Method and device for processing burying point data

Abstract

The invention discloses a buried point data processing method and device, and relates to the technical field of computers. A specific embodiment of the method comprises the steps of generating a first association identifier and a first association scene identifier corresponding to a first burying point according to received first burying point data of the first burying point; storing the first association identifier in a storage space corresponding to the first association scene identifier; generating a second associated scene identifier corresponding to a second burying point according to received second burying point data of the second burying point, and generating a second associated identifier corresponding to the second burying point according to the first associated identifier and the second burying point data in response to the fact that the first associated scene identifier is the same as the second associated scene identifier, and updating the storage space by using the second association identifier. According to the embodiment, the association identifier representing the execution sequence between the burying points is generated, so that the burying point data of each scene can be accurately positioned and associated subsequently according to the association identifier.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method and device for processing buried point data. Background Art

[0002] With the development of digital technology, data analysis has become an indispensable part of various business fields. The source of data analysis is data collection, and tracking is an important means of data collection. In the actual use of tracking data, it is often necessary to associate each tracking data in the order of execution in order to perform scenario-based business data analysis. The existing tracking data query method can only obtain all tracking data for each scene through the defined scene tags. For the association of tracking data across scenes, manual screening and comparison are required to narrow the positioning range, and then the tracking data of each small range are integrated to approximate representation.

[0003] In the process of implementing the present invention, the inventors found that the prior art has the following problems:

[0004] The existing method of associating and integrating buried point data cannot accurately locate the required buried point data among all the buried point data in the scene. When the amount of buried point data in the scene is relatively large, not only will the query and positioning be time-consuming, but the accuracy will also be further affected, which cannot meet actual needs. Summary of the invention

[0005] In view of this, an embodiment of the present invention provides a method and device for processing buried point data, generates an association identifier that can characterize the execution order between buried points, and further provides basic support for the association query of buried point data, so that the buried point data of each scene can be accurately located and associated according to the association identifier in the storage space, thereby providing accurate and reliable buried point data for scenario-based and business-oriented data analysis.

[0006] To achieve the above object, according to one aspect of an embodiment of the present invention, a method for processing buried point data is provided, comprising:

[0007] Generate a first association identifier and a first association scene identifier corresponding to the first burying point according to the received first burying point data;

[0008] Storing the first association identifier in a storage space corresponding to the first association scenario identifier;

[0009] Based on the second buried point data received from the second buried point, a second associated scene identifier corresponding to the second buried point is generated. In response to the first associated scene identifier being the same as the second associated scene identifier, a second associated identifier corresponding to the second buried point is generated based on the first associated identifier and the second buried point data, and the second associated identifier is used to update the storage space.

[0010] Optionally, based on the first buried point data of the received first buried point, a first association identifier and a first associated scene identifier corresponding to the first buried point are generated, including: based on the business scenario to which the first buried point belongs, querying the associated scene corresponding to the business scenario from a preset associated scene identifier table, and then obtaining the first associated scene identifier; generating the first association identifier based on the scene behavior identifier corresponding to the business scenario and the buried point identifier of the first buried point.

[0011] Optionally, a second association identifier corresponding to the second buried point is generated based on the first association identifier and the second buried point data, including: generating a native association identifier of the second buried point based on a scenario behavior identifier corresponding to the business scenario to which the second buried point data belongs and the buried point identifier of the second buried point; and concatenating the native association identifier at the end of the first association identifier to obtain a second association identifier corresponding to the second buried point.

[0012] Optionally, the storage space has an upper limit on the number of cascade identifiers; before using the second association identifier to update the storage space, the method also includes: verifying that the number of cascade identifiers in the second association identifier does not exceed the upper limit; in response to the number of cascade identifiers in the second association identifier exceeding the upper limit, deleting the second association identifier according to the upper limit to update the storage space using association identifiers that meet the upper limit.

[0013] Optionally, after generating the first association identifier and the first association scene identifier corresponding to the first burial point, or generating the second association identifier corresponding to the second burial point, the method further includes: associating the first association identifier and the first association scene identifier with the first burial point data for system reporting, and storing them in a reporting database; or, associating the second association identifier and the second association scene identifier with the second burial point data for system reporting, and storing them in a reporting database.

[0014] Optionally, the method further includes: obtaining an associated scene identifier according to an associated query task of the received buried point data; obtaining an associated identifier from the storage space corresponding to the associated scene identifier; and back-tracing and querying the target buried point data from the reporting database according to the associated identifier.

[0015] Optionally, the association identifier has a cascade connector that represents the execution order between different embedding points; based on the association identifier, backtrackingly querying the target embedding point data from the reporting database, including: based on the cascade connector in the association identifier, cascadingly splitting the association identifier to obtain the previous-level association identifier corresponding to the previous-level embedding point before the embedding point corresponding to the association identifier is executed; based on the association identifier and the previous-level association identifier, backtrackingly querying the corresponding embedding point data from the reporting database, and associating and assembling the embedding point data in the order of the backtracking query to obtain the target embedding point data.

[0016] Optionally, after backtracking and querying the target burial point data from the reporting database, the method further includes: clearing the association identifiers stored in the storage space.

[0017] According to a second aspect of an embodiment of the present invention, a device for processing buried point data is provided, including:

[0018] An association identifier generating module, used for generating a first association identifier and a first association scene identifier corresponding to the first burying point according to the received first burying point data;

[0019] An association identifier storage module, used to store the first association identifier in a storage space corresponding to the first association scenario identifier;

[0020] An association identifier update module is used to generate a second associated scene identifier corresponding to the second buried point based on the second buried point data received from the second buried point, and in response to the first associated scene identifier being the same as the second associated scene identifier, generate a second associated identifier corresponding to the second buried point based on the first associated identifier and the second buried point data, and use the second associated identifier to update the storage space.

[0021] According to a third aspect of an embodiment of the present invention, there is provided an electronic processing device for buried point data, comprising:

[0022] one or more processors;

[0023] a storage device for storing one or more programs,

[0024] When the one or more programs are executed by the one or more processors, the one or more processors implement the method provided in the first aspect of the embodiment of the present invention.

[0025] According to a fourth aspect of an embodiment of the present invention, a computer-readable medium is provided, on which a computer program is stored, and when the program is executed by a processor, the method provided by the first aspect of the embodiment of the present invention is implemented.

[0026] According to a fifth aspect of an embodiment of the present invention, there is provided a computer program product, including a computer program, wherein when the computer program is executed by a processor, the method provided in the first aspect of the embodiment of the present invention is implemented.

[0027] An embodiment of the invention has the following advantages or beneficial effects: by generating a first association identifier and a first associated scene identifier corresponding to the first buried point according to the first buried point data received; storing the first association identifier in the storage space corresponding to the first associated scene identifier; generating a second associated scene identifier corresponding to the second buried point according to the second buried point data received, in response to the first associated scene identifier being the same as the second associated scene identifier, generating a second association identifier corresponding to the second buried point according to the first association identifier and the second buried point data, and using the second association identifier to update the storage space. The technical solution generates an association identifier that can characterize the execution order between the buried points, thereby providing basic support for the associated query of the buried point data, so that the buried point data of each scene can be accurately located and associated according to the associated identifier in the storage space, providing accurate and reliable buried point data for scenario-based and business-based data analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The accompanying drawings are used to better understand the present invention and do not constitute an improper limitation of the present invention.

[0029] Figure 1 is a schematic diagram of the main process of the method for processing buried point data according to an embodiment of the present invention;

[0030] Figure 2 It is a schematic diagram of a business scenario and corresponding burying points in a scenario associated with a message sending failure according to an embodiment of the present invention;

[0031] Figure 3 It is a schematic diagram of association identifiers corresponding to various tracking points executed successively in an association scenario of message sending failure in an embodiment of the present invention;

[0032] Figure 4 This is a schematic diagram of reporting point data according to an embodiment of the present invention;

[0033] Figure 5 Schematic diagram of a method for associative query of buried point data according to an embodiment of the present invention;

[0034] Figure 6 It is a schematic diagram of the overall principle of processing the buried point data according to an embodiment of the present invention;

[0035] Figure 7 2 is a schematic diagram of main modules of a device for processing buried point data according to an embodiment of the present invention;

[0036] Figure 8is an exemplary system architecture diagram to which embodiments of the present invention may be applied;

[0037] Fig. 9 It is a schematic diagram of the structure of a computer system of a terminal device or a server suitable for implementing an embodiment of the present invention. DETAILED DESCRIPTION

[0038] It should be noted that the acquisition, storage and application of user personal information involved in the technical solution of the present disclosure are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0039] The following is a description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0040] The existing method of associating and integrating buried point data cannot accurately locate the required buried point data among all the buried point data in the scene. When the amount of buried point data in the scene is relatively large, not only will the query and positioning be time-consuming, but the accuracy will also be further affected, which cannot meet actual needs.

[0041] In order to solve the above-mentioned problems existing in the prior art, the present invention proposes a method for processing buried point data. When the buried point data is received, a corresponding association identifier is generated, and the association identifier of the latest buried point data belonging to the same associated scene identifier is updated and stored in the storage space corresponding to the associated scene identifier. The second association identifier of the second buried point is generated based on the first association identifier of the first buried point, thereby realizing a method for generating and recording association identifiers that can characterize the execution order between buried points, thereby providing basic support for the associated query of buried point data, so that the buried point data of each scene can be accurately located and associated according to the association identifier in the storage space, thereby providing accurate and reliable buried point data for scenario-based and business-oriented data analysis.

[0042] Figure 1 FIG. 1 is a schematic diagram of the main process of the method for processing buried point data according to an embodiment of the present invention. Figure 1 As shown, the method for processing buried point data according to an embodiment of the present invention includes the following steps S101 to S103.

[0043] Step S101: Generate a first association identifier and a first association scene identifier corresponding to the first buried point according to the received first buried point data.

[0044] Specifically, in the actual business execution process, the tracking points deployed in the business execution code generate tracking point data when they are triggered by user behavior or a specific running action. It can be understood that in the existing microservice architecture, various business scenarios are associated with each other, and different business scenarios correspond to different scenario codes. The embodiment of the present invention classifies the business scenarios with associated relationships together, and defines the first and second tracking points according to the order of the tracking point triggering. Of course, the third and fourth tracking points can also be defined after the second tracking point. The embodiment of the present invention uses the first and second tracking points as illustrative objects, and the processing of other subsequent tracking points is similar to the processing method of the second tracking point. The processing of the first and second tracking points is used to illustrate the method of associating the tracking point data in the scenario codes of these business scenarios with associated relationships.

[0045] Exemplarily, the associated scenarios of the embodiments of the present invention can be understood as scenarios with associated relationships at the execution level, such as user online shopping associated scenarios, where business scenarios include browsing scenarios, consulting scenarios, ordering scenarios, payment scenarios, etc.; they can also be understood as scenarios associated with a certain abnormal problem, such as message sending failure associated scenarios, and their corresponding business scenarios are the various scenarios where the reasons for the message sending failure are located, such as: network abnormality business scenarios, connection abnormality business scenarios, receipt timeout business scenarios, etc. In short, the associated scenarios of the embodiments of the present invention are equivalent to the general term for some business scenarios with associated relationships, and these business scenarios are classified together through associated scenarios. In actual applications, each business scenario in the associated scenario can be defined as needed, as long as there is a certain association relationship between these business scenarios and they have a sequential execution order.

[0046] Figure 2 It is a schematic diagram of the business scenarios and corresponding burying points in the associated scenarios of message sending failure in an embodiment of the present invention. The associated scenarios of message sending failure include business scenarios of network abnormality, business scenarios of connection abnormality, business scenarios of message business abnormality, business scenarios of receipt timeout and business scenarios of message sending failure, and definitions are added for the burying points in the code of each business scenario. For example, the burying point of the business scenario of network abnormality is the net network abnormality burying point, the burying point of the business scenario of connection abnormality is the cnt connection abnormality burying point, the burying point of the business scenario of message sending failure is the sfm message sending failure burying point, etc.

[0047] Furthermore, when the tracking system receives the first tracking data generated after the first tracking is triggered, that is, when the tracking system receives the tracking data of the first tracking, it identifies the associated scene to which the business scene belongs according to the business scene where the first tracking corresponds to the first tracking data, and uses the name of the associated scene as the first associated scene identifier. And the business scene where the first tracking corresponds to the first tracking data and the name of the first tracking are input into the unique identification code UUID generation tool to obtain the first associated identifier output by the UUID generation tool.

[0048] According to one embodiment of the present invention, based on the first buried point data of the received first buried point, a first association identifier and a first associated scene identifier corresponding to the first buried point are generated, including: based on the business scenario to which the first buried point belongs, querying the associated scene corresponding to the business scenario from a preset associated scene identifier table, and then obtaining the first associated scene identifier; generating the first association identifier based on the scene behavior identifier corresponding to the business scenario and the buried point identifier of the first buried point.

[0049] Although the above method of generating the first association identifier can generate corresponding identifiers for different buried point data, the first association identifier is based on the encoding of the business scenario and the buried point name. The scene behavior characteristics of the user in the business scenario cannot be directly obtained from the first association identifier, and it cannot meet the finer-grained requirements of the buried point system. For example, the buried point system only needs to obtain the buried point data of the user's operation behavior between business scenario A and business scenario B in the associated scenario, but does not need to obtain the buried point data of the user performing a full-process behavior in the associated scenario. Therefore, an embodiment of the present invention provides a method for generating an association identifier that can characterize both a unique identifier of buried point data and a scene behavior of buried point data.

[0050] Specifically, in order to improve efficiency, the present invention sets the associated scene identifiers of various associated scenes in advance, and lists the business scenarios contained in each associated scene after the associated scene identifier of the associated scene, forming an associated scene identifier table with a table structure. According to the business scenario to which the first buried point belongs, the associated scene corresponding to the business scenario is queried from the associated scene identifier table, and then the associated scene identifier corresponding to the associated scene is obtained, and the queried associated scene identifier is used as the first associated scene identifier.

[0051] Furthermore, based on the business scenario to which the first buried point corresponds to the first buried point data, a corresponding scenario behavior identifier is generated, and based on the buried point information of the first buried point, such as the buried point name, the location where the buried point is deployed, etc., a buried point identifier is generated. The scenario behavior identifier and the buried point identifier are combined to generate a first associated identifier, such as the scenario behavior identifier ack. If the buried point identifier of the first buried point is a1, then the first associated identifier is ack_a1.

[0052] Table 1 below is a schematic table of the first association marks corresponding to different business scenarios of the embodiments of the present invention. The association scenario identifier of the association scenario of message sending failure in Table 1 is also determined as msg_send_fail by querying the preset association scenario identifier table. The association scenario includes several business scenarios such as network anomaly, connection anomaly, message service anomaly, receipt timeout, and message sending failure. The corresponding scenario behavior identifiers are net, cnt, bzm, ack, and sfm, respectively, and the corresponding association identifiers are generated according to the buried point identifiers of each business scenario: net_n1, cnt_c1, bzm_b1, ack_a1, sfm_s1. From the association identifier of this example, it can be seen that the generation rule of the buried point identifier of each business scenario is a combination of the first character of the scenario behavior identifier and the order of the buried point in the code. Of course, this is only one of the generation rules of the buried point identifier, and a unique identifier can also be randomly generated, which is selected according to needs.

[0053] Step S102: Store the first association identifier in a storage space corresponding to the first association scenario identifier.

[0054] Specifically, in order to record the execution of the burial point in the associated scene, the embodiment of the present invention establishes a corresponding storage space for the first associated scene identifier after generating the first associated scene identifier, which is used to store the associated identifier of the currently acquired burial point data. Since the currently acquired burial point data comes from the first burial point, the first associated identifier of the first burial point is stored in the storage space.

[0055] Step S103: Generate a second associated scene identifier corresponding to the second buried point based on the second buried point data received; in response to the first associated scene identifier being the same as the second associated scene identifier, generate a second associated identifier corresponding to the second buried point based on the first associated identifier and the second buried point data, and use the second associated identifier to update the storage space.

[0056] Specifically, after receiving the first buried point data of the first buried point, the second buried point data of the second buried point is received, and according to the business scenario to which the second buried point corresponding to the received second buried point data belongs, the associated scenario corresponding to the business scenario is queried from the preset associated scenario identification table, and then the second associated scenario identification is obtained. It is determined whether the second associated scenario identification is the same as the first associated scenario identification. If they are the same, the buried point system needs to update the second associated identification of the second buried point and store it in the above-mentioned storage space, that is, clear the first associated identification of the first buried point originally stored in the storage space, and record the second associated identification of the second buried point currently triggered. In order to record the previous and next association relationship between the second buried point and the first buried point while recording the second associated identification, the second associated identification is jointly generated by the first associated identification and the second buried point data, so as to achieve the purpose of simultaneously recording the second buried point and the association relationship between the second buried point and the first buried point.

[0057] It can be understood that if the second associated scene identifier is different from the first associated scene identifier, then the second buried point and the first buried point do not belong to the same associated scene, and the generation of the second associated identifier of the second buried point requires obtaining the associated identifier of the previous buried point earlier than the second buried point from the storage space corresponding to the second associated scene identifier, generating the second associated identifier based on the obtained associated identifier and the second buried point data, and using the second associated identifier to update the storage space corresponding to the second associated scene identifier. Of course, if the associated identifier cannot be obtained from the storage space corresponding to the second associated scene identifier, it means that the second buried point is the first triggered buried point for the associated scene to which it belongs, then the corresponding associated identifier is generated according to the processing method of the first buried point in the embodiment of the present invention, and the associated identifier is recorded in the storage space corresponding to the second associated scene identifier.

[0058] According to one embodiment of the present invention, a second association identifier corresponding to the second buried point is generated based on the first association identifier and the second buried point data, including: generating a native association identifier of the second buried point based on a scenario behavior identifier corresponding to the business scenario to which the second buried point data belongs and a buried point identifier of the second buried point; and cascading the native association identifier to the end of the first association identifier to obtain a second association identifier corresponding to the second buried point.

[0059] Specifically, after determining that the second associated scene identifier is the same as the first associated scene identifier, it is determined that the second buried point is triggered after the first buried point. In this case, the second associated identifier is generated by first determining the corresponding scene behavior identifier based on the business scenario to which the second buried point data belongs, and determining the buried point identifier based on the buried point information of the second buried point. The scene behavior identifier and the buried point identifier are combined into a native associated identifier. The generation of the native associated identifier in the embodiment of the present invention is similar to the method for generating the first associated identifier of the first buried point mentioned above.

[0060] Furthermore, based on the second associated scene identifier or the first associated scene identifier, the first associated identifier of the first tracking point stored in the corresponding storage space is read, and the native associated identifier is cascaded to the end of the first associated identifier to obtain the second associated identifier.

[0061] It can be understood that if the third buried point data of the third buried point is subsequently received, the processing method is similar to the second buried point data. First, the third associated scene identifier corresponding to the third buried point is generated, and when the third associated scene identifier is the same as the first associated scene identifier (which can also be the second associated scene identifier), the third associated identifier is generated according to the second associated identifier stored in the storage space and the native associated identifier of the third buried point, and the storage space is updated with the third associated identifier. The subsequent fourth, fifth, sixth buried points, etc. are also processed in this way.

[0062] Figure 3 It is a schematic diagram of the association identifiers corresponding to the various buried points executed successively in the associated scenario of message sending failure in the embodiment of the present invention. Taking the associated scenario of message sending failure as an example, if the order of buried point execution (that is, the buried point is triggered) is net network abnormality buried point → cnt connection abnormality buried point → sfm message sending failure buried point, then the net network abnormality buried point is the first buried point, the cnt connection abnormality buried point is the second buried point, and the sfm message sending failure buried point is the third buried point after the second buried point. Then the first association identifier of the first buried point is the combination of the scene behavior identifier net and the buried point identifier n1, net_n1, and net_n1 is stored in the storage space corresponding to the first associated scene identifier. The second association identifier of the second buried point is the cascade net_n1-cnt_c1 of the native association identifier cnt_c1 of the combination of the scene behavior identifier cnt and the buried point identifier c1 and the net_n1 of the storage space, and net_n1-cnt_c1 is used to update the storage space. According to the similar processing as the second buried point, the native association identifier sfm_s1 of the third buried point and the net_n1-cnt_c1 of the storage space are cascaded to obtain the third association identifier net_n1-cnt_c1-sfm_s1, and the storage space is updated using net_n1-cnt_c1-sfm_s1.

[0063] According to another embodiment of the present invention, the storage space has an upper limit on the number of cascade identifiers; before using the second association identifier to update the storage space, the method also includes: verifying that the number of cascade identifiers in the second association identifier does not exceed the upper limit; in response to the number of cascade identifiers in the second association identifier exceeding the upper limit, deleting the second association identifier according to the upper limit to update the storage space using association identifiers that meet the upper limit.

[0064] Specifically, in order to avoid occupying too many resources, the embodiment of the present invention sets an upper limit on the number of cascaded association identifiers for the storage space. Before using the second association identifier to update the storage space, it is necessary to first verify that the number of cascade identifiers in the second association identifier does not exceed the upper limit. The embodiment of the present invention can set 3 or other values. The specific number of cascade identifiers is mainly identified by the cascade connector. For example, the net_n1-cnt_c1-sfm_s1 in the above example contains 2 cascade connectors "-", so the number of its consecutive identifiers is 3. It can be understood that under normal circumstances, the number of cascade identifiers of the second association identifier is 2, which will not exceed 3. However, for the subsequent fourth buried point, fifth buried point, and sixth buried point, the number of cascade identifiers will exceed the upper limit. Since the number of cascade identifiers is checked before each storage space update, the first time it is found that the upper limit is exceeded, it is exceeded by 1 cascade identifier. At this time, you only need to delete the cascade identifier of the frontmost level, that is, the first associated identifier, to meet the upper limit requirement. When the storage space is subsequently updated with a new associated identifier, the cascade identifier of the frontmost level also needs to be deleted. This ensures the appropriate length of the associated identifier and retains the cascade identifier of the latest associated tracking point.

[0065] For example, after the third buried point sfm message sending buried point mentioned above fails, there is a fourth buried point vsm, and the upper limit of the number of cascade identifiers set is 3. Then, based on the native association identifier vsm_v1 of the fourth buried point, the corresponding association identifier generated is net_n1-cnt_c1-sfm_s1-vsm_v1. When net_n1-cnt_c1-sfm_s1-vsm_v1 is used to update the storage space, the check of the number of cascade identifiers fails, and the front-end net_n1 is deleted, and the cascade connector after it is also deleted to obtain the deleted association identifier cnt_c1-sfm_s1-vsm_v1, and cnt_c1-sfm_s1-vsm_v1 is used to update the storage space.

[0066] In addition, in addition to generating the corresponding first association identifier and second association identifier when receiving the first burial point data and the second burial point data, the complete burial point data will also be reported.

[0067] According to another embodiment of the present invention, after generating the first association identifier and the first association scene identifier corresponding to the first burial point, or generating the second association identifier corresponding to the second burial point, the method further includes: associating the first association identifier and the first association scene identifier with the first burial point data for system reporting, and storing them in a reporting database; or, associating the second association identifier and the second association scene identifier with the second burial point data for system reporting, and storing them in a reporting database.

[0068] Specifically, the first association identifier and the first association scene identifier are associated with the first buried point data for system reporting and stored in the system's reporting database; the second association identifier and the second association scene identifier are associated with the second buried point data for system reporting and also stored in the system's reporting database. It can be understood that what is stored at this time is the complete association identifier, and the storage space corresponding to the above-mentioned first association scene identifier is only a cache for recording the currently executed buried point, while the complete data related to the buried point data are persistently stored in the reporting database, providing a stable and reliable data source support for the subsequent use of the buried point data for data analysis.

[0069] Figure 4 The figure shows the reporting of the buried data generated by two different call relationships. The business scenario A, business scenario B and business scenario C in the figure belong to a related scenario, and the corresponding related scenario is identified as rft1.

[0070] For call relationship 1, the first buried point of business scenario A is triggered, the first buried point data is received, and the first associated scene identifier rft1 of the business scenario A where the first buried point data is located is queried. Since the scene behavior identifier of business scenario A is A and the buried point identifier of the first buried point is A1, the first associated identifier A_A1 is generated, and A_A1 is stored in the storage space corresponding to rft1, and then the first associated scene identifier rft1 and the first associated identifier A_A1 are associated with the first buried point data for system reporting. Next, the tracking system receives the second tracking data from business scenario B, and obtains the second associated scene identifier of business scenario B where the second tracking data is located, which is also rft1, the same as the first associated scene identifier, so the first associated identifier A_A1 is read from the storage space, and then the scene behavior identifier of business scenario B is identified as B and the tracking identifier of the second tracking is B1, and the native associated identifier B_B1 is generated, and then B_B1 is cascaded to the end of A_A1 to obtain the second associated identifier A_A1-B_B1, and A_A1-B_B1 is used to update the storage space, and then the second associated scene identifier rft1 and the second associated identifier A_A1-B_B1 are associated with the second tracking data for system reporting.

[0071] For call relationship 2, a method similar to that of call relationship 1 is adopted. For the first buried point received from business scenario C, its corresponding first associated scene identifier is rft1. Since the scene behavior identifier of business scenario C is C and the buried point identifier of the first buried point is C1, a first associated identifier C_C1 is generated, and C_C1 is stored in the storage space corresponding to rft1. Then, the first associated scene identifier rft1 and the first associated identifier C_C1 are associated with the first buried point data for system reporting. Then the second buried point data is received, and the second associated scene identifier of the business scenario B where the second buried point data is located is queried and found to be rft1, which is the same as the first associated scene identifier. Therefore, the first associated identifier C_C1 is read from the storage space, and then the scene behavior identifier of the business scenario B is identified as B, and the buried point identifier of the second buried point is B2, and the native associated identifier B_B2 is generated. B_B1 is then cascaded to the end of C_C1 to obtain the second associated identifier C_C1-B_B2, and C_C1-B_B2 is used to update the storage space, and then the second associated scene identifier rft1 and the second associated identifier C_C1-B_B2 are associated with the second buried point data for system reporting.

[0072] Based on the above generated association identifier, the update of the storage space, and the persistence of the reporting of the complete buried point data, the embodiment of the present invention also provides a method for association query of buried point data. Figure 5 Schematic diagram of a method for associative query of buried point data according to an embodiment of the present invention, which may include:

[0073] Step S501: Obtain an associated scene identifier according to the associated query task of the received buried point data.

[0074] Specifically, the tracking point system receives the associated query task of the tracking point data, which can be initiated by the demand side or triggered by the storage space. In the embodiment of the present invention, a timer can be deployed in the storage space. When the update waiting time of the storage space exceeds the preset update threshold, it is determined that all the tracking points in the associated scene have been executed. At this time, the storage space triggers the associated query task of the tracking point data. The corresponding associated scene identifier is parsed from the associated query task.

[0075] Step S502: Acquire an association identifier from the storage space corresponding to the association scene identifier.

[0076] Specifically, the tracking point system obtains the associated identifier of the tracking point data of the most recently executed tracking point stored in the storage space corresponding to the associated scene identifier based on the obtained associated scene identifier.

[0077] Step S503: According to the association identifier, backtrack and query the target buried point data from the reporting database.

[0078] Specifically, the association identifier obtained by the above query is the association identifier of the last buried point executed in the current business scenario, that is, the identifier of the execution end point, and the association identifier of the previous buried point is also cascaded. Based on the association identifier, the previous buried points of the last buried point are queried step by step from the reporting database, and the buried point data of the previous buried point and the buried point data of the last buried point are combined in the order of backtracking to obtain the associated target buried point data.

[0079] According to one embodiment of the present invention, the association identifier has a cascade connector that represents the execution order between different embedding points; based on the association identifier, the target embedding point data is back-traced from the reporting database, including: based on the cascade connector in the association identifier, the association identifier is cascade-splitting to obtain the previous-level association identifier corresponding to the previous-level embedding point before the embedding point corresponding to the association identifier is executed; based on the association identifier and the previous-level association identifier, the corresponding embedding point data is back-traced from the reporting database, and the embedding point data is associated and assembled in the order of the back-tracing query to obtain the target embedding point data.

[0080] Specifically, for the obtained association identifier, the association identifier is cascaded and split from back to front according to the cascade connector contained therein, and the previous level association identifier before the execution of the buried point corresponding to the association identifier is obtained. For example, in the above net_n1-cnt_c1-sfm_s1, delete the last cascade connector and the identifier behind it, and obtain the association identifier net_n1-cnt_c1 of the previous level of the current buried point; then delete the last cascade connector and the identifier behind it in net_n1-cnt_c1, and obtain the association identifier net_n1 of the first two levels of the current buried point.

[0081] Furthermore, based on the previous-level association identifiers obtained by the splitting, the buried point data associated with the buried point identifier of the previous level of the current buried point is backtracked from the reporting database, and the buried point data queried is the previous level of buried point data. Then, the buried point data associated with the buried point identifiers of the first two levels of buried points are backtracked from the reporting database, and the buried point data queried at this time is the first two levels of buried point data.

[0082] Finally, in the order of first two levels → previous level → current, the first two levels of buried point data, the previous level of buried point data and the current buried point data are connected in series and combined together to obtain the target buried point data.

[0083] It can be understood that, for the case where the association identifiers stored in the storage space are deleted due to the upper limit of the number of cascade identifiers, first, according to the association identifier, the target association identifier ending with the association identifier is queried from the reporting database, and the target association identifier is the complete association identifier of the current buried point. Correspondingly, the buried point data corresponding to the target association identifier is the buried point data of the current buried point. The association identifier is cascaded and split using a method similar to the above to obtain the previous level association identifier (previous level association identifier, previous two level association identifier, previous three level association identifier, etc.). Then, the previous level target association identifier ending with the buried point identifier of the previous level of the current buried point is back-tracked from the reporting database. The previous level target association identifier is the complete association identifier of the previous level buried point, and its associated buried point data is the previous level buried point data; similarly, the first two levels of target association identifiers ending with the buried point identifiers of the previous two levels of buried points are back-tracked from the reporting database. The first two levels of target association identifiers are the complete association identifiers of the first two levels of buried points, and their associated buried point data is the first two levels of buried point data. And so on, until the buried point data of the buried point starting from the starting point is traced back, and finally the found buried point data are associated and assembled in the order of the backtracking query according to the above method to obtain the target buried point data.

[0084] According to another embodiment of the present invention, after backtracking and querying the target burial point data from the reporting database, the method further includes: cleaning the association identifiers stored in the storage space.

[0085] Specifically, after backtracking and querying the target tracking point data from the reporting database, the cascading relationship between each business scenario is ended, and the association identifier in the storage space is cleared, so that when the associated scenario starts a new round of calls between business scenarios, the association identifier stored in the storage space starts from the association identifier of the starting tracking point, avoiding the influence of historical records.

[0086] Figure 6 It is a schematic diagram of the overall principle of processing the buried point data of an embodiment of the present invention. When the buried point system receives the buried point data generated by the triggered buried point of the business scenario in the associated scenario, it caches the buried point data, queries to determine its corresponding associated scene identifier, and starts the cascade initialization inside the associated scene, such as establishing a storage space corresponding to the associated scene identifier. Then, an associated identifier is generated based on the scene behavior identifier and the buried point identifier of the current buried point business scenario. The associated scene identifier and the associated identifier are associated with the buried point data, and the system is reported. The data receiving end receives the reported data, stores the reported data in the reporting database, and returns a message of successful reporting, and then cleans and deletes the buried point data in the cache.

[0087] Among them, the determination of the association identifier, for the first embedding point, can be generated directly based on the scene behavior identifier and the embedding point identifier. For non-first embedding points, it is necessary to determine it by cascading the native association identifier generated by the scene behavior identifier and the embedding point identifier and the association identifier of the previous embedding point stored in the storage space.

[0088] Furthermore, the determined association identifier is used to update the storage space corresponding to the associated scene identifier, and before the update, it is determined that the number of cascade identifiers of the association identifier does not exceed the preset upper limit of the storage space. If it exceeds, the association identifier is first deleted, and then the deleted association identifier is used to update the storage space.

[0089] When the tracking point system receives the associated query task of the tracking point data, it first obtains the associated scene identifier, and then obtains the associated identifier from the storage space corresponding to the associated scene identifier; according to the associated identifier, the target tracking point data is back-searched from the reporting database. Of course, the tracking point data can also be queried from different dimensions. For example, the query task of the tracking point data with certain associated identifiers can be directly specified. In this case, the corresponding tracking point data can be directly searched from the reporting database according to the associated identifier, and then returned to the initiator of the query task. It is also possible to specify the query task of the tracking point data with a certain associated scene identifier. In this case, all the tracking point data associated with the associated scene identifier can be directly summarized from the reporting database, and then returned to the initiator of the query task. It is also possible to specify the query task of the tracking point data of the scene behavior. In this case, the tracking point data corresponding to all the associated identifiers containing the scene behavior identifier can be directly obtained from the reporting database according to the scene behavior identifier, and then returned to the initiator of the query task.

[0090] Finally, after backtracking and querying the target tracking point data from the reporting database, the cascading relationship between the business scenarios is ended, and the associated identifiers stored in the storage space of the tracking point system are cleaned up and deleted.

[0091] The embodiment of the present invention constructs an association identifier that can characterize the before and after execution relationship between the buried points, and records the association identifier of the last executed buried point, thereby realizing accurate and efficient retrospective association query of the buried point data through management identifiers. It can be seen from the above that the generation and management method of association tags based on the embodiment of the present invention also realizes flexible query of buried point data, which can perform association query of buried point data, and can also query the buried point data in the business scenario dimension, or query the buried point data in the association identifier dimension, or query the buried point data in the association scenario dimension according to the query requirements of specified different dimensions, thereby flexibly meeting various different requirements and providing a strong guarantee for efficient and accurate data analysis.

[0092] Figure 7 Schematic diagram of the main modules of the device for processing buried point data according to an embodiment of the present invention. Figure 7 As shown, the processing device 700 for burial point data mainly includes an association identifier generation module 701, an association identifier storage module 702 and an association identifier update module 703.

[0093] The association identifier generating module 701 is used to generate a first association identifier and a first association scene identifier corresponding to the first burying point according to the received first burying point data;

[0094] An association identifier storage module 702, configured to store the first association identifier in a storage space corresponding to the first association scenario identifier;

[0095] The association identifier update module 703 is used to generate a second associated scene identifier corresponding to the second buried point based on the second buried point data received from the second buried point, and in response to the first associated scene identifier being the same as the second associated scene identifier, generate a second associated identifier corresponding to the second buried point based on the first associated identifier and the second buried point data, and use the second associated identifier to update the storage space.

[0096] According to one embodiment of the present invention, the association identifier generation module 701 can also be used to: query the associated scenario corresponding to the business scenario from a preset associated scenario identifier table according to the business scenario to which the first buried point belongs, and then obtain the first associated scenario identifier; generate the first association identifier according to the scenario behavior identifier corresponding to the business scenario and the buried point identifier of the first buried point.

[0097] According to another embodiment of the present invention, the association identifier update module 703 can also be used to: generate a native association identifier of the second buried point based on the scenario behavior identifier corresponding to the business scenario to which the second buried point data belongs and the buried point identifier of the second buried point; cascade the native association identifier to the end of the first association identifier to obtain a second association identifier corresponding to the second buried point.

[0098] According to another embodiment of the present invention, the storage space has an upper limit on the number of cascade identifiers; the processing device 700 for the buried point data also includes a cascade number verification module (not shown in the figure), which is used to: before using the second association identifier to update the storage space, verify that the number of cascade identifiers in the second association identifier does not exceed the upper limit; in response to the number of cascade identifiers in the second association identifier exceeding the upper limit, the second association identifier is deleted according to the upper limit to update the storage space using association identifiers that meet the upper limit.

[0099] According to another embodiment of the present invention, the processing device 700 of the buried point data also includes a data reporting module (not shown in the figure), which is used to associate the first association identifier and the first association scene identifier with the first buried point data for system reporting and store it in a reporting database after generating a first association identifier and a first association scene identifier corresponding to the first buried point, or generating a second association identifier corresponding to the second buried point; or, associate the second association identifier and the second association scene identifier with the second buried point data for system reporting and store it in a reporting database.

[0100] According to another embodiment of the present invention, the processing device 700 of the buried point data also includes a buried point data association query module (not shown in the figure), which is used to: obtain an associated scene identifier according to an associated query task of the received buried point data; obtain an associated identifier from the storage space corresponding to the associated scene identifier; and back-track query the target buried point data from the reporting database according to the associated identifier.

[0101] According to another embodiment of the present invention, the association identifier has a cascade connector that represents the execution order between different buried points; the buried point data association query module (not shown in the figure) can also be used to: according to the cascade connector in the association identifier, cascade split the association identifier to obtain the previous-level association identifier corresponding to the previous-level buried point before the buried point corresponding to the association identifier is executed; according to the association identifier and the previous-level association identifier, backtrack and query the corresponding buried point data from the reporting database, and associate and assemble the buried point data in the order of the backtracking query to obtain the target buried point data.

[0102] According to another embodiment of the present invention, the device 700 for processing the buried point data further includes a cleaning module (not shown in the figure) for cleaning the associated identifiers stored in the storage space after backtracking and querying the target buried point data from the reporting database.

[0103] Figure 8 is an exemplary system architecture diagram to which embodiments of the present invention can be applied.

[0104] like Figure 8 As shown, system architecture 800 may include terminal devices 801, 802, 803, a network 804, and a server 805. Network 804 is used to provide a medium for communication links between terminal devices 801, 802, 803 and server 805. Network 804 may include various connection types, such as wired, wireless communication links, or optical fiber cables, etc.

[0105] Users can use terminal devices 801, 802, 803 to interact with server 805 through network 804 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 801, 802, 803, such as buried point data processing applications, etc. (only as an example).

[0106] The terminal devices 801 , 802 , and 803 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and the like.

[0107] Server 805 can be a server that provides various services, such as a background management server that supports the processing of the buried point data performed by the user using the terminal devices 801, 802, and 803 (only as an example). The background management server can generate a first association identifier and a first associated scene identifier corresponding to the first buried point based on the first buried point data received; store the first association identifier in the storage space corresponding to the first associated scene identifier; generate a second associated scene identifier corresponding to the second buried point based on the second buried point data received, and in response to the first associated scene identifier being the same as the second associated scene identifier, generate a second associated identifier corresponding to the second buried point based on the first associated identifier and the second buried point data, and use the second associated identifier to update the storage space, etc., and feed back the processing results to the terminal device.

[0108] It should be noted that the method for processing the buried point data provided in the embodiment of the present invention is generally executed by the server 805 , and accordingly, the processing device for the buried point data is generally arranged in the server 805 .

[0109] It should be understood that Figure 8 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to the implementation requirements.

[0110] Reference below Fig. 9 , Fig. 9 It is a schematic diagram of the structure of a computer system of a terminal device or a server suitable for implementing an embodiment of the present invention. Fig. 9 The terminal device or server shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0111] like Fig. 9As shown, the computer system 900 includes a central processing unit (CPU) 901, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 902 or a program loaded from a storage part 908 into a random access memory (RAM) 903. In the RAM 903, various programs and data required for the operation of the system 900 are also stored. The CPU 901, the ROM 902, and the RAM 903 are connected to each other through a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0112] The following components are connected to the I / O interface 905: an input section 906 including a keyboard, a mouse, etc.; an output section 907 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 908 including a hard disk, etc.; and a communication section 909 including a network interface card such as a LAN card, a modem, etc. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the I / O interface 905 as needed. A removable medium 911, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 910 as needed, so that a computer program read therefrom is installed into the storage section 908 as needed.

[0113] In particular, according to the embodiments disclosed in the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 909, and / or installed from the removable medium 911. When the computer program is executed by the central processing unit (CPU) 901, the above-mentioned functions defined in the system of the present invention are executed.

[0114] It should be noted that the computer-readable medium shown in the present invention may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination thereof.

[0115] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0116] The units involved in the embodiments of the present invention may be implemented by software or hardware. The units described may also be arranged in a processor, for example, it may be described as follows: a processor includes: an association identifier generation module, an association identifier storage module and an association identifier update module.

[0117] Among them, the names of these modules do not constitute a limitation on the modules themselves in some cases. For example, the association identifier storage module can also be described as "a module for storing the first association identifier in the storage space corresponding to the first association scene identifier."

[0118] On the other hand, the present invention also provides a computer-readable medium, which may be included in the device described in the embodiment; or it may exist independently without being assembled into the device. The computer-readable medium carries one or more programs. When the one or more programs are executed by a device, the device includes: generating a first association identifier and a first association scene identifier corresponding to the first buried point according to the first buried point data received; storing the first association identifier in a storage space corresponding to the first association scene identifier; generating a second association scene identifier corresponding to the second buried point according to the second buried point data received, in response to the first association scene identifier being the same as the second association scene identifier, generating a second association identifier corresponding to the second buried point according to the first association identifier and the second buried point data, and updating the storage space with the second association identifier.

[0119] The technical solution according to the embodiment of the present invention has the following advantages or beneficial effects: by generating a first association identifier and a first associated scene identifier corresponding to the first buried point according to the first buried point data received; storing the first association identifier in the storage space corresponding to the first associated scene identifier; generating a second associated scene identifier corresponding to the second buried point according to the second buried point data received, in response to the first associated scene identifier being the same as the second associated scene identifier, generating a second association identifier corresponding to the second buried point according to the first association identifier and the second buried point data, and using the second association identifier to update the storage space. The technical solution generates an association identifier that can characterize the execution order between the buried points, thereby providing basic support for the associated query of the buried point data, so that the buried point data of each scene can be accurately located and associated according to the associated identifier in the storage space, providing accurate and reliable buried point data for scenario-based and business-based data analysis.

[0120] The specific implementation methods described herein do not constitute limitations on the scope of protection of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention shall be included in the scope of protection of the present invention.

Claims

1. A method for processing buried point data, characterized in that: include: Generate a first association identifier and a first association scene identifier corresponding to the first burying point according to the received first burying point data; Storing the first association identifier in a storage space corresponding to the first association scenario identifier; Based on the second buried point data received from the second buried point, a second associated scene identifier corresponding to the second buried point is generated. In response to the first associated scene identifier being the same as the second associated scene identifier, a second associated identifier corresponding to the second buried point is generated based on the first associated identifier and the second buried point data, and the second associated identifier is used to update the storage space.

2. The method according to claim 1, characterized in that: Generating a first association identifier and a first association scene identifier corresponding to the first burying point according to the received first burying point data includes: According to the business scenario to which the first tracking point belongs, querying the associated scenario corresponding to the business scenario from a preset associated scenario identifier table, thereby obtaining the first associated scenario identifier; The first association identifier is generated according to the scenario behavior identifier corresponding to the business scenario and the burying point identifier of the first burying point.

3. The method according to claim 1, characterized in that Generating a second association identifier corresponding to the second buried point according to the first association identifier and the second buried point data includes: Generate a native association identifier of the second buried point according to the scenario behavior identifier corresponding to the business scenario to which the second buried point data belongs and the buried point identifier of the second buried point; The native association identifier is cascaded to the end of the first association identifier to obtain a second association identifier corresponding to the second burial point.

4. The method according to claim 3, characterized in that The storage space has an upper limit on the number of cascade identifiers; Before using the second association identifier to update the storage space, the method further includes: Verifying that the number of cascade identifiers in the second association identifier does not exceed the upper limit; In response to the number of cascade identifiers in the second association identifier exceeding the upper limit, the second association identifiers are deleted according to the upper limit to update the storage space with association identifiers that meet the upper limit.

5. The method according to claim 1, characterized in that: After generating a first association identifier and a first association scene identifier corresponding to the first burying point, or generating a second association identifier corresponding to the second burying point, the method further includes: Associating the first association identifier and the first association scenario identifier with the first buried point data, reporting the data to the system, and storing the data in a reporting database; Alternatively, the second association identifier and the second association scene identifier are associated with the second buried point data for system reporting and stored in a reporting database.

6. The method according to claim 5, characterized in that The method further comprises: According to the associated query task of the received tracking data, the associated scene identifier is obtained; Acquire an association identifier from the storage space corresponding to the association scene identifier; According to the association identifier, the target buried point data is back-tracked and queried from the reporting database.

7. The method according to claim 6, characterized in that The association identifier has a cascade connector that represents the execution order between different embedding points; According to the association identifier, backtracking and querying the target buried point data from the reporting database includes: According to the cascade connector in the association identifier, the association identifier is cascade-split to obtain a previous-level association identifier corresponding to a previous-level embedding point before the embedding point corresponding to the association identifier is executed; According to the association identifier and the previous level association identifier, the corresponding buried point data is back-tracked from the reporting database, and the buried point data is associated and assembled in the order of the back-tracking query to obtain the target buried point data.

8. The method according to claim 6, characterized in that After backtracking and querying the target buried point data from the reporting database, the method further includes: The association identifiers stored in the storage space are cleared.

9. A device for processing buried point data, characterized in that: include: An association identifier generating module, used for generating a first association identifier and a first association scene identifier corresponding to the first burying point according to the received first burying point data; An association identifier storage module, used to store the first association identifier in a storage space corresponding to the first association scenario identifier; An association identifier update module is used to generate a second associated scene identifier corresponding to the second buried point based on the second buried point data received from the second buried point, and in response to the first associated scene identifier being the same as the second associated scene identifier, generate a second associated identifier corresponding to the second buried point based on the first associated identifier and the second buried point data, and use the second associated identifier to update the storage space.

10. A mobile electronic device terminal, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 8.

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

12. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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