Cloud platform data-oriented storage adjustment method and apparatus, and terminal device

Abstract

The invention discloses a cloud platform data-oriented storage adjustment method and device and terminal equipment, and the method comprises the steps: comparing the business access amount corresponding to each virtual block in a cloud platform with a preset access amount, thereby achieving the adjustment of the business access amount of a target virtual block in the cloud platform when the business access amount corresponding to the target virtual block in the cloud platform is larger than the preset access amount. And dividing each part of data in the target virtual block into different categories, for example, classifying the data with high current access frequency as hot data, classifying the data with medium current access frequency as warm data and classifying the data with low current access frequency as cold data, so that the data can be classified based on the category corresponding to each part of data. And migrating the data to different storage media. Compared with the prior art, the method has the advantages that the storage modes of various types of data can be reasonably adjusted according to the actual access frequency of the data to balance the distribution of the storage resources, so that the utilization rate of the storage resources and the response speed of the data under the condition of high service requirements are improved.

Description

Technical Field

[0001] The present invention relates to the field of cloud platform storage technology, and in particular to a storage adjustment method, device and terminal equipment for cloud platform data. Background Art

[0002] Cloud platforms generally use virtualization technology to divide physical resources (such as CPU, memory, storage, and network) into multiple virtual blocks, and these virtual blocks can share physical resources. In the prior art, cloud platforms often use fixed storage strategies for each virtual block, that is, they cannot dynamically adjust the storage method of data according to the actual usage of the data. Therefore, when a virtual block has high business demand or high access volume, since the storage strategy is fixed, it is impossible to dynamically adjust its storage strategy according to the current access situation of various types of data in real time, such as being unable to dynamically adjust the storage medium corresponding to various types of data, thereby failing to meet high business demand.

[0003] Fixed storage strategies will also prevent data with different access frequencies from being stored on storage media with corresponding performance. For example, data with high access frequencies will be stored on storage media with lower performance, which will increase data access latency. When data with low access frequencies is stored on high-performance storage media, it will cause resource waste, resulting in unbalanced resource allocation, and low storage resource utilization and slow data response speed under high business demand conditions on the cloud platform. Summary of the invention

[0004] The embodiments of the present invention provide a storage adjustment method, apparatus and terminal device for cloud platform data. By storing data with different access frequencies in storage media with different performances, the allocation of storage resources can be balanced, and high utilization of storage resources can be met. This can effectively solve the problem of unbalanced resource allocation in the prior art, which leads to low storage resource utilization of the cloud platform under high business demand.

[0005] An embodiment of the present invention provides a storage adjustment method for cloud platform data, comprising:

[0006] Compare the business access volume corresponding to each virtual block in the cloud platform with the preset access volume; wherein each virtual block stores a number of data, each data corresponding to a current access frequency; the current access frequency is high frequency, medium frequency or low frequency;

[0007] When it is determined that the business access volume corresponding to a target virtual block in the cloud platform is greater than the preset access volume, each piece of data is divided into different categories according to the current access frequency corresponding to each piece of data; wherein the categories are hot data, warm data or cold data; the hot data, warm data and cold data correspond to the high frequency, medium frequency and low frequency of the current access frequency respectively;

[0008] According to the category of each piece of data, the storage medium corresponding to each piece of data in the cloud platform is adjusted; wherein the cloud platform is provided with: a first storage medium with low capacity but high read / write speed, a second storage medium with high capacity but low read / write speed, and a third storage medium for archival storage;

[0009] Among them, adjusting the storage medium corresponding to each piece of data in the cloud platform according to the category of each piece of data includes: migrating each piece of data classified as hot data to the first storage medium, migrating each piece of data classified as warm data to the second storage medium, or migrating each piece of data classified as cold data to the third storage medium.

[0010] Preferably, each piece of data also corresponds to a life cycle; wherein the life cycle is an active period, a stable period or an archiving period;

[0011] The data is divided into different categories, including:

[0012] Each piece of data with a high current access frequency is used as first target data, and when it is determined that the life cycle corresponding to the first target data is an active period or a stable period, the first target data is classified as hot data;

[0013] Each piece of data with a current access frequency of medium frequency is used as the second target data, and when it is determined that the life cycle corresponding to the second target data is an active period or a stable period, the second target data is classified as warm data;

[0014] Each piece of data with a low current access frequency is used as the third target data, each piece of data corresponding to a life cycle of an archiving period is used as the fourth target data, and the third target data and the fourth target data are classified as cold data.

[0015] Preferably, the step of migrating each piece of data classified as hot data to the first storage medium includes:

[0016] Uploading each piece of hot data to each storage space in the first storage medium in the form of an object; wherein each object corresponds to a key value for identifying the object;

[0017] Setting a lifecycle management strategy for each object; wherein the lifecycle management strategy includes: after determining that the storage time of the object in the storage space exceeds a preset time range, migrating the object to a second storage medium; or,

[0018] When it is determined that the current access frequency of the object is low, the object is migrated to the third storage medium.

[0019] Preferably, after adjusting the storage medium corresponding to each piece of data in the cloud platform, the method further includes:

[0020] Get the KMS key entered by the user;

[0021] Each piece of data is encrypted based on the KMS key.

[0022] Preferably, the method further includes: when it is determined that the business access volume corresponding to a target virtual block in the cloud platform is greater than a preset access volume, adding a cloud server instance corresponding to the cloud platform for providing computing resources.

[0023] Preferably, it also includes:

[0024] When it is determined that the business access volume corresponding to a target virtual block in the cloud platform is not greater than the preset access volume, each piece of data with a current low access frequency is classified as cold data;

[0025] Migrating each piece of data classified as cold data to a third storage medium for archival storage;

[0026] Allocate the storage space corresponding to each piece of data classified as cold data in the first storage medium with low capacity but high read / write speed and the second storage medium with high capacity but low read / write speed to other virtual blocks in the cloud platform;

[0027] The service access volume of the other virtual blocks is greater than the preset access volume.

[0028] Preferably, the method further includes: when it is determined that the business access volume corresponding to a target virtual block in the cloud platform is not greater than a preset access volume, reducing the cloud server instance corresponding to the cloud platform for providing computing resources.

[0029] Based on the above method embodiments, the present invention provides corresponding device embodiments.

[0030] An embodiment of the present invention provides a storage adjustment device for cloud platform data, comprising: a comparison module and a first storage adjustment module;

[0031] The comparison module is used to compare the service access volume corresponding to each virtual block in the cloud platform with the preset access volume; wherein each virtual block stores a number of data, each data corresponding to a current access frequency; the current access frequency is high frequency, medium frequency or low frequency;

[0032] The first storage adjustment module is used to classify each piece of data into different categories according to the current access frequency corresponding to each piece of data when determining that the business access volume corresponding to a target virtual block in the cloud platform is greater than the preset access volume; wherein the categories are hot data, warm data or cold data; and the hot data, warm data and cold data correspond to the high frequency, medium frequency and low frequency of the current access frequency respectively;

[0033] According to the category of each piece of data, the storage medium corresponding to each piece of data in the cloud platform is adjusted; wherein the cloud platform is provided with: a first storage medium with low capacity but high read / write speed, a second storage medium with high capacity but low read / write speed, and a third storage medium for archival storage;

[0034] Among them, adjusting the storage medium corresponding to each piece of data in the cloud platform according to the category of each piece of data includes: migrating each piece of data classified as hot data to the first storage medium, migrating each piece of data classified as warm data to the second storage medium, or migrating each piece of data classified as cold data to the third storage medium.

[0035] Preferably, it also includes: a second storage adjustment module;

[0036] The second storage adjustment module is used to classify each piece of data with a low current access frequency as cold data when it is determined that the business access volume corresponding to a target virtual block in the cloud platform is not greater than a preset access volume;

[0037] Migrating each piece of data classified as cold data to a third storage medium for archival storage;

[0038] Allocate the storage space corresponding to each piece of data classified as cold data in the first storage medium with low capacity but high read / write speed and the second storage medium with high capacity but low read / write speed to other virtual blocks in the cloud platform;

[0039] The service access volume of the other virtual blocks is greater than the preset access volume.

[0040] Based on the above method embodiments, the present invention provides corresponding terminal device embodiments.

[0041] Another embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, it implements a storage adjustment method for cloud platform data described in the above-mentioned embodiment of the invention.

[0042] The following beneficial effects are achieved by implementing the present invention:

[0043] The embodiments of the present invention provide a storage adjustment method, apparatus and terminal device for cloud platform data. The present invention compares the business access volume corresponding to each virtual block in the cloud platform with the preset access volume. Therefore, when it is determined that the business access volume corresponding to a target virtual block in the cloud platform is greater than the preset access volume, each piece of data in the target virtual block can be divided into different categories. For example, data with a current access frequency of high frequency can be classified as hot data, data with a current access frequency of medium frequency can be classified as warm data, and data with a current access frequency of low frequency can be classified as cold data. Therefore, based on the category corresponding to each piece of data, the data can be migrated to different storage media to achieve efficient use of storage resources. Specifically, hot data has a higher access frequency, so it needs to be stored in a storage medium with a faster read and write speed to ensure a fast response of the data, and is then migrated to a first storage medium with a low capacity but a high read and write speed; the access frequency of warm data is between that of hot data and cold data, and can be stored in a storage medium with a slightly slower read and write speed but a larger capacity, and can be migrated to a second storage medium with a higher capacity but a lower read and write speed; cold data has a lower access frequency, but may have long-term archival value, and is then migrated to a third storage medium for archival storage to save high-performance storage resources. Compared with the prior art, by storing data with different access frequencies in storage media with different performances, the present invention can reasonably allocate storage methods according to the actual access requirements of the data (i.e., the current access frequency) to balance the allocation of storage resources, thereby improving the utilization rate of storage resources of the cloud platform under high business demand and improving the response speed of data by adjusting the storage methods of various types of data. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a flowchart of a storage adjustment method for cloud platform data provided by one embodiment of the present invention.

[0045] Figure 2 It is a schematic diagram of another storage strategy adjustment provided by another embodiment of the present invention.

[0046] Figure 3 It is a structural schematic diagram of a storage device for cloud platform data provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] like Figure 1FIG. 1 is a flow chart of a method for adjusting storage of cloud platform data provided by an embodiment of the present invention. The method for adjusting storage of cloud platform data includes:

[0049] Step S1: Compare the service access volume corresponding to each virtual block in the cloud platform with the preset access volume;

[0050] Wherein, each virtual block stores a number of data, each data corresponding to a current access frequency; the current access frequency is a high frequency, a medium frequency or a low frequency;

[0051] Step S2: when it is determined that the service access volume corresponding to a target virtual block in the cloud platform is greater than the preset access volume, each piece of data is divided into different categories according to the current access frequency corresponding to each piece of data; wherein the categories are hot data, warm data or cold data; the hot data, warm data and cold data correspond to the high frequency, medium frequency and low frequency of the current access frequency respectively;

[0052] According to the category of each piece of data, the storage medium corresponding to each piece of data in the cloud platform is adjusted; wherein the cloud platform is provided with: a first storage medium with low capacity but high read / write speed, a second storage medium with high capacity but low read / write speed, and a third storage medium for archival storage;

[0053] Among them, adjusting the storage medium corresponding to each piece of data in the cloud platform according to the category of each piece of data includes: migrating each piece of data classified as hot data to the first storage medium, migrating each piece of data classified as warm data to the second storage medium, or migrating each piece of data classified as cold data to the third storage medium.

[0054] For step S1, in a preferred embodiment, Figure 2 As shown, the present invention can first create various virtual blocks in the cloud platform. These virtual blocks (i.e., virtual block devices) can be used for elastic storage, and operations such as creation, deletion, and expansion can be performed as needed;

[0055] Based on the analysis results of business needs or business policies, it is determined whether the storage policy needs to be adjusted. If the data is accessed frequently, stored for a long time, or the data size is large, it may be necessary to increase storage resources or adopt a more efficient storage policy. On the contrary, if the data is accessed less frequently, stored for a short time, or the data size is small, it may be appropriate to reduce storage resources or adopt a more economical storage policy. If it is determined that adjustment is necessary, the storage policy will be adjusted based on the determination results.

[0056] In an embodiment of the present invention, the business access volume corresponding to each virtual block in the cloud platform can be compared with the preset access volume, so as to determine whether the storage strategy needs to be adjusted according to the comparison result. In a preferred embodiment, the present invention can also monitor the usage of the virtual block device in real time, including key indicators such as storage capacity, I / O performance, and read and write frequency, to determine whether the corresponding storage strategy needs to be adjusted.

[0057] When adjusting the storage strategy, the present invention needs to obtain each piece of data to be processed from the corresponding target virtual block device. These data can be various types of data, such as structured data, unstructured data, etc. Indicatively, the data can be obtained by communicating with the virtual block device through a corresponding interface or protocol.

[0058] After obtaining the data to be processed, the system needs to analyze the business needs or business strategies of the data. This can include factors such as data access frequency, storage time, and data size. By analyzing these factors, the system can understand the storage needs and usage of the data and adjust the storage strategy.

[0059] For step S2, when the present invention determines that the service access volume corresponding to a target virtual block in the cloud platform is greater than the preset access volume, the data are divided into different categories according to the current access frequency corresponding to each data;

[0060] Since each piece of data corresponds to a current access frequency, and the current access frequency is high frequency, medium frequency or low frequency; based on hot data, warm data and cold data, and the rules corresponding to the high frequency, medium frequency and low frequency in the current access frequency, hot data, warm data and cold data can be classified according to the high frequency, medium frequency or low frequency of the data.

[0061] Schematically, hot data generally refers to data with high access frequency, which needs to be read and written frequently and has high requirements on system performance, such as real-time transaction data in online trading systems and data queried by users in real time.

[0062] Warm data generally refers to data with a moderate access frequency. This data does not need to be accessed in real time like hot data, but also needs to be stored and accessed reliably within a certain period of time. For example, recent historical transaction data, log data, etc.

[0063] Cold data generally refers to data with low access frequency. This data may not be accessed for a long time, but is still important to the business or application and needs to be preserved for a long time. For example, historical transaction data and archived documents from many years ago.

[0064] It is understandable that the present invention can classify data with high access frequency, which is critical to the business and needs to be accessed in real time as hot data. Data with moderate access frequency, which is of certain importance to the business and needs to be reliably stored and accessed within a certain period of time as warm data. Data with low access frequency, which is not very important to the business but needs to be stored for a long time is classified as cold data.

[0065] Finally, the present invention can adjust the storage medium corresponding to each piece of data in the cloud platform according to the category of each piece of data, specifically:

[0066] Each piece of data classified as hot data is migrated to a first storage medium, each piece of data classified as warm data is migrated to a second storage medium, or each piece of data classified as cold data is migrated to a third storage medium.

[0067] It is understandable that the first storage medium with low capacity but high read / write speed, the second storage medium with high capacity but low read / write speed, and the third storage medium for archival storage can be summarized as follows:

[0068] The first storage medium with low capacity but high read and write speed: usually refers to solid-state drives (SSDs), especially SSDs using NVMe (Non-Volume Memory Express) technology. Compared with traditional mechanical hard disks (HDDs), SSDs have higher read and write speeds, lower latency, and better performance stability. They are suitable for application scenarios that require high-speed I / O performance, such as databases, online transaction processing (OLTP), and virtualized environments.

[0069] Secondary storage media with high capacity but low read / write speed: usually refers to mechanical hard disk drives (HDDs), especially large-capacity, high-density HDDs. HDDs are more cost-effective than SSDs and are suitable for scenarios that require large-capacity storage but less demanding performance. HDDs are also commonly used for backup, archiving, and cold data storage because they can provide a large amount of storage space at a lower cost.

[0070] Third storage medium for archival storage: This usually refers to the archival storage tier in cloud storage services, such as Amazon S3's Glassy storage class or Google Cloud Storage's Coldline storage class. Archival storage services provide long-term, low-cost storage solutions for data that is infrequently accessed but needs to be retained for a long time. Data is usually stored on physical media after being compressed and encrypted, and may require some latency when accessed. The cost of archival storage services usually decreases as the data retention period increases.

[0071] Therefore, for hot data, the present invention can use a high-performance first storage medium, such as SSD (solid state drive), to improve data access speed. For warm data, a more cost-effective second storage medium, such as HDD (mechanical hard disk), can be used, and caching technology can be combined to improve performance. For cold data, a third storage medium that provides archival storage or cloud storage services can be used to reduce storage costs and ensure data security.

[0072] Therefore, the present invention can migrate data to different storage media according to the classification of each piece of data, so as to achieve efficient use of storage resources. By storing data with different access frequencies in storage media with different performances, the present invention can reasonably allocate storage resources according to the actual needs of the data, avoiding waste of resources.

[0073] At the same time, the present invention can also improve the response speed of data access. By storing hot data in a high-performance storage medium, the system can respond to high-priority access requests more quickly, thereby improving the user experience. In addition, the present invention also takes into account the long-term archiving needs of data. By storing cold data in an archival storage medium, the system can save high-performance storage resources while ensuring the long-term accessibility of data.

[0074] In a preferred embodiment, each piece of data also corresponds to a life cycle; wherein the life cycle is an active period, a stable period or an archiving period;

[0075] When differentiating each piece of data into different categories, the specific categories are:

[0076] Each piece of data with a high current access frequency is used as first target data, and when it is determined that the life cycle corresponding to the first target data is an active period or a stable period, the first target data is classified as hot data;

[0077] Each piece of data with a current access frequency of medium frequency is used as the second target data, and when it is determined that the life cycle corresponding to the second target data is an active period or a stable period, the second target data is classified as warm data;

[0078] Each piece of data with a low current access frequency is used as the third target data, each piece of data corresponding to a life cycle of an archiving period is used as the fourth target data, and the third target data and the fourth target data are classified as cold data.

[0079] Therefore, by understanding the life cycle of data, the present invention can more accurately distinguish different data categories according to the access frequency and life cycle of data, so that resources (such as high-performance storage, network bandwidth, etc.) can be allocated to hot data in the active or stable period in a priority manner to ensure that these hot data with high frequency of access can be quickly accessed and processed. Therefore, by associating data with the life cycle, the storage strategy or storage method of data can be better managed and controlled.

[0080] In a preferred embodiment, when each piece of data classified as hot data is migrated to the first storage medium, it specifically includes:

[0081] Uploading each piece of hot data to each storage space in the first storage medium in the form of an object; wherein each object corresponds to a key value for identifying the object;

[0082] Setting a lifecycle management strategy for each object; wherein the lifecycle management strategy includes: after determining that the storage time of the object in the storage space exceeds a preset time range, migrating the object to a second storage medium; or,

[0083] When it is determined that the current access frequency of the object is low, the object is migrated to the third storage medium.

[0084] It is understandable that hot data generally refers to data that is frequently accessed, updated, and used. These data are critical to business operations because they may contain real-time information, user activity records, transaction data, etc., which require quick response and efficient processing. Storing data through objects can support high-concurrency data access, and this storage method is particularly important for hot data because multiple users or applications can access and modify the same object at the same time without causing performance degradation or data conflicts. Moreover, the object storage of the present invention uses a flat namespace to organize data, and each object has a unique identifier (such as a key or hash value). This makes data search, access, and management very simple and efficient, and is particularly suitable for processing large amounts of hot data.

[0085] Furthermore, the object storage of the present invention can also set an independent lifecycle management policy for each object, and by setting the lifecycle management policy, automatic data migration can be achieved. When the storage time of the object in the storage space exceeds the preset time range or the access frequency decreases, the present invention can automatically trigger the migration process without manual intervention.

[0086] By migrating hot data objects that are not frequently accessed to storage media with lower costs (such as the second or third storage media), the overall storage cost can be reduced. At the same time, since data migration is automatic, labor costs can also be saved.

[0087] In a preferred embodiment, after adjusting the storage medium corresponding to each piece of data in the cloud platform, the present invention further includes:

[0088] Get the KMS key entered by the user;

[0089] Each piece of data is encrypted based on the KMS key.

[0090] The present invention uses the KMS key to encrypt data, which can ensure that even if the data is intercepted during transmission or storage, the data content cannot be decrypted and read without the corresponding key, thereby greatly improving the confidentiality and security of the data.

[0091] In a preferred embodiment, when determining that the service access volume corresponding to a target virtual block in the cloud platform is greater than a preset access volume, the present invention further includes:

[0092] Add a cloud server instance corresponding to the cloud platform for providing computing resources.

[0093] It is understandable that increasing cloud server instances means increasing available computing resources, which can process a large number of business requests more quickly. This helps to improve the response speed and throughput of the cloud platform to meet business needs during peak hours.

[0094] In a preferred embodiment, the present invention further comprises:

[0095] When it is determined that the business access volume corresponding to a target virtual block in the cloud platform is not greater than the preset access volume, each piece of data with a current low access frequency is classified as cold data;

[0096] Migrating each piece of data classified as cold data to a third storage medium for archival storage;

[0097] Allocate the storage space corresponding to each piece of data classified as cold data in the first storage medium with low capacity but high read / write speed and the second storage medium with high capacity but low read / write speed to other virtual blocks in the cloud platform;

[0098] The service access volume of the other virtual blocks is greater than the preset access volume.

[0099] Illustratively, the present invention can not only adjust the storage method when the business access volume is greater than the preset access volume, but also migrate the data classified as cold data to a third storage medium for archival storage when it is determined that the business access volume corresponding to a target virtual block in the cloud platform is not greater than the preset access volume. In this way, the cold data can be removed from the high-performance storage medium and the space of these storage media can be released, so that the high-performance storage medium can be more focused on storing and processing hot data. This can improve the efficiency of the entire storage system (i.e., the cloud platform) and ensure that high-performance storage resources are fully utilized.

[0100] Therefore, the storage adjustment strategy based on data access frequency of the present invention enables storage resources to be dynamically allocated, and can adjust the storage method when the business access volume is not greater than the preset access volume, that is, when the business demand decreases. For example, cold data usually does not need to be stored on high-performance storage media due to its low access frequency, so it can be migrated to a low-cost archival storage medium, which can significantly reduce storage costs and improve the utilization of storage space. Therefore, when business needs change, the present invention can automatically adjust the allocation of storage resources to ensure that resources are reasonably used.

[0101] In a preferred embodiment, the present invention further comprises:

[0102] When it is determined that the business access volume corresponding to a target virtual block in the cloud platform is not greater than the preset access volume, the cloud server instance corresponding to the cloud platform for providing computing resources is reduced.

[0103] Schematically, when the business access volume decreases, reducing the number of cloud server instances can reduce unnecessary resource consumption, thereby reducing operating costs. In addition, reducing unnecessary cloud server instances can release computing resources so that these resources can be reallocated to other virtual blocks or applications that require higher computing power. This helps to improve the overall resource utilization.

[0104] like Figure 3 As shown, based on the above-mentioned various embodiments of the storage adjustment method for cloud platform data, the present invention provides a corresponding device embodiment;

[0105] An embodiment of the present invention provides a storage adjustment device for cloud platform data, comprising: a comparison module and a first storage adjustment module;

[0106] The comparison module is used to compare the service access volume corresponding to each virtual block in the cloud platform with the preset access volume; wherein each virtual block stores a number of data, each data corresponding to a current access frequency; the current access frequency is high frequency, medium frequency or low frequency;

[0107] The first storage adjustment module is used to classify each piece of data into different categories according to the current access frequency corresponding to each piece of data when determining that the business access volume corresponding to a target virtual block in the cloud platform is greater than the preset access volume; wherein the categories are hot data, warm data or cold data; and the hot data, warm data and cold data correspond to the high frequency, medium frequency and low frequency of the current access frequency respectively;

[0108] According to the category of each piece of data, the storage medium corresponding to each piece of data in the cloud platform is adjusted; wherein the cloud platform is provided with: a first storage medium with low capacity but high read / write speed, a second storage medium with high capacity but low read / write speed, and a third storage medium for archival storage;

[0109] Among them, adjusting the storage medium corresponding to each piece of data in the cloud platform according to the category of each piece of data includes: migrating each piece of data classified as hot data to the first storage medium, migrating each piece of data classified as warm data to the second storage medium, or migrating each piece of data classified as cold data to the third storage medium.

[0110] In a preferred embodiment, the present invention further comprises: a second storage adjustment module;

[0111] The second storage adjustment module is used to classify each piece of data with a low current access frequency as cold data when it is determined that the business access volume corresponding to a target virtual block in the cloud platform is not greater than a preset access volume;

[0112] Migrating each piece of data classified as cold data to a third storage medium for archival storage;

[0113] Allocate the storage space corresponding to each piece of data classified as cold data in the first storage medium with low capacity but high read / write speed and the second storage medium with high capacity but low read / write speed to other virtual blocks in the cloud platform;

[0114] The service access volume of the other virtual blocks is greater than the preset access volume.

[0115] It should be noted that the device embodiments described above are merely schematic, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. Those of ordinary skill in the art can understand and implement it without paying creative labor.

[0116] Those skilled in the art can clearly understand that, for the sake of convenience and simplicity, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0117] Based on the above-mentioned various embodiments of the storage adjustment method for cloud platform data, the present invention provides corresponding terminal device embodiments.

[0118] An embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements a storage adjustment method for cloud platform data as described in any method embodiment of the present invention.

[0119] The terminal device may be a computing terminal device such as a desktop computer, a notebook, a palm computer, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0120] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, and uses various interfaces and lines to connect various parts of the entire terminal device.

[0121] The memory can be used to store the computer program, and the processor realizes various functions of the terminal device by running or executing the computer program stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Med i aCard, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device or other volatile solid-state storage device.

[0122] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A storage adjustment method for cloud platform data, characterized in that: include: Compare the business access volume corresponding to each virtual block in the cloud platform with the preset access volume; wherein each virtual block stores a number of data, each data corresponding to a current access frequency; the current access frequency is high frequency, medium frequency or low frequency; When it is determined that the business access volume corresponding to a target virtual block in the cloud platform is greater than the preset access volume, each piece of data is divided into different categories according to the current access frequency corresponding to each piece of data; wherein the categories are hot data, warm data or cold data; the hot data, warm data and cold data correspond to the high frequency, medium frequency and low frequency of the current access frequency respectively; According to the category of each piece of data, the storage medium corresponding to each piece of data in the cloud platform is adjusted; wherein the cloud platform is provided with: a first storage medium with low capacity but high read / write speed, a second storage medium with high capacity but low read / write speed, and a third storage medium for archival storage; Among them, adjusting the storage medium corresponding to each piece of data in the cloud platform according to the category of each piece of data includes: migrating each piece of data classified as hot data to the first storage medium, migrating each piece of data classified as warm data to the second storage medium, or migrating each piece of data classified as cold data to the third storage medium.

2. A method for adjusting storage of cloud platform data as claimed in claim 1, characterized in that: Each piece of data also corresponds to a life cycle; wherein the life cycle is an active period, a stable period or an archiving period; The data is divided into different categories, including: Each piece of data with a high current access frequency is used as first target data, and when it is determined that the life cycle corresponding to the first target data is an active period or a stable period, the first target data is classified as hot data; Each piece of data with a current access frequency of medium frequency is used as the second target data, and when it is determined that the life cycle corresponding to the second target data is an active period or a stable period, the second target data is classified as warm data; Each piece of data with a low current access frequency is used as the third target data, each piece of data corresponding to a life cycle of an archiving period is used as the fourth target data, and the third target data and the fourth target data are classified as cold data.

3. A method for adjusting storage of cloud platform data as claimed in claim 2, characterized in that: The step of migrating each piece of data classified as hot data to the first storage medium includes: Uploading each piece of hot data to each storage space in the first storage medium in the form of an object; wherein each object corresponds to a key value for identifying the object; Setting a lifecycle management strategy for each object; wherein the lifecycle management strategy includes: after determining that the storage time of the object in the storage space exceeds a preset time range, migrating the object to a second storage medium; or, When it is determined that the current access frequency of the object is low, the object is migrated to the third storage medium.

4. A method for adjusting storage of cloud platform data as claimed in claim 3, characterized in that: After adjusting the storage medium corresponding to each piece of data in the cloud platform, it also includes: Get the KMS key entered by the user; Each piece of data is encrypted based on the KMS key.

5. A method for adjusting storage of cloud platform data as claimed in claim 4, characterized in that: Also includes: When it is determined that the service access volume corresponding to a target virtual block in the cloud platform is greater than the preset access volume, a cloud server instance corresponding to the cloud platform for providing computing resources is added.

6. The method for adjusting storage of cloud platform data according to claim 1, characterized in that: Also includes: When it is determined that the business access volume corresponding to a target virtual block in the cloud platform is not greater than the preset access volume, each piece of data with a current low access frequency is classified as cold data; Migrating each piece of data classified as cold data to a third storage medium for archival storage; Allocate the storage space corresponding to each piece of data classified as cold data in the first storage medium with low capacity but high read / write speed and the second storage medium with high capacity but low read / write speed to other virtual blocks in the cloud platform; The service access volume of the other virtual blocks is greater than the preset access volume.

7. A method for adjusting storage of cloud platform data as claimed in claim 6, characterized in that: Also includes: When it is determined that the business access volume corresponding to a target virtual block in the cloud platform is not greater than the preset access volume, the cloud server instance corresponding to the cloud platform for providing computing resources is reduced.

8. A storage adjustment device for cloud platform data, characterized in that: include: A comparison module and a first storage adjustment module; The comparison module is used to compare the service access volume corresponding to each virtual block in the cloud platform with the preset access volume; wherein each virtual block stores a number of data, each data corresponding to a current access frequency; the current access frequency is high frequency, medium frequency or low frequency; The first storage adjustment module is used to classify each piece of data into different categories according to the current access frequency corresponding to each piece of data when determining that the business access volume corresponding to a target virtual block in the cloud platform is greater than the preset access volume; wherein the categories are hot data, warm data or cold data; and the hot data, warm data and cold data correspond to the high frequency, medium frequency and low frequency of the current access frequency respectively; According to the category of each piece of data, the storage medium corresponding to each piece of data in the cloud platform is adjusted; wherein the cloud platform is provided with: a first storage medium with low capacity but high read / write speed, a second storage medium with high capacity but low read / write speed, and a third storage medium for archival storage; Among them, adjusting the storage medium corresponding to each piece of data in the cloud platform according to the category of each piece of data includes: migrating each piece of data classified as hot data to the first storage medium, migrating each piece of data classified as warm data to the second storage medium, or migrating each piece of data classified as cold data to the third storage medium.

9. A storage adjustment device for cloud platform data as claimed in claim 8, characterized in that: Also included: a second storage adjustment module; The second storage adjustment module is used to classify each piece of data with a low current access frequency as cold data when it is determined that the business access volume corresponding to a target virtual block in the cloud platform is not greater than a preset access volume; Migrating each piece of data classified as cold data to a third storage medium for archival storage; Allocate the storage space corresponding to each piece of data classified as cold data in the first storage medium with low capacity but high read / write speed and the second storage medium with high capacity but low read / write speed to other virtual blocks in the cloud platform; The service access volume of the other virtual blocks is greater than the preset access volume.

10. A terminal device, characterized in that: It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, it implements a storage adjustment method for cloud platform data as described in any one of claims 1 to 7.

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