CN111858466A - Data storage method, device, equipment and storage medium - Google Patents
Data storage method, device, equipment and storage medium Download PDFInfo
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Abstract
The application discloses a data storage method, a data storage device, data storage equipment and a data storage medium. The method comprises the following steps: acquiring target metadata of target data; extracting attribute values of a plurality of target attributes in the target metadata; judging a target storage strategy corresponding to the combination relation between the target storage strategy and each attribute value by using a preset strategy judgment model; and executing the data storage operation on the target data by using the target storage strategy. According to the method, the target storage strategy corresponding to the target data is obtained by comprehensively judging the attribute values of the plurality of target attributes in the target metadata through the strategy judgment model, so that the accuracy of selecting the corresponding storage strategy according to the data is relatively ensured, the storage cost is effectively saved, and the efficiency of the multi-element storage medium is utilized to the maximum extent. In addition, the application also provides a data storage device, equipment and a storage medium, and the beneficial effects are as described above.
Description
Technical Field
The present application relates to the field of data storage, and in particular, to a data storage method, apparatus, device, and storage medium.
Background
Under the current distributed file system, a storage mode for data derives a plurality of storage strategies which are more optimized under different dimensions from a storage strategy of a single copy, such as an EC strategy, a heterogeneous storage strategy, a small file combination strategy and the like.
Facing to the increasingly developed high-speed network and novel storage media, the storage strategies can meet the requirements of storage optimization from different angles, but when the data are stored at present, the storage strategies are basically selected manually according to certain characteristics of the data, so whether the proper storage strategies can be selected for the data depends on the experience of decision makers.
When the storage strategy for the data is manually selected, a technician is required to have relatively strong professional knowledge, and when the data quantity to be stored is huge, the data increment is high, and the data types are mixed, the storage strategy selected manually causes uneven utilization of storage resources and expansion of storage cost.
Therefore, the data storage method is provided to relatively ensure the accuracy when the corresponding storage strategy is selected according to the data, further effectively save the storage cost, and maximally utilize the efficiency of the multivariate storage medium, which is a problem to be solved by the technical personnel in the field.
Disclosure of Invention
The application aims to provide a data storage method, a data storage device, data storage equipment and a data storage medium, so that the accuracy of selecting a corresponding storage strategy according to data is relatively ensured, the storage cost is effectively saved, and the efficiency of a multi-element storage medium is utilized to the maximum extent.
In order to solve the above technical problem, the present application provides a data storage method, including:
acquiring target metadata of target data;
extracting attribute values of a plurality of target attributes in the target metadata;
judging a target storage strategy corresponding to the combination relation between the target storage strategy and each attribute value by using a preset strategy judgment model;
and executing the data storage operation on the target data by using the target storage strategy.
Preferably, the generation process of the policy decision model includes:
acquiring a preset storage strategy;
and establishing a corresponding relation between a preset storage strategy and an attribute threshold value of the metadata attribute to obtain a strategy judgment model.
Preferably, when the number of the preset storage policies is greater than 1, determining, by using a preset policy determination model, a target storage policy corresponding to a combination relationship between the target storage policy and each attribute value includes:
acquiring attribute thresholds corresponding to preset storage strategies through a strategy judgment model;
Counting the attribute value matching amount of the attribute values in the combined relationship under each attribute threshold;
selecting the maximum attribute value matching amount in the attribute value matching amounts;
and setting the preset storage strategy corresponding to the maximum attribute value matching amount as a target storage strategy.
Preferably, before extracting the attribute values of the plurality of target attributes in the target metadata, the method further comprises:
acquiring a storage strategy type;
extracting attribute values of a plurality of target attributes in the target metadata, including:
extracting attribute values of a plurality of target attributes corresponding to the storage strategy type in the target metadata;
the method for judging the target storage strategy corresponding to the combination relationship among the attribute values by using the preset strategy judgment model comprises the following steps:
and judging the target storage strategy corresponding to the combination relation between the attribute values by utilizing a strategy judgment model corresponding to the storage strategy type.
Preferably, before performing the data storage operation on the target data using the target storage policy, the method further comprises:
acquiring an operation execution identifier;
judging whether the operation execution identifier meets a preset execution standard or not;
and executing the step of executing the data storage operation on the target data by using the target storage strategy if the operation execution identification meets the preset execution standard.
Preferably, the target attribute includes any of the file size, the number of files, the number of file accesses, the file type, the file compression ratio, and the file read-write rate.
In addition, the present application also provides a data storage device including:
the metadata acquisition module is used for acquiring target metadata of the target data;
the attribute value extraction module is used for extracting attribute values of a plurality of target attributes in the target metadata;
the storage strategy judgment module is used for judging a target storage strategy corresponding to the combination relation between each attribute value by using a preset strategy judgment model;
and the storage strategy execution module is used for executing data storage operation on the target data by using the target storage strategy.
Preferably, the apparatus further comprises:
the strategy acquisition module is used for acquiring a preset storage strategy;
and the model establishing module is used for establishing a corresponding relation between a preset storage strategy and an attribute threshold value of the metadata attribute to obtain a strategy judgment model.
In addition, the present application also provides a data storage device, including:
a memory for storing a computer program;
a processor for implementing the steps of the data storage method as described above when executing the computer program.
Furthermore, the present application also provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps of the data storage method as described above.
According to the data storage method, the target metadata of the target data are firstly obtained, the attribute values of a plurality of target attributes in the target metadata are extracted, the target storage strategy corresponding to the combination relation among the attribute values is judged by using the preset strategy judgment model, and finally the data storage operation is executed on the target data by using the target storage strategy, so that the data storage of the target data is realized. According to the method, the target storage strategy corresponding to the target data is obtained by comprehensively judging the attribute values of the plurality of target attributes in the target metadata through the strategy judgment model, so that the accuracy of selecting the corresponding storage strategy according to the data is relatively ensured, the storage cost is effectively saved, and the efficiency of the multi-element storage medium is utilized to the maximum extent. In addition, the application also provides a data storage device, equipment and a storage medium, and the beneficial effects are as described above.
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In order to more clearly illustrate the embodiments of the present application, the drawings needed for the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings can be obtained by those skilled in the art without inventive effort.
FIG. 1 is a flow chart of a data storage method disclosed in an embodiment of the present application;
fig. 2 is a schematic structural diagram of a data storage device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without any creative effort belong to the protection scope of the present application.
Facing to the increasingly developed high-speed network and novel storage media, the storage strategies can meet the requirements of storage optimization from different angles, but when the data are stored at present, the storage strategies are basically selected manually according to certain characteristics of the data, so whether the proper storage strategies can be selected for the data depends on the experience of decision makers.
When the storage strategy for the data is manually selected, a technician is required to have relatively strong professional knowledge, and when the data quantity to be stored is huge, the data increment is high, and the data types are mixed, the storage strategy selected manually causes uneven utilization of storage resources and expansion of storage cost.
Therefore, the core of the application is to provide a data storage method to relatively ensure the accuracy when selecting a corresponding storage strategy according to data, thereby effectively saving the storage cost and maximally utilizing the efficiency of the multi-element storage medium.
In order that those skilled in the art will better understand the disclosure, the following detailed description will be given with reference to the accompanying drawings.
Referring to fig. 1, an embodiment of the present application discloses a data storage method, including:
step S10: target metadata of the target data is obtained.
It should be noted that the target data in this step refers to data stored in a subsequent step by using a specific storage policy. The target data may be a file or a directory path, and is determined according to actual requirements, and is not limited specifically herein. The target metadata is data corresponding to the target data and describing attributes related to the target data, and the attributes related to the target data reflect the entire situation in which the target data is applied, so that the target metadata can be acquired and an appropriate storage policy for the target data can be analyzed based on the target metadata.
Step S11: attribute values of a plurality of target attributes in the target metadata are extracted.
After the target metadata of the target data is acquired, the attribute values of a plurality of target attributes in the target metadata are further extracted in the step, so that the storage strategy matched with the target data can be analyzed in the subsequent step according to the attribute values of the plurality of target attributes in the target metadata, namely the storage strategy corresponding to the target data is comprehensively analyzed according to the relevant attributes in the plurality of dimensions of the target data.
Step S12: and judging a target storage strategy corresponding to the combination relation between the attribute values by using a preset strategy judgment model.
After extracting the attribute values of the plurality of target attributes in the target metadata, the step further determines a target storage policy corresponding to a combination relationship between the attribute values by using a preset policy decision model.
The policy decision model in this step essentially records the correspondence between the attribute values of different attributes in the metadata and the storage policy, and thus when the target data is stored, after the attribute values of a plurality of target attributes in the target metadata of the target data are extracted, the target storage policy corresponding to the combination relationship between the attribute values of the different attributes in the policy decision model and the storage policy can be further determined by using the correspondence between the attribute values of the different attributes in the policy decision model and the storage policy.
Furthermore, the target storage policy determined by the preset policy determination model in this step is a storage policy used when the target data is stored in the subsequent step. The storage policy herein refers to a specific storage means adopted for data, including but not limited to heterogeneous storage, compressed storage, and EC (Erasure code) storage.
Step S13: and executing the data storage operation on the target data by using the target storage strategy.
After the target storage strategy corresponding to the combination relationship between the attribute values is judged by using the preset strategy judgment model, the step further performs data storage operation on the target data by using the target storage strategy, so as to realize data storage of the target data.
According to the data storage method, the target metadata of the target data are firstly obtained, the attribute values of a plurality of target attributes in the target metadata are extracted, the target storage strategy corresponding to the combination relation among the attribute values is judged by using the preset strategy judgment model, and finally the data storage operation is executed on the target data by using the target storage strategy, so that the data storage of the target data is realized. According to the method, the target storage strategy corresponding to the target data is obtained by comprehensively judging the attribute values of the plurality of target attributes in the target metadata through the strategy judgment model, so that the accuracy of selecting the corresponding storage strategy according to the data is relatively ensured, the storage cost is effectively saved, and the efficiency of the multi-element storage medium is utilized to the maximum extent.
On the basis of the above embodiment, as a preferred implementation manner, the generating process of the policy decision model includes:
acquiring a preset storage strategy;
and establishing a corresponding relation between a preset storage strategy and an attribute threshold value of the metadata attribute to obtain a strategy judgment model.
In this embodiment, the generating process of the policy decision model essentially acquires the preset storage policy, and establishes a corresponding relationship between the preset storage policy and the attribute threshold of the metadata attribute, so as to generate the policy decision model. In addition, it should be emphasized that, in this embodiment, 1 preset storage policy may be specifically acquired when the policy decision model is generated, or multiple preset storage policies may also be acquired, and depending on the actual generation requirement of the policy decision model, when the number of the acquired preset storage policies is greater than 1, and when the corresponding relationship between the preset storage policies and the attribute threshold of the metadata attribute is established, the corresponding relationship between each preset storage policy and the attribute threshold of the metadata attribute is specifically established, respectively. According to the embodiment, the strategy judgment model is obtained by establishing the corresponding relation between the preset storage strategy and the attribute threshold value of the metadata attribute, so that the target storage strategy corresponding to the combined relation between the target storage strategy and each attribute value of the target data can be relatively accurately judged when the strategy judgment model is used subsequently, the storage cost is further effectively saved, and the efficiency of the multi-element storage medium is utilized to the maximum extent.
On the basis of the foregoing embodiment, as a further preferable embodiment, when the number of the preset storage policies is greater than 1, determining, by using a preset policy determination model, a target storage policy corresponding to a combination relationship between the attribute values includes:
acquiring attribute thresholds corresponding to preset storage strategies through a strategy judgment model;
counting the attribute value matching amount of the attribute values in the combined relationship under each attribute threshold;
selecting the maximum attribute value matching amount in the attribute value matching amounts;
and setting the preset storage strategy corresponding to the maximum attribute value matching amount as a target storage strategy.
It should be noted that, in this embodiment, when the number of the preset storage policies is greater than 1 in the generation process of the policy decision model, when the preset policy decision model is used to decide the target storage policy corresponding to the combination relationship between the preset storage policy and each attribute value, specifically, the policy decision model is used to obtain the attribute threshold corresponding to each preset storage policy, where the attribute threshold corresponding to each preset storage policy specifically refers to the attribute threshold corresponding to each metadata attribute under each preset policy, after the attribute threshold corresponding to each preset storage policy in the policy decision model is obtained, the combination relationship of multiple attribute values corresponding to the target metadata is further counted, where the attribute value matching amount refers to the number of attribute values of the target attribute reaching the corresponding attribute threshold, and further setting the preset storage strategy corresponding to the maximum attribute value matching amount in each attribute value matching amount as a target storage strategy after counting the attribute value matching amount of the attribute values in the combination relationship under each attribute threshold.
The embodiment can further and accurately judge the target storage strategy corresponding to the combination relation between the attribute values of the target data, thereby further effectively saving the storage cost and maximally utilizing the efficiency of the multi-element storage medium.
To further enhance the understanding of the present embodiment, the following description is provided by way of a scenario example in a specific application scenario.
In a specific application scenario, taking a policy determination model corresponding to a heterogeneous storage policy type as an example, the policy determination model includes four preset storage policies (DISK, ARCHIVE, ONE _ SSD, and ALL _ SSD); the metadata attributes include file size, file number and access times, and the correspondence between the preset storage policy and the attribute threshold of the metadata attributes can be shown in table 1.
| Heterogeneous storage policy | File size | Number of files | Number of accesses |
| DISK | 0.9 | 0.1 | 0.3 |
| ARCHIVE | 0.1 | 0.5 | 0.2 |
| ONE_SSD | 0.3 | 0.7 | 0.4 |
| ALL_SSD | 0.5 | 0.8 | 0.7 |
TABLE 1
After a strategy judgment model is generated, when a preset strategy judgment model is used for judging a target storage strategy corresponding to the combination relation between the preset strategy judgment model and each attribute value, an attribute threshold value corresponding to each preset storage strategy is obtained through the strategy judgment model; and (3) counting the attribute value matching amount of the attribute values in the combined relation under each attribute threshold, and calculating a formula:
Wherein s is a heterogeneous storage strategy, and n is ljThe number of contained attributes; alpha is an attribute factor, and when the matched attributes are inconsistent in the values of the attributes, proper weight is given; beta is a matching factor when the corresponding attribute aiIs 1 if the attribute value of (2) matches the attribute threshold, otherwise is 0. And finally, calculating the attribute value matching amount of each heterogeneous storage strategy, and setting the preset storage strategy corresponding to the maximum attribute value matching amount as a target storage strategy.
On the basis of the foregoing embodiment, as a preferred implementation manner, before extracting attribute values of a plurality of target attributes in the target metadata, the method further includes:
acquiring a storage strategy type;
extracting attribute values of a plurality of target attributes in the target metadata, including:
extracting attribute values of a plurality of target attributes corresponding to the storage strategy type in the target metadata;
the method for judging the target storage strategy corresponding to the combination relationship among the attribute values by using the preset strategy judgment model comprises the following steps:
and judging the target storage strategy corresponding to the combination relation between the attribute values by utilizing a strategy judgment model corresponding to the storage strategy type.
It should be noted that, considering that the storage policy can be macroscopically divided into different policy types, the present embodiment focuses on obtaining the storage policy type before extracting the attribute values of the multiple target attributes in the target metadata, where the storage policy type may be set by a user in advance according to the execution requirement of the storage policy, that is, in the context of the present embodiment, only the storage policy in the storage policy type can be executed on the target data, and further, after obtaining the storage policy type, the present embodiment further extracts the attribute values of the multiple target attributes corresponding to the storage policy type in the target metadata, and further determines the target storage policy corresponding to the combination relationship between the attribute values by using the policy determination model corresponding to the storage policy type. When the embodiment executes the storage of the specific storage strategy type on the data, the accuracy of selecting the storage strategy is further ensured, the storage cost is effectively saved, and the efficiency of the multi-element storage medium is utilized to the maximum extent.
On the basis of the foregoing embodiment, as a preferred implementation manner, before performing a data storage operation on target data by using a target storage policy, the method further includes:
acquiring an operation execution identifier;
judging whether the operation execution identifier meets a preset execution standard or not;
and executing the step of executing the data storage operation on the target data by using the target storage strategy if the operation execution identification meets the preset execution standard.
It should be noted that, in the embodiment, before the data storage operation is performed on the target data by using the target storage policy, the operation execution identifier is first obtained, and then it is determined whether the operation execution identifier meets the preset execution criterion, and if the operation execution identifier meets the preset execution criterion, the step of performing the data storage operation on the target data by using the target storage policy is executed, so that the accuracy of the time for executing the data storage operation on the target data by using the target storage policy is ensured, and further, the storage cost is effectively saved, and the efficiency of using the multi-element storage medium is maximized.
On the basis of the above series of embodiments, as a preferred embodiment, the target attribute includes any of a file size, a file number, a file access frequency, a file type, a file compression ratio, and a file read-write rate.
It should be noted that the file size in this embodiment refers to a storage space occupied by a file, and the number of files refers to the number of files; the number of file accesses refers to the number of times a file is read; the file type refers to the data type of the file; the file compression ratio refers to the ratio of the current file size to the file size before the file is data compressed; the file read-write rate refers to the rate at which a file is read and written by the storage system. The target attributes in the embodiment further include any multiple items of file size, file number, file access times, file type, file compression ratio and file read-write rate, so that richness of metadata attribute dimensionality based on analysis of the storage strategy of the target data is further improved, accuracy of storage strategy selection is further ensured, storage cost is effectively saved, and efficiency of the multi-element storage medium is utilized to the maximum extent.
Referring to fig. 2, an embodiment of the present application provides a data storage device, including:
a metadata obtaining module 10, configured to obtain target metadata of target data;
an attribute value extraction module 11, configured to extract attribute values of a plurality of target attributes in the target metadata;
A storage policy decision module 12, configured to decide, by using a preset policy decision model, a target storage policy corresponding to a combination relationship between each attribute value;
and a storage policy executing module 13, configured to execute a data storage operation on the target data by using the target storage policy.
Further, as a preferred embodiment, the apparatus further comprises:
the strategy acquisition module is used for acquiring a preset storage strategy;
and the model establishing module is used for establishing a corresponding relation between a preset storage strategy and an attribute threshold value of the metadata attribute to obtain a strategy judgment model.
According to the data storage device, the target metadata of the target data are firstly obtained, the attribute values of a plurality of target attributes in the target metadata are extracted, the target storage strategy corresponding to the combination relation among the attribute values is judged by using the preset strategy judgment model, and finally the data storage operation is executed on the target data by using the target storage strategy, so that the data storage of the target data is realized. The device obtains the target storage strategy corresponding to the target data in a mode of comprehensively judging the attribute values of the target attributes in the target metadata through the strategy judgment model, so that the accuracy of selecting the corresponding storage strategy according to the data is relatively ensured, the storage cost is effectively saved, and the efficiency of the multi-element storage medium is utilized to the maximum extent.
In addition, an embodiment of the present application further provides a data storage device, including:
a memory for storing a computer program;
a processor for implementing the steps of the data storage method as described above when executing the computer program.
According to the data storage device, the target metadata of the target data are firstly obtained, the attribute values of a plurality of target attributes in the target metadata are extracted, the target storage strategy corresponding to the combination relation among the attribute values is judged by using the preset strategy judgment model, and finally the data storage operation is executed on the target data by using the target storage strategy, so that the data storage of the target data is realized. The device obtains the target storage strategy corresponding to the target data in a mode of comprehensively judging the attribute values of the target attributes in the target metadata through the strategy judgment model, so that the accuracy of selecting the corresponding storage strategy according to the data is relatively ensured, the storage cost is effectively saved, and the efficiency of the multi-element storage medium is utilized to the maximum extent.
In addition, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the data storage method as described above are implemented.
The computer-readable storage medium provided by the application firstly acquires target metadata of target data, extracts attribute values of a plurality of target attributes in the target metadata, further judges a target storage strategy corresponding to a combination relationship between the attribute values by using a preset strategy judgment model, and finally executes data storage operation on the target data by using the target storage strategy, so as to realize data storage on the target data. The computer readable storage medium obtains the target storage strategy corresponding to the target data by comprehensively judging the attribute values of the plurality of target attributes in the target metadata through the strategy judgment model, so that the accuracy of selecting the corresponding storage strategy according to the data is relatively ensured, the storage cost is effectively saved, and the efficiency of the multi-element storage medium is utilized to the maximum extent.
A data storage method, an apparatus, a device and a storage medium provided by the present application are described in detail above. The embodiments are described in a progressive manner in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description. It should be noted that, for those skilled in the art, it is possible to make several improvements and modifications to the present application without departing from the principle of the present application, and such improvements and modifications also fall within the scope of the claims of the present application.
It is further noted that, in the present specification, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Claims (10)
1. A method of storing data, comprising:
acquiring target metadata of target data;
extracting attribute values of a plurality of target attributes in the target metadata;
judging a target storage strategy corresponding to the combination relation between the attribute values by using a preset strategy judgment model;
And executing data storage operation on the target data by utilizing the target storage strategy.
2. The data storage method of claim 1, wherein the generation process of the policy decision model comprises:
acquiring a preset storage strategy;
and establishing a corresponding relation between the preset storage strategy and an attribute threshold value of the metadata attribute to obtain the strategy judgment model.
3. The data storage method according to claim 2, wherein when the number of the preset storage policies is greater than 1, the determining, by using a preset policy determination model, a target storage policy corresponding to a combination relationship between the attribute values includes:
obtaining attribute threshold values corresponding to the preset storage strategies through the strategy judgment model;
counting attribute value matching quantity of the attribute values in the combined relation under each attribute threshold value;
selecting the maximum attribute value matching amount in the attribute value matching amounts;
and setting the preset storage strategy corresponding to the maximum attribute value matching amount as the target storage strategy.
4. The data storage method of claim 1, wherein prior to said extracting attribute values of a plurality of target attributes in said target metadata, said method further comprises:
Acquiring a storage strategy type;
the extracting attribute values of a plurality of target attributes in the target metadata includes:
extracting attribute values of a plurality of target attributes corresponding to the storage policy type in the target metadata;
the method for judging the target storage strategy corresponding to the combination relationship between the target storage strategy and each attribute value by using the preset strategy judgment model comprises the following steps:
and judging a target storage strategy corresponding to the combination relation between the attribute values by using the strategy judgment model corresponding to the storage strategy type.
5. The data storage method of claim 1, wherein prior to said performing data storage operations on said target data using said target storage policy, said method further comprises:
acquiring an operation execution identifier;
judging whether the operation execution identifier meets a preset execution standard or not;
and if the operation execution identifier meets the preset execution standard, executing the step of executing the data storage operation on the target data by using the target storage strategy.
6. The data storage method according to any one of claims 1 to 5, wherein the target attributes include any plurality of file sizes, file numbers, file access times, file types, file compression ratios, and file read-write rates.
7. A data storage device, comprising:
the metadata acquisition module is used for acquiring target metadata of the target data;
the attribute value extraction module is used for extracting attribute values of a plurality of target attributes in the target metadata;
the storage strategy judgment module is used for judging a target storage strategy corresponding to the combination relation between the attribute values by using a preset strategy judgment model;
and the storage strategy execution module is used for executing data storage operation on the target data by using the target storage strategy.
8. The data storage device of claim 7, wherein the device further comprises:
the strategy acquisition module is used for acquiring a preset storage strategy;
and the model establishing module is used for establishing the corresponding relation between the preset storage strategy and the attribute threshold value of the metadata attribute to obtain the strategy judgment model.
9. A data storage device, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the data storage method of any one of claims 1 to 6 when executing said computer program.
10. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of the data storage method according to any one of claims 1 to 6.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114760326A (en) * | 2022-03-02 | 2022-07-15 | 杭州华橙软件技术有限公司 | Data storage method, data query method, data storage system and electronic device |
| CN115695454A (en) * | 2022-06-13 | 2023-02-03 | 中移互联网有限公司 | Data storage method, device, equipment and storage medium of MEC host |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114760326A (en) * | 2022-03-02 | 2022-07-15 | 杭州华橙软件技术有限公司 | Data storage method, data query method, data storage system and electronic device |
| CN115695454A (en) * | 2022-06-13 | 2023-02-03 | 中移互联网有限公司 | Data storage method, device, equipment and storage medium of MEC host |
| CN115695454B (en) * | 2022-06-13 | 2023-10-27 | 中移互联网有限公司 | Data storage method, device and equipment of MEC host and storage medium |
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