A data management method and device, electronic equipment and storage medium

Abstract

The embodiment of the application provides a data management method and device, electronic equipment and storage medium, the method obtains monitoring information of data by responding to the execution time of the set task, and judges whether the data meets the preset operation condition according to the monitoring information, and when the data meets the operation condition, the target operation associated with the operation condition is used to process the data, based on the above-mentioned mode, for each data to be managed, the target operation associated with the operation condition can be automatically processed when the corresponding set operation condition is met, effectively reducing data accumulation, thereby improving the query efficiency of the data, at the same time, the processing result of the data is monitored and recorded, the life cycle management of the data is realized, thereby facilitating the management personnel to more clearly and directly understand the running state of each data based on the record period, and improving the data management efficiency.

Description

Technical Field

[0001] This invention relates to the field of computer software technology, and in particular to a data management method, apparatus, electronic device, and storage medium. Background Technology

[0002] With the advent of the big data era, the amount of data generated and stored in various industries has increased dramatically, which can easily lead to data accumulation. Under these circumstances, how to efficiently manage the accumulated data has become an important problem that urgently needs to be solved.

[0003] In related technologies, processing strategies for relevant datasets are typically determined based on multiple set active durations. However, when the number of unprocessed data in the dataset is large under the same active duration, the above method can easily lead to data accumulation in the dataset, affecting processing efficiency. Furthermore, the above method only uses a single feature of active duration for management, without considering the different characteristics of different data, which means that when the data volume is large, it cannot meet the actual needs of management personnel. Summary of the Invention

[0004] This application provides a data management method, apparatus, electronic device, and storage medium to avoid data accumulation and improve data management efficiency.

[0005] In a first aspect, embodiments of this application provide a data management method, including:

[0006] In response to the execution time of a set task, monitoring information of the data is acquired, wherein the monitoring information is used to characterize the current attributes of the data.

[0007] Based on the monitoring information, it is determined whether the data meets the preset operation conditions, wherein the operation conditions are associated with the target operation set for the data.

[0008] In response to the data satisfying the operating conditions, the data is processed using the target operation.

[0009] Monitor and record the processing results of the data, and perform lifecycle management of the data based on the processing results.

[0010] Secondly, embodiments of this application provide a data management device, including:

[0011] The task execution module is used to obtain data monitoring information in response to the execution time of a set task, wherein the monitoring information is used to characterize the current attributes of the data.

[0012] The condition judgment module is used to determine whether the data meets preset operation conditions based on the monitoring information, wherein the operation conditions are associated with a target operation set for the data.

[0013] An operation processing module is used to process the data using the target operation in response to the data satisfying the operation conditions.

[0014] The monitoring and management module is used to monitor and record the processing results of the data, and to perform lifecycle management of the data based on the processing results.

[0015] In an optional embodiment, the step of determining whether the data meets preset operating conditions based on the monitoring information, wherein the condition determination module is used to:

[0016] In response to the monitoring information satisfying the set automatic triggering rules, the operation probability of the data corresponding to the target operation is calculated, and when the operation probability is not less than a preset threshold, it is determined that the data satisfies the preset operation conditions.

[0017] And / or,

[0018] In response to the monitoring information satisfying the set custom triggering rule, at least one custom triggering field corresponding to the custom triggering rule is obtained, and when the monitoring information matches the at least one custom triggering field, it is determined that the data meets the preset operation conditions, wherein the custom triggering field is used to indicate the target operation environment of the data.

[0019] In an optional embodiment, the condition judgment module is used to calculate the operation probability of the target operation corresponding to the data, wherein the condition judgment module is configured to:

[0020] Based on the data retrieval date contained in the monitoring information, a first operation probability corresponding to the target operation is calculated using a first parameter, wherein the first parameter represents the maximum storage time of the data.

[0021] Based on the number of times the data is called contained in the monitoring information, a second operation probability corresponding to the target operation is calculated using a second parameter, wherein the second parameter represents the total number of times the data is called.

[0022] The first operation probability and the second operation probability are weighted and summed using a first weight and a second weight respectively to obtain a weighted sum. Based on the weighted sum, the operation probability of the data corresponding to the target operation is calculated using a preset function and a third operation probability. The sum of the first weight and the second weight is one, and the third operation probability is calculated based on the number of stored data entries.

[0023] In an optional embodiment, the step of calculating the operation probability of the target operation corresponding to the data based on the weighted sum value, using a preset function and a third operation probability, wherein the condition judgment module is used to:

[0024] Based on the number of stored records of the data, a third operation probability corresponding to the target operation is calculated using a third parameter, wherein the third parameter represents the maximum number of stored records of the data.

[0025] The target function value corresponding to the weighted sum is calculated according to the preset function, and the target function value is calculated using the third operation probability to obtain the operation probability of the target operation corresponding to the data.

[0026] In an optional embodiment, if the target operation is data archiving, then the operation processing module is used to process the data using the target operation, and the module is configured to:

[0027] The data is saved in file format using file archiving.

[0028] or,

[0029] Database archiving is used to save the data to a specified database table.

[0030] In an optional embodiment, if the target operation is data destruction, then the operation processing module is used to process the data using the target operation, and the module is configured to:

[0031] The data is destroyed using a recycle bin and migrated to the target recycling space.

[0032] or,

[0033] The data is permanently deleted.

[0034] In an optional embodiment, after monitoring and recording the processing results of the data, the monitoring management module is further configured to:

[0035] Based on the processing result, update the current data volume of the data, and update the processed data volume of the data corresponding to the target operation.

[0036] The current data volume and the processed data volume are used to analyze the data's operational status, and the operational status is displayed in a preset display interface.

[0037] Thirdly, an electronic device is proposed, comprising a processor and a memory, wherein the memory stores program code that, when executed by the processor, causes the processor to perform the steps of the data management method described in the first aspect.

[0038] Fourthly, a computer-readable storage medium is provided, comprising program code that, when executed on an electronic device, causes the electronic device to perform the steps of the data management method described in the first aspect.

[0039] The technical effects of the embodiments of this application are as follows:

[0040] This application provides a data management method, apparatus, electronic device, and storage medium. The method acquires data monitoring information in response to the execution time of a set task, determines whether the data meets preset operating conditions based on the monitoring information, and processes the data using a target operation associated with the operating conditions when the data meets the operating conditions. Based on this approach, each piece of data to be managed can be automatically processed by its associated target operation when the corresponding set operating conditions are met, effectively reducing data accumulation and improving data query efficiency. Simultaneously, the processing results of the data are monitored and recorded, realizing data lifecycle management. This allows managers to more clearly and directly understand the operational status of each piece of data based on the recording cycle, thereby improving data management efficiency. Attached Figure Description

[0041] Figure 1 This is a schematic diagram illustrating a possible application scenario provided by an embodiment of this application;

[0042] Figure 2 A schematic diagram of a management system provided in an embodiment of this application;

[0043] Figure 3 A flowchart illustrating a data management method provided in an embodiment of this application;

[0044] Figure 4 A schematic diagram of a timed task provided in an embodiment of this application;

[0045] Figure 5 A schematic diagram of data archiving provided in an embodiment of this application;

[0046] Figure 6 This application provides a schematic diagram of data destruction as an embodiment of the present application.

[0047] Figure 7 A schematic diagram of lifecycle monitoring provided in an embodiment of this application;

[0048] Figure 8 This is a schematic diagram of the structure of a data management device provided in an embodiment of this application;

[0049] Figure 9 This is a schematic diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0050] The technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this invention.

[0051] It should be noted that in the description of this application, "multiple" is understood as "at least two". "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. A connected to B can represent: A and B directly connected, or A and B connected through C. Furthermore, in the description of this application, terms such as "first" and "second" are used only for descriptive purposes and should not be construed as indicating or implying relative importance or order.

[0052] Furthermore, the data collection, dissemination, and use in the technical solution of this application all comply with the requirements of relevant national laws and regulations.

[0053] The data management method provided in the embodiments of this application will now be described and explained in detail with reference to the accompanying drawings.

[0054] See Figure 1 As shown, it is a schematic diagram of a possible application scenario provided by an embodiment of this application. The application scenario includes: platform 11 and server 12, wherein platform 11 and server 12 can interact with each other through a communication network. The communication network can adopt communication methods including wireless communication and wired communication.

[0055] For example, platform 11 can access the network and communicate with server 12 via cellular mobile communication technology, including 5th Generation Mobile Networks (5G) technology; optionally, platform 11 can also access the network and communicate with server 12 via short-range wireless communication, including Wireless Fidelity (Wi-Fi) technology.

[0056] Optionally, the server 12 can be an independent physical server or a server cluster consisting of multiple physical servers. This application embodiment does not limit this. For ease of understanding, a single server is used as an example for description. The following is a brief introduction to the above devices and their respective functions.

[0057] Platform 11 is a device that can provide users with interface display and / or data connectivity functions, such as handheld terminal devices, vehicle-mounted terminal devices, or any electronic device with data visualization functions.

[0058] For example, platform 11 includes, but is not limited to: Android devices, iOS devices, mobile internet devices (MIDs), or wireless terminal devices in smart cities.

[0059] Furthermore, the target terminal 11 may have a data management-related client installed. This client can be software (e.g., an app, browser, short video app, etc.), or a webpage, mini-program, etc. Optionally, in this embodiment, the platform 11 can use the aforementioned client to provide a display interface to administrators and dynamically display the operational status of relevant data.

[0060] Furthermore, server 12 can generate and / or store large amounts of data, such as user access data, system log data, etc. (See [reference]). Figure 2 As shown, in a specific embodiment, a management system 20 is deployed on the server 102. The management system 20 can be used to manage all (or specified multiple) data in the server 12 according to their respective set operation conditions. Specifically, the management system 20 includes an archiving / destruction condition module 201, an archiving module 202, a destruction module 203, a scheduled task module 204, and a lifecycle monitoring module 205.

[0061] The archiving / destruction condition module 201 is used to set operation conditions for one or more data, wherein the operation conditions are associated with a target operation, and the target operation is an archiving / destruction related operation.

[0062] The archiving module 202 is used to archive at least a portion of the data that meets the conditions for the archiving associated operation, that is, when the target operation is data archiving, it archives at least a portion of the data that meets the operation conditions.

[0063] The destruction module 203 is used to destroy at least a portion of the data that meets the conditions associated with the destruction operation, that is, when the target operation is data destruction, it destroys at least a portion of the data that meets the operation conditions.

[0064] The scheduled task module 204 is used to set the execution time of tasks, that is, to set the execution time for each piece of data, such as daily / monthly / specific date execution, etc.

[0065] The lifecycle monitoring module 205 is used to monitor and record the entire lifecycle processing results of data and analyze its operation status. Optionally, the lifecycle monitoring module 205 can also perform statistics on the execution status of each target operation and / or the operation status of the data, and dynamically display the relevant results (such as generation, archiving, destruction records, etc.) on the display interface of the platform 11 through the aforementioned client.

[0066] Based on the above application scenarios, the data management method provided in the embodiments of this application will be further described and explained below with reference to the accompanying drawings. Figure 3 As shown, it includes:

[0067] S301: In response to the execution time of the set task, acquire monitoring information of the data.

[0068] S302: Determine whether the data meets the preset operating conditions based on the monitoring information.

[0069] Specifically, setting a task refers to a scheduled task for data, used to indicate the execution time of a method. For example, it can be set to execute daily / monthly / on a specified date, meaning that data will be retrieved at the designated execution time. For instance, multiple tasks (Task 1-Task n) can be set via scheduled tasks, with each task having its own execution time. The execution of each task will then proceed as follows: Figure 4 As shown.

[0070] Specifically, monitoring information is used to characterize the current attributes of the data, such as specified data fields, including but not limited to the call date field, the number of calls field, or some fields containing characters of a specified type.

[0071] Furthermore, the operation conditions are associated with the target operations set for the data, such as, but not limited to, data archiving and data destruction.

[0072] In an optional embodiment, in step S302, determining whether the data meets preset operating conditions based on monitoring information includes any one or a combination of the following:

[0073] 1) In response to the monitoring information meeting the set automatic triggering rules, calculate the operation probability of the target operation corresponding to the data, and determine that the data meets the preset operation conditions when the operation probability is not less than the preset threshold.

[0074] Specifically, the operation conditions can be automatic triggering conditions set for the data through an automated algorithm. In the above case, when it is determined that the monitoring information meets the set automatic triggering rules, it can be judged whether the data meets the preset operation conditions based on the calculated operation probability of the target operation corresponding to the data.

[0075] In one optional embodiment, the automatic triggering rule indicates that the monitoring information indicates the data contains specified fields, such as call date and / or call count fields. Based on these fields, the operation probability corresponding to the target operation is calculated, including:

[0076] Step 11: Based on the data retrieval date contained in the monitoring information, use the first parameter to calculate the first operation probability of the target operation corresponding to the data.

[0077] Step 12: Based on the number of times the data is called contained in the monitoring information, use the second parameter to calculate the second operation probability of the target operation corresponding to the data.

[0078] Step 13: Using the first weight and the second weight respectively, the first operation probability and the second operation probability are weighted and summed to obtain a weighted sum value. Based on the weighted sum value, the operation probability of the data corresponding to the target operation is calculated using a preset function and the third operation probability.

[0079] Specifically, the first parameter represents the maximum storage time of the data. Based on the first parameter and the data retrieval date, the probability of the first operation corresponding to the target operation is calculated for the data within the storage time, as shown in the following formula:

[0080]

[0081] Where d is the stored time of the data as determined by the date of the call, and D is the first parameter set. The first operational probability characterizing the data.

[0082] Furthermore, the second parameter represents the total number of times the data is called. Based on the second parameter and the number of times the data is called, the probability of the second operation corresponding to the target operation is calculated based on the number of times the data is called, as shown in the following formula:

[0083]

[0084] Where c is the number of times the data is called, sum(c1, c2, ..., c) n ) represents the total number of times the data was called, and c1, c2, ..., cn represents the historical number of times the data was called. The second operational probability characterizes the data.

[0085] Furthermore, based on the first and second operation probabilities obtained from the above calculations, a weighted sum is performed using a set first and second weight. Then, according to a preset function and the third operation probability, the operation probability of the target operation corresponding to the data is calculated. The sum of the first and second weights is one, as shown in the following formula:

[0086]

[0087] w1 + w2 = 1

[0088] Where w1 and w2 are the first and second weights set, respectively. This is a preset function. For the third operation probability, The data represents the probability of the current target operation.

[0089] Specifically, the aforementioned third operation probability can be calculated based on the number of stored data records using a third parameter representing the maximum number of stored data records. The aforementioned preset function can be used to normalize the calculated weighted sum value, as shown in the following formula:

[0090]

[0091]

[0092] Where l is the current number of stored records of the data, and L is the maximum number of stored records of the data. Let p be the preset function, and p be the function's independent variable.

[0093] Furthermore, based on the operation probability of the target operation (e.g., data archiving / data destruction) corresponding to the data obtained from the above calculation, if the operation probability is not less than a preset threshold (e.g., 0.8), it is determined that the data meets the preset operation conditions.

[0094] 2) In response to the monitoring information meeting the set custom trigger rules, obtain at least one custom trigger field set by the corresponding custom trigger rule, and determine that the data meets the preset operation conditions when the monitoring information matches at least one custom trigger field.

[0095] Specifically, the operation conditions can be user-defined data operation conditions. In the above case, when it is determined that the monitoring information meets the set custom trigger rules, it can be determined whether the data meets the preset operation conditions based on at least one corresponding custom trigger field.

[0096] In one specific embodiment, a custom trigger field can be used to indicate the target operating environment of the data. That is, when the data matches the target operating environment indicated by at least one custom trigger field, the target operation is used to process it. For example, the custom trigger field can be composed of fields / characters of any type such as date, character, or integer. For example, a custom trigger field represented as "(TODAY()-date_+1)>10" can be used to determine that the data matches the target operating environment and to process it with the target operation when the data's call time (date) is more than 10 days away from the current time.

[0097] It is worth noting that the aforementioned custom trigger fields can be one or more. When the monitoring information matches each custom trigger field, it is determined that it meets the preset operation conditions. As can be seen, based on the above method, users can flexibly set different custom conditions according to their own needs to maximize the satisfaction of their own needs and the different characteristics of different data.

[0098] S303: In response to the data meeting the operation conditions, the target operation is used to process the data.

[0099] In one optional embodiment, the target operation includes data archiving to reduce data backlog, facilitate data organization, and standardize data storage. Specifically, for a given set of data, when the data meets the operation conditions corresponding to data archiving, the target operation is used to process the data, including: file archiving to save the data in file format; or database archiving to save the data to a specified database table.

[0100] For example, see Figure 5 As shown, when the target operation is data archiving, it can include two methods: file archiving and database archiving. Database archiving refers to saving the database table containing the data, which means saving the data that meets the operation conditions to an existing specified database table, or saving the data and multiple data under the same operation conditions as a new database table. File archiving refers to saving the data as a data file, that is, saving the data that meets the operation conditions as a file, as shown in the figure, in formats such as csv, db, excel, xml, md, sql, etc.

[0101] In one optional embodiment, the target operation includes data destruction to reduce data backlog, delete redundant data, and reduce the storage space occupied by the data. Specifically, when the data meets the operation conditions corresponding to data destruction, the target operation is used to process the data, including: using a recycle bin to destroy the data and migrate the data to a target recycle space; or using permanent destruction to directly delete the data.

[0102] For example, see Figure 6 As shown, when the target operation is data archiving, there are two methods: recycle bin destruction and permanent destruction. Recycle bin destruction means moving the data that meets the operation conditions to the target recycle space (e.g., the system recycle bin), and the data can be recovered or permanently deleted as needed. Permanent destruction means deleting the data directly in the storage space.

[0103] S304: Monitor and record the data processing results, and perform lifecycle management of the data based on the processing results.

[0104] Specifically, after monitoring and recording the processing results of the data, the operation status of the data is updated in real time based on the processing results, including: the current data volume, the archived data volume (database archived data volume and file archived data volume), and the destroyed data volume (recycle bin destroyed data volume and permanently deleted data volume). Based on the above analysis of the data's operational status, it is convenient for managers to understand the operational status of the data analysis in the display interface.

[0105] For example, see Figure 7 As shown, taking multiple data sets (data 1 to data n) as an example, the lifecycle monitoring monitors and records the processing results of each data set under its corresponding target operation. It also updates and displays the current data volume, database archive data volume, file archive data volume, recycle bin destroyed data volume, and permanently deleted data volume. Furthermore, it displays the upcoming database archive data volume, upcoming file archive data volume, upcoming recycle bin destroyed data volume, and upcoming permanent deletion data volume. Optionally, it dynamically displays the current data volume, archive data volume, and destroyed data volume information within a specified period (e.g., monthly / daily / specified time range) to reflect its operational status and facilitate management personnel's understanding. It is understandable that it can also display the total data volume corresponding to each target operation for the above multiple data sets, i.e., display the current total data volume, database archive data volume, file archive data volume, ..., the total data to be destroyed in the recycle bin, and the total data to be permanently deleted, etc., which will not be elaborated further here.

[0106] Furthermore, based on the same technical concept, embodiments of this application also provide a data management device for implementing the above-described method flow of embodiments of this application. See also... Figure 8 As shown, the device includes: a task execution module 801, a condition judgment module 802, an operation processing module 803, and a monitoring and management module 804, wherein:

[0107] The task execution module 801 is used to obtain data monitoring information in response to the execution time of a set task, wherein the monitoring information is used to characterize the current attributes of the data.

[0108] The condition judgment module 802 is used to determine whether the data meets the preset operation conditions based on the monitoring information, wherein the operation conditions are associated with the target operation set for the data.

[0109] The operation processing module 803 is used to process the data using the target operation in response to the data satisfying the operation conditions.

[0110] The monitoring and management module 804 is used to monitor and record the processing results of the data, and to perform lifecycle management of the data based on the processing results.

[0111] In an optional embodiment, the step of determining whether the data meets preset operating conditions based on the monitoring information, wherein the condition determination module 802 is used for:

[0112] In response to the monitoring information satisfying the set automatic triggering rules, the operation probability of the data corresponding to the target operation is calculated, and when the operation probability is not less than a preset threshold, it is determined that the data satisfies the preset operation conditions.

[0113] And / or,

[0114] In response to the monitoring information satisfying the set custom triggering rule, at least one custom triggering field corresponding to the custom triggering rule is obtained, and when the monitoring information matches the at least one custom triggering field, it is determined that the data meets the preset operation conditions, wherein the custom triggering field is used to indicate the target operation environment of the data.

[0115] In an optional embodiment, the condition judgment module 802 is used to calculate the operation probability of the data corresponding to the target operation, and the condition judgment module 802 is used to:

[0116] Based on the data retrieval date contained in the monitoring information, a first operation probability corresponding to the target operation is calculated using a first parameter, wherein the first parameter represents the maximum storage time of the data.

[0117] Based on the number of times the data is called contained in the monitoring information, a second operation probability corresponding to the target operation is calculated using a second parameter, wherein the second parameter represents the total number of times the data is called.

[0118] The first operation probability and the second operation probability are weighted and summed using a first weight and a second weight respectively to obtain a weighted sum. Based on the weighted sum, the operation probability of the data corresponding to the target operation is calculated using a preset function and a third operation probability. The sum of the first weight and the second weight is one, and the third operation probability is calculated based on the number of stored data entries.

[0119] In an optional embodiment, the step of calculating the operation probability of the target operation corresponding to the data based on the weighted sum value, using a preset function and a third operation probability, wherein the condition judgment module 802 is used for:

[0120] Based on the number of stored records of the data, a third operation probability corresponding to the target operation is calculated using a third parameter, wherein the third parameter represents the maximum number of stored records of the data.

[0121] The target function value corresponding to the weighted sum is calculated according to the preset function, and the target function value is calculated using the third operation probability to obtain the operation probability of the target operation corresponding to the data.

[0122] In an optional embodiment, if the target operation is data archiving, then the operation processing module 803 is used to process the data using the target operation, and the module is configured to:

[0123] The data is archived using file archiving and stored in file format.

[0124] or,

[0125] Database archiving is used to save the data to a specified database table.

[0126] In an optional embodiment, if the target operation is data destruction, then the operation processing module 803 is used to process the data using the target operation, and the module is configured to:

[0127] The data is destroyed using a recycle bin and migrated to the target recycling space.

[0128] or,

[0129] The data is permanently deleted.

[0130] In an optional embodiment, after monitoring and recording the processing results of the data, the monitoring management module 804 is further configured to:

[0131] Based on the processing result, update the current data volume of the data, and update the processed data volume of the data corresponding to the target operation.

[0132] The current data volume and the processed data volume are used to analyze the data's operational status, and the operational status is displayed in a preset display interface.

[0133] Based on the same inventive concept as the embodiments described above, this application also provides an electronic device for data management. In one embodiment, the electronic device can be a server, a terminal device, or another electronic device. In this embodiment, the structure of the electronic device can be as follows: Figure 9 As shown, it includes a memory 901, a communication interface 903, and one or more processors 902.

[0134] The memory 901 is used to store computer programs executed by the processor 902. The memory 901 may mainly include a program storage area and a data storage area. The program storage area may store the operating system and programs required to run instant messaging functions, etc.; the data storage area may store various instant messaging information and operation instruction sets, etc.

[0135] Memory 901 may be volatile memory, such as random-access memory (RAM); memory 901 may also be non-volatile memory, such as read-only memory, flash memory, hard disk drive (HDD), or solid-state drive (SSD); or memory 901 may be any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto. Memory 901 may be a combination of the above-mentioned memories.

[0136] The processor 902 may include one or more central processing units (CPUs) or digital processing units, etc. The processor 902 is used to implement the aforementioned data management method when calling computer programs stored in the memory 901.

[0137] Communication interface 903 is used to communicate with terminal devices and other servers.

[0138] This application embodiment does not limit the specific connection medium between the memory 901, the communication interface 903, and the processor 902. This application embodiment... Figure 9 The memory 901 and the processor 902 are connected via a bus 904, and the bus 904 is in Figure 9 The connections between other components are shown in thick lines and are for illustrative purposes only, not as limiting information. The 904 bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, Figure 9 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0139] Based on the same inventive concept, embodiments of this application also provide a storage medium storing computer instructions that, when executed on a computer, cause the computer to perform a data management method described above.

[0140] It should be noted that although several units or sub-units of the device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of this application, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided and embodied by multiple units.

[0141] Furthermore, although the operations of the method of this application are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0142] This application provides a data management method, apparatus, electronic device, and storage medium. The method acquires data monitoring information in response to the execution time of a set task, determines whether the data meets preset operating conditions based on the monitoring information, and processes the data using a target operation associated with the operating conditions when the data meets the operating conditions. Based on this approach, each piece of data to be managed can be automatically processed by its associated target operation when the corresponding set operating conditions are met, effectively reducing data accumulation and improving data query efficiency. Simultaneously, the processing results of the data are monitored and recorded, realizing data lifecycle management. This allows managers to more clearly and directly understand the operational status of each piece of data based on the recording cycle, thereby improving data management efficiency.

[0143] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0144] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a server, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the process. Figure 1One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0145] Program code for performing the operations of this application can be written using any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0146] In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0147] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0148] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0149] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A data management method, characterized in that, include: In response to the execution time of a set task, monitoring information of the data is acquired, wherein the monitoring information is used to characterize the current attributes of the data; In response to the monitoring information satisfying the set automatic triggering rules, based on the data call date contained in the monitoring information, a first operation probability of the target operation corresponding to the data is calculated using a first parameter, wherein the first parameter represents the maximum storage time of the data; Based on the number of times the data is called contained in the monitoring information, a second operation probability corresponding to the target operation of the data is calculated using a second parameter, wherein the second parameter represents the total number of times the data is called; The first operation probability and the second operation probability are weighted and summed using a first weight and a second weight, respectively, to obtain a weighted sum. Based on the weighted sum, a preset function and a third operation probability are used to calculate the operation probability of the data corresponding to the target operation. When the operation probability is not less than a preset threshold, it is determined that the data meets the preset operation conditions. The operation conditions are associated with the target operation set for the data, wherein the target operation is data archiving or data destruction. In response to the data satisfying the operation conditions, the data is processed using the target operation; Monitor and record the processing results of the data, and perform lifecycle management of the data based on the processing results.

2. The method as described in claim 1, characterized in that, The step of determining whether the data meets the preset operating conditions based on the monitoring information includes: In response to the monitoring information satisfying the set custom triggering rule, at least one custom triggering field corresponding to the custom triggering rule is obtained, and when the monitoring information matches the at least one custom triggering field, it is determined that the data satisfies the preset operation conditions, wherein the custom triggering field is used to indicate the target operation environment of the data.

3. The method as described in claim 1, characterized in that, The step of calculating the operation probability of the target operation corresponding to the data based on the weighted sum value, using a preset function and a third operation probability, includes: Based on the number of stored records of the data, a third operation probability corresponding to the target operation is calculated using a third parameter, wherein the third parameter represents the maximum number of stored records of the data; The target function value corresponding to the weighted sum is calculated according to the preset function, and the target function value is calculated using the third operation probability to obtain the operation probability of the target operation corresponding to the data.

4. The method according to any one of claims 1-3, characterized in that, If the target operation is data archiving, then processing the data using the target operation includes: The data is saved in file format using file archiving. or, Database archiving is used to save the data to a specified database table.

5. The method according to any one of claims 1-3, characterized in that, If the target operation is data destruction, then processing the data using the target operation includes: The data is destroyed using a recycle bin and migrated to the target recycling space. or, The data is permanently deleted.

6. The method according to any one of claims 1-3, characterized in that, After monitoring and recording the data processing results, the method further includes: Based on the processing result, update the current data volume of the data, and update the processed data volume of the data corresponding to the target operation; The current data volume and the processed data volume are used to analyze the data's operational status, and the operational status is displayed in a preset display interface.

7. A data management device, characterized in that, include: The task execution module is used to obtain data monitoring information in response to the execution time of a set task, wherein the monitoring information is used to characterize the current attributes of the data; The condition judgment module is used to respond to the monitoring information satisfying the set automatic triggering rules, and calculate the first operation probability of the target operation corresponding to the data based on the data call date contained in the monitoring information and using the first parameter, wherein the first parameter represents the maximum storage time of the data; Based on the number of times the data is called contained in the monitoring information, a second operation probability corresponding to the target operation of the data is calculated using a second parameter, wherein the second parameter represents the total number of times the data is called; The first operation probability and the second operation probability are weighted and summed using a first weight and a second weight, respectively, to obtain a weighted sum. Based on the weighted sum, a preset function and a third operation probability are used to calculate the operation probability of the data corresponding to the target operation. When the operation probability is not less than a preset threshold, it is determined that the data meets the preset operation conditions. The operation conditions are associated with the target operation set for the data, wherein the target operation is data archiving or data destruction. An operation processing module is used to process the data using the target operation in response to the data satisfying the operation conditions; The monitoring and management module is used to monitor and record the processing results of the data, and to perform lifecycle management of the data based on the processing results.

8. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1-6.

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