage frequency is greater than a preset value.

Step S502, delimiting a memory space of a preset size, and buffering the data whose usage frequency is greater than a preset value into the memory space.

Specifically, the preset size is set by the administrator according to the number of employees and the calculation period. For example, when the number of employees is small and the calculation period is short, the memory space can be set to be relatively small, for example, 1G memory. Conversely, when the number of employees is large and the calculation period is long, the memory space can be set relatively large. For example, 10G memory. In this embodiment, the data whose usage frequency is greater than the preset value is cached into the memory space, which can implement data sharing of multiple calculation processes, reduce data read and write times, improve computing performance, and maintain data consistency.

Step S503, setting an access interface for accessing the memory space.

In this embodiment, the access interface supports data reading in the k/v mode and the list mode.

Step S504, monitoring the salary calculation process, and acquiring data required by the salary calculation process. The application server 1 obtains data required by the salary calculation process by:

The application server 1 first intercepts a data retrieval command generated by the salary calculation process. Then, parsing the data retrieval command to obtain identification information of the required data.

Step S505, determining whether data required by the salary calculation process belongs to data in the memory space. If the data required by the salary calculation process belongs to the data in the memory space, step S506 is performed, otherwise, it ends.

Further, the application server 1 compares the identification information of the required data with the identification information of the data in the memory space. If they are consistent, the application server 1 determines that the data required by the salary calculation process belongs to the data in the memory space whose usage frequency is greater than a preset value.

Step S506, the data required in the salary calculation process is retrieved from the memory space through the access interface.

Step S507, performing salary calculation according to the data required in the salary calculation process that is obtained. Further, the salary calculation result may be displayed by the mobile terminal. In this embodiment, the mobile terminal may be a mobile phone, a smart phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a navigation device, and a car. A mobile device such as a device, and a fixed terminal such as a digital TV, a desktop computer, a notebook, a server, and the like.

Through the above steps S501-507, the data processing method of the salary calculation proposed by the present application, first, the application server 1 uses the data whose frequency is greater than the preset value in the statistical salary calculation process in a preset time period; a memory space of a preset size, the data whose usage frequency is greater than a preset value is cached to the memory space; secondly, an access interface for accessing the memory space is set; and again, the salary calculation process is monitored to obtain the salary calculation Data required by the process; thereafter, determining whether the data required by the salary calculation process belongs to data in the memory space; and when the data required by the salary calculation process belongs to data in the memory space, The access interface retrieves data required in the salary calculation process from the memory space; finally, performs salary calculation according to the data required in the salary calculation process that is retrieved. In this way, it can avoid the repeated reading and writing of the hard disk data in the prior art and affect the service life of the hard disk, and also cause the inefficiency of the entire salary calculation process due to repeated data read and write, which can make the memory read and write. The speed is faster, the salary calculation speed is greatly improved, and the overall operation speed is greatly improved compared with the conventional processing method.

Referring to FIG. 6, it is a schematic flowchart of the implementation of the second embodiment of the data processing method of the salary calculation of the present application. In this embodiment, the order of execution of the steps in the flowchart shown in FIG. 6 may be changed according to different requirements, and some steps may be omitted.

In step S601, the data whose frequency is greater than the preset value is used in the statistical salary calculation process in the preset time period. The application server 1 collects data with a preset time period using a frequency greater than a preset value in the salary calculation process by:

The application server 1 obtains identification information of data used in the salary calculation process, and counts the number of times the data represented by the identification information is read from the hard disk by using the identification information.

Step S602, delimiting a memory space of a preset size, and buffering the data whose usage frequency is greater than a preset value into the memory space.

Step S603, setting an access interface for accessing the memory space.

Step S604, monitoring the salary calculation process, and acquiring data required by the salary calculation process.

Step S605, determining whether data required by the salary calculation process belongs to data in the memory space. If the data required by the salary calculation process belongs to the data in the memory space, step S606 is performed, otherwise, it ends.

Step S606, the data required in the salary calculation process is retrieved from the memory space through the access interface.

Step S607, performing salary calculation according to the data required in the salary calculation process that is obtained.

Step S608, after the salary calculation ends, the data of the memory space is erased.

Through the above steps S601-608, the data processing method of the salary calculation proposed by the present application can timely clear the invalid data in the memory and improve the data processing speed.

Referring to FIG. 7, it is a schematic flowchart of the implementation of the third embodiment of the data processing method of the salary calculation of the present application. In this embodiment, the order of execution of the steps in the flowchart shown in FIG. 7 may be changed according to different requirements, and some steps may be omitted.

In step S701, the data whose frequency is greater than the preset value is used in the statistical salary calculation process in the preset time period.

The application server 1 collects data with a preset time period using a frequency greater than a preset value in the salary calculation process by:

The application server 1 obtains identification information of data used in the salary calculation process, and counts the number of times the data represented by the identification information is read from the hard disk by using the identification information.

Step S702, delimiting a memory space of a preset size, and buffering the data whose usage frequency is greater than a preset value into the memory space.

Step S703, backing up data of the memory space to the cloud.

Step S704, setting an access interface for accessing the memory space.

Step S705, monitoring the salary calculation process, and acquiring data required by the salary calculation process.

The application server 1 obtains data required by the salary calculation process by:

The application server 1 first intercepts a data retrieval command generated by the salary calculation process. Then, parsing the data retrieval command to obtain identification information of the required data.

Step S706, determining whether data required by the salary calculation process belongs to data in the memory space. If the data required by the salary calculation process belongs to the data in the memory space, step S807 is performed, otherwise, it ends.

Step S707, the data required in the salary calculation process is retrieved from the memory space through the access interface.

Step S708, performing salary calculation according to the data required in the salary calculation process that is retrieved.

Through the above steps S701-708, the data processing method of the salary calculation proposed by the present application can ensure that the data is not lost after the disk is damaged by backing up the data of the memory space to the cloud. On the other hand, through the backup storage of the memory data, the intermediate calculation process data can also be saved, which is convenient for verifying the correctness of the salary calculation process.

Further, in order to achieve the above object, the present application further provides a computer readable storage medium storing a data processing program of salary calculation, the data processing program of the salary calculation may be at least one processor Executing, in order for the at least one processor to perform the steps of the data processing method of the salary calculation as described above.

The serial numbers of the embodiments of the present application are merely for the description, and do not represent the advantages and disadvantages of the embodiments.

Through the description of the above embodiments, those skilled in the art can clearly understand that the foregoing embodiment method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be through hardware, but in many cases, the former is better. Implementation. Based on such understanding, the technical solution of the present application, which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a storage medium (such as ROM/RAM, disk, The optical disc includes a number of instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the methods described in the various embodiments of the present application.

The above is only a preferred embodiment of the present application, and is not intended to limit the scope of the patent application, and the equivalent structure or equivalent process transformations made by the specification and the drawings of the present application, or directly or indirectly applied to other related technical fields. The same is included in the scope of patent protection of this application.

Claims (20)

A data processing method for salary calculation is applied to an application server, characterized in that the method comprises the steps of: Data used in a salary calculation process that is greater than a preset value during a preset time period; Delimiting a memory space of a preset size, and buffering the data whose usage frequency is greater than a preset value into the memory space; Setting an access interface for accessing the memory space; Monitoring the salary calculation process to obtain data required for the salary calculation process; Determining whether data required by the salary calculation process belongs to data in the memory space; If the data required by the salary calculation process belongs to the data in the memory space, the data required in the salary calculation process is retrieved from the memory space through the access interface; and The salary calculation is performed based on the data required during the salary calculation process. The data processing method for salary calculation according to claim 1, wherein the method further comprises the steps of: After the salary calculation ends, the data of the memory space is erased. The data processing method of the salary calculation according to claim 1, wherein after the step of buffering the data in the preset interval to the memory space, the method further comprises the steps of: Back up the data in the memory space to the cloud. The data processing method of the salary calculation according to claim 1, wherein the step of using the data whose frequency is greater than the preset value in the statistical salary calculation process in the preset time period comprises: Obtaining identification information of data used in the salary calculation process; and The number of times the data represented by the identification information is read from the hard disk is counted by the identification information. The data processing method of the salary calculation according to claim 1, wherein the step of acquiring data required for the salary calculation process further comprises: Intercepting the data retrieval command generated by the salary calculation process; and Parsing the data retrieval command to obtain identification information of the required data. The data processing method of the salary calculation according to claim 5, wherein the step of determining whether the data required by the salary calculation process belongs to the data in the memory space comprises: Whether the identification information of the required data is consistent with the identification information of the data in the memory space; and If the identification information of the required data is consistent with the identification information of the data in the memory space, the data required by the salary calculation process belongs to the data in the memory space whose usage frequency is greater than a preset value. The data processing method for salary calculation according to claim 1, wherein the method further comprises the steps of: The access interface supports data reading in the k/v mode and the list mode. An application server, characterized in that the application server comprises a memory, a processor, and a data processing program for calculating salary calculations executable on the processor, where the data processing program of the salary calculation is The processor implements the following steps when executed: Data used in a salary calculation process that is greater than a preset value during a preset time period; Delimiting a memory space of a preset size, and buffering the data whose usage frequency is greater than a preset value into the memory space; Setting an access interface for accessing the memory space; Monitoring the salary calculation process to obtain data required for the salary calculation process; Determining whether data required by the salary calculation process belongs to data in the memory space; If the data required by the salary calculation process belongs to the data in the memory space, the data required in the salary calculation process is retrieved from the memory space through the access interface; and The salary calculation is performed based on the data required during the salary calculation process. The application server according to claim 8, wherein when the data processing program of the salary calculation is executed by the processor, the following steps are further implemented: After the salary calculation ends, the data of the memory space is erased. The application server according to claim 8, wherein when the data processing program of the salary calculation is executed by the processor, the following steps are further implemented: Back up the data in the memory space to the cloud. The application server according to claim 8, wherein the step of using the data whose frequency is greater than the preset value in the statistical salary calculation process in the preset time period comprises: Obtaining identification information of data used in the salary calculation process; and The number of times the data represented by the identification information is read from the hard disk is counted by the identification information. The application server according to claim 8, wherein the step of acquiring data required for the salary calculation process further comprises: Intercepting the data retrieval command generated by the salary calculation process; and Parsing the data retrieval command to obtain identification information of the required data. The application server according to claim 12, wherein the step of determining whether data required by the salary calculation process belongs to data in the memory space comprises: Whether the identification information of the required data is consistent with the identification information of the data in the memory space; and If the identification information of the required data is consistent with the identification information of the data in the memory space, the data required by the salary calculation process belongs to the data in the memory space whose usage frequency is greater than a preset value. The application server according to claim 8, wherein when the data processing program of the salary calculation is executed by the processor, the following steps are further implemented: The access interface supports data reading in the k/v mode and the list mode. A computer readable storage medium storing a data processing program of a salary calculation, the data processing program of the salary calculation being executable by at least one processor to cause the at least one processor to perform the following step: Data used in a salary calculation process that is greater than a preset value during a preset time period; Delimiting a memory space of a preset size, and buffering the data whose usage frequency is greater than a preset value into the memory space; Setting an access interface for accessing the memory space; Monitoring the salary calculation process to obtain data required for the salary calculation process; Determining whether data required by the salary calculation process belongs to data in the memory space; If the data required by the salary calculation process belongs to the data in the memory space, the data required in the salary calculation process is retrieved from the memory space through the access interface; and The salary calculation is performed based on the data required during the salary calculation process. The computer readable storage medium of claim 15, wherein when the data processing program of the salary calculation is executed by the processor, the following steps are further implemented: After the salary calculation ends, the data of the memory space is erased. The computer readable storage medium of claim 15, wherein when the data processing program of the salary calculation is executed by the processor, the following steps are further implemented: Back up the data in the memory space to the cloud. The computer readable storage medium according to claim 15, wherein the step of using data having a frequency greater than a preset value in the statistical salary calculation process in a preset time period comprises: Obtaining identification information of data used in the salary calculation process; and The number of times the data represented by the identification information is read from the hard disk is counted by the identification information. The computer readable storage medium according to claim 15, wherein the step of acquiring data required by the salary calculation process further comprises: Intercepting the data retrieval command generated by the salary calculation process; and Parsing the data retrieval command to obtain identification information of the required data. The computer readable storage medium according to claim 19, wherein the step of determining whether data required by the salary calculation process belongs to data in the memory space comprises: Whether the identification information of the required data is consistent with the identification information of the data in the memory space; and If the identification information of the required data is consistent with the identification information of the data in the memory space, the data required by the salary calculation process belongs to the data in the memory space whose usage frequency is greater than a preset value.

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