CN112529626A - Method, device and equipment for clearing integral data and storage medium - Google Patents
Method, device and equipment for clearing integral data and storage medium Download PDFInfo
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- CN112529626A CN112529626A CN202011480458.3A CN202011480458A CN112529626A CN 112529626 A CN112529626 A CN 112529626A CN 202011480458 A CN202011480458 A CN 202011480458A CN 112529626 A CN112529626 A CN 112529626A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
The invention discloses a method, a device, equipment and a storage medium for clearing integral data, wherein the method comprises the following steps: acquiring to-be-processed integral data of a client, and determining integral adding time of the to-be-processed integral data; determining an integral conversion rule according to integral data to be processed; selecting target integral data from the data to be processed according to an integral conversion rule and integral adding time; and carrying out integral data clearing according to the target integral data. In the prior art, the integral data needs to be manually selected for data clearing, but the integral data clearing processing efficiency is low, in the invention, the target integral data is selected from the data to be processed according to the integral conversion rule and the integral adding time, and then the integral data is cleared according to the target integral data, so that the integral data clearing processing efficiency is improved, and the user experience is improved.
Description
Technical Field
The invention relates to the technical field of data clearing, in particular to a method, a device, equipment and a storage medium for clearing integral data.
Background
At present, with the continuous integration of social networking, cloud computing and other technologies into people's lives and the rapid development of existing computing power, storage space, network bandwidth and the like, data accumulated by humans are continuously increased and accumulated in various fields such as the internet, communication, finance, commerce and the like. In the related art, it is necessary to process various data such as point data, including performing a clearing process, and in the related art, a method for clearing point data is to randomly select corresponding point data manually and perform data clearing on the point data, but this method may cause inefficient processing of point data clearing.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide a method, a device, equipment and a storage medium for clearing integral data, and aims to solve the technical problem of improving the processing efficiency of clearing the integral data.
In order to achieve the above object, the present invention provides an integral data clearing method, including:
acquiring to-be-processed integral data of a client, and determining integral adding time of the to-be-processed integral data;
determining an integral conversion rule according to the integral data to be processed;
selecting target integral data from the data to be processed according to the integral conversion rule and the integral adding time;
and carrying out integral data clearing according to the target integral data.
Optionally, the step of determining an integral conversion rule according to the integral data to be processed includes:
dividing the integral data to be processed to obtain a plurality of integral data sets;
respectively acquiring integral types corresponding to the integral data sets;
and determining an integral conversion rule according to the integral type.
Optionally, the step of determining an integral conversion rule according to the integral type includes:
searching a corresponding sample integral conversion rule from a preset integral mapping relation table according to the integral type, and taking the sample integral conversion rule as the integral conversion rule of the integral type;
the preset integral mapping relation table comprises a corresponding relation between an integral type and a sample integral conversion rule.
Optionally, the step of dividing the integral data to be processed to obtain a plurality of integral data sets includes:
carrying out priority sequencing from front to back according to the integral adding time of the integral data to be processed to obtain a time sequencing result;
and dividing the integral data to be processed according to the time sequencing result to obtain a plurality of integral data sets.
Optionally, the step of performing integral data clearing according to the target integral data includes:
judging whether the target integral data is larger than a preset clearing threshold value or not;
and when the target integral data is larger than the preset clearing threshold value, determining integral data to be cleared according to the target integral data and the preset clearing threshold value, and clearing the integral data according to the integral data to be cleared.
Optionally, after the step of determining whether the target integral data is greater than a preset clearing threshold, the method further includes:
and when the target integral data is equal to the preset clearing threshold value, taking the target integral data as integral data to be cleared, and clearing the integral data according to the integral data to be cleared.
Optionally, after the step of determining whether the target integral data is greater than a preset clearing threshold, the method further includes:
when the target integral data is smaller than the preset clearing threshold value, judging whether the integral adding time of the target integral data meets a preset integral clearing condition;
and when the preset integral clearing condition is met, taking the target integral data as integral data to be cleared, and clearing the integral data according to the integral data to be cleared.
Further, in order to achieve the above object, the present invention also provides an integrated point data clearing apparatus including:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring the integral data to be processed of a client and determining the integral adding time of the integral data to be processed;
the determining module is used for determining an integral conversion rule according to the integral data to be processed;
the selection module is used for selecting target integral data from the data to be processed according to the integral conversion rule and the integral adding time;
and the clearing module is used for clearing the integral data according to the target integral data.
Further, to achieve the above object, the present invention also provides an integrated data liquidation apparatus including: a memory, a processor and a credit data clearing program stored on the memory and executable on the processor, the credit data clearing program being configured to implement the steps of the credit data clearing method as described above.
Furthermore, to achieve the above object, the present invention also proposes a storage medium having stored thereon an integral data clearing program which, when executed by a processor, implements the steps of the integral data clearing method as described above.
The method comprises the steps of firstly obtaining to-be-processed integral data of a client, determining integral adding time of the to-be-processed integral data, then determining an integral conversion rule according to the to-be-processed integral data, then selecting target integral data from the to-be-processed data according to the integral conversion rule and the integral adding time, and clearing the integral data according to the target integral data. In the prior art, the integral data needs to be manually selected for data clearing, but the integral data clearing processing efficiency is low, in the invention, the target integral data is selected from the data to be processed according to the integral conversion rule and the integral adding time, and then the integral data is cleared according to the target integral data, so that the integral data clearing processing efficiency is improved, and the user experience is improved.
Drawings
FIG. 1 is a schematic diagram of an integrated data clearing device of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a first embodiment of the method for clearing accumulated data according to the present invention;
FIG. 3 is a flow chart illustrating a second embodiment of the method for clearing accumulated data according to the present invention;
fig. 4 is a block diagram showing the structure of the first embodiment of the integrated data liquidation apparatus of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of an integral data clearing device of a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the integrated data liquidation apparatus may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WIreless-FIdelity (WI-FI) interface). The Memory 1005 may be a Random Access Memory (RAM) Memory, or may be a Non-Volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration shown in fig. 1 does not constitute a limitation of the integral data clearing device, and may include more or less components than those shown, or some components in combination, or a different arrangement of components.
As shown in fig. 1, the memory 1005, which is a storage medium, may include therein an operating system, a data storage module, a network communication module, a user interface module, and a point data clearing program.
In the tally data liquidation apparatus shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the integral data clearing apparatus of the present invention may be provided in the integral data clearing apparatus which calls the integral data clearing program stored in the memory 1005 through the processor 1001 and executes the integral data clearing method provided by the embodiment of the present invention.
An embodiment of the present invention provides a method for clearing integral data, and referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of the method for clearing integral data according to the present invention.
In this embodiment, the method for clearing the integral data includes the following steps:
step S10: the method comprises the steps of obtaining to-be-processed point data of a client, and determining point adding time of the to-be-processed point data.
It is easy to understand that the execution subject of the embodiment may be a credit data clearing device having functions of data processing, network communication, program operation, and the like, or may be other computer devices having similar functions, and the embodiment is not limited.
It can be understood that the point data to be processed may be total point data obtained by the user during daily consumption, point exchange may be performed according to the point data, and the point adding time is obtaining time corresponding to the point, and the like, and this embodiment is not limited.
Assuming that a user number 12 consumes 100 yuan and obtains 100 points, and the user has 100 points in total, the 100 points are point data to be processed, and the 12 points are point adding time and the like; assuming that the user 12 consumes 100 yuan and obtains 100 points, the user 13 consumes 50 yuan and obtains 50 points, and the total of the users is 150 points, 150 points are to-be-processed point data, the point 12 is 100 point adding time, the point 13 is 50 point adding time, and the like.
Step S20: and determining an integral conversion rule according to the integral data to be processed.
The integral conversion rule may be set by a user, may be 2-time integral conversion, may be 3-time integral conversion, or the like.
Assuming that the user has 100 points, and the food point and the decoration point exist in the 100 points, the food point may be converted into 2-time points, and the clothing point may be converted into 1-time points, or the like, that is, assuming that the food point is 50 points and the clothing point is 50 points in the 100 points of the user, the converted food point may be 25 points, and the converted clothing point may be 50 points, or the like.
Further, in order to accurately obtain the corresponding integral conversion rule, the step of determining the integral conversion rule according to the integral data to be processed may be dividing the integral data to be processed to obtain a plurality of integral data sets, respectively obtaining the integral type corresponding to each integral data set, determining the integral conversion rule according to the integral type, and the like, where the integral type may be a food type, a clothing type, and the like.
The method comprises the steps of dividing integral data to be processed to obtain a plurality of integral data sets, carrying out priority sequencing from front to back according to integral adding time of the integral data to be processed to obtain time sequencing results, dividing the integral data to be processed according to the time sequencing results to obtain a plurality of integral data sets and the like.
The integral data sets are provided with a plurality of integral data, the integral data are subjected to priority sequencing in the integral data sets according to integral adding time corresponding to the integral data, and then the integral data to be processed are divided according to the types of the integral to obtain a plurality of integral data sets and the like.
In the assumption that 100 points of a user are 100 points, the 100 points are divided to obtain 50 points of a food area diversity and 50 points of a clothing area diversity, wherein not only point data but also point adding time corresponding to the point data exist in the food area diversity, the point type corresponding to the food area diversity is a food type, the point type corresponding to the clothing area diversity is a clothing type, and then point conversion rules and the like are respectively determined according to the food type and the clothing type.
It can be understood that the step of determining the integral conversion rule according to the integral type may be to look up a corresponding sample integral conversion rule from a preset integral mapping relation table according to the integral type, and use the sample integral conversion rule as the integral conversion rule of the integral type, where the preset integral mapping relation table includes a corresponding relation between the integral type and the sample integral conversion rule, and there are multiple integral types and multiple sample integral conversion rules in the preset integral mapping relation table.
Step S30: and selecting target integral data from the data to be processed according to the integral conversion rule and the integral adding time.
The target integral data may be integral data that needs to be cleared, the integral data to be processed may also be target integral data, and a part of the integral data to be processed may also be target integral data, and the like, which is not limited in this embodiment.
Assuming that a user 12 consumes 100 yuan, obtains 100 credits, a user 13 consumes 50 yuan, obtains 50 credits, and the user has 150 credits in total, 150 credits are to-be-processed credit data, the user 12 has 100 credit adding time and the user 13 has 50 credit adding time, target credit data can be selected according to user requirements, the target credit data needs to be selected from the user 12 credits first, and if the user requirements cannot be met by the user 12 credits, the target credit data can be selected from the user 13.
Step S40: and carrying out integral data clearing according to the target integral data.
The step of performing integral data clearing according to the target integral data may be to determine whether the target integral data is greater than a preset clearing threshold, determine integral data to be cleared according to the target integral data and the preset clearing threshold when the target integral data is greater than the preset clearing threshold, perform integral data clearing according to the integral data to be cleared, and the like.
Assuming integral data to be processed 100, selecting target integral data from the integral data to be processed, wherein the target integral data is 90, judging whether the target integral data 90 is greater than a preset clearing threshold value 70, when the target integral data is greater than the preset clearing threshold value, determining the integral data to be cleared 70 from the target integral data 90 according to integral adding time corresponding to the target integral data, clearing the integral data according to the integral data to be cleared 70, and the like.
And when the target integral data is equal to a preset clearing threshold value, taking the target integral data as integral data to be cleared, and clearing the integral data according to the integral data to be cleared.
Assuming the integral data to be processed 70, selecting target integral data from the integral data to be processed, wherein the target integral data is 60, when the target integral data 60 is equal to a preset clearing threshold 60, taking the target integral data 60 as the integral data to be cleared 60, and clearing the integral data according to the integral data to be cleared 60, and the like.
And when the target integral data is smaller than a preset clearing threshold value, judging whether the integral adding time of the target integral data meets a preset integral clearing condition, and when the preset integral clearing condition is met, taking the target integral data as integral data to be cleared, clearing the integral data according to the integral data to be cleared, and the like.
Data clearing may be understood to mean redeeming and using point data to clear corresponding point data, etc.
The preset clearing threshold is set by a user, and may be 80, or may also be 100, and the present embodiment is not limited.
Assuming integral data 80 to be processed, selecting target integral data from the integral data to be processed, wherein the target integral data is 70, judging whether the target integral number 90 is smaller than a preset clearing threshold 80, judging whether integral adding time of the target integral data meets a preset integral clearing condition when the target integral data is smaller than the preset clearing threshold, taking the target integral data 80 as the integral data to be cleared when the preset integral clearing condition is met, clearing the integral data according to the integral data to be cleared, and the like, wherein the preset integral clearing condition can be that whether the integral adding time corresponding to the target integral data is normally usable time, and the like.
In this embodiment, to-be-processed integral data of a client is first acquired, integral adding time of the to-be-processed integral data is determined, an integral conversion rule is then determined according to the to-be-processed integral data, target integral data is selected from the to-be-processed data according to the integral conversion rule and the integral adding time, and integral data clearing is performed according to the target integral data. In the prior art, the integral data needs to be manually selected for data clearing, but the integral data clearing processing efficiency is low, but in the embodiment, the target integral data is selected from the data to be processed according to the integral conversion rule and the integral adding time, and then the integral data is cleared according to the target integral data, so that the integral data clearing processing efficiency is improved, and the user experience is further improved.
Referring to fig. 3, fig. 3 is a flow chart illustrating a second embodiment of the method for clearing the accumulated data according to the present invention.
Based on the first embodiment, in this embodiment, the step S40 further includes:
step S401: and judging whether the target integral data is larger than a preset clearing threshold value or not.
The preset clearing threshold is set by a user, and may be 80, or may also be 100, and the present embodiment is not limited.
Step S402: and when the target integral data is larger than the preset clearing threshold value, determining integral data to be cleared according to the target integral data and the preset clearing threshold value, and clearing the integral data according to the integral data to be cleared.
Data clearing may be understood to mean redeeming and using point data to clear corresponding point data, etc.
Assuming integral data to be processed 100, selecting target integral data from the integral data to be processed, wherein the target integral data is 90, judging whether the target integral data 90 is greater than a preset clearing threshold value 70, when the target integral data is greater than the preset clearing threshold value, determining the integral data to be cleared 70 from the target integral data 90 according to integral adding time corresponding to the target integral data, clearing the integral data according to the integral data to be cleared 70, and the like.
And when the target integral data is equal to a preset clearing threshold value, taking the target integral data as integral data to be cleared, and clearing the integral data according to the integral data to be cleared.
Assuming the integral data to be processed 70, selecting target integral data from the integral data to be processed, wherein the target integral data is 60, when the target integral data 60 is equal to a preset clearing threshold 60, taking the target integral data 60 as the integral data to be cleared 60, and clearing the integral data according to the integral data to be cleared 60, and the like.
And when the target integral data is smaller than a preset clearing threshold value, judging whether the integral adding time of the target integral data meets a preset integral clearing condition, and when the preset integral clearing condition is met, taking the target integral data as integral data to be cleared, clearing the integral data according to the integral data to be cleared, and the like.
Assuming integral data 80 to be processed, selecting target integral data from the integral data to be processed, wherein the target integral data is 70, judging whether the target integral number 90 is smaller than a preset clearing threshold 80, judging whether integral adding time of the target integral data meets a preset integral clearing condition when the target integral data is smaller than the preset clearing threshold, taking the target integral data 80 as the integral data to be cleared when the preset integral clearing condition is met, clearing the integral data according to the integral data to be cleared, and the like, wherein the preset integral clearing condition can be that whether the integral adding time corresponding to the target integral data is normally usable time, and the like.
In this embodiment, it is determined whether the target integral data is greater than a preset clearing threshold, and when the target integral data is greater than the preset clearing threshold, the integral data to be cleared is determined according to the target integral data and the preset clearing threshold, and the integral data is cleared according to the integral data to be cleared, so as to improve the processing efficiency of the integral data clearing.
Referring to fig. 4, fig. 4 is a block diagram showing the structure of the first embodiment of the integrated data cleansing apparatus according to the present invention.
As shown in fig. 4, the accumulated data liquidation apparatus according to the embodiment of the present invention includes:
an obtaining module 4001, configured to obtain to-be-processed point data of a client, and determine a point adding time of the to-be-processed point data;
a determining module 4002, configured to determine an integral conversion rule according to the integral data to be processed;
a selecting module 4003, configured to select target integral data from the to-be-processed data according to the integral conversion rule and the integral adding time;
and the clearing module 4004 is used for clearing the integral data according to the target integral data.
In this embodiment, to-be-processed integral data of a client is first acquired, integral adding time of the to-be-processed integral data is determined, an integral conversion rule is then determined according to the to-be-processed integral data, target integral data is selected from the to-be-processed data according to the integral conversion rule and the integral adding time, and integral data clearing is performed according to the target integral data. In the prior art, the integral data needs to be manually selected for data clearing, but the integral data clearing processing efficiency is low, but in the embodiment, the target integral data is selected from the data to be processed according to the integral conversion rule and the integral adding time, and then the integral data is cleared according to the target integral data, so that the integral data clearing processing efficiency is improved, and the user experience is further improved.
Further, the determining module 4002 is further configured to divide the integral data to be processed to obtain a plurality of integral data sets;
the determining module 4002 is further configured to obtain integral types corresponding to the integral data sets respectively;
the determining module 4002 is further configured to determine an integral conversion rule according to the integral type.
Further, the determining module 4002 is further configured to search a corresponding sample integral conversion rule from a preset integral mapping relationship table according to the integral type, and use the sample integral conversion rule as the integral conversion rule of the integral type;
the preset integral mapping relation table comprises a corresponding relation between an integral type and a sample integral conversion rule.
Further, the determining module 4002 is further configured to perform priority ranking from front to back according to the integral adding time of the integral data to be processed, so as to obtain a time ranking result;
the determining module 4002 is further configured to divide the to-be-processed integral data according to the time sorting result to obtain a plurality of integral data sets.
Further, the clearing module 4004 is further configured to determine whether the target integral data is greater than a preset clearing threshold;
the clearing module 4004 is further configured to determine, when the target integral data is greater than the preset clearing threshold, integral data to be cleared according to the target integral data and the preset clearing threshold, and clear the integral data according to the integral data to be cleared.
Further, the clearing module 4004 is further configured to, when the target integral data is equal to the preset clearing threshold, take the target integral data as integral data to be cleared, and clear the integral data according to the integral data to be cleared.
Further, the clearing module 4004 is further configured to determine whether the integral adding time of the target integral data meets a preset integral clearing condition when the target integral data is smaller than the preset clearing threshold;
the clearing module 4004 is further configured to use the target integral data as integral data to be cleared when the preset integral clearing condition is met, and clear the integral data according to the integral data to be cleared.
Other embodiments or specific implementation manners of the device for clearing accumulated data of the present invention may refer to the above method embodiments, and are not described herein again.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., a rom/ram, a magnetic disk, an optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A point data clearing method, characterized by comprising:
acquiring to-be-processed integral data of a client, and determining integral adding time of the to-be-processed integral data;
determining an integral conversion rule according to the integral data to be processed;
selecting target integral data from the data to be processed according to the integral conversion rule and the integral adding time;
and carrying out integral data clearing according to the target integral data.
2. The method of claim 1, wherein the step of determining an integral scaling rule based on the integral data to be processed comprises:
dividing the integral data to be processed to obtain a plurality of integral data sets;
respectively acquiring integral types corresponding to the integral data sets;
and determining an integral conversion rule according to the integral type.
3. The method of claim 2, wherein the step of determining a score scaling rule based on the score type comprises:
searching a corresponding sample integral conversion rule from a preset integral mapping relation table according to the integral type, and taking the sample integral conversion rule as the integral conversion rule of the integral type;
the preset integral mapping relation table comprises a corresponding relation between an integral type and a sample integral conversion rule.
4. The method of claim 2, wherein the step of dividing the integral data to be processed to obtain a plurality of integral data sets comprises:
carrying out priority sequencing from front to back according to the integral adding time of the integral data to be processed to obtain a time sequencing result;
and dividing the integral data to be processed according to the time sequencing result to obtain a plurality of integral data sets.
5. The method of any one of claims 1-4, wherein the step of performing a credit data clearing based on the target credit data comprises:
judging whether the target integral data is larger than a preset clearing threshold value or not;
and when the target integral data is larger than the preset clearing threshold value, determining integral data to be cleared according to the target integral data and the preset clearing threshold value, and clearing the integral data according to the integral data to be cleared.
6. The method of claim 5, wherein the step of determining whether the target integration data is greater than a preset clearing threshold is followed by:
and when the target integral data is equal to the preset clearing threshold value, taking the target integral data as integral data to be cleared, and clearing the integral data according to the integral data to be cleared.
7. The method of claim 5, wherein the step of determining whether the target integration data is greater than a preset clearing threshold is followed by:
when the target integral data is smaller than the preset clearing threshold value, judging whether the integral adding time of the target integral data meets a preset integral clearing condition;
and when the preset integral clearing condition is met, taking the target integral data as integral data to be cleared, and clearing the integral data according to the integral data to be cleared.
8. An integrated data liquidation apparatus, characterized by comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring the integral data to be processed of a client and determining the integral adding time of the integral data to be processed;
the determining module is used for determining an integral conversion rule according to the integral data to be processed;
the selection module is used for selecting target integral data from the data to be processed according to the integral conversion rule and the integral adding time;
and the clearing module is used for clearing the integral data according to the target integral data.
9. A point data liquidation apparatus, characterized by comprising: memory, a processor and a credit data clearing program stored on the memory and executable on the processor, which when executed by the processor implements the steps of the credit data clearing method as claimed in any one of claims 1 to 7.
10. A storage medium, characterized in that the storage medium has stored thereon an integral data clearing program which, when executed by a processor, implements the steps of the integral data clearing method according to any one of claims 1 to 7.
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