CN116932465B - Mirror image file management method, system, equipment and medium - Google Patents
Mirror image file management method, system, equipment and medium Download PDFInfo
- Publication number
- CN116932465B CN116932465B CN202311187648.XA CN202311187648A CN116932465B CN 116932465 B CN116932465 B CN 116932465B CN 202311187648 A CN202311187648 A CN 202311187648A CN 116932465 B CN116932465 B CN 116932465B
- Authority
- CN
- China
- Prior art keywords
- directory
- file
- files
- access data
- probability
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000007726 management method Methods 0.000 title claims abstract description 22
- 230000001419 dependent effect Effects 0.000 claims abstract description 83
- 238000004364 calculation method Methods 0.000 claims abstract description 15
- 230000001172 regenerating effect Effects 0.000 claims abstract 3
- 238000000034 method Methods 0.000 claims description 38
- 238000004590 computer program Methods 0.000 claims description 15
- 238000010586 diagram Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 230000003068 static effect Effects 0.000 description 4
- 238000012360 testing method Methods 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 238000012217 deletion Methods 0.000 description 2
- 230000037430 deletion Effects 0.000 description 2
- 238000009795 derivation Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 238000013138 pruning Methods 0.000 description 2
- 239000000523 sample Substances 0.000 description 2
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 238000011038 discontinuous diafiltration by volume reduction Methods 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000004806 packaging method and process Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/10—File systems; File servers
- G06F16/11—File system administration, e.g. details of archiving or snapshots
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention relates to the technical field of container mirroring, and discloses a mirrored file management method, a mirrored file management system, mirrored file management equipment and a mirrored file management medium, wherein the mirrored file management method comprises the following steps: access data in the operation period of the Linux container is acquired, wherein the access data comprises all directory information and mirror image dependent file information; searching and acquiring directory information corresponding to a target directory and mirror image dependent file information under the target directory in access data according to the target directory to be exported; substituting directory information corresponding to the target directory, mirror image dependent file information under the target directory and all mirror image dependent file information of the Linux container into a conditional probability prediction model for calculation to obtain the export probability of the target directory; comparing the derived probability with a preset probability threshold value, and deriving corresponding access data according to a comparison result; and regenerating a new image file according to the exported access data. The invention can reduce the size of the mirror image file and ensure the integrity of the function of the container after the container is started.
Description
Technical Field
The present invention relates to the field of container mirroring technologies, and in particular, to a method, a system, an apparatus, and a medium for managing a mirrored file.
Background
The Linux container is a lightweight virtualization technology, and can package application programs, services and dependent items into a mirror image and then run in the Linux container. The Linux container solves the problems of application packaging and deployment, ensures the high consistency of the local environment and the cloud environment, and avoids the painful process that a user manually debugs to match the difference between two different running environments.
In order to enable the Linux container to multiplex mirror layer data to the greatest extent and reduce the occupied space of a disk, the Linux container mirror is designed in a layered mode, and each layered mode is a read-only CoW file system. CoW is a write optimization strategy for file systems. In a CoW file system, when a certain file needs to be modified, the system will first copy the block where the file is located into a copy, and then modify the copy, instead of directly modifying the original file block. Thus, the modification of the original file can be avoided, and the consistency and the safety of the data are ensured. When the upper layer needs to delete a certain existing file of the lower layer, the Linux container uses Whiteout technology to mark the deleted file, the marked file is not deleted or covered, and a special file named Whiteout is created to mark that the file has been deleted or modified. Further, in subsequent file access and operation, the system may determine the visibility and status of the file based on the presence or absence of the whisteout file. But in reality the file still exists in the lower layer and the actual disk space occupied is not reduced.
The above-described characteristics of CoW file system and whisteout technology determine that image files only increase and not decrease. If the mirror volume is required to be reduced, the related content is simply deleted from the upper Linux container and does not act on the lower mirror layer. Since multiple images may share the same basic hierarchy, if a certain image layer is directly processed, there is a risk of affecting other Linux containers that rely on that image layer.
Aiming at the characteristics of the Docker image, the optimization is carried out when the image is exported, so that the image occupies less storage space, the completeness of the original function can be ensured, and the method has challenging and practical application significance.
Currently, there are three main schemes for pruning the mirror layer. Firstly, the specification is carried out on the writing of the dockerfile file, such as deleting unnecessary components and files, selecting a small basic mirror mode and the like, and since each instruction in the dockerfile creates a layer, the mirror volume reduction can be realized in an instruction merging mode. However, although this solution may make the generated image smaller and safer, it relies largely on manual orchestration experience and cannot handle the already made image. And secondly, searching a whisteout file in the mirror image by adopting a static analysis algorithm according to the CoW characteristic of the mirror image layer, and then directly deleting the corresponding file in the mirror image layer. However, the scheme is only suitable for a specific mirror image driven by using an aufs file, and other file driving modes such as device-mapper, btrfs and the like cannot be processed. The storage locations and read/write modes of these file drives are very different from those of aufs, so that these images cannot be directly accessed through paths, and the deletion operation of the images cannot be performed. Furthermore, this approach does not eliminate mirror layers that do not contain the whisteout file. Thirdly, a dynamic analysis method is used for obtaining files on which the Linux container runs. The program creates a Linux container through the mirror image to be modified, and a probe is added into the Linux container to monitor the process and file access in the Linux container. When the Linux container is running, the probe collects all relevant information of the dependent files and exports the information to reproduce a new image. The scheme can effectively reduce the size of the mirror image and is not limited by a specific file driver. However, this scheme has a disadvantage in that it relies only on files that are actually accessed by the Linux container runtime. If the Linux container does not fully cover the required files in the running process, excessive deletion may be caused. Therefore, it is necessary to ensure that the Linux container's operating environment contains as comprehensively as possible the required files to avoid accidental pruning when in use.
Disclosure of Invention
The embodiment of the invention provides a method, a system, equipment and a medium for managing mirror image files, which are used for solving the technical problems in the prior art.
The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview and is intended to neither identify key/critical elements nor delineate the scope of such embodiments. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.
According to a first aspect of an embodiment of the present invention, there is provided an image file management method.
In one embodiment, the image file management method includes:
the method comprises the steps of obtaining access data during operation of a Linux container, wherein the access data comprises all directory information and mirror image dependent file information;
searching and acquiring directory information corresponding to a target directory and mirror image dependent file information under the target directory in the access data according to the target directory to be exported;
substituting directory information corresponding to the target directory, mirror image dependent file information under the target directory and all mirror image dependent file information of the Linux container into a pre-configured conditional probability prediction model for calculation to obtain the export probability of the target directory;
comparing the derived probability with a preset probability threshold value, and deriving corresponding access data according to a comparison result; and regenerates a new image file based on the exported access data.
In one embodiment, the directory information includes master directory information and the number of subdirectories recursion levels under each master directory; the image dependent file information comprises the number of all image dependent files of the Linux container and the number of image dependent files of each subdirectory recursion layer.
In one embodiment, the calculation formula of the conditional probability prediction model is:
；
in the method, in the process of the invention,P(D) Deriving probabilities for the target directory;nthe number of files is dependent for all images of the Linux container,for the number of image dependent files contained under the target directory,mfor the number of subdirectories,pthe number of layers is recursively set for the subdirectories,m k the number of files is dependent for each sub-directory recursion level of mirroring.
In one embodiment, deriving the corresponding access data based on the comparison result includes: if the comparison result is that the derived probability is greater than the preset probability threshold value, all files in the target directory are derived; and under the condition that the comparison result is that the derived probability is smaller than the preset probability threshold value, the image dependent file in the target directory is derived.
According to a second aspect of an embodiment of the present invention, there is provided an image file management system.
In one embodiment, the image file management system comprises:
the container data acquisition module is used for acquiring access data in the operation period of the Linux container, wherein the access data comprises all directory information and mirror image dependent file information;
the catalog data acquisition module is used for searching and acquiring catalog information corresponding to a target catalog and mirror image dependent file information under the target catalog in the access data according to the target catalog to be exported;
the export probability calculation module is used for substituting the directory information corresponding to the target directory, the mirror image dependent file information under the target directory and all the mirror image dependent file information of the Linux container into a pre-configured conditional probability prediction model for calculation to obtain the export probability of the target directory;
the file export generating module is used for comparing the export probability with a preset probability threshold value and exporting corresponding access data according to a comparison result; and regenerates a new image file based on the exported access data.
In one embodiment, the directory information includes master directory information and the number of subdirectories recursion levels under each master directory; the image dependent file information comprises the number of all image dependent files of the Linux container and the number of image dependent files of each subdirectory recursion layer.
In one embodiment, the calculation formula of the conditional probability prediction model is:
；
in the method, in the process of the invention,P(D) Deriving probabilities for the target directory;nthe number of files is dependent for all images of the Linux container,is the object ofThe images contained under the directory depend on the number of files,mfor the number of subdirectories,pthe number of layers is recursively set for the subdirectories,m k the number of files is dependent for each sub-directory recursion level of mirroring.
In one embodiment, when the corresponding access data is derived according to the comparison result, the file derivation generation module derives all files in the target directory under the condition that the derivation probability is larger than the preset probability threshold value; and under the condition that the comparison result is that the derived probability is smaller than the preset probability threshold value, the image dependent file in the target directory is derived.
According to a third aspect of embodiments of the present invention, a computer device is provided.
In an embodiment, the computer device comprises a memory storing a computer program and a processor implementing the steps of the above method when the processor executes the computer program.
According to a fourth aspect of embodiments of the present invention, a computer-readable storage medium is provided.
In an embodiment, the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the above method.
The technical scheme provided by the embodiment of the invention can have the following beneficial effects:
according to the method, for the container image to be exported, based on all the dependent files accessed during the running of the original image, a conditional probability prediction model is established, all directory files reaching the target threshold are exported, and the image dependent files not reaching the export threshold are exported as they are, so that the size of the image file can be reduced, and the integrity of the functions of the container after being started can be ensured.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
FIG. 1 is a flow diagram illustrating a method of image file management according to an exemplary embodiment;
FIG. 2 is a block diagram illustrating an image file management system in accordance with an exemplary embodiment;
fig. 3 is a schematic diagram of a computer device according to an exemplary embodiment.
Detailed Description
FIG. 1 illustrates one embodiment of a method of image file management of the present invention.
In this alternative embodiment, the image file management method includes:
step S101, access data during the operation of a Linux container is obtained, wherein the access data comprises all directory information and mirror image dependent file information;
step S103, searching and acquiring directory information corresponding to a target directory and mirror image dependent file information under the target directory in the access data according to the target directory to be exported;
step S105, substituting directory information corresponding to the target directory, mirror image dependent file information under the target directory and all mirror image dependent file information of the Linux container into a pre-configured conditional probability prediction model for calculation to obtain the export probability of the target directory;
step S107, comparing the derived probability with a preset probability threshold value, and deriving corresponding access data according to the comparison result; and regenerates a new image file based on the exported access data.
FIG. 2 illustrates one embodiment of an image file management system of the present invention.
In this alternative embodiment, the image file management system includes:
a container data obtaining module 201, configured to obtain access data during operation of the Linux container, where the access data includes all directory information and image dependent file information;
the catalog data acquisition module 203 is configured to search and acquire catalog information corresponding to a target catalog and image dependent file information under the target catalog in the access data according to the target catalog to be exported;
the export probability calculation module 205 is configured to substitute directory information corresponding to the target directory, image dependent file information under the target directory, and all image dependent file information of the Linux container into a pre-configured conditional probability prediction model to perform calculation, so as to obtain export probability of the target directory;
a file export generating module 207, configured to compare the export probability with a predetermined probability threshold, and export corresponding access data according to the comparison result; and regenerates a new image file based on the exported access data.
In this alternative embodiment, the directory information includes master directory information and the number of subdirectories recursion levels under each master directory; the image dependent file information comprises the number of all image dependent files of the Linux container and the number of image dependent files of each subdirectory recursion layer. The calculation formula of the conditional probability prediction model is as follows:
；
in the method, in the process of the invention,P(D) Deriving probabilities for the target directory;nthe number of files is dependent for all images of the Linux container,for the number of image dependent files contained under the target directory,mfor the number of subdirectories,pthe number of layers is recursively set for the subdirectories,m k the number of files is dependent for each sub-directory recursion level of mirroring.
In this alternative embodiment, when the corresponding access data is derived according to the comparison result, if the comparison result is that the derived probability is greater than the predetermined probability threshold, all files in the target directory are derived; and under the condition that the comparison result is that the derived probability is smaller than the preset probability threshold value, the image dependent file in the target directory is derived.
In order to better understand the above technical scheme of the present invention, the following detailed description of the technical scheme of the present invention will be given by way of example
In units of a catalog, define: destination d= { subdirectory set SF, mirror dependent file set DF, other non-accessed files OIF }, event d= { directory D all exported }.
Defining the probability that the directory d file is totally exported asP(D) Obviously, the more files accessed in a directory, the more core this directory file is explained, the greater the probability that all files under the directory will be exported in their entirety.
To implement the conditional probability prediction model, further define: mirror all dependent file setsCapacity ofnThe method comprises the steps of carrying out a first treatment on the surface of the Mirror dependency File set contained in directory d +.>The method comprises the steps of carrying out a first treatment on the surface of the Subdirectory set contained in directory d。
Since the image dependent file must be exported, the event in directory d that exports the image dependent file is defined asThen->The method comprises the steps of carrying out a first treatment on the surface of the To simplify the predictive model, suppose File +.>The probabilities derived for all directories d are equal, i.e. +.>。
Also, define sonCatalogueThe probability of being derived entirely is +.>The value is found recursively by the subdirectory, which is also a simplified model, assuming the subdirectory +.>File->The probabilities derived for all directories d decrease in order with the recursion level, i.e. the probability of the current level is the upper level probability +.>Suppose subdirectory +.>Recursively p layers, the number of files per layer is +.>And (4) then->The values of (2) are:
；
assuming that the subdirectories and dependent files have the same influence on the export, then the subdirectoriesThe conditional probability derived for directory d is +.>。
For any directory, including 0 to multiple files and subdirectories, the probability of all of them being derived for any directory dThe total probability of all dependent files and subdirectories under a directory can be described as:
；
as can be seen from the definition above,then the formula can further be written as:
；
from the following componentsThe method can obtain:
；
wherein,nthe number of files is dependent for all images of the Linux container,for the number of image dependent files contained under the target directory,mfor the number of subdirectories,pthe number of layers is recursively set for the subdirectories,m k the number of files is dependent for each sub-directory recursion level of mirroring.
Taking cutting the nginx mirror image as required as an example, the complete flow comprises the following steps:
creating and running a container image to be modified by running the following commands：
；
Parameter description: -d nginx: setting the container to run all the time in the background; -name nmginx_test: a container name; -v: the format that indicates which directory needs to be locally mounted into the container: v < host directory >: container directory >;
all dependent files of the container run-time are obtained using the following commands:
；
description: executing an in-container lsof system command in an interactive mode in an operating container Nginx_test, acquiring all file names which are already opened by a current system, and recording the file names into a file/root/dependence file;
repeating step 2 for 20 times every minute; after 20 minutes, the command was usedStopping the container Nginx_test;
after the operation of the isovessel is finished, the system automatically enters a bash interface of the host machine to check the/root/dependence file.txt files of the host machine, wherein all the dependent files accessed in the operation process of the vessel are summarized;
description: the host's/root/depend directory is mounted to the container's/root/depend/directory using the-v parameter, and what is actually operated in the container is the host's/root/depend directory.
The following system commands were used to sort and de-duplicate the/root/dependent file.The method comprises the steps of carrying out a first treatment on the surface of the And generating/root/dependencies/new_dependency file. Txt (recording all accessed directories and files during the running of the nginx container), taking the directory/home/fast as an example, how to decide whether the directory is fully exported or only the container dependent files under the directory, wherein the main focused index items are: the number n of all dependent files of the container; the number of dependent files/contained under the directory/home/fast; the number m of subdirectories of the directory/home/fast, the number p of recursion layers of the subdirectories and the number +.>；
Description: the number of the files with TYPE being REG in the root/dependence file.txt files is the number of all the dependent files of the container; TYPE is REG and NAME is the number of files per home/fast/xx, namely the number of dependent files contained under the directory/home/fast; as for the number of subdirectories of the directory/home/fast, the number of recursion layers of the subdirectories, and the number of files per layer, reference to the directory can be directly obtained.
Substituting the obtained value into a derived conditional probability prediction model as follows:the method comprises the steps of carrying out a first treatment on the surface of the Calculating the export probability p of the catalog/home/fast;
setting a threshold valueIf the export probability p of the directory/home/fast is greater than the threshold value, directly exporting all files in the directory; the threshold value is not exceeded, and only the files depending on the mirror image in the directory are exported;
repeating the steps, calculating the export probability of all the directories, and determining whether to export all the files under the directories or only rely on the files according to the export probability; passing the exported file through the commandA new image is regenerated.
FIG. 3 illustrates one embodiment of a computer device of the present invention. The computer device may be a server including a processor, memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured 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, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used to store static information and dynamic information data. The network interface of the computer device is used for communicating with an external terminal through a network connection. Which computer program, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.
It will be appreciated by those skilled in the art that the structure shown in FIG. 3 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
The invention further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to realize the steps in the embodiment of the method.
In addition, the invention also provides a computer readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, implements the steps of the above-mentioned method embodiments.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, or the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like.
The present invention is not limited to the structure that has been described above and shown in the drawings, and various modifications and changes can be made without departing from the scope thereof.
Claims (8)
1. A method for managing image files, comprising:
the method comprises the steps of obtaining access data during operation of a Linux container, wherein the access data comprises all directory information and mirror image dependent file information;
searching and acquiring directory information corresponding to a target directory and mirror image dependent file information under the target directory in the access data according to the target directory to be exported;
substituting directory information corresponding to the target directory, mirror image dependent file information under the target directory and all mirror image dependent file information of the Linux container into a pre-configured conditional probability prediction model for calculation to obtain the export probability of the target directory;
comparing the derived probability with a preset probability threshold value, and deriving corresponding access data according to a comparison result; regenerating a new image file according to the exported access data;
the calculation formula of the conditional probability prediction model is as follows:
；
in the method, in the process of the invention,P(D) Deriving probabilities for the target directory;nthe number of files is dependent for all images of the Linux container,for the number of image dependent files contained under the target directory,mfor the number of subdirectories,pthe number of layers is recursively set for the subdirectories,m k the number of files is dependent for each sub-directory recursion level of mirroring.
2. The image file management method according to claim 1, wherein said directory information includes master directory information and the number of subdirectories recursion layers under each master directory; the image dependent file information comprises the number of all image dependent files of the Linux container and the number of image dependent files of each subdirectory recursion layer.
3. The image file management method according to claim 1, wherein deriving the corresponding access data based on the comparison result comprises:
if the comparison result is that the derived probability is greater than the preset probability threshold value, all files in the target directory are derived;
and under the condition that the comparison result is that the derived probability is smaller than the preset probability threshold value, the image dependent file in the target directory is derived.
4. An image file management system, comprising:
the container data acquisition module is used for acquiring access data in the operation period of the Linux container, wherein the access data comprises all directory information and mirror image dependent file information;
the catalog data acquisition module is used for searching and acquiring catalog information corresponding to a target catalog and mirror image dependent file information under the target catalog in the access data according to the target catalog to be exported;
the export probability calculation module is used for substituting the directory information corresponding to the target directory, the mirror image dependent file information under the target directory and all the mirror image dependent file information of the Linux container into a pre-configured conditional probability prediction model for calculation to obtain the export probability of the target directory;
the file export generating module is used for comparing the export probability with a preset probability threshold value and exporting corresponding access data according to a comparison result; regenerating a new image file according to the exported access data;
the calculation formula of the conditional probability prediction model is as follows:
；
in the method, in the process of the invention,P(D) Deriving probabilities for the target directory;nthe number of files is dependent for all images of the Linux container,for the number of image dependent files contained under the target directory,mfor the number of subdirectories,pthe number of layers is recursively set for the subdirectories,m k the number of files is dependent for each sub-directory recursion level of mirroring.
5. The image file management system according to claim 4, wherein said directory information includes master directory information and the number of subdirectories recursion levels under each master directory; the image dependent file information comprises the number of all image dependent files of the Linux container and the number of image dependent files of each subdirectory recursion layer.
6. The image file management system according to claim 4, wherein said file export creation module, when exporting the corresponding access data based on the comparison result, exports all files in the target directory if the comparison result is that the export probability is greater than the predetermined probability threshold; and under the condition that the comparison result is that the derived probability is smaller than the preset probability threshold value, the image dependent file in the target directory is derived.
7. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 3 when the computer program is executed.
8. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311187648.XA CN116932465B (en) | 2023-09-15 | 2023-09-15 | Mirror image file management method, system, equipment and medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311187648.XA CN116932465B (en) | 2023-09-15 | 2023-09-15 | Mirror image file management method, system, equipment and medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116932465A CN116932465A (en) | 2023-10-24 |
| CN116932465B true CN116932465B (en) | 2024-01-23 |
Family
ID=88375646
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311187648.XA Active CN116932465B (en) | 2023-09-15 | 2023-09-15 | Mirror image file management method, system, equipment and medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116932465B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017049828A1 (en) * | 2015-09-25 | 2017-03-30 | 中兴通讯股份有限公司 | Method, device and system for data processing based on linux |
| CN107809467A (en) * | 2017-10-10 | 2018-03-16 | 暨南大学 | Container mirror image data deletes method under a kind of cloud environment |
| CN115544496A (en) * | 2022-10-14 | 2022-12-30 | 北京火山引擎科技有限公司 | Server-free computing method, device and equipment based on trusted execution environment |
| CN115599398A (en) * | 2022-11-28 | 2023-01-13 | 中国电子科技集团公司第十五研究所（Cn） | Container-based mirror image separation integration and loading method |
| CN116204305A (en) * | 2022-12-21 | 2023-06-02 | 山东未来网络研究院(紫金山实验室工业互联网创新应用基地) | Method for limiting number of dock container inodes |
| CN116340940A (en) * | 2022-12-19 | 2023-06-27 | 深圳开鸿数字产业发展有限公司 | Code identification method, terminal device and storage medium |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108415795B (en) * | 2018-02-12 | 2019-04-05 | 人和未来生物科技（长沙）有限公司 | A kind of container Dockerfile, container mirror image rapid generation and system |
| US11263120B2 (en) * | 2020-02-12 | 2022-03-01 | Capital One Services, Llc | Feature-based deployment pipelines |
| CN113051036A (en) * | 2021-03-31 | 2021-06-29 | 京东方科技集团股份有限公司 | Application program licensing method, device, equipment and medium based on Docker container |
-
2023
- 2023-09-15 CN CN202311187648.XA patent/CN116932465B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017049828A1 (en) * | 2015-09-25 | 2017-03-30 | 中兴通讯股份有限公司 | Method, device and system for data processing based on linux |
| CN107809467A (en) * | 2017-10-10 | 2018-03-16 | 暨南大学 | Container mirror image data deletes method under a kind of cloud environment |
| CN115544496A (en) * | 2022-10-14 | 2022-12-30 | 北京火山引擎科技有限公司 | Server-free computing method, device and equipment based on trusted execution environment |
| CN115599398A (en) * | 2022-11-28 | 2023-01-13 | 中国电子科技集团公司第十五研究所（Cn） | Container-based mirror image separation integration and loading method |
| CN116340940A (en) * | 2022-12-19 | 2023-06-27 | 深圳开鸿数字产业发展有限公司 | Code identification method, terminal device and storage medium |
| CN116204305A (en) * | 2022-12-21 | 2023-06-02 | 山东未来网络研究院(紫金山实验室工业互联网创新应用基地) | Method for limiting number of dock container inodes |
Non-Patent Citations (1)
| Title |
|---|
| 一种概率模型的Docker镜像删减策略;周毅;邓玉辉;;小型微型计算机系统(第09期);22-27 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116932465A (en) | 2023-10-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US7873601B1 (en) | Backup of incremental metadata in block based backup systems | |
| US10248556B2 (en) | Forward-only paged data storage management where virtual cursor moves in only one direction from header of a session to data field of the session | |
| US20150006581A1 (en) | Method for a Storage Device Accessing a File and Storage Device | |
| US20050240590A1 (en) | File system updating metadata of files according to results of keyword search | |
| JP6598996B2 (en) | Signature-based cache optimization for data preparation | |
| US11853566B2 (en) | Management method and system for address space of low delay file system and medium | |
| CN108920725B (en) | Object storage method and object storage gateway | |
| US10838624B2 (en) | Extent pool allocations based on file system instance identifiers | |
| CN113568582B (en) | Data management method, device and storage equipment | |
| US11841826B2 (en) | Embedded reference counts for file clones | |
| CN114048185A (en) | Method for transparently packaging, storing and accessing massive small files in distributed file system | |
| JP6598997B2 (en) | Cache optimization for data preparation | |
| JP2012505461A (en) | Storage system and control method thereof | |
| CA2959647C (en) | Data migration tool with intermediate incremental copies | |
| CN111459764B (en) | Log management method and terminal | |
| CN116932465B (en) | Mirror image file management method, system, equipment and medium | |
| US9471437B1 (en) | Common backup format and log based virtual full construction | |
| US20230334325A1 (en) | Model Training Method and Apparatus, Storage Medium, and Device | |
| CN115658619A (en) | Process processing method and device, processor and electronic equipment | |
| CN109241011B (en) | Virtual machine file processing method and device | |
| CN113282563A (en) | File gateway high availability implementation method based on object storage and electronic equipment | |
| CN110471623B (en) | Hard disk file writing method, device, computer equipment and storage medium | |
| US11928082B1 (en) | Container image file system performance enhancement | |
| CN117194350B (en) | Document storage method and system in engineering construction stage of data center | |
| CN112698976B (en) | Metadata restoration method, device, equipment and medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |