CN112559460B - File storage method, device, equipment and storage medium based on artificial intelligence - Google Patents
File storage method, device, equipment and storage medium based on artificial intelligence Download PDFInfo
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- CN112559460B CN112559460B CN202011490492.9A CN202011490492A CN112559460B CN 112559460 B CN112559460 B CN 112559460B CN 202011490492 A CN202011490492 A CN 202011490492A CN 112559460 B CN112559460 B CN 112559460B
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- 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
- G06F16/17—Details of further file system functions
- G06F16/172—Caching, prefetching or hoarding of files
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- 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
- G06F16/119—Details of migration of file systems
Abstract
The invention discloses a file storage method, device and equipment based on artificial intelligence and a storage medium, and belongs to the technical field of file storage based on artificial intelligence. According to the method, the target files are screened from the user identity files by acquiring the user identity files input by each service subsystem, the target files based on the artificial intelligence are stored in the first server, the storage time of the target files in the first server is acquired, when the storage time reaches the preset time, the target files are migrated from the first server to the second server to be stored, the target files are stored in the first server first, then the target files based on the artificial intelligence are stored in the second server, and the storage attributes of different servers are utilized, so that the storage space of the database server is saved, and the service performance of the database server is improved. Wherein the target file may be stored in a blockchain.
Description
Technical Field
The present invention relates to the field of file storage technologies based on artificial intelligence, and in particular, to a file storage method, device, equipment and storage medium based on artificial intelligence.
Background
The life insurance intelligent authentication platform is an identity card service platform unified by life insurance companies, wherein the three-element personnel interface participating comprises a customer big head photo file transmitted by a business subsystem, the size of each file is about 100k, and the three-element authentication needs to be stored after the completion of the three-element authentication so as to facilitate the follow-up business tracing, and the tracing of customer head portraits generally occurs within one week from the date of authentication.
At present, the authentication platform stores files into a database list table, the authentication amount is about 15w per day, only the data occupies a storage space of 1.5G per day, the storage space of a single database server is limited, the files stored in the database list table are usually read again in a short time, and the files are in an idle state most of the time, so that the high-performance storage of the database server is extremely wasted, and the service performance of the whole database is influenced by the overlarge data amount of the list table, so that the method is extremely dangerous.
The foregoing is provided merely for the purpose of facilitating understanding of the technical solutions of the present invention and is not intended to represent an admission that the foregoing is prior art.
Disclosure of Invention
The invention mainly aims to provide a file storage method, device, equipment and storage medium based on artificial intelligence, and aims to solve the technical problem that the service performance of a database is affected by storing a large number of files based on the artificial intelligence into a database list in the prior art.
In order to achieve the above object, the present invention provides an artificial intelligence based file storage method, which includes the steps of:
acquiring a user identity file input by a service subsystem;
screening out a target file from the user identity file;
storing the target file to a first server, and acquiring the storage time length of the target file in the first server;
and when the storage time length reaches a preset time length, migrating the target file from the first server to a second server for storage.
Optionally, the screening the target file from the user identity files includes:
screening a user head portrait file from the user identity file according to the preset byte quantity;
acquiring a service scene corresponding to the user head portrait file;
and comparing the service scene with a preset service scene, and taking a user head image file conforming to the preset service scene as a target file.
Optionally, before the storing the target file in the first server, the method further includes:
acquiring historical service flow of the service subsystem;
determining the peak flow of the service subsystem in a preset period according to the historical service flow;
and comparing the peak flow with a preset flow, and changing the initial storage space of the first server into a target storage space according to a comparison result.
Optionally, the storing the target file in the first server includes:
establishing network connection with a first server based on a preset interface;
acquiring a target address and an operation parameter corresponding to the first server;
determining a disk array corresponding to the first server according to the operation parameters;
and writing the target file into the disk array through the network connection according to the target address.
Optionally, the obtaining the storage duration of the target file in the first server includes:
acquiring an initial time when a target file is stored in the first server;
detecting the current time mark of the target file in the first server in real time;
determining the current moment corresponding to the target file according to the current time identifier;
and determining the storage time length of the target file in the first server according to the initial time and the current time.
Optionally, the migration of the target file from the first server to the second server for storage includes:
downloading the target file from the first server to an object storage device of a second server;
establishing a storage object in the object storage equipment according to a preset storage attribute;
and storing the target file through the storage object.
Optionally, after the migration of the target file from the first server to the second server for storage, the method further includes:
acquiring abstract information corresponding to the stored target file;
inquiring a storage path corresponding to the target file in the first server or the second server according to the file identifier corresponding to the abstract information;
and calling the target file from the first server or the second server according to the storage path.
In addition, in order to achieve the above object, the present invention also proposes a file storage device based on artificial intelligence, the device comprising:
the acquisition module is used for acquiring the user identity file input by the service subsystem;
the screening module is used for screening out target files from the user identity files;
the storage module is used for storing the target file to a first server and acquiring the storage time length of the target file in the first server;
and the transfer module is used for transferring the target file from the first server to the second server for storage when the storage duration reaches a preset duration.
In addition, in order to achieve the above object, the present invention also proposes an artificial intelligence based file storage device, including: a memory, a processor, and an artificial intelligence based file storage program stored on the memory and executable on the processor, the artificial intelligence based file storage program configured to implement the steps of the artificial intelligence based file storage method as described above.
In addition, in order to achieve the above object, the present invention also proposes a storage medium having stored thereon an artificial intelligence based file storage program which, when executed by a processor, implements the steps of the artificial intelligence based file storage method as described above.
According to the method, the target files are screened from the user identity files by acquiring the user identity files input by each service subsystem, the target files are stored in the first server, the storage time of the target files in the first server is acquired, when the storage time reaches the preset time, the target files are migrated from the first server to the second server for storage, the target files are stored in the first server first, then the target files are stored in the second server, and the storage attributes of different servers are utilized, so that the storage space of the database server is saved, and the service performance of the database server is improved.
Drawings
FIG. 1 is a schematic diagram of an artificial intelligence based file storage device of a hardware runtime environment in accordance with an embodiment of the present invention;
FIG. 2 is a flow chart of a first embodiment of an artificial intelligence based file storage method of the present invention;
FIG. 3 is a flow chart of a second embodiment of an artificial intelligence based file storage method of the present invention;
FIG. 4 is a flow chart of a third embodiment of an artificial intelligence based file storage method of the present invention;
FIG. 5 is a block diagram of a first embodiment of an artificial intelligence based file storage device of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of an artificial intelligence-based file storage device in a hardware running environment according to an embodiment of the present invention.
As shown in fig. 1, the artificial intelligence based file storage device may include: a processor 1001, such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, a memory 1005. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WIreless-FIdelity (WI-FI) interface). The Memory 1005 may be a high-speed random access Memory (Random Access Memory, RAM) Memory or a stable nonvolatile Memory (NVM), such as a disk Memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
It will be appreciated by those skilled in the art that the architecture shown in FIG. 1 is not limiting and that artificial intelligence based file storage devices may include more or fewer components than illustrated, or may combine certain components, or a different arrangement of components.
As shown in fig. 1, an operating system, a network communication module, a user interface module, and an artificial intelligence-based file storage program may be included in the memory 1005 as one type of storage medium.
In the artificial intelligence based file storage device shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the file storage device based on the artificial intelligence of the present invention may be disposed in the file storage device based on the artificial intelligence, and the file storage device based on the artificial intelligence invokes the file storage program based on the artificial intelligence stored in the memory 1005 through the processor 1001, and executes the file storage method based on the artificial intelligence provided by the embodiment of the present invention.
The embodiment of the invention provides a file storage method based on artificial intelligence, and referring to fig. 2, fig. 2 is a flow chart of a first embodiment of the file storage method based on artificial intelligence.
In this embodiment, the file storage method based on artificial intelligence includes the following steps:
step S10: and acquiring a user identity file input by the service subsystem.
It should be noted that, the execution body of the embodiment may be an intelligent authentication platform, or may be other devices with the same or similar functions, and the implementation is not limited to this, and the intelligent authentication platform is taken as an example for explanation. In this embodiment, the intelligent authentication platform may receive the user identity file transmitted by the service subsystem, for example, the information such as the user identity card information and the user big-end photograph, and the intelligent authentication platform may also verify the user identity file transmitted by the service subsystem, and store the user identity file that passes the verification in the database server.
It should be noted that, the user may transact various insurance services through the service subsystem, for example, the user may transact insurance services such as property insurance, transportation insurance, and product liability insurance through the property service subsystem, or transact insurance services such as personal health insurance, personal accident injury insurance, and disease insurance through the personal insurance service subsystem, it is easy to understand that transacting insurance services needs to correspond to the user to ensure that transacted insurance services match with actual identity information of the user, so that user identity information needs to be authenticated when transacting various insurance services.
In a specific implementation, when a user handles insurance service through a service subsystem, the service subsystem collects a user identity file of the user who handles the service, and then inputs the obtained user identity file to an intelligent authentication platform so as to enable the intelligent authentication platform to verify the user identity. In this embodiment, a communication connection is established between the intelligent authentication platform and each service subsystem, the intelligent authentication platform obtains the user identity file input by each service subsystem through the established communication connection, and may obtain the user identity file input by each service subsystem from the network based on an internet mode, where the internet communication may use network communication protocols such as TCP/IP protocol, IPX/SPX protocol, netBEUI protocol, etc., and this embodiment is not limited thereto.
Step S20: and screening out target files from the user identity files.
In this embodiment, the user identity file is an important file in insurance business handling, and can be used for subsequent business tracing and legal disputes among the applicant, the insured, the insurer and the beneficiary, and the importance of the user identity file is considered, so after the identity files input by each business subsystem are acquired, the user identity file is usually saved in a server, and due to the limitation of factors such as server memory and authority, the user identity file meeting the conditions needs to be screened out from the user identity file before the user identity file is saved, namely, the target file.
In a specific implementation, the present embodiment may screen the target file from the user identity files according to the size of the user identity files, for example, obtain the byte number of the user identity files, compare the byte number with the preset byte number, use the user identity files with the byte number less than or equal to the preset number as the target file, for example, use the user identity files with the byte number less than or equal to 1000kb as the target file, and the preset number may be set to 1000kb, or may be set by itself according to the actual design requirement. Furthermore, the screening of the target file can be performed according to the file identification of the user identity file, and the user identity file meeting the preset identification is used as the target file.
Further, in order to make the screened target file more conform to the storage requirement of the server, the step S20 specifically includes: screening a user head portrait file from the user identity file according to the preset byte quantity; acquiring a service scene corresponding to the user head portrait file; and comparing the service scene with a preset service scene, and taking a user head image file conforming to the preset service scene as a target file.
It should be noted that, in this embodiment, the target files may be screened out from the user identity files according to the service scenario and byte number corresponding to the user identity files, the user identity files include various information related to the user identity, since the storage capacity of the server is limited, the user head portrait files in the user identity files are usually stored in the server, in this embodiment, the user head portrait files may be screened out through a preset number, further, considering that the user head portrait files of most service scenarios may be frequently queried and downloaded in a short time, in this embodiment, the user head portrait files which may be frequently queried and downloaded in a short time may be screened out through a preset service scenario, meanwhile, the target files need to conform to the preset number, the preset number may be set as the byte number of the general user head portrait files, for example, 1000kb, the preset service scenario may be set as a insurance service scenario, where the insurance service scenario includes property insurance service scenario and insurance service scenario, for facilitating understanding, for example, it is now assumed that the user identity files A, B and C need to be stored, the preset number is 1000kb, the user head portrait files may be frequently queried and downloaded in a short time, the user head portrait files may be screened out from the preset number corresponding to the user head portrait files a ' and the user head portrait files B ' and the personal traffic scenario B ' are respectively, and the user head portrait files may be a personal traffic scenario B ' and the personal traffic conditions may be assumed to be corresponding to the user head portrait files B ' and the user head portrait files are assumed to be a traffic condition, the traffic transportation insurance service and the health insurance service belong to insurance service, and it is seen that the user head portrait files A ' and B ' conform to preset service scenes, the user head portrait file C ' does not conform to the preset service scenes, and the target files are the user head portrait files A ' and B '.
It should be emphasized that, to further ensure the privacy and security of the user identity files and user avatar files, the user identity files and user avatar files may also be stored in a blockchain node.
Step S30: and storing the target file to a first server, and acquiring the storage time length of the target file in the first server.
It should be noted that, the target file is a user header file meeting the storage requirement of the server, after the target file is screened, the target file can be stored, and because the target file can be frequently queried and downloaded in a short time, a higher query efficiency is required to meet the traceability requirement of the user, and the higher the query downloading efficiency of the file is related to the downloading performance of the server storing the file, the higher the downloading performance of the server is, and it can be understood that in this embodiment, the first server is a server with a stronger downloading performance, for example, a network attached storage (NAS, networkAttachedStorage) server.
It should be noted that, the object file is stored in the first server to improve the query downloading efficiency of the user's avatar file in a short time, so that the user can conveniently trace back the object file, and the object file is stored in the first server for a short time, for example, a week, so that after the object file is stored in the first server, the storage duration of the object file in the first server needs to be detected.
In a specific implementation, when the target file is stored in the first server, the first server adds a corresponding time identifier to the target file, the current time of the target file can be obtained through real-time detection of the target file, then the initial time of the target file when the target file is stored in the first server can be determined according to the time identifier of the target file, and the storage time of the target file in the first server can be obtained according to the current time and the initial time.
It is easy to understand that the service flow of the service subsystem is different in different time periods, and the size of the file to be stored is also different, so that in order to enable the first server to meet the storage requirement, in this embodiment, the storage space of the first server may be adjusted correspondingly according to the service flow of the service subsystem, and specifically, before step S30, the method further includes: acquiring historical service flow of the service subsystem; determining the peak flow of the service subsystem in a preset period according to the historical service flow; and comparing the peak flow with a preset flow, and changing the initial storage space of the first server into a target storage space according to a comparison result.
It should be noted that, the service flow of each time of day of the service subsystem has a corresponding record, and the historical service flow of the service system can be obtained from the service processing log of the service subsystem, where the historical service flow not only includes a specific service flow, but also has a corresponding time identifier, according to which the peak flow of the service subsystem in a preset period can be obtained, the preset time can be set to the morning of monday, or the peak period of the marketing activity day can be set to other periods according to the actual situation, and the service flow in the preset period is far greater than the service flow in other periods, so that the storage space required in the preset period is also the largest, i.e. the storage space corresponding to the peak flow. After determining the peak flow, the peak flow needs to be compared with a preset flow, the preset flow is the service flow of the service subsystem in most of time, the size of the preset flow can be determined according to the service handling condition of the service subsystem based on a big data technology, of course, the preset flow can also be set according to the needs, in this embodiment, the peak flow is compared with the preset flow to determine the multiple relation between the peak flow and the preset flow, that is, how many times the peak flow is the preset flow, then the initial storage space of the first server is changed into the target storage space according to the multiple, the initial storage space is the storage space required when the service flow is the preset flow, the target storage space is the storage space required when the service flow is the peak flow, for example, if the peak flow A is 5 times the preset flow B, the initial storage space X of the first server is changed into 5X, and 5X is the target storage space required by the peak flow A.
Step S40: and when the storage time length reaches a preset time length, migrating the target file from the first server to a second server for storage.
It should be noted that, when the target file is used for short-term tracing, after a certain period of time is exceeded, the target file is not generally queried and downloaded any more, if the target file is continuously stored in the first server, the storage capacity of the first server is wasted, and the storage capacity of the first server with stronger downloading performance is generally smaller, which is not suitable for mass storage. The preset time length can be set to one week or other time lengths, the preset time length is not limited in this embodiment, the preset time length indicates the maximum time length that the target file can be queried and downloaded in the first server, the downloading performance of the second server is far greater than that of the first server although the downloading performance of the second server is weaker than that of the first server, the fact that the storage capacity of the second server is far greater than that of the first server exceeds the preset time length indicates that the user can not query and download the target file any more, and in order to save the storage space of the first server, the target file is migrated from the first server to the second server when the storage time length reaches the preset time length, and the second server is used for storing the target file for a long time.
According to the embodiment, the target files are screened from the user identity files by acquiring the user identity files input by each service subsystem, the target files are stored in the first server, the storage time of the target files in the first server is acquired, when the storage time reaches the preset time, the target files are migrated from the first server to the second server for storage, the target files are stored in the first server first, then the target files are stored in the second server, and the storage attributes of different servers are utilized, so that the storage space of the database server is saved, and the service performance of the database server is improved.
Referring to fig. 3, fig. 3 is a flowchart illustrating a second embodiment of an artificial intelligence-based file storage method according to the present invention.
Based on the first embodiment, the step S30 in this embodiment specifically includes:
step S301: and establishing network connection with the first server based on the preset interface.
It should be noted that, the target file is a file that can be frequently downloaded in a short period, and a server with higher downloading performance is required to improve the downloading efficiency of the target file. Before storing the target file in the first server, a network connection needs to be established with the first server, in this embodiment, the network is established with the first server through a preset interface, and the preset interface may be set as an optical fiber communication interface or may be set as an interface in another form, which is not limited in this embodiment.
Step S302: and acquiring a target address and an operation parameter corresponding to the first server.
It should be noted that, in this embodiment, the target file is stored in the first server through network connection, after the network connection is established with the first server, the target address corresponding to the first server may be obtained, where the target address is a network address, including an IP address, an MAC address, and the like, and in addition to the need of obtaining the target address of the first server, the operation parameters of the first server need to be obtained, where the operation parameters in this embodiment include, but are not limited to, parameters such as a network structure, a disk channel, and a storage space
Step S303: and determining a disk array corresponding to the first server according to the operation parameters.
It is easy to understand that the disk array is a storage unit in the first server for storing files, and based on the operation parameters of the first server, the disk array of the first server may be determined, for example, the specific structure of the corresponding disk array is determined according to the disk channels and the arrangement manner in the operation parameters.
Step S304: and writing the target file into the disk array through the network connection according to the target address.
In an implementation, after determining the target address
The step S30 in this embodiment further includes:
step S305: and acquiring the initial time when the target file is stored in the first server.
It can be appreciated that, since the target file is stored in the first server for a short period of time, in order to be able to migrate the target file from the first server to the second server in time, it is necessary to detect the storage duration of the target file in the first server in real time. In this embodiment, the storage duration of the target file is determined according to the initial time and the current time, where the initial time is the time when the target file is first stored in the first server.
Step S306: and detecting the current time mark of the target file in the first server in real time.
It should be noted that, after the target file is stored in the first server, the first server adds a corresponding time identifier for the stored target file, and as time changes, the first server also updates a time corresponding to the time identifier in real time, for example, after the target file is stored in the first server, the first server adds a current time identifier T for the target file, records the time at this time as X, and after a period of time, the first server updates the time X corresponding to the current time identifier M as the current time Y.
Step S307: and determining the current moment corresponding to the target file according to the current time identifier.
It will be appreciated that the current time identifier corresponds to the stored time of the target file, and the current time corresponding to the target file may be determined based on the current time identifier, for example, according to the current time identifier M 1 The current time of the target file can be determined to be T 1 Again assume that the current time is identified as M 2 The current time of the target file can be determined to be T 2 。
Step S308: and determining the storage time length of the target file in the first server according to the initial time and the current time.
It should be noted that, after the initial time and the current time are obtained, the storage duration of the target file in the first server may be determined by subtracting the initial time from the current time, for example, assuming that the initial time is T 3 At the current moment T 4 The storage duration of the target file in the first server is T 4 -T 3 。
According to the embodiment, the initial time when the target file is stored in the first server is obtained; detecting the current time mark of the target file in the first server in real time; determining the current moment corresponding to the target file according to the current time identifier; and determining the storage time length of the target file in the first server according to the initial time and the current time, and timely transferring the target file out of the first server by determining the storage time length of the target file in the first server according to the initial time and the current time, so that the waste of storage space is avoided.
Referring to fig. 4, fig. 4 is a flowchart illustrating a third embodiment of an artificial intelligence-based file storage method according to the present invention.
Based on the first embodiment or the second embodiment, a third embodiment of the file storage method based on artificial intelligence according to the present invention is presented.
Taking the first embodiment as an example, the step S40 in this embodiment includes:
step S401: and downloading the target file from the first server to the object storage device of the second server.
It should be noted that, the first server is configured to store the target file in a short period, while the second server has a relatively poor downloading performance, but has a relatively large storage space, so that the second server is suitable for storing the target file migrated from the first server in an idle state.
Step S402: and establishing a storage object in the object storage equipment according to the preset storage attribute.
It should be noted that, the storage object is a storage unit in the object storage device, and is used for storing the target file, where the storage object has a corresponding storage attribute, and the storage attribute includes, but is not limited to, a storage structure, a storage protocol, and other attributes, and the storage attribute may be preset according to an actual situation, which is not limited in this embodiment.
Step S403: and storing the target file through the storage object.
It should be noted that, according to the different attributes such as the size of the target file, the storage objects with different attributes are allocated, and then the target file is stored into the corresponding storage object, so that the storage of the target file can be completed.
Further, in this embodiment, after the step S40, the method further includes: acquiring abstract information corresponding to the stored target file; inquiring a storage path corresponding to the target file in the first server or the second server according to the file identifier corresponding to the abstract information; and calling the target file from the first server or the second server according to the storage path.
It can be understood that the server is not only used for storing, but also can provide query service, after the target file is stored in the first server or the second server, the first server and the second server can add corresponding file identifications for the target file, the basis for adding the file identifications is summary information of the target file, the summary information comprises information such as user names and user identification numbers, in order to avoid confusion of information storage, the first server and the second server set different storage paths for the target files of different users, and set corresponding relations between the storage paths and the file identifications, so that after the file identifications are determined, the corresponding target file can be searched through the storage paths corresponding to the file identifications.
In the embodiment, the target file is downloaded from the first server to the object storage device of the second server; establishing a storage object in the object storage equipment according to a preset storage attribute; the target file is stored through the storage object, and in the embodiment, the target file transferred from the first server is stored in the second server for a long time, so that the performance of the first server is prevented from being reduced due to the fact that the stored target file occupies too large storage space, and the performance of the server is improved.
In addition, the embodiment of the invention also provides a storage medium, wherein the storage medium is stored with an artificial intelligence-based file storage program, and the artificial intelligence-based file storage program realizes the steps of the artificial intelligence-based file storage method when being executed by a processor.
Because the storage medium adopts all the technical schemes of all the embodiments, the storage medium has at least all the beneficial effects brought by the technical schemes of the embodiments, and the description is omitted here.
Referring to FIG. 5, FIG. 5 is a block diagram illustrating a first embodiment of an artificial intelligence based file storage device according to the present invention.
As shown in fig. 5, an artificial intelligence-based file storage device according to an embodiment of the present invention includes:
the acquisition module 10 is used for acquiring the user identity file input by the service subsystem;
a screening module 20, configured to screen a target file from the user identity files;
the storage module 30 is configured to store the target file to a first server, and obtain a storage duration of the target file in the first server;
and the transferring module 40 is configured to transfer the target file from the first server to the second server for storage when the storage duration reaches a preset duration.
According to the embodiment, the target files are screened from the user identity files by acquiring the user identity files input by each service subsystem, the target files are stored in the first server, the storage time of the target files in the first server is acquired, when the storage time reaches the preset time, the target files are migrated from the first server to the second server for storage, the target files are stored in the first server first, then the target files are stored in the second server, and the storage attributes of different servers are utilized, so that the storage space of the database server is saved, and the service performance of the database server is improved.
In an embodiment, the filtering module 20 is further configured to filter a user avatar file from the user identity files according to a preset number of bytes; acquiring a service scene corresponding to the user head portrait file; and comparing the service scene with a preset service scene, and taking a user head image file conforming to the preset service scene as a target file.
In one embodiment, the artificial intelligence based file storage device further comprises: a change module;
the change module is used for acquiring the historical service flow of the service subsystem; determining the peak flow of the service subsystem in a preset period according to the historical service flow; and comparing the peak flow with a preset flow, and changing the initial storage space of the first server into a target storage space according to a comparison result.
In an embodiment, the storage module 30 is further configured to establish a network connection with the first server based on a preset interface; acquiring a target address and an operation parameter corresponding to the first server; determining a disk array corresponding to the first server according to the operation parameters; and writing the target file into the disk array through the network connection according to the target address.
In an embodiment, the storage module 30 is further configured to obtain an initial time when the target file is stored in the first server; detecting the current time mark of the target file in the first server in real time; determining the current moment corresponding to the target file according to the current time identifier; and determining the storage time length of the target file in the first server according to the initial time and the current time.
In an embodiment, the transferring module 40 is further configured to download, from the first server, the target file to an object storage device of a second server; establishing a storage object in the object storage equipment according to a preset storage attribute; and storing the target file through the storage object.
In one embodiment, the artificial intelligence based file storage device further comprises: a query module;
the query module is used for acquiring abstract information corresponding to the stored target file; inquiring a storage path corresponding to the target file in the first server or the second server according to the file identifier corresponding to the abstract information; and calling the target file from the first server or the second server according to the storage path.
It should be understood that the foregoing is illustrative only and is not limiting, and that in specific applications, those skilled in the art may set the invention as desired, and the invention is not limited thereto.
It should be noted that the above-described working procedure is merely illustrative, and does not limit the scope of the present invention, and in practical application, a person skilled in the art may select part or all of them according to actual needs to achieve the purpose of the embodiment, which is not limited herein.
In addition, technical details not described in detail in this embodiment may refer to the file storage method based on artificial intelligence provided in any embodiment of the present invention, which is not described herein.
Furthermore, it should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system 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 system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. Read Only Memory)/RAM, magnetic disk, optical disk) and including several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm and the like. The Blockchain (Blockchain), which is essentially a decentralised database, is a string of data blocks that are generated by cryptographic means in association, each data block containing a batch of information of network transactions for verifying the validity of the information (anti-counterfeiting) and generating the next block. The blockchain may include a blockchain underlying platform, a platform product services layer, an application services layer, and the like.
Claims (5)
1. The file storage method based on the artificial intelligence is characterized by comprising the following steps of:
acquiring a user identity file input by a service subsystem;
screening out a target file from the user identity file;
storing the target file to a first server, and acquiring the storage time length of the target file in the first server;
when the storage time length reaches a preset time length, the target file is migrated from the first server to a second server for storage;
screening the target file from the user identity file, including:
screening a user head portrait file from the user identity file according to the preset byte quantity;
acquiring a service scene corresponding to the user head portrait file;
comparing the service scene with a preset service scene, and taking a user head portrait file conforming to the preset service scene as a target file, wherein the user identity file and the user head portrait file are stored in a block chain;
before the target file is stored in the first server, the method further comprises:
acquiring historical service flow of the service subsystem;
determining the peak flow of the service subsystem in a preset period according to the historical service flow;
comparing the peak flow with a preset flow, and changing the initial storage space of the first server into a target storage space according to a comparison result;
the storing the target file to the first server includes:
establishing network connection with a first server based on a preset interface;
acquiring a target address and an operation parameter corresponding to the first server;
determining a disk array corresponding to the first server according to the operation parameters;
writing the target file into the disk array through the network connection according to the target address;
the obtaining the storage duration of the target file in the first server includes:
acquiring an initial time when a target file is stored in the first server;
detecting the current time mark of the target file in the first server in real time;
determining the current moment corresponding to the target file according to the current time identifier;
determining the storage time length of the target file in the first server according to the initial time and the current time;
the migration of the target file from the first server to a second server for storage includes:
downloading the target file from the first server to an object storage device of a second server;
establishing a storage object in the object storage equipment according to a preset storage attribute;
and storing the target file through the storage object.
2. The artificial intelligence based file storage method of claim 1, wherein after the migration of the target file from the first server to a second server for storage, further comprising:
acquiring abstract information corresponding to the stored target file;
inquiring a storage path corresponding to the target file in the first server or the second server according to the file identifier corresponding to the abstract information;
and calling the target file from the first server or the second server according to the storage path.
3. An artificial intelligence based file storage device, the artificial intelligence based file storage device comprising:
the acquisition module is used for acquiring the user identity file input by the service subsystem;
the screening module is used for screening out target files from the user identity files;
the storage module is used for storing the target file to a first server and acquiring the storage time length of the target file in the first server;
the transfer module is used for transferring the target file from the first server to a second server for storage when the storage duration reaches a preset duration;
the screening module is further used for screening user head portrait files from the user identity files according to the preset byte quantity; acquiring a service scene corresponding to the user head portrait file; comparing the service scene with a preset service scene, and taking a user head portrait file conforming to the preset service scene as a target file, wherein the user identity file and the user head portrait file are stored in a block chain;
the storage module is also used for acquiring the historical service flow of the service subsystem; determining the peak flow of the service subsystem in a preset period according to the historical service flow; comparing the peak flow with a preset flow, and changing the initial storage space of the first server into a target storage space according to a comparison result;
the storage module is further used for establishing network connection with the first server based on a preset interface; acquiring a target address and an operation parameter corresponding to the first server; determining a disk array corresponding to the first server according to the operation parameters; writing the target file into the disk array through the network connection according to the target address;
the storage module is further used for acquiring the initial time when the target file is stored in the first server; detecting the current time mark of the target file in the first server in real time; determining the current moment corresponding to the target file according to the current time identifier; determining the storage time length of the target file in the first server according to the initial time and the current time;
the transfer module is further used for downloading the target file from the first server to the object storage device of the second server; establishing a storage object in the object storage equipment according to a preset storage attribute; and storing the target file through the storage object.
4. An artificial intelligence based file storage device, the artificial intelligence based file storage device comprising: a memory, a processor, and an artificial intelligence based file storage program stored on the memory and executable on the processor, the artificial intelligence based file storage program configured to implement the steps of the artificial intelligence based file storage method of any one of claims 1 or 2.
5. A storage medium having stored thereon an artificial intelligence based file storage program which when executed by a processor performs the steps of the artificial intelligence based file storage method of any of claims 1 or 2.
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