Data updating method and device, computer equipment, readable storage medium and program product

Abstract

The invention relates to a data updating method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the steps that in response to a received data updating instruction, a change data set and a state data set matched with the data updating instruction are determined, the change data set is used for storing data state change information, and the state data set is used for storing data state information; under the condition that the data size of the change data set is larger than a preset threshold value, data screening is conducted on the change data set according to field information corresponding to data in the state data set, and a screened change data set is obtained; and determining to-be-updated data according to the state data set and the screened change data set, and updating the to-be-updated data. By adopting the method, the data updating efficiency and accuracy can be improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a data updating method, apparatus, computer equipment, computer-readable storage medium and computer program product. Background Art

[0002] When processing data, data can be updated through data operations such as adding, deleting, checking and modifying data. With the advancement of science and technology and the development of the information age, the requirements for the efficiency and accuracy of data updates are becoming higher and higher.

[0003] In the related art, data change information and data status information can be obtained and data can be updated. However, updating data in this way requires a large amount of data to be processed, and when processing large-scale data updates, the efficiency is low and it is difficult to meet the needs. Summary of the invention

[0004] Based on this, it is necessary to provide a data updating method, apparatus, computer device, computer-readable storage medium and computer program product that can improve efficiency in response to the above technical problems.

[0005] In a first aspect, the present application provides a data updating method, the method comprising:

[0006] In response to receiving a data update instruction, determining a change data group and a state data group that match the data update instruction, wherein the change data group is used to store data state change information, and the state data group is used to store data state information;

[0007] When the amount of data in the changed data group is greater than a preset threshold, filtering the changed data group according to field information corresponding to the data in the status data group to obtain a filtered changed data group;

[0008] The data to be updated is determined according to the state data group and the filtered change data group, and the data to be updated is updated.

[0009] In one embodiment, filtering the changed data group according to the field information corresponding to the data in the state data group to obtain the filtered changed data group includes:

[0010] Obtaining field information corresponding to the data in the status data group;

[0011] Serializing the field information to generate a target byte array;

[0012] The changed data group is screened based on the target byte array to obtain a screened changed data group.

[0013] In one embodiment, the step of filtering the changed data group based on the target byte array to obtain the filtered changed data group includes:

[0014] generating a screening data structure matching the target byte array;

[0015] Data matching the screening data structure is determined from the change data group to obtain a screened change data group.

[0016] In one embodiment, the preset threshold is set in the following manner:

[0017] Determine preset storage attribute data, wherein the preset storage attribute data includes at least one of a data storage type, a data storage quantity threshold, and a data group capacity;

[0018] According to the preset storage attribute data, a target data volume is determined, and a preset threshold value matching the target data volume is determined.

[0019] In one embodiment, the method further comprises:

[0020] When the data amount of the changed data group is less than or equal to the preset threshold, the data to be updated is determined according to the state data group and the changed data group, and the data to be updated is updated.

[0021] In a second aspect, the present application further provides a data updating device, the device comprising:

[0022] a determination module, configured to, in response to receiving a data update instruction, determine a change data group and a state data group that match the data update instruction, wherein the change data group is used to store data state change information, and the state data group is used to store data state information;

[0023] A screening module, configured to screen the changed data group according to field information corresponding to the data in the status data group to obtain a screened changed data group when the amount of data in the changed data group is greater than a preset threshold;

[0024] The updating module is used to determine the data to be updated according to the state data group and the filtered change data group, and to update the data to be updated.

[0025] In one embodiment, the screening module is further used to:

[0026] Obtaining field information corresponding to the data in the status data group;

[0027] Serializing the field information to generate a target byte array;

[0028] The changed data group is screened based on the target byte array to obtain a screened changed data group.

[0029] In one embodiment, the screening module is further used to:

[0030] generating a screening data structure matching the target byte array;

[0031] Data matching the screening data structure is determined from the change data group to obtain a screened change data group.

[0032] In one embodiment, the device includes a setting module of the preset module, and the setting module of the preset threshold includes:

[0033] A first determination submodule is used to determine preset storage attribute data, wherein the preset storage attribute data includes at least one of a data storage type, a data storage quantity threshold, and a data group capacity;

[0034] The second determination submodule is used to determine the target data volume according to the preset storage attribute data, and determine a preset threshold value matching the target data volume.

[0035] In one embodiment, the device further comprises:

[0036] The third determining submodule is used to determine the data to be updated according to the state data group and the changed data group, and update the data to be updated when the data amount of the changed data group is less than or equal to the preset threshold.

[0037] In a third aspect, an embodiment of the present disclosure further provides a computer device, wherein the computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of any one of the methods in the embodiments of the present disclosure are implemented.

[0038] In a fourth aspect, the embodiments of the present disclosure further provide a computer-readable storage medium, wherein a computer program is stored thereon, and when the computer program is executed by a processor, the steps of any one of the methods in the embodiments of the present disclosure are implemented.

[0039] In a fifth aspect, the embodiments of the present disclosure further provide a computer program product, wherein the computer program product includes a computer program, and when the computer program is executed by a processor, the steps of any one of the methods in the embodiments of the present disclosure are implemented.

[0040] The above-mentioned data update method, device, computer equipment, computer-readable storage medium and computer program product, when receiving a data update instruction, determine the change data group and status data group that match the data update instruction, and when the data amount of the change data group is greater than a preset threshold, filter the change data group according to the field information corresponding to the data in the status data group to obtain the filtered change data group, determine the data to be updated according to the status data group and the filtered change data group, and update the data to be updated, so that when updating the data, the change data group can be filtered first, and the data related to the current data state can be filtered out from the data state change information, effectively reducing the data processing amount, and at the same time, taking into account the accuracy of data update, when processing large-scale data, avoiding the problem of low update efficiency caused by excessive data processing amount, realizing efficient and accurate data update, and being suitable for more application scenarios; by filtering the change data group, the use of storage space and processor can be reduced, data processing performance is guaranteed, and the stability and reliability of data processing are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 is a flow chart of a data updating method in one embodiment;

[0043] Figure 2 is a flow chart of a data updating method in another embodiment;

[0044] Figure 3 is a flow chart of a data updating method in another embodiment;

[0045] Figure 4 A schematic diagram of a flow chart of a method for determining a preset threshold in one embodiment;

[0046] Figure 5 is a structural block diagram of a data updating device in one embodiment;

[0047] Figure 6 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0049] In one embodiment, Figure 1 As shown, a data update method is provided. This embodiment takes the method applied to a terminal as an example. It can be understood that the method can also be applied to a server, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0050] Step S110, in response to receiving a data update instruction, determining a change data group and a state data group that match the data update instruction, wherein the change data group is used to store data state change information, and the state data group is used to store data state information;

[0051] Exemplarily, the data update instruction can be sent by the user; it can also be automatically triggered when data changes occur in the database, etc., which can be determined according to the actual application scenario. In one example, after the data in the database changes, the data update instruction will be triggered, and the data group will be queried and the data will be updated in response to the data update instruction.

[0052] In one example, a change data group and a status data group that match a data update instruction are determined according to the instruction, and the change data group and the status data group are for the same data change operation, wherein the change data group is used to store data status change information, including but not limited to deleted data, data marked as deleted, the status before data modification, etc.; the status data group is used to store data status information, including but not limited to currently valid data, data in the latest status, etc.

[0053] In an example, this embodiment can be applied to a scenario where data is queried after streaming Iceberg. The change data group can be a plurality of EQ-DELETE folders, and the status data group can be a DATA File folder.

[0054] Step S120, when the amount of data in the change data group is greater than a preset threshold, filtering the change data group according to field information corresponding to the data in the status data group to obtain a filtered change data group;

[0055] Exemplarily, the data volume of the changed data group is judged. When the data volume of the changed data group is greater than a preset threshold, it can be considered that the data volume of the changed data group is large and data screening is required to filter out some data. The preset threshold is determined according to the actual application scenario. In one example, the preset threshold can be determined according to the data processing volume required for the filtering and screening process and the data volume of the changed data group. Different preset thresholds can correspond to different scenarios.

[0056] Optionally, when performing data screening, since the state data group is used to store data state information, the state data group includes data recording the current state of the data, and data screening can be performed based on the field information of the data in the state data group. In one example, data whose field information matches the field information of the data in the state data group can be screened out from the change data group to obtain a screened change data group. The field information can include but is not limited to data attributes, data identifiers, etc., which can be determined based on the actual application scenario.

[0057] Step S130: determining the data to be updated according to the state data group and the filtered change data group, and updating the data to be updated.

[0058] Exemplarily, the data to be updated can be determined by combining the state data group and the filtered change data group. According to the data state information in the state data group and the data state change information in the filtered change data group, the data change situation is determined, and the data to be changed and the changed data information are obtained, which are the data to be updated. The data to be updated is updated to achieve the data change.

[0059] In a possible implementation, the data update method described in this embodiment is applied in an Apache Iceberg scenario, wherein Apache Iceberg is a table format repository project that can provide an efficient and scalable data storage solution in a big data and data lake environment.

[0060] Iceberg supports columnar storage, which can better utilize the performance characteristics of modern storage systems. Data can be partitioned on demand to improve query performance. Iceberg supports ACID (atomicity, consistency, isolation, and persistence) transactions, which enables data consistency and integrity to be maintained when multiple users operate data concurrently. It supports data time travel, allowing users to view and query historical versions of data. Iceberg is compatible with various computing engines (such as ApacheSpark, Flink, Hive, Trino, etc.), allowing data to flow seamlessly between different data processing frameworks. It provides rich metadata management functions to facilitate users to effectively manage and monitor data, including Schema management and data quality control. Iceberg supports various optimization strategies, such as file merging and lazy loading, which can significantly improve query efficiency. In this scenario, when updating data, there are change data groups and status data groups. By filtering the change data groups, the data update efficiency can be further improved.

[0061] In the embodiment of the present disclosure, when a data update instruction is received, a change data group and a status data group that match the data update instruction are determined; when the data volume of the change data group is greater than a preset threshold, the change data group is screened according to the field information corresponding to the data in the status data group to obtain a screened change data group; data to be updated is determined according to the status data group and the screened change data group, and the data to be updated is updated; thus, when updating data, the change data group can be screened first, and data related to the current data state can be screened out from the data state change information, thereby effectively reducing the amount of data processing; at the same time, the accuracy of data update is taken into account; when processing large-scale data, the problem of low update efficiency caused by excessive data processing volume is avoided, thereby achieving efficient and accurate data update, which is suitable for more application scenarios; by screening the change data group, the use of storage space and processor can be reduced, data processing performance can be guaranteed, and the stability and reliability of data processing can be improved.

[0062] In one embodiment, Figure 2 As shown, the data of the change data group is filtered according to the field information corresponding to the data in the status data group to obtain the filtered change data group, including:

[0063] Step S121, obtaining field information corresponding to the data in the status data group;

[0064] Step S122, serializing the field information to generate a target byte array;

[0065] Step S123: filter the changed data group based on the target byte array to obtain a filtered changed data group.

[0066] Exemplarily, when performing data screening, the field information corresponding to the data of the status data group may be serialized.

[0067] In one example, field information corresponding to data in a status data group is obtained, and the field information is serialized to generate a target byte array. Serialization refers to a specific method or protocol for converting a data structure or object into a format that can be stored or transmitted.

[0068] Serialization is the process of converting complex data (such as objects, data structures, etc.) into byte streams or strings so that they can be saved in files, sent to the network, or saved in a database, while deserialization is the process of converting these byte streams or strings back to the original data structure. Serialization processing solutions may include but are not limited to JSON, XML, protobuf (Protocol Buffers), Thrift, Avro, etc., which can be determined based on the actual application scenario. In an example, a suitable serialization framework can be selected for serialization processing based on the actual application scenario.

[0069] In an example, the field information of the data in the state data group may include primary key information, attribute information, etc. of the data. The primary key information of the data includes but is not limited to the value of the primary key field of the data, which can be determined based on the actual application scenario.

[0070] The changed data group is filtered based on the target byte array. In one example, the data in the changed data group can be traversed and read to determine whether the field information of the data in the changed data group conforms to the target byte array to obtain the filtered changed data group.

[0071] In the disclosed embodiment, when filtering the change data group, the field information corresponding to the data of the status data group is serialized to generate a target byte array, and the change data group is filtered based on the target byte array, so that the change data group can be efficiently and accurately filtered based on the status data group, effectively reducing the amount of data processing, ensuring the correlation between the filtered change data group and the status data group, and being suitable for more application scenarios.

[0072] In one embodiment, Figure 3 As shown, the data filtering of the changed data group based on the target byte array to obtain the filtered changed data group includes:

[0073] Step S1231, generating a screening data structure matching the target byte array;

[0074] Step S1232: determine data matching the screening data structure from the changed data group to obtain a screened changed data group.

[0075] Exemplarily, data screening is performed based on the screening data structure. After determining the target byte array, a screening data structure matching the target byte array is generated, and data matching the screening data structure is determined from the changed data group to obtain a screened changed data group.

[0076] In one example, the screening data structure may include a data structure with a data screening function. For example, the screening data structure may be a Bloom filter. A Bloom filter corresponding to the state data group is generated according to the target byte array. The Bloom filter can be used to screen out data that matches the target byte array from the change data group to obtain a filtered change data group.

[0077] The disclosed embodiment, when performing data screening based on a target byte array, generates a screening data structure that matches the target byte array, determines data that matches the screening data structure from the changed data group, and performs data screening based on the screening data structure, thereby further improving the accuracy and efficiency of data screening, and is easy to implement, avoiding the problem of inefficiency caused by a large amount of data processing during screening, effectively improving data update efficiency, reducing resource usage, avoiding resource waste, and being suitable for more application scenarios.

[0078] In one embodiment, Figure 4 As shown, the setting method of the preset threshold includes:

[0079] Step S410, determining preset storage attribute data, wherein the preset storage attribute data includes at least one of a data storage type, a data storage quantity threshold, and a data group capacity;

[0080] Step S420: determining a target data volume according to the preset storage attribute data, and determining a preset threshold value matching the target data volume.

[0081] Exemplarily, the preset threshold value may be determined according to the preset storage attribute data. In one example, the preset storage attribute data is determined, and the preset storage attribute data may include a data storage type, a data storage quantity threshold value, and a data group capacity. The data storage type may include but is not limited to an SDD, an HDD, etc., data may be stored in the form of a data group, each data group may correspond to a data group capacity, and the data storage quantity threshold value may be an upper limit of the amount of data that the database can store.

[0082] According to the preset storage attribute data, the target data volume is determined, and the target data volume can be the amount of data that can be processed while taking into account efficiency and accuracy. Exemplarily, the data processing capacity can be determined according to the preset storage attribute data, thereby determining the target data volume. In an example, the preset threshold value can be less than or equal to the target data volume, which can be determined according to the actual application scenario.

[0083] In the embodiments of the present disclosure, when setting a preset threshold, the target data volume is determined according to the preset storage attribute data, and the corresponding preset threshold is determined, so that the corresponding preset threshold can be determined according to the actual needs in the actual application scenario. When updating data, data filtering is adaptively performed to avoid the problem of low update efficiency caused by the data filtering process, and it is suitable for more application scenarios.

[0084] In one embodiment, the method further comprises:

[0085] When the data amount of the changed data group is less than or equal to the preset threshold, the data to be updated is determined according to the state data group and the changed data group, and the data to be updated is updated.

[0086] Exemplarily, when the data volume of the changed data group is less than or equal to the preset threshold, it can be considered that the data volume of the changed data group is small, and there is no need to perform data screening. The data to be updated can be directly determined to ensure data processing efficiency.

[0087] Optionally, when the data amount of the changed data group is small, the data to be updated is directly determined according to the changed data group and the status data group, and the data to be updated is updated.

[0088] In the disclosed embodiment, when the data volume of the change data group is less than or equal to a preset threshold, the data to be updated is determined based on the status data group and the filtered change data group, and the data to be updated is updated; when the data volume of the change data group is small, the data is updated directly based on the acquired data group without filtering, thereby ensuring the efficiency of data updating and avoiding the problem of low update efficiency due to filtering, and being suitable for more application scenarios.

[0089] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0090] Based on the same inventive concept, the embodiment of the present application also provides a data updating device for implementing the data updating method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more data updating device embodiments provided below can refer to the limitations on the data updating method above, and will not be repeated here.

[0091] In an exemplary embodiment, Figure 5 As shown, a data updating device 500 is provided, comprising:

[0092] A determination module 510, configured to, in response to receiving a data update instruction, determine a change data group and a state data group that match the data update instruction, wherein the change data group is used to store data state change information, and the state data group is used to store data state information;

[0093] A screening module 520 is used to screen the changed data group according to field information corresponding to the data in the status data group to obtain a screened changed data group when the data amount of the changed data group is greater than a preset threshold;

[0094] The updating module 530 is used to determine the data to be updated according to the state data group and the filtered change data group, and to update the data to be updated.

[0095] In one embodiment, the screening module is further used to:

[0096] Obtaining field information corresponding to the data in the status data group;

[0097] Serializing the field information to generate a target byte array;

[0098] The changed data group is screened based on the target byte array to obtain a screened changed data group.

[0099] In one embodiment, the screening module is further used to:

[0100] generating a screening data structure matching the target byte array;

[0101] Data matching the screening data structure is determined from the change data group to obtain a screened change data group.

[0102] In one embodiment, the device includes a setting module of the preset module, and the setting module of the preset threshold includes:

[0103] A first determination submodule is used to determine preset storage attribute data, wherein the preset storage attribute data includes at least one of a data storage type, a data storage quantity threshold, and a data group capacity;

[0104] The second determination submodule is used to determine the target data volume according to the preset storage attribute data, and determine a preset threshold value matching the target data volume.

[0105] In one embodiment, the device further comprises:

[0106] The third determining submodule is used to determine the data to be updated according to the state data group and the changed data group, and update the data to be updated when the data amount of the changed data group is less than or equal to the preset threshold.

[0107] Each module in the above data updating device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0108] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 6As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store change data groups, status data groups and other data involved in the method described in this embodiment. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a data update method is implemented.

[0109] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0110] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0111] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0112] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0113] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0114] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0115] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0116] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A data updating method, characterized in that: The method comprises: In response to receiving a data update instruction, determining a change data group and a state data group that match the data update instruction, wherein the change data group is used to store data state change information, and the state data group is used to store data state information; When the amount of data in the changed data group is greater than a preset threshold, filtering the changed data group according to field information corresponding to the data in the status data group to obtain a filtered changed data group; The data to be updated is determined according to the state data group and the filtered change data group, and the data to be updated is updated.

2. The method according to claim 1, characterized in that The step of filtering the changed data group according to the field information corresponding to the data in the status data group to obtain the filtered changed data group includes: Obtaining field information corresponding to the data in the status data group; Serializing the field information to generate a target byte array; The changed data group is screened based on the target byte array to obtain a screened changed data group.

3. The method according to claim 2, characterized in that The step of filtering the changed data group based on the target byte array to obtain the filtered changed data group includes: generating a screening data structure matching the target byte array; Data matching the screening data structure is determined from the change data group to obtain a screened change data group.

4. The method according to claim 1, characterized in that: The preset threshold value may be set as follows: Determine preset storage attribute data, wherein the preset storage attribute data includes at least one of a data storage type, a data storage quantity threshold, and a data group capacity; According to the preset storage attribute data, a target data volume is determined, and a preset threshold value matching the target data volume is determined.

5. The method according to claim 1, characterized in that: The method further comprises: When the data amount of the changed data group is less than or equal to the preset threshold, the data to be updated is determined according to the state data group and the changed data group, and the data to be updated is updated.

6. A data updating device, characterized in that: The device comprises: a determination module, configured to, in response to receiving a data update instruction, determine a change data group and a state data group that match the data update instruction, wherein the change data group is used to store data state change information, and the state data group is used to store data state information; A screening module, configured to screen the changed data group according to field information corresponding to the data in the status data group to obtain a screened changed data group when the amount of data in the changed data group is greater than a preset threshold; The updating module is used to determine the data to be updated according to the state data group and the filtered change data group, and to update the data to be updated.

7. The device according to claim 6, characterized in that The screening module is also used for: Obtaining field information corresponding to the data in the status data group; Serializing the field information to generate a target byte array; The changed data group is screened based on the target byte array to obtain a screened changed data group.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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