CN113778343A - Storage implementation method for expanding data volume of docker container to HDFS (Hadoop distributed File System) - Google Patents
Storage implementation method for expanding data volume of docker container to HDFS (Hadoop distributed File System) Download PDFInfo
- Publication number
- CN113778343A CN113778343A CN202111118851.2A CN202111118851A CN113778343A CN 113778343 A CN113778343 A CN 113778343A CN 202111118851 A CN202111118851 A CN 202111118851A CN 113778343 A CN113778343 A CN 113778343A
- Authority
- CN
- China
- Prior art keywords
- hdfs
- data
- container
- physical machine
- data volume
- 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.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 38
- 238000004590 computer program Methods 0.000 claims description 13
- 238000009434 installation Methods 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 12
- 238000013500 data storage Methods 0.000 description 6
- 230000006870 function Effects 0.000 description 6
- 238000012545 processing Methods 0.000 description 5
- 238000004891 communication Methods 0.000 description 3
- 238000013507 mapping Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000002688 persistence Effects 0.000 description 1
- 230000002085 persistent effect Effects 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
- G06F3/0601—Interfaces specially adapted for storage systems
- G06F3/0602—Interfaces specially adapted for storage systems specifically adapted to achieve a particular effect
- G06F3/0614—Improving the reliability of storage systems
-
- 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
- G06F16/18—File system types
- G06F16/182—Distributed file systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
- G06F3/0601—Interfaces specially adapted for storage systems
- G06F3/0602—Interfaces specially adapted for storage systems specifically adapted to achieve a particular effect
- G06F3/062—Securing storage systems
- G06F3/0623—Securing storage systems in relation to content
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
- G06F3/0601—Interfaces specially adapted for storage systems
- G06F3/0628—Interfaces specially adapted for storage systems making use of a particular technique
- G06F3/0638—Organizing or formatting or addressing of data
- G06F3/0643—Management of files
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
- G06F3/0601—Interfaces specially adapted for storage systems
- G06F3/0668—Interfaces specially adapted for storage systems adopting a particular infrastructure
- G06F3/067—Distributed or networked storage systems, e.g. storage area networks [SAN], network attached storage [NAS]
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Human Computer Interaction (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Stored Programmes (AREA)
Abstract
The invention relates to a storage implementation method for expanding a data volume of a docker container to an HDFS (Hadoop distributed File System), which comprises the following steps: installing docker data volume extension plug-ins which accord with the set use rule of the container to each physical machine; carrying out SeaboxdataFtpSever mounting on each physical machine; when data operation is carried out in the container physical machine, the data operation is automatically transmitted to the SeaboxadataFtpPer through the mounting point; SeaboxadataFtpSever calls the API of the HDFS to write data into the HDFS. The invention realizes that the docker container accesses shared data across hosts and can provide reliable storage for the docker container.
Description
Technical Field
The invention relates to a storage implementation method for expanding a data volume of a docker container to an HDFS (Hadoop distributed File System), and relates to the technical field of containerization.
Background
The Docker container storage problem has been a bottleneck in container technology, particularly in distributed computing based on Docker containers. Although the docker container can mount the file directory of the host machine into the container for data storage by creating the local data volume, the data loss is prevented. However, when using docker as a distributed computing engine, the same computing task is divided into different small tasks. A small task corresponds to a docker container, the container runs on different hosts, and cross-host data access sharing becomes a biggest problem, and mounting a local data directory of the hosts and data storage capacity are bottlenecks.
The defects of the existing docker data volume are as follows: when the instance of the Docker container runs in a physical machine and the service in the container needs to perform data persistence, the disk path mapping of the host needs to be mounted, and the disk path mapping is used as the data volume of the Docker container and is used for persisting the data which the container needs to store. However, in an actual application scenario, most instances of docker applications are distributed services. The distributed service is characterized in that the docker container needs to be deployed across physical machines, and all data of the distributed docker container needs to be shared, for example, the service F1 is a distributed service, and the docker container of the service F1 runs in the physical machines a1, a2, and A3, respectively. As shown in FIG. 1, the data for docker container 1 in physical machine A1 is stored under path/path 1/path, and by default, the docker containers in physical machines A2, A3 have no access to data under/path 2/path in physical machine A1. When the physical machines A1, A2 and A3 are read and written with high frequency for a long time, the physical machine magnetic disks are easy to age and damage, and once the disks are damaged, the data recovery is often difficult to recover.
Therefore, the docker container has several problems to mount local data: 1) data cannot be shared across physics; 2) data cannot guarantee reliability; 3) local disk storage, for distributed applications, data storage is a significant bottleneck.
Disclosure of Invention
In view of the foregoing problems, an object of the present invention is to provide a storage implementation method capable of expanding a data volume of a docker container, which is used for enabling the docker container to access shared data across hosts, to an HDFS.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, the storage implementation method for expanding a data volume of a docker container to an HDFS provided by the present invention includes:
installing docker data volume extension plug-ins which accord with the set use rule of the container to each physical machine;
carrying out SeaboxdataFtpSever mounting on each physical machine;
when data operation is carried out in the container physical machine, the data operation is automatically transmitted to the SeaboxadataFtpPer through the mounting point;
SeaboxadataFtpSever calls the API of the HDFS to write data into the HDFS.
Further, the mounting mode is carried out by adopting a command line plus parameter form.
In a second aspect, the present invention further provides a storage implementation system for expanding a data volume of a docker container to an HDFS, where the system includes:
the plug-in installation unit is configured to install the Seaboxdata Volume plug which accords with the set use rule of the container to each physical machine;
a mounting unit configured to mount SeaboxadataFtpPer on each physical machine;
the container operation unit is configured to automatically transmit the data operation to the SeaboxadataFtpSeever through the mounting point when the data operation is carried out in the container physical machine;
and the data writing unit is configured to call the API of the HDFS by the SeaboxadataFtpPer and write the data into the HDFS.
Further, the mounting mode can be performed in a form of a command line and a parameter.
In a third aspect, the present invention further provides an electronic device, which at least includes a processor and a memory, where the memory stores a computer program, and the processor executes the method when executing the computer program.
In a fourth aspect, the present invention also provides a computer storage medium having computer-readable instructions stored thereon which are executable by a processor to implement the method.
Due to the adoption of the technical scheme, the invention has the following advantages:
1. according to the method, the API of the HDFS is called through the SeaboxadataFtpPer, data are written into the HDFS, and a docker container accesses shared data across hosts;
2. the method realizes the big data storage of the docker container, and can provide reliable storage of the docker container;
3. the invention can solve the problem of the data storage capacity of the container;
in conclusion, the invention can be widely applied to container storage.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Like reference numerals refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a schematic diagram of a conventional principle of docker container mounted local data;
FIG. 2 is a schematic diagram of a storage implementation method for expanding a data volume of a docker container to an HDFS according to an embodiment of the present invention;
FIG. 3 is a flowchart of a storage implementation method for expanding a data volume of a docker container to an HDFS according to an embodiment of the present invention;
fig. 4 is a block diagram of an electronic device according to an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
It is to be understood that the terminology used herein is for the purpose of describing particular example embodiments only, and is not intended to be limiting. As used herein, the singular forms "a", "an" and "the" may be intended to include the plural forms as well, unless the context clearly indicates otherwise. The terms "comprises," "comprising," "including," and "having" are inclusive and therefore specify the presence of stated features, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, and/or groups thereof. The method steps, processes, and operations described herein are not to be construed as necessarily requiring their performance in the particular order described or illustrated, unless specifically identified as an order of performance. It should also be understood that additional or alternative steps may be used.
Although the terms first, second, third, etc. may be used herein to describe various elements, components, regions, layers and/or sections, these elements, components, regions, layers and/or sections should not be limited by these terms. These terms may be only used to distinguish one element, component, region, layer or section from another region, layer or section. Terms such as "first," "second," and other numerical terms when used herein do not imply a sequence or order unless clearly indicated by the context. Thus, a first element, component, region, layer or section discussed below could be termed a second element, component, region, layer or section without departing from the teachings of the example embodiments.
For convenience of description, spatially relative terms, such as "inner", "outer", "lower", "upper", and the like, may be used herein to describe one element or feature's relationship to another element or feature as illustrated in the figures. Such spatially relative terms are intended to encompass different orientations of the device in use or operation in addition to the orientation depicted in the figures.
The invention provides a storage implementation method, a system and a storage medium method for expanding a data volume of a docker container to an HDFS (Hadoop distributed File System), wherein the storage implementation method comprises the following steps: installing docker data volume extension plug-ins which accord with the set use rule of the container to each physical machine; carrying out SeaboxdataFtpSever mounting on each physical machine; when data operation is carried out in the container physical machine, the data operation is automatically transmitted to the SeaboxadataFtpPer through the mounting point; SeaboxadataFtpSever calls the API of the HDFS to write data into the HDFS. According to the invention, the API of the HDFS is called by the SeaboxadataFtpPer, data is written into the HDFS, and the purpose that a docker container accesses shared data across hosts is achieved.
Example one
The Docker provides an interface for data volume plug-in extension, and the method is realized based on the interface for data volume plug-in extension.
As shown in fig. 2, the reliability and data volume of data storage are realized by using a distributed file storage system (HDFS) of a sea-box big data platform, which can solve the problem of accessing data across hosts. Overall, the expanded docker container volume plugin loads, when the docker container data volume is loaded, the SeaboxdataFtpServer is loaded through the plug-in, so that the advantages of docker container calculation and the advantages of the sea-box distributed file storage system (HDFS) can be combined with each other.
As shown in fig. 3, the storage implementation method for expanding a data volume of a docker container to an HDFS provided in this embodiment includes:
s1, installing Seabox data Volume plugin (docker data Volume extension plug-in) meeting the use rule of the container setting to each physical machine 1 … n;
s2, performing SeaboxdataFtpSever mounting on each physical machine, where the mounting may be performed in a form of command line plus parameters, for example: the parameter may be an http address, a port, a name, or a password, and may be selected according to an actual use requirement, which is not limited herein.
S3, when data operation is carried out in the container physical machine, the data operation can be automatically transmitted to the SeaboxadataFtpSevere through the mounting point.
S4, seatoxdataftpsever calls an API (application programming interface) of the HDFS and writes data to the HDFS.
According to the storage implementation method for expanding the data volume of the docker container to the HDFS, after the containers in the physical machines 1 and 2 … mount the HDFS through the data volume plug-in units, data sharing read-write of all data stored in the physical machines can be achieved through the HDFS, the problem of cross-host computer of the docker container is achieved by means of Seabox dataFtpserver, and the reliability and the large data volume of data of the docker container are guaranteed by means of the HDFS. The reliability and the data volume of data of the docker container are guaranteed by relying on HDFS.
Example two
Correspondingly, the embodiment provides a system for realizing storage of a data volume of a docker container extended to an HDFS. The system provided in this embodiment may implement the method for implementing storage of expanding a data volume of a docker container to an HDFS in the first embodiment, and the system may be implemented by software, hardware, or a combination of software and hardware. For convenience of description, the present embodiment is described with the functions divided into various units, which are described separately. Of course, the functions of the units may be implemented in the same software and/or hardware or in one or more pieces. For example, the system may comprise integrated or separate functional modules or units to perform the corresponding steps in the method of an embodiment. Since the system of this embodiment is substantially similar to the method embodiment, the description process of this embodiment is relatively simple, and reference may be made to a part of the description of the embodiment a related part, and the embodiment of the system for implementing storage of a docker container data volume extended to HDFS provided by the present invention is only schematic.
Specifically, the system for implementing storage of a docker container data volume extended to HDFS provided by this embodiment includes:
a plug-in installation unit configured to install the seabox data Volume plugin conforming to the container setting use rule to each physical machine 1 … n;
the mounting unit is configured to mount the SeaboxadataFtpSever on each physical machine, and the mounting mode can be performed in a form of a command line and parameters, such as: the parameter may be an http address, a port, a name, or a password, and may be selected according to an actual use requirement, which is not limited herein.
And the container operation unit is configured to automatically transfer the data operation to the SeaboxadataFtpSeever through the mounting point when the data operation is carried out in the container physical machine.
The data write unit, SeaboxdataFtpSever, calls an API (application programming interface) of the HDFS to write data into the HDFS.
EXAMPLE III
The present embodiment provides an electronic device corresponding to the method for implementing storage of a data volume of a docker container extended to HDFS provided in the first embodiment, where the electronic device may be an electronic device for a client, such as a mobile phone, a notebook computer, a tablet computer, a desktop computer, and the like, to execute the method in the first embodiment.
As shown in fig. 4, the electronic device includes a processor, a memory, a communication interface, and a bus, and the processor, the memory, and the communication interface are connected by the bus to complete communication therebetween. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The storage device is configured to store a computer program that can be executed on the processor, and when the processor executes the computer program, the storage implementation method for expanding a data volume of a docker container to an HDFS provided in this embodiment is executed. Those skilled in the art will appreciate that the architecture shown in fig. 4 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects may be applied, and that a particular computing device may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In some implementations, the logic instructions in the memory may be implemented in software functional units and stored in a computer readable storage medium when sold or used as a stand-alone product. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), an optical disk, and various other media capable of storing program codes.
In other implementations, the processor may be various general-purpose processors such as a Central Processing Unit (CPU), a Digital Signal Processor (DSP), and the like, and is not limited herein.
Example four
The method for implementing storage of a docker container data volume extended to an HDFS in this embodiment may be embodied as a computer program product, where the computer program product may include a computer readable storage medium on which computer readable program instructions for executing the method for implementing storage of a docker container data volume extended to an HDFS in this embodiment are loaded.
The computer readable storage medium may be a tangible device that retains and stores instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any combination of the foregoing.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment. In the description herein, references to the description of "one embodiment," "some implementations," or the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of an embodiment of the specification. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (6)
1. A storage implementation method for expanding a data volume of a docker container to an HDFS (Hadoop distributed File System) is characterized by comprising the following steps:
installing docker data volume extension plug-ins which accord with the set use rule of the container to each physical machine;
carrying out SeaboxdataFtpSever mounting on each physical machine;
when data operation is carried out in the container physical machine, the data operation is automatically transmitted to the SeaboxadataFtpPer through the mounting point;
SeaboxadataFtpSever calls the API of the HDFS to write data into the HDFS.
2. The storage implementation method for expanding the data volume of the docker container to the HDFS according to claim 1, wherein the mounting is performed in a form of a command line plus a parameter.
3. A storage implementation system for expanding data volume of a docker container to HDFS (Hadoop distributed File System), which is characterized by comprising:
the plug-in installation unit is configured to install the Seaboxdata Volume plug which accords with the set use rule of the container to each physical machine;
a mounting unit configured to mount SeaboxadataFtpPer on each physical machine;
the container operation unit is configured to automatically transmit the data operation to the SeaboxadataFtpSeever through the mounting point when the data operation is carried out in the container physical machine;
and the data writing unit is configured to call the API of the HDFS by the SeaboxadataFtpPer and write the data into the HDFS.
4. The system for storage implementation of docker container data volume extension to HDFS according to claim 3, characterized in that the mounting may be performed in a command line plus parameter format.
5. An electronic device comprising at least a processor and a memory, the memory having stored thereon a computer program, characterized in that the processor, when executing the computer program, executes to carry out the method of claim 1 or 2.
6. A computer storage medium having computer readable instructions stored thereon which are executable by a processor to implement the method of claim 1 or 2.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111118851.2A CN113778343A (en) | 2021-09-24 | 2021-09-24 | Storage implementation method for expanding data volume of docker container to HDFS (Hadoop distributed File System) |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111118851.2A CN113778343A (en) | 2021-09-24 | 2021-09-24 | Storage implementation method for expanding data volume of docker container to HDFS (Hadoop distributed File System) |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113778343A true CN113778343A (en) | 2021-12-10 |
Family
ID=78853175
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111118851.2A Pending CN113778343A (en) | 2021-09-24 | 2021-09-24 | Storage implementation method for expanding data volume of docker container to HDFS (Hadoop distributed File System) |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113778343A (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150254319A1 (en) * | 2012-03-28 | 2015-09-10 | Netapp, Inc. | Methods and systems for replicating an expandable storage volume |
| CN105160269A (en) * | 2015-08-13 | 2015-12-16 | 浪潮电子信息产业股份有限公司 | Method and apparatus for accessing data in Docker container |
| CN109274722A (en) * | 2018-08-24 | 2019-01-25 | 北京北信源信息安全技术有限公司 | Data sharing method, device and electronic equipment |
| CN110704162A (en) * | 2019-09-27 | 2020-01-17 | 北京百度网讯科技有限公司 | Method, device and equipment for sharing container mirror image by physical machine and storage medium |
-
2021
- 2021-09-24 CN CN202111118851.2A patent/CN113778343A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150254319A1 (en) * | 2012-03-28 | 2015-09-10 | Netapp, Inc. | Methods and systems for replicating an expandable storage volume |
| CN105160269A (en) * | 2015-08-13 | 2015-12-16 | 浪潮电子信息产业股份有限公司 | Method and apparatus for accessing data in Docker container |
| CN109274722A (en) * | 2018-08-24 | 2019-01-25 | 北京北信源信息安全技术有限公司 | Data sharing method, device and electronic equipment |
| CN110704162A (en) * | 2019-09-27 | 2020-01-17 | 北京百度网讯科技有限公司 | Method, device and equipment for sharing container mirror image by physical machine and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107870728B (en) | Method and apparatus for moving data | |
| US9015519B2 (en) | Method and system for cluster wide adaptive I/O scheduling by a multipathing driver | |
| CN110865888A (en) | Resource loading method and device, server and storage medium | |
| TWI694700B (en) | Data processing method and device, user terminal | |
| US8862857B2 (en) | Data access processing method and apparatus | |
| CN105446811A (en) | Application process associated starting method and associated starting apparatus | |
| EP3497586A1 (en) | Discovery of calling application for control of file hydration behavior | |
| US20210132860A1 (en) | Management of multiple physical function non-volatile memory devices | |
| CN115686932B (en) | Backup set file recovery method and device and computer equipment | |
| US8683169B2 (en) | Selecting an auxiliary storage medium for writing data of real storage pages | |
| CN104572431A (en) | Test method and test device | |
| CN110069217B (en) | Data storage method and device | |
| WO2017105965A2 (en) | Automatic system response to external field-replaceable unit (fru) process | |
| CN105700942A (en) | Associated start method and associated start device for application process | |
| CN111949297B (en) | Block chain intelligent contract upgrading method and device and electronic equipment | |
| CN112596669A (en) | Data processing method and device based on distributed storage | |
| CN113778343A (en) | Storage implementation method for expanding data volume of docker container to HDFS (Hadoop distributed File System) | |
| CN105653364A (en) | Application process management method and application process management device | |
| CN110489392A (en) | Data access method, device, system, storage medium and equipment between multi-tenant | |
| CN105653339A (en) | Application process starting method and application process starting device | |
| CN115714706A (en) | Access acceleration system and method based on embedded H5, storage medium and electronic equipment | |
| CN111142972B (en) | Method, apparatus, system, and medium for extending functions of application program | |
| CN113342270A (en) | Volume unloading method and device and electronic equipment | |
| CN114356446A (en) | Method, device and equipment for processing inter-process event and storage medium | |
| CN114116676A (en) | Data migration method and device, electronic equipment and computer readable storage 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 |