WO2021189902A1 - 基于云存储的数据存储方法、装置、计算机设备及存储介质 - Google Patents

基于云存储的数据存储方法、装置、计算机设备及存储介质 Download PDF

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Publication number
WO2021189902A1
WO2021189902A1 PCT/CN2020/131981 CN2020131981W WO2021189902A1 WO 2021189902 A1 WO2021189902 A1 WO 2021189902A1 CN 2020131981 W CN2020131981 W CN 2020131981W WO 2021189902 A1 WO2021189902 A1 WO 2021189902A1
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files
data
storage
backed
fragment
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PCT/CN2020/131981
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English (en)
French (fr)
Inventor
兰东平
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平安科技（深圳）有限公司
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Publication of WO2021189902A1 publication Critical patent/WO2021189902A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
    • G06F11/14—Error detection or correction of the data by redundancy in operation
    • G06F11/1402—Saving, restoring, recovering or retrying
    • G06F11/1446—Point-in-time backing up or restoration of persistent data
    • G06F11/1448—Management of the data involved in backup or backup restore
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor

Definitions

  • This application relates to cloud technology, and in particular to a data storage method, device, computer equipment, and storage medium based on cloud storage.
  • hybrid cloud gateway products With the development of cloud computing, more and more users store data in hybrid clouds to achieve the effect of remote disaster recovery. Among them, the most common is to use hybrid cloud gateway products to achieve data storage and replication. In related technologies, hybrid cloud gateway products generally adopt the "local database + public cloud" model, that is, only the local database stores a copy of the original data, and the public cloud mirrors and stores a copy of the backup data.
  • the inventor realizes that although the data disaster recovery backup is realized in this way, a complete backup data is stored in the public cloud. Once the original data and the backup data are damaged, the data cannot be restored.
  • a data storage method based on cloud storage comprising:
  • n is a positive integer greater than or equal to 2;
  • the n fragment files and the m check files are stored in the first storage mode or the first storage mode.
  • Two storage mode storage where the first storage mode is: store the n fragment files in a local database, and store the m verification files in a cloud database, and the second storage mode is: store all The n fragment files and the m verification files are stored in at least two cloud databases.
  • a data storage device based on cloud storage comprising:
  • Splitting module used to split the data to be backed up into n sliced files, where n is a positive integer greater than or equal to 2;
  • Generation module used to generate m verification files according to the n fragment files, where m is a positive integer
  • the n fragment files and the m check files are stored as the first Storage mode or second storage mode, where the first storage mode is: storing the n fragment files in a local database, and storing the m verification files in a cloud database, and the second storage mode is : Store the n fragment files and the m verification files in at least two cloud databases.
  • a computer device includes:
  • At least one processor and,
  • a memory communicatively connected with the at least one processor; wherein,
  • the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can execute the following steps:
  • n is a positive integer greater than or equal to 2;
  • the n fragment files and the m check files are stored in the first storage mode or the first storage mode.
  • Two storage mode storage where the first storage mode is: store the n fragment files in a local database, and store the m verification files in a cloud database, and the second storage mode is: store all The n fragment files and the m verification files are stored in at least two cloud databases.
  • a computer-readable storage medium includes a storage data area and a storage program area, the storage data area stores data created according to the use of a blockchain node, and the storage program area stores a data storage program, When the data storage program is executed by the processor, the following steps are implemented:
  • n is a positive integer greater than or equal to 2;
  • the n fragment files and the m check files are stored in the first storage mode or the first storage mode.
  • Two storage mode storage where the first storage mode is: store the n fragment files in a local database, and store the m verification files in a cloud database, and the second storage mode is: store all The n fragment files and the m verification files are stored in at least two cloud databases.
  • This application implements data disaster recovery backup. Even if both the fragment file and the check file are damaged, as long as the sum of the two damaged quantities is less than or equal to m, the data can still be restored.
  • Figure 1 is a schematic diagram of a preferred embodiment of the computer equipment of this application.
  • FIG. 2 is a schematic diagram of modules of a preferred embodiment of the cloud storage-based data storage device in FIG. 1;
  • FIG. 3 is a flowchart of a preferred embodiment of a data storage method based on cloud storage according to this application;
  • FIG. 1 it is a schematic diagram of a preferred embodiment of the computer device 1 of this application.
  • the computer device 1 includes, but is not limited to: a memory 11, a processor 12, a display 13, and a network interface 14.
  • the computer device 1 is connected to the network through the network interface 14 to obtain original data.
  • the network may be an intranet (Intranet), the Internet (Internet), a global mobile communication system (Global System of Mobile communication, GSM), Wideband Code Division Multiple Access (WCDMA), 4G network, 5G network, Bluetooth (Bluetooth), Wi-Fi, call network and other wireless or wired networks.
  • the memory 11 includes at least one type of readable storage medium
  • the readable storage medium includes flash memory, hard disk, multimedia card, card type memory (for example, SD or DX memory, etc.), random access memory (RAM), static Random access memory (SRAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), programmable read only memory (PROM), magnetic memory, magnetic disks, optical disks, etc.
  • the memory 11 may be an internal storage unit of the computer device 1, for example, a hard disk or a memory of the computer device 1.
  • the memory 11 may also be an external storage device of the computer device 1, such as a plug-in hard disk equipped with the computer device 1, a smart memory card (Smart Media Card, SMC), Secure Digital (SD) card, Flash Card, etc.
  • the memory 11 may also include both the internal storage unit of the computer device 1 and its external storage device.
  • the memory 11 is generally used to store the operating system and various application software installed in the computer device 1, for example, the program code of the data storage program 10, and so on.
  • the memory 11 can also be used to temporarily store various types of data that have been output or will be output.
  • the processor 12 may be a central processing unit (Central Processing Unit) in some embodiments. Processing Unit, CPU), controller, microcontroller, microprocessor, or other data processing chip.
  • the processor 12 is generally used to control the overall operation of the computer device 1, such as performing data interaction or communication-related control and processing.
  • the processor 12 is configured to run the program code or process data stored in the memory 11, for example, run the program code of the data storage program 10, and so on.
  • the display 13 may be referred to as a display screen or a display unit.
  • the display 13 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an organic light-emitting diode (Organic Light Emitting Diode). Light-Emitting Diode, OLED) touch device, etc.
  • the display 13 is used for displaying the information processed in the computer device 1 and for displaying a visualized work interface, for example, displaying the results of data statistics.
  • the network interface 14 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface).
  • the network interface 14 is generally used to establish a communication connection between the computer device 1 and other computer devices.
  • Figure 1 only shows a computer device 1 and a cloud database 2 with components 11-14 and a data storage program 10, but it should be understood that it is not required to implement all the components shown, and more or less may be implemented instead. s component.
  • the computer device 1 may further include a user interface.
  • the user interface may include a display (Display) and an input unit such as a keyboard (Keyboard).
  • the optional user interface may also include a standard wired interface and a wireless interface.
  • the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an organic light-emitting diode (Organic Light-Emitting Diode, OLED) touch device, etc.
  • the display can also be called a display screen or a display unit as appropriate, and is used to display the information processed in the computer device 1 and to display a visualized user interface.
  • the computer equipment 1 may also include a radio frequency (Radio Frequency, RF) circuits, sensors and audio circuits, etc., will not be repeated here.
  • RF Radio Frequency
  • n is a positive integer greater than or equal to 2;
  • the n fragment files and the m check files are stored in the first storage mode or the first storage mode.
  • Two storage mode storage where the first storage mode is: store the n fragment files in a local database, and store the m verification files in the cloud database 2, and the second storage mode is:
  • the n fragment files and the m verification files are stored in at least two cloud databases 2.
  • FIG. 2 the functional module diagram of the data storage device 100 based on cloud storage of this application is shown.
  • the cloud storage-based data storage device 100 described in this application can be installed in a computer device.
  • the cloud storage-based data storage device 100 may include a segmentation module 110, a generation module 120, and a storage module 130.
  • the module described in the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of a computer device and can complete fixed functions, and are stored in the memory of the computer device.
  • each module/unit is as follows:
  • the segmentation module 110 is configured to segment the data to be backed up into n segment files, where n is a positive integer greater than or equal to 2.
  • a data slicing algorithm is used to divide the data to be backed up into n sliced files.
  • the data slicing algorithm is, for example, a hash algorithm, a modulo algorithm, and an interval range algorithm.
  • n is a positive integer greater than or equal to 2, such as 2, 3, 4, and so on.
  • each fragment file divided from the data to be backed up is the same.
  • the size of the data to be backed up is 100k
  • the data to be backed up is divided into two fragment files, and the sizes of the two fragment files are equal. For 50k.
  • the generating module 120 is configured to generate m verification files according to the n fragment files, and m is a positive integer.
  • the erasure code can be used to generate m check files based on n fragment files.
  • Erasure code is an encoding technology that can add m parity files to n fragment files, and can pass n+m fragment files and any n fragment files in the parity file and/or Verify the file and restore it to the data to be backed up. That is, if any fragment file and/or check file less than or equal to m fails, the backup data can still be restored through at least n fragment files and/or check files that have not expired.
  • m is a positive integer, such as 1, 2, 3, 4, etc.
  • n and m are independent of each other. For example, when n is 5, m is 2; or, when n is 2, m is 5.
  • each generated check file is the same as the size of each fragment file, and the m is smaller than the n.
  • n is 2
  • m is 1
  • the size of the data to be backed up is 100k.
  • the two fragment files stored in the same local database are equivalent to the original data to be backed up.
  • the size of the two fragment files is 100k.
  • the file size is 50k
  • the total size of the fragment file and the check file is 150k; according to the mirror backup scheme in the prior art, the original data to be backed up is 100k, the backup data is 100k, and the total storage size is 200k.
  • the storage size of the technical solution of the present application is 0.75 times that of the prior art, which reduces the storage cost.
  • the fragment file and the check file can also be combined in other ways, such as 5 fragment files and 2 check files, the size of the data to be backed up is 100k, and the size of each fragment file is 20k at this time.
  • the size of each check file is 20k, and the total size of the fragment file and check file is 140k, which can also reduce storage costs. Users can set the number of fragment files and check files according to actual needs. In this way, compared to a solution in which a local database stores a copy of original data and a mirror image stores a copy of backup data on the public cloud, the technical solution of the present application occupies a smaller storage space and has a lower storage cost.
  • the storage module 130 is configured to, according to the access frequency of the data to be backed up, the generation time of the data to be backed up, and the current time of the computer device, divide the n fragment files and the m check files into the first Storage mode or second storage mode, wherein the first storage mode is: storing the n fragment files in a local database, storing the m verification files in the cloud database 2, and the second storage The mode is: storing the n fragment files and the m verification files in at least two cloud databases 2.
  • the access frequency of the data to be backed up, the generation time of the data to be backed up, and the current time of the computer device are acquired, based on the access frequency of the data to be backed up, the generation time of the data to be backed up, and The current time of the computer equipment can be used to determine the degree of hot or cold of the data to be backed up. According to the degree of coldness and heat of the data to be backed up, the n fragment files and the m verification files are stored in the first storage mode or the second storage mode.
  • the difference between the generation time of the data to be backed up and the current time of the computer device is calculated.
  • the difference is less than or equal to the preset value, or the difference is greater than the preset value but the access frequency of the data to be backed up is greater than the preset frequency, it indicates that the data to be backed up is hot, and the data to be backed up
  • the access frequency of the data to be backed up may be the average access frequency since the data to be backed up is generated, or it may be the number of accesses within a unit time closest to the current time of the computer device.
  • the generation time of the data to be backed up is April 1, 2020, and the current time of the computer equipment is April 3, 2020, the difference between the two is 2 days, the difference is If it is less than the preset value, the n fragment files and the m verification files are stored according to the first storage mode.
  • the default value is set to 10 days
  • the generation time of the data to be backed up is April 1, 2020
  • the current time of the computer equipment is April 15, 2020
  • the difference between the two is 14 days, which is the difference
  • the value is greater than the preset value; the preset frequency is 2 times a month, and the access frequency of the data to be backed up is 3 times a month.
  • Storage mode storage is
  • the difference is greater than the preset value and/or the access frequency of the data to be backed up is less than or equal to the preset frequency, it indicates that the popularity of the data to be backed up is low, and the possibility that the data to be backed up will be accessed in the future is low , Storing the n fragment files and the m verification files according to the second storage mode.
  • the generation time of the data to be backed up is April 1, 2020, and the current time of the computer device is April 15, 2020, the difference between the two is 14 days, the difference is Greater than the preset value; the preset frequency is twice a month, the access frequency of the data to be backed up is once a month, and the access frequency is less than the preset frequency, then the n fragmented files and the m calibration
  • the verification file is stored in the second storage mode.
  • the first storage mode is: storing the n fragment files in a local database, and storing the m verification files in the cloud database 2.
  • storing all the fragmented files in the same local database is equivalent to storing a complete copy of data to be backed up in a local database. In this way, all the fragmented files are stored in the same local database, and the data read response time is faster, which is conducive to timely reading.
  • the number of verification files stored in any one of the cloud databases 2 is less than n, so as to reduce the risk of data leakage to be backed up. For example, when n is 3 and m is 4, two of the verification files are stored in one cloud database 2 and the remaining two verification files are stored in another cloud database 2.
  • the second storage mode is: storing the n fragment files and the m verification files in at least two cloud databases 2.
  • the cloud database 2 is used to store all the fragment files and verification files, and the storage cost is lower.
  • the second storage mode is: storing the n fragment files and the m verification files in at least three cloud databases 2, and any fragment file and/or collation stored in the cloud database 2
  • the number of verification files is less than n.
  • the cloud database 2 storing fragment files and the verification file the sum of the number of stored fragment files and the verification file is less than n; for the cloud database 2 storing only fragment files, Then the number of stored fragment files is less than n; for the cloud database 2 that only stores verification files, the number of stored verification files is less than n.
  • n is 3 and m is 2
  • three cloud databases 2 are used for storage.
  • one of the shard files and one of the verification files are stored in one cloud database 2, and the other shard file And another verification file are stored in another cloud database 2, and the remaining fragment file is stored in the remaining cloud database 2.
  • two verification files are stored in one cloud database 2
  • two of the fragment files are stored in another cloud database 2
  • the remaining one fragment file is stored in the remaining cloud database 2.
  • each of the fragment files and each of the verification files are stored in a different cloud database 2 respectively. In this way, the effect of remote disaster recovery is improved.
  • the access frequency of the n fragment files is determined every preset cycle time Whether it is less than or equal to the preset frequency, and when the judgment result is that the access frequency of the n fragmented files is less than or equal to the preset frequency, transfer the n fragmented files from the local database to the preset frequency.
  • the cloud database 2 is stored.
  • the judgment result is that the access frequency of the n fragment files is greater than the preset frequency, the n fragment files continue to be stored in the local database.
  • access to fragmented files is to restore the backup data.
  • access to n fragmented files using erasure codes, can restore the said fragments based on n fragmented files Data to be backed up.
  • the access frequency of the fragmented file is less than or equal to the preset frequency, indicating that the possibility that the fragmented file will be restored to the data to be backed up in the future is low; the n fragmented files are transferred from the local database to the cloud Database 2 is stored, reducing storage costs.
  • the access frequency of the n fragmented files may be the access frequency of using the fragmented file to restore the backup data since the fragmented file was generated, or it may be the use of fragments within the unit time closest to the current time of the computer device
  • the number of times the file is restored with the backup data may also be a frequency further calculated in combination with the access frequency of the data to be backed up.
  • n fragmented files After transferring n fragmented files from the local database to the cloud database 2 for storage, obtain the access frequency of the fragmented file and/or the verification file, and determine the access frequency of the fragmented file and/or the verification file Whether it is greater than the preset frequency, when the judgment result is yes, transfer the n fragment files from the cloud database 2 to the local database for storage; when the judgment result is no, continue the n fragment files Stored in cloud database 2.
  • access to fragmented files and/or check files is to restore the backup data.
  • the data to be backed up needs to be restored, at least n fragmented files and/or check files are accessed, and the correct By deleting the code, the data to be backed up can be restored based on at least n fragment files and/or check files.
  • the access frequency of the fragment file and/or the check file is greater than the preset frequency, indicating that the fragment file and/or the check file are more likely to be restored to the data to be backed up in the future;
  • the slice files are transferred from the cloud database 2 to the local database for storage, which facilitates the user to quickly restore the original data to be backed up through the slice files in the local database.
  • the access frequency of the fragment file and/or the check file may be the frequency of using the fragment file and/or the check file to restore the backup data since the fragment file and/or the check file was generated, or It is the number of times of recovering the backed-up data using the fragmented file and/or the check file in the unit time closest to the current time of the computer device, and may also be the frequency further calculated in combination with the access frequency of the data to be backed up.
  • the access frequency of the fragment files and/or check files is obtained.
  • the fragment files and/or check files are When the access frequency is greater than the preset frequency, the n fragment files are transferred from the cloud database 2 to a local database for storage.
  • the access frequency of the fragment file and/or the verification file is less than or equal to the preset frequency, the fragment file and the verification file are continuously stored in the cloud database 2.
  • the access frequency of the n fragment files is obtained, and it is determined whether the access frequency of the n fragment files is greater than the predetermined Suppose the frequency, when the judgment result is yes, continue to store the n fragment files in the local database; when the judgment result is no, transfer the n fragment files from the local database to the cloud database 2 for storage .
  • the cloud storage-based data storage device proposed in this application divides the data to be backed up into n fragment files, generates m check files according to the n fragment files, and according to the access frequency of the data to be backed up and the data to be backed up.
  • a cloud database 2 realizes data disaster recovery and backup. Even if both the fragment file and the check file are damaged, as long as the sum of the two damaged quantities is less than or equal to m, the data can still be recovered.
  • this application also provides a data storage method based on cloud storage, which is applied to computer equipment.
  • FIG. 3 is a schematic diagram of a method flow of an embodiment of a data storage method based on cloud storage of this application.
  • the processor 12 of the computer device 1 executes the data storage program 10 stored in the memory 11, the following steps of the cloud storage-based data storage method are implemented:
  • Step S10 Divide the data to be backed up into n fragmented files, where n is a positive integer greater than or equal to 2.
  • a data slicing algorithm is used to divide the data to be backed up into n sliced files.
  • the data slicing algorithm is, for example, a hash algorithm, a modulo algorithm, and an interval range algorithm.
  • n is a positive integer greater than or equal to 2, such as 2, 3, 4, and so on.
  • each fragment file divided from the data to be backed up is the same.
  • the size of the data to be backed up is 100k
  • the data to be backed up is divided into two fragment files, and the sizes of the two fragment files are equal. For 50k.
  • Step S20 Generate m verification files according to the n fragment files, and m is a positive integer.
  • the erasure code can be used to generate m check files based on n fragment files.
  • Erasure code is an encoding technology that can add m parity files to n fragment files, and can pass n+m fragment files and any n fragment files in the parity file and/or Verify the file and restore it to the data to be backed up. That is, if any fragment file and/or check file less than or equal to m fails, the backup data can still be restored through at least n fragment files and/or check files that have not expired.
  • m is a positive integer, such as 1, 2, 3, 4, etc.
  • n and m are independent of each other. For example, when n is 5, m is 2; or, when n is 2, m is 5.
  • each generated check file is the same as the size of each fragment file, and the m is smaller than the n.
  • n is 2
  • m is 1
  • the size of the data to be backed up is 100k.
  • the two fragment files stored in the same local database are equivalent to the original data to be backed up.
  • the size of the two fragment files is 100k.
  • the file size is 50k
  • the total size of the fragment file and the check file is 150k; according to the mirror backup scheme in the prior art, the original data to be backed up is 100k, the backup data is 100k, and the total storage size is 200k.
  • the storage size of the technical solution of the present application is 0.75 times that of the prior art, which reduces the storage cost.
  • the fragment file and the check file can also be combined in other ways, such as 5 fragment files and 2 check files, the size of the data to be backed up is 100k, and the size of each fragment file is 20k at this time.
  • the size of each check file is 20k, and the total size of the fragment file and check file is 140k, which can also reduce storage costs. Users can set the number of fragment files and check files according to actual needs. In this way, compared to a solution in which a local database stores a copy of original data and a mirror image stores a copy of backup data on the public cloud, the technical solution of the present application occupies a smaller storage space and has a lower storage cost.
  • Step S30 According to the access frequency of the data to be backed up, the generation time of the data to be backed up, and the current time of the computer device, the n fragment files and the m check files are stored in the first storage mode or The second storage mode storage, wherein the first storage mode is: store the n fragment files in a local database, and store the m verification files in the cloud database 2, and the second storage mode is: The n fragment files and the m verification files are stored in at least two cloud databases 2.
  • the access frequency of the data to be backed up, the generation time of the data to be backed up, and the current time of the computer device are acquired, based on the access frequency of the data to be backed up, the generation time of the data to be backed up, and The current time of the computer equipment can be used to determine the degree of hot or cold of the data to be backed up. According to the degree of coldness and heat of the data to be backed up, the n fragment files and the m verification files are stored in the first storage mode or the second storage mode.
  • the difference between the generation time of the data to be backed up and the current time of the computer device is calculated.
  • the difference is less than or equal to the preset value, or the difference is greater than the preset value but the access frequency of the data to be backed up is greater than the preset frequency, it indicates that the data to be backed up is hot, and the data to be backed up
  • the access frequency of the data to be backed up can be the average access frequency since the data to be backed up is generated, or it can be the number of accesses within a unit time closest to the current time of the computer device.
  • the generation time of the data to be backed up is April 1, 2020, and the current time of the computer equipment is April 3, 2020, the difference between the two is 2 days, the difference is If it is less than the preset value, the n fragment files and the m verification files are stored according to the first storage mode.
  • the default value is set to 10 days
  • the generation time of the data to be backed up is April 1, 2020
  • the current time of the computer device is April 15, 2020
  • the difference between the two is 14 days, which is the difference
  • the value is greater than the preset value; the preset frequency is 2 times a month, and the access frequency of the data to be backed up is 3 times a month.
  • Storage mode storage is
  • the difference is greater than the preset value and/or the access frequency of the data to be backed up is less than or equal to the preset frequency, it indicates that the popularity of the data to be backed up is low, and the possibility that the data to be backed up will be accessed in the future is low , Storing the n fragment files and the m verification files according to the second storage mode.
  • the generation time of the data to be backed up is April 1, 2020, and the current time of the computer device is April 15, 2020, the difference between the two is 14 days, the difference is Greater than the preset value; the preset frequency is twice a month, the access frequency of the data to be backed up is once a month, and the access frequency is less than the preset frequency, then the n fragmented files and the m calibration
  • the verification file is stored in the second storage mode.
  • the first storage mode is: storing the n fragment files in a local database, and storing the m verification files in the cloud database 2.
  • storing all the fragmented files in the same local database is equivalent to storing a complete copy of data to be backed up in a local database. In this way, all the fragmented files are stored in the same local database, and the data read response time is faster, which is conducive to timely reading.
  • the number of verification files stored in any one of the cloud databases 2 is less than n, so as to reduce the risk of data leakage to be backed up. For example, when n is 3 and m is 4, two of the verification files are stored in one cloud database 2 and the remaining two verification files are stored in another cloud database 2.
  • the second storage mode is: storing the n fragment files and the m verification files in at least two cloud databases 2.
  • the cloud database 2 is used to store all the fragment files and verification files, and the storage cost is lower.
  • the second storage mode is: storing the n fragment files and the m verification files in at least three cloud databases 2, and any fragment file and/or collation stored in the cloud database 2
  • the number of verification files is less than n.
  • the cloud database 2 storing fragment files and the verification file the sum of the number of stored fragment files and the verification file is less than n; for the cloud database 2 storing only fragment files, Then the number of stored fragment files is less than n; for the cloud database 2 that only stores verification files, the number of stored verification files is less than n.
  • n is 3 and m is 2
  • three cloud databases 2 are used for storage.
  • one of the shard files and one of the verification files are stored in one cloud database 2, and the other shard file And another verification file are stored in another cloud database 2, and the remaining fragment file is stored in the remaining cloud database 2.
  • two verification files are stored in one cloud database 2
  • two of the fragment files are stored in another cloud database 2
  • the remaining one fragment file is stored in the remaining cloud database 2.
  • each of the fragment files and each of the verification files are stored in a different cloud database 2 respectively. In this way, the effect of remote disaster tolerance is improved.
  • the access frequency of the n fragment files is determined every preset cycle time Whether it is less than or equal to the preset frequency, and when the judgment result is that the access frequency of the n fragmented files is less than or equal to the preset frequency, transfer the n fragmented files from the local database to the preset frequency.
  • the cloud database 2 is stored.
  • the judgment result is that the access frequency of the n fragment files is greater than the preset frequency, the n fragment files continue to be stored in the local database.
  • access to fragmented files is to restore the backup data.
  • access to n fragmented files using erasure codes, can restore the said fragments based on n fragmented files Data to be backed up.
  • the access frequency of the fragmented file is less than or equal to the preset frequency, indicating that the possibility that the fragmented file will be restored to the data to be backed up in the future is low; the n fragmented files are transferred from the local database to the cloud Database 2 is stored, reducing storage costs.
  • the access frequency of the n fragmented files may be the access frequency of using the fragmented file to restore the backup data since the fragmented file was generated, or it may be the use of fragments within the unit time closest to the current time of the computer device
  • the number of times the file is restored with the backup data may also be a frequency further calculated in combination with the access frequency of the data to be backed up.
  • n fragmented files After transferring n fragmented files from the local database to the cloud database 2 for storage, obtain the access frequency of the fragmented file and/or the verification file, and determine the access frequency of the fragmented file and/or the verification file Whether it is greater than the preset frequency, when the judgment result is yes, transfer the n fragment files from the cloud database 2 to the local database for storage; when the judgment result is no, continue the n fragment files Stored in cloud database 2.
  • access to fragmented files and/or check files is to restore the backup data.
  • the data to be backed up needs to be restored, at least n fragment files and/or check files are accessed, using the correct By deleting the code, the data to be backed up can be restored based on at least n fragment files and/or check files.
  • the access frequency of the fragment file and/or the check file is greater than the preset frequency, indicating that the fragment file and/or the check file are more likely to be restored to the data to be backed up in the future;
  • the slice files are transferred from the cloud database 2 to the local database for storage, which facilitates the user to quickly restore the original data to be backed up through the slice files in the local database.
  • the access frequency of the fragment file and/or the check file may be the frequency of using the fragment file and/or the check file to restore the backup data since the fragment file and/or the check file was generated, or It is the number of times of recovering the backed-up data using the fragmented file and/or the check file in the unit time closest to the current time of the computer device, and may also be a frequency further calculated in combination with the access frequency of the data to be backed up.
  • the access frequency of the fragment files and/or check files is obtained.
  • the fragment files and/or check files are When the access frequency is greater than the preset frequency, the n fragment files are transferred from the cloud database 2 to a local database for storage.
  • the access frequency of the fragment file and/or the verification file is less than or equal to the preset frequency, the fragment file and the verification file are continuously stored in the cloud database 2.
  • the access frequency of the n fragment files is obtained, and it is determined whether the access frequency of the n fragment files is greater than the predetermined Suppose the frequency, when the judgment result is yes, continue to store the n fragment files in the local database; when the judgment result is no, transfer the n fragment files from the local database to the cloud database 2 for storage .
  • the data storage method proposed in this application divides the data to be backed up into n fragment files, generates m check files according to the n fragment files, and generates m check files according to the access frequency of the data to be backed up, the generation time of the data to be backed up, and For the current time of the computer device, store n slice files in a local database and m check files in a cloud database, or store n slice files and m check files in at least two cloud databases to achieve Data disaster recovery backup. Even if the fragment file and the check file are damaged, as long as the sum of the two damaged quantities is less than or equal to m, the data can still be recovered.
  • the embodiment of the present application also proposes a computer-readable storage medium.
  • the computer-readable storage medium may be volatile or non-volatile.
  • the computer-readable storage medium may be a hard disk, a multimedia card, SD card, flash memory card, SMC, read only memory (ROM), erasable programmable read only memory (EPROM), portable compact disk read only memory (CD-ROM), USB memory, etc. or Any combination of several.
  • the computer-readable storage medium includes a storage data area and a storage program area.
  • the storage data area stores data created according to the use of blockchain nodes.
  • the storage program area stores a data storage program 10, and the data storage program 10 is The following operations are implemented when the processor is executed:
  • n is a positive integer greater than or equal to 2;
  • the n fragment files and the m check files are stored in the first storage mode or the first storage mode.
  • Two storage mode storage where the first storage mode is: store the n fragment files in a local database, and store the m verification files in a cloud database, and the second storage mode is: store all The n fragment files and the m verification files are stored in at least two cloud databases.
  • all the above-mentioned data can also be stored in a node of a blockchain.
  • a node of a blockchain For example, fragment files, check files, etc., these data can be stored in the blockchain node.
  • Blockchain is a new application mode of computer technology such as distributed data storage, point-to-point transmission, consensus mechanism, and encryption algorithm.
  • Blockchain is essentially a decentralized database. It is a series of data blocks associated with cryptographic methods. Each data block contains a batch of network transaction information for verification. The validity of the information (anti-counterfeiting) and the generation of the next block.
  • the blockchain can include the underlying platform of the blockchain, the platform product service layer, and the application service layer.

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Abstract

涉及云技术，提供了一种基于云存储的数据存储方法、装置、计算机设备及存储介质。该方法将待备份数据切分为n个分片文件，n为大于或等于2的正整数（S10）；根据所述n个分片文件，生成m个校验文件，m为正整数（S20）；根据所述待备份数据的访问频率、所述待备份数据的生成时间及所述计算机设备的当前时间，将所述n个分片文件和所述m个校验文件按第一存储模式或第二存储模式存储，其中，所述第一存储模式为：将所述n个分片文件存储至本地数据库、所述m个校验文件存储到云端数据库，所述第二存储模式为：将所述n个分片文件和所述m个校验文件存储到至少两个云端数据库（S30）。可以降低存储成本。

Description

基于云存储的数据存储方法、装置、计算机设备及存储介质
本申请要求于2020年9月24日提交中国专利局、申请号为CN202011015397.3，发明名称为“基于云存储的数据存储方法、装置、计算机设备及存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及云技术，尤其涉及一种基于云存储的数据存储方法、装置、计算机设备及存储介质。
 背景技术
随着云计算的发展，越来越多的用户将数据以混合云的方式存储，以达到异地容灾的效果。其中，最常见的是使用混合云网关产品，实现数据的存储复制。相关技术中，混合云网关产品一般采用“本地数据库+公有云”的模式，即只本地数据库存储一份原始数据，公有云上镜像存储一份备份数据。
 技术问题
发明人意识到这样虽然实现了数据容灾备份，但将一份完整的备份数据存储在公有云，一旦原始数据和备份数据都发生损毁，则无法实现数据修复。
 技术解决方案
一种基于云存储的数据存储方法，该方法包括：
将待备份数据切分为n个分片文件，n为大于或等于2的正整数；
根据所述n个分片文件，生成m个校验文件，m为正整数；
根据所述待备份数据的访问频率、所述待备份数据的生成时间及所述计算机设备的当前时间，将所述n个分片文件和所述m个校验文件按第一存储模式或第二存储模式存储，其中，所述第一存储模式为：将所述n个分片文件存储至本地数据库、所述m个校验文件存储到云端数据库，所述第二存储模式为：将所述n个分片文件和所述m个校验文件存储到至少两个云端数据库。
一种基于云存储的数据存储装置，该装置包括：
切分模块：用于将待备份数据切分为n个分片文件，n为大于或等于2的正整数；
生成模块：用于根据所述n个分片文件，生成m个校验文件，m为正整数；
存储模块：用于根据所述待备份数据的访问频率、所述待备份数据的生成时间及计算机设备的当前时间，将所述n个分片文件和所述m个校验文件按第一存储模式或第二存储模式存储，其中，所述第一存储模式为：将所述n个分片文件存储至本地数据库、所述m个校验文件存储到云端数据库，所述第二存储模式为：将所述n个分片文件和所述m个校验文件存储到至少两个云端数据库。
一种计算机设备，所述计算机设备包括：
至少一个处理器；以及，
与所述至少一个处理器通信连接的存储器；其中，
所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行如下步骤：
将待备份数据切分为n个分片文件，n为大于或等于2的正整数；
根据所述n个分片文件，生成m个校验文件，m为正整数；
根据所述待备份数据的访问频率、所述待备份数据的生成时间及所述计算机设备的当前时间，将所述n个分片文件和所述m个校验文件按第一存储模式或第二存储模式存储，其中，所述第一存储模式为：将所述n个分片文件存储至本地数据库、所述m个校验文件存储到云端数据库，所述第二存储模式为：将所述n个分片文件和所述m个校验文件存储到至少两个云端数据库。
一种计算机可读存储介质，所述计算机可读存储介质中包括存储数据区和存储程序区，存储数据区存储根据区块链节点的使用所创建的数据，存储程序区存储有数据存储程序，所述数据存储程序被处理器执行时，实现如下步骤：
将待备份数据切分为n个分片文件，n为大于或等于2的正整数；
根据所述n个分片文件，生成m个校验文件，m为正整数；
根据所述待备份数据的访问频率、所述待备份数据的生成时间及所述计算机设备的当前时间，将所述n个分片文件和所述m个校验文件按第一存储模式或第二存储模式存储，其中，所述第一存储模式为：将所述n个分片文件存储至本地数据库、所述m个校验文件存储到云端数据库，所述第二存储模式为：将所述n个分片文件和所述m个校验文件存储到至少两个云端数据库。
本申请实现了数据容灾备份，即使分片文件和校验文件都损坏，只要两者损坏数量的总和小于或等于m，仍能恢复数据。
 附图说明
图1为本申请计算机设备较佳实施例的示意图；
图2为图1中基于云存储的数据存储装置较佳实施例的模块示意图；
图3为本申请基于云存储的数据存储方法较佳实施例的流程图；
本申请目的的实现、功能特点及优点将结合实施例，参照附图做进一步说明。
 本发明的实施方式
为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处所描述的具体实施例仅用以解释本申请，并不用于限定本申请。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
参照图1所示，为本申请计算机设备1较佳实施例的示意图。
该计算机设备1包括但不限于：存储器11、处理器12、显示器13及网络接口14。所述计算机设备1通过网络接口14连接网络，获取原始数据。其中，所述网络可以是企业内部网（Intranet）、互联网（Internet）、全球移动通讯系统（Global System of Mobile communication，GSM）、宽带码分多址（Wideband Code Division Multiple Access，WCDMA）、4G网络、5G网络、蓝牙（Bluetooth）、Wi-Fi、通话网络等无线或有线网络。
其中，存储器11至少包括一种类型的可读存储介质，所述可读存储介质包括闪存、硬盘、多媒体卡、卡型存储器（例如，SD或DX存储器等）、随机访问存储器（RAM）、静态随机访问存储器（SRAM）、只读存储器（ROM）、电可擦除可编程只读存储器（EEPROM）、可编程只读存储器（PROM）、磁性存储器、磁盘、光盘等。在一些实施例中，所述存储器11可以是所述计算机设备1的内部存储单元，例如该计算机设备1的硬盘或内存。在另一些实施例中，所述存储器11也可以是所述计算机设备1的外部存储设备，例如该计算机设备1配备的插接式硬盘，智能存储卡（Smart Media Card, SMC），安全数字（Secure Digital, SD）卡，闪存卡（Flash Card）等。当然，所述存储器11还可以既包括所述计算机设备1的内部存储单元也包括其外部存储设备。本实施例中，存储器11通常用于存储安装于所述计算机设备1的操作系统和各类应用软件，例如数据存储程序10的程序代码等。此外，存储器11还可以用于暂时地存储已经输出或者将要输出的各类数据。
处理器12在一些实施例中可以是中央处理器（Central Processing Unit，CPU）、控制器、微控制器、微处理器、或其他数据处理芯片。该处理器12通常用于控制所述计算机设备1的总体操作，例如执行数据交互或者通信相关的控制和处理等。本实施例中，所述处理器12用于运行所述存储器11中存储的程序代码或者处理数据，例如运行数据存储程序10的程序代码等。
显示器13可以称为显示屏或显示单元。在一些实施例中显示器13可以是LED显示器、液晶显示器、触控式液晶显示器以及有机发光二极管（Organic Light-Emitting Diode，OLED）触摸器等。显示器13用于显示在计算机设备1中处理的信息以及用于显示可视化的工作界面，例如显示数据统计的结果。
网络接口14可选地可以包括标准的有线接口、无线接口（如WI-FI接口），该网络接口14通常用于在所述计算机设备1与其它计算机设备之间建立通信连接。
图1仅示出了具有组件11-14以及数据存储程序10的计算机设备1和云端数据库2，但是应理解的是，并不要求实施所有示出的组件，可以替代的实施更多或者更少的组件。
可选地，所述计算机设备1还可以包括用户接口，用户接口可以包括显示器（Display）、输入单元比如键盘（Keyboard），可选的用户接口还可以包括标准的有线接口、无线接口。可选地，在一些实施例中，显示器可以是LED显示器、液晶显示器、触控式液晶显示器以及有机发光二极管（Organic Light-Emitting Diode，OLED）触摸器等。其中，显示器也可以适当的称为显示屏或显示单元，用于显示在计算机设备1中处理的信息以及用于显示可视化的用户界面。
该计算机设备1还可以包括射频（Radio Frequency，RF）电路、传感器和音频电路等等，在此不再赘述。
在上述实施例中，处理器12执行存储器11中存储的数据存储程序10时可以实现如下步骤：
将待备份数据切分为n个分片文件，n为大于或等于2的正整数；
根据所述n个分片文件，生成m个校验文件，m为正整数；
根据所述待备份数据的访问频率、所述待备份数据的生成时间及所述计算机设备的当前时间，将所述n个分片文件和所述m个校验文件按第一存储模式或第二存储模式存储，其中，所述第一存储模式为：将所述n个分片文件存储至本地数据库、所述m个校验文件存储到云端数据库2，所述第二存储模式为：将所述n个分片文件和所述m个校验文件存储到至少两个云端数据库2。
关于上述步骤的详细介绍，请参照下述图2关于基于云存储的数据存储装置100实施例的功能模块图以及图3关于基于云存储的数据存储方法实施例的流程图的说明。
参照图2所示，为本申请基于云存储的数据存储装置100的功能模块图。
本申请所述基于云存储的数据存储装置100可以安装于计算机设备中。根据实现的功能，所述基于云存储的数据存储装置100可以包括切分模块110、生成模块120、及存储模块130。本发所述模块也可以称之为单元，是指一种能够被计算机设备处理器所执行，并且能够完成固定功能的一系列计算机程序段，其存储在计算机设备的存储器中。
在本实施例中，关于各模块/单元的功能如下：
切分模块110，用于将待备份数据切分为n个分片文件，n为大于或等于2的正整数。
在本实施例中，利用数据切片算法将待备份数据切分为n个分片文件，数据切片算法例如哈希算法、取模算法、区间范围算法等。当然也可采用等分等其他方式将待备份数据切分为n个分片文件。n为大于或等于2的正整数，例如2、3、4等。
进一步地，由待备份数据切分出的各个分片文件的大小相同，例如，待备份数据的大小为100k，将待备份数据切分为两个分片文件，两个分片文件的大小均为50k。
生成模块120，用于根据所述n个分片文件，生成m个校验文件，m为正整数。
在本实施例中，利用纠删码可以根据n个分片文件生成m个校验文件。纠删码是一种编码技术，它可以将n个分片文件，增加m个校验文件，并能通过n+m个分片文件和校验文件中的任意n个分片文件和/或校验文件，还原为待备份数据。即如果有任意小于或等于m个的分片文件和/或校验文件失效，仍然能通过至少n个未失效的分片文件和/或校验文件将带备份数据还原出来。m为正整数，例如1、2、3、4等。n和m相互独立，例如n取5时，m取2；或者，n取2时，m取5。
进一步地，生成的每个校验文件的大小与每个分片文件的大小相同，所述m小于所述n。例如，n取2，m取1，待备份数据的大小为100k，存储到同一本地数据库的2个分片文件相当于一个原始的待备份数据，2个分片文件的大小为100k，校验文件的大小为50k，分片文件和校验文件的总大小为150k；根据现有技术中的镜像备份的方案，原始的待备份数据为100k，备份数据为100k，总存储大小为200k，而本申请技术方案的存储大小为现有技术的0.75倍，降低了存储成本。当然，分片文件和校验文件也可采用其他组合方式，例如5个分片文件和2个校验文件，待备份数据的大小为100k，此时每个分片文件的大小均为20k，每个校验文件的大小均为20k，分片文件和校验文件的总和大小为140k，也可降低存储成本。用户可根据实际需要设置分片文件和校验文件的数量。如此，相较于本地数据库存储一份原始数据且公有云上镜像存储一份备份数据的方案，本申请的技术方案占用的存储空间较小，存储成本较低。
存储模块130，用于根据所述待备份数据的访问频率、所述待备份数据的生成时间及计算机设备的当前时间，将所述n个分片文件和所述m个校验文件按第一存储模式或第二存储模式存储，其中，所述第一存储模式为：将所述n个分片文件存储至本地数据库、所述m个校验文件存储到云端数据库2，所述第二存储模式为：将所述n个分片文件和所述m个校验文件存储到至少两个云端数据库2。
在本实施例中，获取所述待备份数据的访问频率、所述待备份数据的生成时间和计算机设备的当前时间，根据所述待备份数据的访问频率、所述待备份数据的生成时间和计算机设备的当前时间，可以判断出待备份数据的冷热程度。根据待备份数据的冷热程度，将所述n个分片文件和所述m个校验文件按第一存储模式或第二存储模式存储。
具体地，计算所述待备份数据的生成时间与计算机设备的当前时间之间的差值。当所述差值小于或等于预设值，或者，所述差值大于预设值但所述待备份数据的访问频率大于预设频率时，说明待备份数据的热度较高，所述待备份数据将来被访问的可能性较高，将所述n个分片文件和所述m个校验文件按所述第一存储模式存储。其中，待备份数据的访问频率可以为待备份数据产生以来的平均访问频率，也可以是距离计算机设备的当前时间最近的单位时间内的访问次数。
例如，预设值设定为10天，待备份数据的生成时间为2020年4月1日，计算机设备的当前时间为2020年4月3日，则两者的差值为2天，差值小于预设值，将所述n个分片文件和所述m个校验文件按所述第一存储模式存储。再例如，预设值设定为10天，待备份数据的生成时间为2020年4月1日，计算机设备的当前时间为2020年4月15日，则两者的差值为14天，差值大于预设值；预设频率为1个月2次，待备份数据的访问频率为1个月3次，将所述n个分片文件和所述m个校验文件按所述第一存储模式存储。
当所述差值大于预设值及/或所述待备份数据的访问频率小于或等于预设频率时，说明待备份数据的热度较低，所述待备份数据将来被访问的可能性较低，将所述n个分片文件和所述m个校验文件按所述第二存储模式存储。
例如，预设值设定为10天，待备份数据的生成时间为2020年4月1日，计算机设备的当前时间为2020年4月15日，则两者的差值为14天，差值大于预设值；预设频率为1个月2次，待备份数据的访问频率为1个月1次，访问频率小于预设频率，则将所述n个分片文件和所述m个校验文件按所述第二存储模式存储。
其中，所述第一存储模式为：将所述n个分片文件存储至本地数据库、所述m个校验文件存储到云端数据库2。具体地，将所有的分片文件均存储至同一本地数据库，相当于将一份完整的待备份数据存储到一个本地数据库。如此，所有的分片文件存放在同一本地数据库，数据读响应时间较快，利于及时读取。将m个校验文件存储到一个或多个云端数据库2中。
进一步地，任意一个所述云端数据库2存储的校验文件的数量小于n，以降低待备份数据泄露的风险。例如，当n为3且m为4时，将其中两个校验文件存储到一个云端数据库2中，将剩余两个校验文件存储到另一个云端数据库2中。
所述第二存储模式为：将所述n个分片文件和所述m个校验文件存储到至少两个云端数据库2。如此，利用云端数据库2存储所有的分片文件和校验文件，存储成本较低。
具体地，第二存储模式为：将所述n个分片文件和所述m个校验文件存储到至少三个云端数据库2，任意一个所述云端数据库2存储的分片文件和/或校验文件的数量小于n。换言之，对于存储有分片文件和所述校验文件的云端数据库2，则其存储的分片文件和所述校验文件的数量总和小于n；对于只存储有分片文件的云端数据库2，则其存储的分片文件的数量小于n；对于只存储有校验文件的云端数据库2，则其存储的校验文件的数量小于n。
例如，当n为3且m为2时，采用三个云端数据库2进行存储，具体地，将其中一个分片文件和其中一个校验文件存储到一个云端数据库2中，将另一个分片文件和另一个校验文件存储到另一个云端数据库2中，将剩余的一个分片文件存储到剩余的一个云端数据库2中。或者，将两个校验文件存储到一个云端数据库2中，将其中两个分片文件存储到另一个云端数据库2中，将剩余的一个分片文件存储到剩余的一个云端数据库2中。
进一步地，将每个所述分片文件和每个所述校验文件分别存储至不同的所述云端数据库2。如此，提高了异地容灾的效果。
需要指出的是，所述将n个分片文件和所述m个校验文件按所述第一存储模式存储之后，每隔预设的周期时间，判断所述n个分片文件的访问频率是否小于或等于所述预设频率，当判断结果为所述n个分片文件的访问频率小于或等于所述预设频率时，将所述n个分片文件从所述本地数据库转移至所述云端数据库2存储。当然，当判断结果为所述n个分片文件的访问频率大于所述预设频率时，所述n个分片文件继续存储在所述本地数据库中。
可以理解的是，一般来说，访问分片文件是为了恢复带备份数据，当需要恢复待备份数据时，访问n个分片文件，利用纠删码，可以根据n个分片文件恢复所述待备份数据。所述分片文件的访问频率小于或等于所述预设频率，说明分片文件将来被还原成待备份数据的可能性较低；将所述n个分片文件从本地数据库转移至所述云端数据库2存储，降低存储成本。
其中，所述n个分片文件的访问频率可以为分片文件产生以来利用分片文件恢复所述带备份数据的访问频率，也可以是距离计算机设备的当前时间最近的单位时间内利用分片文件恢复所述带备份数据的次数，还可以是结合待备份数据的访问频率进一步计算出来的频率。
将n个分片文件从所述本地数据库转移至云端数据库2存储之后，获取所述分片文件和/或校验文件的访问频率，判断所述分片文件和/或校验文件的访问频率是否大于所述预设频率，当判断结果为是时，将所述n个分片文件从云端数据库2转移至本地数据库中存储；当判断结果为否时，将所述n个分片文件继续存储在云端数据库2中。
可以理解的是，一般来说，访问分片文件和/或校验文件是为了恢复带备份数据，当需要恢复待备份数据时，访问至少n个分片文件和/或校验文件，利用纠删码，可以根据至少n个分片文件和/或校验文件恢复所述待备份数据。所述分片文件和/或校验文件的访问频率大于所述预设频率，说明分片文件和/或校验文件将来被还原成待备份数据的可能性较高；将所述n个分片文件从所述云端数据库2转移至本地数据库存储，利于用户通过本地数据库中的分片文件快速恢复出原始的待备份数据。
其中，所述分片文件和/或校验文件的访问频率可以为分片文件和/或校验文件产生以来利用分片文件和/或校验文件恢复所述带备份数据的频率，也可以是距离计算机设备的当前时间最近的单位时间内的利用分片文件和/或校验文件恢复所述带备份数据的次数，还可以是结合待备份数据的访问频率进一步计算出来的频率。
将所述n个分片文件和所述m个校验文件按所述第二存储模式存储之后，获取分片文件和/或校验文件的访问频率，当分片文件和/或校验文件的访问频率大于所述预设频率时，将所述n个分片文件从所述云端数据库2转移至本地数据库中存储。当然，当分片文件和/或校验文件的访问频率小于或等于所述预设频率时，将分片文件和校验文件继续存储于云端数据库2中。
将所述n个分片文件从所述云端数据库2转移至本地数据库中存储之后，获取所述n个分片文件的访问频率，判断所述n个分片文件的访问频率是否大于所述预设频率，当判断结果为是时，将所述n个分片文件继续存储在本地数据库中；当判断结果为否时，将所述n个分片文件从本地数据库转移至云端数据库2中存储。
本申请提出的基于云存储的数据存储装置，将待备份数据切分为n个分片文件，根据n个分片文件，生成m个校验文件，根据待备份数据的访问频率、待备份数据的生成时间及计算机设备的当前时间，将n个分片文件存储至本地数据库、m个校验文件存储到云端数据库2，或者，将n个分片文件和m个校验文件存储到至少两个云端数据库2，实现了数据容灾备份。即使分片文件和校验文件都损坏，只要两者损坏数量的总和小于或等于m，仍能恢复数据。
此外，本申请还提供一种基于云存储的数据存储方法，该方法应用于计算机设备。参照图3所示，为本申请基于云存储的数据存储方法的实施例的方法流程示意图。计算机设备1的处理器12执行存储器11中存储的数据存储程序10时实现基于云存储的数据存储方法的如下步骤：
步骤S10：将待备份数据切分为n个分片文件，n为大于或等于2的正整数。
在本实施例中，利用数据切片算法将待备份数据切分为n个分片文件，数据切片算法例如哈希算法、取模算法、区间范围算法等。当然也可采用等分等其他方式将待备份数据切分为n个分片文件。n为大于或等于2的正整数，例如2、3、4等。
进一步地，由待备份数据切分出的各个分片文件的大小相同，例如，待备份数据的大小为100k，将待备份数据切分为两个分片文件，两个分片文件的大小均为50k。
步骤S20：根据所述n个分片文件，生成m个校验文件，m为正整数。
在本实施例中，利用纠删码可以根据n个分片文件生成m个校验文件。纠删码是一种编码技术，它可以将n个分片文件，增加m个校验文件，并能通过n+m个分片文件和校验文件中的任意n个分片文件和/或校验文件，还原为待备份数据。即如果有任意小于或等于m个的分片文件和/或校验文件失效，仍然能通过至少n个未失效的分片文件和/或校验文件将带备份数据还原出来。m为正整数，例如1、2、3、4等。n和m相互独立，例如n取5时，m取2；或者，n取2时，m取5。
进一步地，生成的每个校验文件的大小与每个分片文件的大小相同，所述m小于所述n。例如，n取2，m取1，待备份数据的大小为100k，存储到同一本地数据库的2个分片文件相当于一个原始的待备份数据，2个分片文件的大小为100k，校验文件的大小为50k，分片文件和校验文件的总大小为150k；根据现有技术中的镜像备份的方案，原始的待备份数据为100k，备份数据为100k，总存储大小为200k，而本申请技术方案的存储大小为现有技术的0.75倍，降低了存储成本。当然，分片文件和校验文件也可采用其他组合方式，例如5个分片文件和2个校验文件，待备份数据的大小为100k，此时每个分片文件的大小均为20k，每个校验文件的大小均为20k，分片文件和校验文件的总和大小为140k，也可降低存储成本。用户可根据实际需要设置分片文件和校验文件的数量。如此，相较于本地数据库存储一份原始数据且公有云上镜像存储一份备份数据的方案，本申请的技术方案占用的存储空间较小，存储成本较低。
步骤S30：根据所述待备份数据的访问频率、所述待备份数据的生成时间及计算机设备的当前时间，将所述n个分片文件和所述m个校验文件按第一存储模式或第二存储模式存储，其中，所述第一存储模式为：将所述n个分片文件存储至本地数据库、所述m个校验文件存储到云端数据库2，所述第二存储模式为：将所述n个分片文件和所述m个校验文件存储到至少两个云端数据库2。
在本实施例中，获取所述待备份数据的访问频率、所述待备份数据的生成时间和计算机设备的当前时间，根据所述待备份数据的访问频率、所述待备份数据的生成时间和计算机设备的当前时间，可以判断出待备份数据的冷热程度。根据待备份数据的冷热程度，将所述n个分片文件和所述m个校验文件按第一存储模式或第二存储模式存储。
具体地，计算所述待备份数据的生成时间与计算机设备的当前时间之间的差值。当所述差值小于或等于预设值，或者，所述差值大于预设值但所述待备份数据的访问频率大于预设频率时，说明待备份数据的热度较高，所述待备份数据将来被访问的可能性较高，将所述n个分片文件和所述m个校验文件按所述第一存储模式存储。其中，待备份数据的访问频率可以为待备份数据产生以来的平均访问频率，也可以是距离计算机设备的当前时间最近的单位时间内的访问次数。
例如，预设值设定为10天，待备份数据的生成时间为2020年4月1日，计算机设备的当前时间为2020年4月3日，则两者的差值为2天，差值小于预设值，将所述n个分片文件和所述m个校验文件按所述第一存储模式存储。再例如，预设值设定为10天，待备份数据的生成时间为2020年4月1日，计算机设备的当前时间为2020年4月15日，则两者的差值为14天，差值大于预设值；预设频率为1个月2次，待备份数据的访问频率为1个月3次，将所述n个分片文件和所述m个校验文件按所述第一存储模式存储。
当所述差值大于预设值及/或所述待备份数据的访问频率小于或等于预设频率时，说明待备份数据的热度较低，所述待备份数据将来被访问的可能性较低，将所述n个分片文件和所述m个校验文件按所述第二存储模式存储。
例如，预设值设定为10天，待备份数据的生成时间为2020年4月1日，计算机设备的当前时间为2020年4月15日，则两者的差值为14天，差值大于预设值；预设频率为1个月2次，待备份数据的访问频率为1个月1次，访问频率小于预设频率，则将所述n个分片文件和所述m个校验文件按所述第二存储模式存储。
其中，所述第一存储模式为：将所述n个分片文件存储至本地数据库、所述m个校验文件存储到云端数据库2。具体地，将所有的分片文件均存储至同一本地数据库，相当于将一份完整的待备份数据存储到一个本地数据库。如此，所有的分片文件存放在同一本地数据库，数据读响应时间较快，利于及时读取。将m个校验文件存储到一个或多个云端数据库2中。
进一步地，任意一个所述云端数据库2存储的校验文件的数量小于n，以降低待备份数据泄露的风险。例如，当n为3且m为4时，将其中两个校验文件存储到一个云端数据库2中，将剩余两个校验文件存储到另一个云端数据库2中。
所述第二存储模式为：将所述n个分片文件和所述m个校验文件存储到至少两个云端数据库2。如此，利用云端数据库2存储所有的分片文件和校验文件，存储成本较低。
具体地，第二存储模式为：将所述n个分片文件和所述m个校验文件存储到至少三个云端数据库2，任意一个所述云端数据库2存储的分片文件和/或校验文件的数量小于n。换言之，对于存储有分片文件和所述校验文件的云端数据库2，则其存储的分片文件和所述校验文件的数量总和小于n；对于只存储有分片文件的云端数据库2，则其存储的分片文件的数量小于n；对于只存储有校验文件的云端数据库2，则其存储的校验文件的数量小于n。
例如，当n为3且m为2时，采用三个云端数据库2进行存储，具体地，将其中一个分片文件和其中一个校验文件存储到一个云端数据库2中，将另一个分片文件和另一个校验文件存储到另一个云端数据库2中，将剩余的一个分片文件存储到剩余的一个云端数据库2中。或者，将两个校验文件存储到一个云端数据库2中，将其中两个分片文件存储到另一个云端数据库2中，将剩余的一个分片文件存储到剩余的一个云端数据库2中。
进一步地，将每个所述分片文件和每个所述校验文件分别存储至不同的所述云端数据库2。如此，提高了异地容灾的效果。
需要指出的是，所述将n个分片文件和所述m个校验文件按所述第一存储模式存储之后，每隔预设的周期时间，判断所述n个分片文件的访问频率是否小于或等于所述预设频率，当判断结果为所述n个分片文件的访问频率小于或等于所述预设频率时，将所述n个分片文件从所述本地数据库转移至所述云端数据库2存储。当然，当判断结果为所述n个分片文件的访问频率大于所述预设频率时，所述n个分片文件继续存储在所述本地数据库中。
可以理解的是，一般来说，访问分片文件是为了恢复带备份数据，当需要恢复待备份数据时，访问n个分片文件，利用纠删码，可以根据n个分片文件恢复所述待备份数据。所述分片文件的访问频率小于或等于所述预设频率，说明分片文件将来被还原成待备份数据的可能性较低；将所述n个分片文件从本地数据库转移至所述云端数据库2存储，降低存储成本。
其中，所述n个分片文件的访问频率可以为分片文件产生以来利用分片文件恢复所述带备份数据的访问频率，也可以是距离计算机设备的当前时间最近的单位时间内利用分片文件恢复所述带备份数据的次数，还可以是结合待备份数据的访问频率进一步计算出来的频率。
将n个分片文件从所述本地数据库转移至云端数据库2存储之后，获取所述分片文件和/或校验文件的访问频率，判断所述分片文件和/或校验文件的访问频率是否大于所述预设频率，当判断结果为是时，将所述n个分片文件从云端数据库2转移至本地数据库中存储；当判断结果为否时，将所述n个分片文件继续存储在云端数据库2中。
可以理解的是，一般来说，访问分片文件和/或校验文件是为了恢复带备份数据，当需要恢复待备份数据时，访问至少n个分片文件和/或校验文件，利用纠删码，可以根据至少n个分片文件和/或校验文件恢复所述待备份数据。所述分片文件和/或校验文件的访问频率大于所述预设频率，说明分片文件和/或校验文件将来被还原成待备份数据的可能性较高；将所述n个分片文件从所述云端数据库2转移至本地数据库存储，利于用户通过本地数据库中的分片文件快速恢复出原始的待备份数据。
其中，所述分片文件和/或校验文件的访问频率可以为分片文件和/或校验文件产生以来利用分片文件和/或校验文件恢复所述带备份数据的频率，也可以是距离计算机设备的当前时间最近的单位时间内的利用分片文件和/或校验文件恢复所述带备份数据的次数，还可以是结合待备份数据的访问频率进一步计算出来的频率。
将所述n个分片文件和所述m个校验文件按所述第二存储模式存储之后，获取分片文件和/或校验文件的访问频率，当分片文件和/或校验文件的访问频率大于所述预设频率时，将所述n个分片文件从所述云端数据库2转移至本地数据库中存储。当然，当分片文件和/或校验文件的访问频率小于或等于所述预设频率时，将分片文件和校验文件继续存储于云端数据库2中。
将n个所述分片文件从所述云端数据库2转移至本地数据库中存储之后，获取所述n个分片文件的访问频率，判断所述n个分片文件的访问频率是否大于所述预设频率，当判断结果为是时，将所述n个分片文件继续存储在本地数据库中；当判断结果为否时，将所述n个分片文件从本地数据库转移至云端数据库2中存储。
本申请提出的数据存储方法，将待备份数据切分为n个分片文件，根据n个分片文件，生成m个校验文件，根据待备份数据的访问频率、待备份数据的生成时间及计算机设备的当前时间，将n个分片文件存储至本地数据库、m个校验文件存储到云端数据库，或者，将n个分片文件和m个校验文件存储到至少两个云端数据库，实现了数据容灾备份。即使分片文件和校验文件都损坏，只要两者损坏数量的总和小于或等于m，仍能恢复数据。
此外，本申请实施例还提出一种计算机可读存储介质，该计算机可读存储介质可以是易失性的，也可以是非易失性的，该计算机可读存储介质可以是硬盘、多媒体卡、SD卡、闪存卡、SMC、只读存储器（ROM）、可擦除可编程只读存储器（EPROM）、便携式紧致盘只读存储器（CD-ROM）、USB存储器等等中的任意一种或者几种的任意组合。所述计算机可读存储介质中包括存储数据区和存储程序区，存储数据区存储根据区块链节点的使用所创建的数据，存储程序区存储有数据存储程序10，所述数据存储程序10被处理器执行时实现如下操作：
将待备份数据切分为n个分片文件，n为大于或等于2的正整数；
根据所述n个分片文件，生成m个校验文件，m为正整数；
根据所述待备份数据的访问频率、所述待备份数据的生成时间及所述计算机设备的当前时间，将所述n个分片文件和所述m个校验文件按第一存储模式或第二存储模式存储，其中，所述第一存储模式为：将所述n个分片文件存储至本地数据库、所述m个校验文件存储到云端数据库，所述第二存储模式为：将所述n个分片文件和所述m个校验文件存储到至少两个云端数据库。
需要强调的是，本申请之计算机可读存储介质的具体实施方式与上述基于云存储的数据存储方法的具体实施方式大致相同，在此不再赘述。
在另一个实施例中，本申请所提供的基于云存储的数据存储方法，为进一步保证上述所有出现的数据的私密和安全性，上述所有数据还可以存储于一区块链的节点中。例如分片文件、校验文件等等，这些数据均可存储在区块链节点中。
需要说明的是，本申请所指区块链是分布式数据存储、点对点传输、共识机制、加密算法等计算机技术的新型应用模式。区块链(Blockchain)，本质上是一个去中心化的数据库，是一串使用密码学方法相关联产生的数据块，每个数据块中包含了一批次网络交易的信息，用于验证其信息的有效性(防伪)和生成下一个区块。区块链可以包括区块链底层平台、平台产品服务层以及应用服务层等。
需要说明的是，上述本申请实施例序号仅仅为了描述，不代表实施例的优劣。并且本文中的术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、装置、物品或者方法不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、装置、物品或者方法所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括该要素的过程、装置、物品或者方法中还存在另外的相同要素。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到上述实施例方法可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件，但很多情况下前者是更佳的实施方式。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在如上所述的一个存储介质(如ROM/RAM、磁碟、光盘)中，包括若干指令用以使得一台终端设备(可以是手机，计算机，电子装置，或者网络设备等)执行本申请各个实施例所述的方法。
以上仅为本申请的优选实施例，并非因此限制本申请的专利范围，凡是利用本申请说明书及附图内容所作的等效结构或等效流程变换，或直接或间接运用在其他相关的技术领域，均同理包括在本申请的专利保护范围内。

Claims (20)

  1. 一种基于云存储的数据存储方法，应用于计算机设备，其中，所述方法包括：
    将待备份数据切分为n个分片文件，n为大于或等于2的正整数；
    根据所述n个分片文件，生成m个校验文件，m为正整数；
    根据所述待备份数据的访问频率、所述待备份数据的生成时间及所述计算机设备的当前时间，将所述n个分片文件和所述m个校验文件按第一存储模式或第二存储模式存储，其中，所述第一存储模式为：将所述n个分片文件存储至本地数据库、所述m个校验文件存储到云端数据库，所述第二存储模式为：将所述n个分片文件和所述m个校验文件存储到至少两个云端数据库。
  2. 如权利要求1所述的基于云存储的数据存储方法，其中，根据所述待备份数据的访问频率、所述待备份数据的生成时间及所述计算机设备的当前时间，将所述n个分片文件和所述m个校验文件按第一存储模式存储，包括：
    计算所述计算机设备的当前时间与所述待备份数据的生成时间之间的差值；
    当所述差值小于或等于预设值，或者，所述差值大于预设值但所述待备份数据的访问频率大于预设频率时，将所述n个分片文件和所述m个校验文件按所述第一存储模式存储。
  3. 如权利要求2所述的基于云存储的数据存储方法，其中，将所述n个分片文件和所述m个校验文件按所述第一存储模式存储之后，所述方法还包括：
    每隔预设的周期时间，判断所述n个分片文件的访问频率是否小于或等于所述预设频率，当判断结果为小于或等于所述预设频率时，将所述n个分片文件转移至所述云端数据库存储。
  4. 如权利要求1所述的基于云存储的数据存储方法，其中，根据所述待备份数据的访问频率、所述待备份数据的生成时间及所述计算机设备的当前时间，将所述n个分片文件和所述m个校验文件按第二存储模式存储，包括：
    计算所述计算机设备的当前时间与所述待备份数据的生成时间之间的差值；
    当所述差值大于预设值及/或所述待备份数据的访问频率小于或等于预设频率时，将所述n个分片文件和所述m个校验文件按所述第二存储模式存储。
  5. 如权利要求4所述的基于云存储的数据存储方法，其中，所述将n个分片文件和所述m个校验文件按所述第二存储模式存储之后，所述方法还包括：
    判断所述分片文件和/或校验文件的访问频率是否大于所述预设频率，当判断结果为是时，将所述n个分片文件转移至所述本地数据库存储。
  6. 如权利要求1所述的基于云存储的数据存储方法，其中，所述将所述n个分片文件存储至本地数据库、所述m个校验文件存储到云端数据库，包括：
    将所述n个分片文件存储至本地数据库，将所述m个校验文件存储到一个或多个云端数据库，任意一个所述云端数据库存储的校验文件的数量小于n。
  7. 如权利要求1所述的基于云存储的数据存储方法，其中，所述将所述n个分片文件和所述m个校验文件存储到至少两个云端数据库，包括：
    将所述n个分片文件和所述m个校验文件存储到至少三个云端数据库，任意一个所述云端数据库存储的分片文件和/或校验文件的数量小于n。
  8. 一种基于云存储的数据存储装置，其中，所述装置包括：
    切分模块：用于将待备份数据切分为n个分片文件，n为大于或等于2的正整数；
    生成模块：用于根据所述n个分片文件，生成m个校验文件，m为正整数；
    存储模块：用于根据所述待备份数据的访问频率、所述待备份数据的生成时间及计算机设备的当前时间，将所述n个分片文件和所述m个校验文件按第一存储模式或第二存储模式存储，其中，所述第一存储模式为：将所述n个分片文件存储至本地数据库、所述m个校验文件存储到云端数据库，所述第二存储模式为：将所述n个分片文件和所述m个校验文件存储到至少两个云端数据库。
  9. 一种计算机设备，其中，所述计算机设备包括：
    至少一个处理器；以及，
    与所述至少一个处理器通信连接的存储器；其中，
    所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行如下步骤：
    将待备份数据切分为n个分片文件，n为大于或等于2的正整数；
    根据所述n个分片文件，生成m个校验文件，m为正整数；
    根据所述待备份数据的访问频率、所述待备份数据的生成时间及所述计算机设备的当前时间，将所述n个分片文件和所述m个校验文件按第一存储模式或第二存储模式存储，其中，所述第一存储模式为：将所述n个分片文件存储至本地数据库、所述m个校验文件存储到云端数据库，所述第二存储模式为：将所述n个分片文件和所述m个校验文件存储到至少两个云端数据库。
  10. 如权利要求9所述的计算机设备，其中，根据所述待备份数据的访问频率、所述待备份数据的生成时间及所述计算机设备的当前时间，将所述n个分片文件和所述m个校验文件按第一存储模式存储，包括：
    计算所述计算机设备的当前时间与所述待备份数据的生成时间之间的差值；
    当所述差值小于或等于预设值，或者，所述差值大于预设值但所述待备份数据的访问频率大于预设频率时，将所述n个分片文件和所述m个校验文件按所述第一存储模式存储。
  11. 如权利要求10所述的计算机设备，其中，将所述n个分片文件和所述m个校验文件按所述第一存储模式存储之后，所述至少一个处理器还执行如下步骤：
    每隔预设的周期时间，判断所述n个分片文件的访问频率是否小于或等于所述预设频率，当判断结果为小于或等于所述预设频率时，将所述n个分片文件转移至所述云端数据库存储。
  12. 如权利要求9所述的计算机设备，其中，根据所述待备份数据的访问频率、所述待备份数据的生成时间及所述计算机设备的当前时间，将所述n个分片文件和所述m个校验文件按第二存储模式存储，包括：
    计算所述计算机设备的当前时间与所述待备份数据的生成时间之间的差值；
    当所述差值大于预设值及/或所述待备份数据的访问频率小于或等于预设频率时，将所述n个分片文件和所述m个校验文件按所述第二存储模式存储。
  13. 如权利要求12所述的基于云存储的数据存储方法，其中，所述将n个分片文件和所述m个校验文件按所述第二存储模式存储之后，所述至少一个处理器还执行如下步骤：
    判断所述分片文件和/或校验文件的访问频率是否大于所述预设频率，当判断结果为是时，将所述n个分片文件转移至所述本地数据库存储。
  14. 如权利要求9所述的计算机设备，其中，所述将所述n个分片文件存储至本地数据库、所述m个校验文件存储到云端数据库，包括：
    将所述n个分片文件存储至本地数据库，将所述m个校验文件存储到一个或多个云端数据库，任意一个所述云端数据库存储的校验文件的数量小于n。
  15. 如权利要求9所述的计算机设备，其中，所述将所述n个分片文件和所述m个校验文件存储到至少两个云端数据库，包括：
    将所述n个分片文件和所述m个校验文件存储到至少三个云端数据库，任意一个所述云端数据库存储的分片文件和/或校验文件的数量小于n。
  16. 一种计算机可读存储介质，其中，所述计算机可读存储介质中包括存储数据区和存储程序区，存储数据区存储根据区块链节点的使用所创建的数据，存储程序区存储有数据存储程序，所述数据存储程序被处理器执行时，实现如下步骤：
    将待备份数据切分为n个分片文件，n为大于或等于2的正整数；
    根据所述n个分片文件，生成m个校验文件，m为正整数；
    根据所述待备份数据的访问频率、所述待备份数据的生成时间及所述计算机设备的当前时间，将所述n个分片文件和所述m个校验文件按第一存储模式或第二存储模式存储，其中，所述第一存储模式为：将所述n个分片文件存储至本地数据库、所述m个校验文件存储到云端数据库，所述第二存储模式为：将所述n个分片文件和所述m个校验文件存储到至少两个云端数据库。
  17. 如权利要求16所述的计算机可读存储介质，其中，根据所述待备份数据的访问频率、所述待备份数据的生成时间及所述计算机设备的当前时间，将所述n个分片文件和所述m个校验文件按第一存储模式存储，包括：
    计算所述计算机设备的当前时间与所述待备份数据的生成时间之间的差值；
    当所述差值小于或等于预设值，或者，所述差值大于预设值但所述待备份数据的访问频率大于预设频率时，将所述n个分片文件和所述m个校验文件按所述第一存储模式存储。
  18. 如权利要求17所述的计算机可读存储介质，其中，将所述n个分片文件和所述m个校验文件按所述第一存储模式存储之后，所述数据存储程序被处理器执行时还实现如下步骤：
    每隔预设的周期时间，判断所述n个分片文件的访问频率是否小于或等于所述预设频率，当判断结果为小于或等于所述预设频率时，将所述n个分片文件转移至所述云端数据库存储。
  19. 如权利要求16所述的计算机可读存储介质，其中，根据所述待备份数据的访问频率、所述待备份数据的生成时间及所述计算机设备的当前时间，将所述n个分片文件和所述m个校验文件按第二存储模式存储，包括：
    计算所述计算机设备的当前时间与所述待备份数据的生成时间之间的差值；
    当所述差值大于预设值及/或所述待备份数据的访问频率小于或等于预设频率时，将所述n个分片文件和所述m个校验文件按所述第二存储模式存储。
  20. 如权利要求19所述的计算机可读存储介质，其中，所述将n个分片文件和所述m个校验文件按所述第二存储模式存储之后，所述数据存储程序被处理器执行时还实现如下步骤：
    判断所述分片文件和/或校验文件的访问频率是否大于所述预设频率，当判断结果为是时，将所述n个分片文件转移至所述本地数据库存储。
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