Data storage and distribution method and device based on cloud application

Abstract

The invention provides a data storage and distribution method and device based on a cloud application, and the method comprises the steps: receiving a scheduling application request sent by a first cluster, determining a second cluster from a cluster system according to the scheduling application request, the scheduling application request being used for requesting to obtain information of a cluster storing related data of the cloud application, the cluster system comprises a central scheduling node and a plurality of clusters, a first cluster is different from a second cluster, the first cluster and the second cluster are one of the plurality of clusters, each cluster is deployed in an Internet data center IDC machine room, and each cluster comprises at least one node; the information of the second cluster is sent to the first cluster, so that the first cluster determines a target node based on the information of the second cluster and downloads a corresponding file from the target node, the target node is at least one node in the second cluster, the bandwidth of each IDC machine room can be fully utilized, the data storage and transmission cost is reduced, and the efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of cloud applications, and in particular to a data storage and distribution method and device based on cloud applications. Background Art

[0002] With the booming development of the cloud application industry, more and more applications are running on cloud platforms. Currently, third-party storage servers are usually used to store and distribute cloud application installation packages and user data, which has led to increasingly prominent cost and efficiency issues in data storage and transmission, becoming a key challenge for the development of the industry.

[0003] In view of this, how to provide a data storage and distribution solution based on cloud applications to reduce the cost of data storage and transmission and improve efficiency has become a technical problem that needs to be solved urgently. Summary of the invention

[0004] In view of the technical problems existing in the prior art, the embodiments of the present application provide a data storage and distribution method and device based on cloud applications.

[0005] In a first aspect, an embodiment of the present application provides a data storage and distribution method based on cloud applications, which is applied to a central scheduling node, including: Receive a scheduling application request sent by the first cluster, and determine a second cluster from the cluster system according to the scheduling application request, wherein the scheduling application request is used to request to obtain information of a cluster storing cloud application related data, the cluster system includes a central scheduling node and multiple clusters, the first cluster and the second cluster are different, the first cluster and the second cluster are each one of the multiple clusters, each cluster is deployed in an Internet data center IDC computer room, and each cluster includes at least one node; The information of the second cluster is sent to the first cluster, so that the first cluster determines a target node based on the information of the second cluster and downloads a corresponding file from the target node, wherein the target node is at least one node in the second cluster.

[0006] In a second aspect, an embodiment of the present application provides a data storage and distribution method based on a cloud application, which is applied to a first cluster and includes: Sending a scheduling application request to the central scheduling node, wherein the scheduling application request is used to request information of a cluster storing cloud application related data; Receive information of the second cluster sent by the central scheduling node, determine the target node based on the information of the second cluster, and download the corresponding file from the target node, wherein the first cluster, the central scheduling node and the second cluster belong to a cluster system, the first cluster and the second cluster are deployed in different Internet data centers (IDC) computer rooms, and the target node is at least one node in the second cluster.

[0007] In a third aspect, the embodiment of the present application further provides a data storage and distribution device based on cloud applications, which is applied to a central scheduling node, including: A determination unit is configured to receive a scheduling application request sent by a first cluster, and determine a second cluster from the cluster system according to the scheduling application request, wherein the scheduling application request is used to request information of a cluster storing cloud application related data, the cluster system includes a central scheduling node and multiple clusters, the first cluster and the second cluster are different, the first cluster and the second cluster are each a cluster among multiple clusters, each cluster is deployed in an Internet data center IDC computer room, and each cluster includes at least one node; The first sending unit is used to send the information of the second cluster to the first cluster, so that the first cluster determines a target node based on the information of the second cluster and downloads a corresponding file from the target node, wherein the target node is at least one node in the second cluster.

[0008] In a fourth aspect, an embodiment of the present application further provides a data storage and distribution device based on cloud applications, applied to a first cluster, including: A second sending unit is used to send a scheduling application request to the central scheduling node, wherein the scheduling application request is used to request to obtain information of a cluster storing cloud application related data; A download unit is used to receive information of the second cluster sent by the central scheduling node, determine a target node based on the information of the second cluster, and download corresponding files from the target node, wherein the first cluster, the central scheduling node and the second cluster belong to a cluster system, the first cluster and the second cluster are deployed in different Internet data center IDC computer rooms, and the target node is at least one node in the second cluster.

[0009] In a fifth aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the cloud application-based data storage and distribution method as described in the first aspect or the second aspect are executed.

[0010] In the sixth aspect, an embodiment of the present application also provides an electronic device, comprising: a processor, a storage medium and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the storage medium communicate through the bus, and the processor executes the machine-readable instructions to perform the steps of the cloud application-based data storage and distribution method as described in the first aspect or the second aspect.

[0011] In summary, the data storage and distribution method and device, electronic device and storage medium based on cloud applications provided in the embodiments of the present application no longer use a third-party storage server to store and distribute cloud application related data, but use a cluster belonging to a cluster system and deployed in an IDC computer room to store and distribute cloud application related data, thereby making full use of the bandwidth of each IDC computer room, reducing the cost of data storage and transmission, and improving efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 A flowchart of an embodiment of a data storage and distribution method based on cloud applications provided in an embodiment of the present application; Figure 2 A flowchart of another embodiment of a cloud application-based data storage and distribution method provided in an embodiment of the present application; Figure 3 A schematic diagram of the structure of an embodiment of a data storage and distribution device based on cloud applications provided in an embodiment of the present application; Figure 4 A schematic diagram of the structure of another embodiment of a data storage and distribution device based on cloud applications provided in an embodiment of the present application; Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0013] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the drawings in the present application only serve the purpose of explanation and description and are not used to limit the scope of protection of the present application. In addition, it should be understood that the schematic drawings are not drawn in real proportion. The flowchart used in this application shows the operations implemented according to some embodiments of the present application. It should be understood that the operations of the flowchart can be implemented out of sequence, and the steps without logical context can be reversed in order or implemented simultaneously. In addition, those skilled in the art can add one or more other operations to the flowchart under the guidance of the content of the present application, or remove one or more operations from the flowchart.

[0014] In addition, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0015] It should be noted that the term "comprising" will be used in the embodiments of the present application to indicate the existence of the features declared thereafter, but does not exclude the addition of other features.

[0016] Reference Figure 1 As shown, an embodiment of the present application provides a flow chart of a data storage and distribution method based on cloud applications, which is applied to a central scheduling node and includes: S10, receiving a scheduling application request sent by the first cluster, and determining a second cluster from the cluster system according to the scheduling application request, wherein the scheduling application request is used to request information of a cluster storing cloud application related data, the cluster system includes a central scheduling node and multiple clusters, the first cluster and the second cluster are different, the first cluster and the second cluster are each one of the multiple clusters, each cluster is deployed in an Internet data center IDC computer room, and each cluster includes at least one node; In this embodiment, it should be noted that the cloud application related data includes cloud application installation packages, cloud application hot update resources, cloud application archives, etc.

[0017] For a cloud application installation package / cloud application hot-change resource (hereinafter collectively referred to as "cloud application data S") of a certain cloud application, it can be uploaded to a cluster C1 in the cluster system (assuming that the cluster system includes the central scheduling node, cluster C1, cluster C2, cluster C3 and cluster C4) for storage, and the central scheduling node records the information that cluster C1 stores cloud application data S. Subsequently, cluster C2 can send a scheduling application request to the central scheduling node, and the central scheduling node determines cluster C1 according to the scheduling application request and sends the information of cluster C1 to cluster C2. Cluster C2 downloads cloud application data S from cluster C1. After cluster C2 downloads cloud application data S from cluster C1, for cluster C3 in the cluster system, there are two data sources of cloud application data S, namely cluster C1 and cluster C2. Cluster C3 can send a scheduling application request to the central scheduling node, and the central scheduling node determines the information of one of clusters C1 and C2 (assuming that the information of cluster C2 is determined) according to the scheduling application request, and sends the information of cluster C2 to cluster C3. Cluster C3 downloads cloud application data S from cluster C2. After cluster C3 downloads cloud application data S from cluster C2, for cluster C4 in the cluster system, there are three data sources of cloud application data S, namely cluster C1, cluster C2 and cluster C3. Cluster C4 can send a scheduling application request to the central scheduling node, and the central scheduling node determines the information of one cluster among clusters C1, cluster C2 and cluster C3 (assuming that the information of cluster C2 is determined) according to the scheduling application request, and sends the information of cluster C2 to cluster C4. Cluster C4 downloads cloud application data S from cluster C2. The instances in the IDC computer rooms to which clusters C1, cluster C2, cluster C3 and cluster C4 belong can install and run cloud applications by mounting the cloud application data on clusters C1, cluster C2, cluster C3 and cluster C4 respectively. At least one copy of the same cloud application data can be saved in the same cluster.

[0018] For a cloud application archive of a certain cloud application, when a user exits the cloud application for the first time, the user's cloud application archive can be saved to the cluster (assuming cluster C3) of the IDC computer room (assuming IDC computer room X) to which the instance running the cloud application belongs, and the central scheduling node records that cluster C3 stores the cloud application archive of the user's cloud application. When the user subsequently applies to use the cloud application, if the cloud service system assigns the user an instance in IDC computer room X, the instance can pull the cloud application archive from cluster C3; and if the cloud service system The system assigns the instance in IDC room Y (IDC room Y is different from IDC room X) to the user. The cluster in IDC room Y does not store the cloud application archive. Then the cluster in IDC room Y can send a scheduling application request to the central scheduling node. The central scheduling node determines that the cloud application archive of the user's cloud application is stored in cluster C3 according to the scheduling application request, and sends the information of cluster C3 to the cluster. The cluster downloads the cloud application archive from cluster C3 according to the information of cluster C3, and then the instance can pull the cloud application archive from the cluster. In addition, it should be noted that when saving the user's cloud application archive, in addition to saving the user's cloud application archive to the cluster of the IDC room to which the instance running the cloud application belongs, it can also be saved in clusters of other IDC rooms. At least one copy of the same cloud application archive can be saved in the same cluster. For a cloud application archive of a certain user using a certain cloud application, if the previous cloud application archive is saved in the same cluster when saving the current cloud application archive, the previous cloud application archive can be deleted after saving the current cloud application archive.

[0019] In addition, it should be noted that the cloud application related data in the cluster is stored in the form of shards, that is, when storing the cloud application related data in the cluster, the cloud application related data needs to be sharded to obtain multiple shard files, and the storage node location of each shard file is calculated according to the settings of the nodes in the cluster (that is, calculate which node each shard file should be stored in), and then each shard file is stored in the corresponding node in the cluster. When the cloud application related data in the cluster is subsequently obtained, it is necessary to determine the storage node location of each shard file of the cloud application related data according to the settings of the nodes in the cluster, and download the shard file stored in the target node from the target node (the target node is the storage node location of the shard file) according to the storage node location. The existing CRUSH algorithm can be used to calculate the storage node location of each shard file according to the settings of the nodes in the cluster. In addition, when obtaining cloud application related data in the cluster, in addition to determining the storage node location of each shard file of the cloud application related data according to the settings of the nodes in the cluster, the storage node location of each shard file of the cloud application related data can also be obtained from the central scheduling node. Of course, in this method, it is necessary to record the storage node location of each shard file of the cloud application related data when recording the information that the cluster stores cloud application related data through the central scheduling node.

[0020] S11. Send information of the second cluster to the first cluster, so that the first cluster determines a target node based on the information of the second cluster and downloads a corresponding file from the target node, wherein the target node is at least one node in the second cluster.

[0021] The data storage and distribution method based on cloud applications provided in the embodiment of the present application no longer uses a third-party storage server to store and distribute cloud application related data, but instead uses a cluster belonging to a cluster system and deployed in an IDC computer room to store and distribute cloud application related data, thereby making full use of the bandwidth of each IDC computer room, reducing the cost of data storage and transmission, and improving efficiency.

[0022] Based on the foregoing method embodiment, determining the second cluster from the cluster system according to the scheduling application request may include: Determine at least one candidate cluster from the cluster system according to the scheduling application request, wherein the data requested by the scheduling application request is stored in each candidate cluster in the form of slices; If the number of the candidate clusters is 1, the candidate cluster is determined to be the second cluster; or If the number of candidate clusters is greater than 1, for each candidate cluster, the scheduling priority of the candidate cluster is calculated based on the number of scheduling tasks completed by the candidate cluster, the number of scheduling tasks currently being performed by the candidate cluster, and the number of scheduling times of the scheduling tasks corresponding to the scheduling application request in the candidate cluster, and the candidate cluster with the highest scheduling priority is determined as the second cluster.

[0023] In this embodiment, it should be noted that the to-be-selected cluster is a cluster in the cluster system that stores cloud application related data except the first cluster.

[0024] Based on the foregoing method embodiment, the step of calculating the scheduling priority of the candidate cluster according to the number of completed scheduling tasks of the candidate cluster, the number of ongoing scheduling tasks of the candidate cluster, and the number of scheduling times of the scheduling tasks corresponding to the scheduling application request in the candidate cluster may include: Calculate the first index, the second index, the third index and the fourth index, where the first index T1 = n1 / N, the second index T2 = (P1-n2) / P1, the third index T3 = (M-n3) / M, and the fourth index T4 = (P2-t) / P2, n1 is the number of scheduling tasks completed by the candidate cluster, N is the number of scheduling tasks completed by all clusters in the cluster system, P1 is the set parameter, n2 is the number of scheduling tasks being performed by the candidate cluster, M is the number of all clusters in the cluster system, n3 is the number of scheduling times of the scheduling task corresponding to the scheduling application request in the candidate cluster, P2 is the set parameter, and t is the round-trip delay between the candidate cluster and the first cluster; A weighted sum is taken for the first indicator, the second indicator, the third indicator, and the fourth indicator, and a result of the weighted sum is used as the scheduling priority of the candidate cluster.

[0025] In this embodiment, it should be noted that the number of completed scheduling tasks of the candidate cluster C1 refers to the sum of the number of cloud application related data that other clusters have downloaded from the candidate cluster C1; the number of ongoing scheduling tasks of the candidate cluster C1 refers to the sum of the number of cloud application related data that other clusters are currently downloading from the candidate cluster C1; the number of scheduling times of the scheduling tasks corresponding to the scheduling application request in the candidate cluster C1 refers to the sum of the number of cloud application related data Q (the cloud application related data Q is the cloud application related data requested to be downloaded by the scheduling application request) that other clusters have downloaded from the candidate cluster C1. P1 and P2 can be set as needed, for example, P1 can be set to 200, and P2 can be set to 1s. The weights corresponding to the first indicator, the second indicator, the third indicator, and the fourth indicator can be set as needed, but it is necessary to ensure that the sum of the weights corresponding to the first indicator, the second indicator, the third indicator, and the fourth indicator is 1. For example, the weights corresponding to the first indicator, the second indicator, the third indicator, and the fourth indicator can be set to 0.1, 0.4, 0.2, and 0.3, respectively.

[0026] Based on the foregoing method embodiment, the method may further include: receiving a clear query request sent by the first cluster; After the first cluster clears the specified data, it is determined whether the number of copies of the specified data is greater than a first value. If so, a feedback message is sent to the first cluster, wherein the feedback message carries information indicating that the first cluster can clear the specified data.

[0027] In this embodiment, it should be noted that the number of copies of the specified data refers to the number of clusters where the specified data is stored. The clear query request can be for specific cloud application-related data or for all cloud application-related data stored in the first cluster. For example, when specific cloud application-related data expires, the first cluster can send a clear query request for the specific cloud application-related data to the central scheduling node. After receiving the clear query request, the central scheduling node determines whether the number of copies of the specific cloud application-related data stored in the first cluster is greater than the first value after deleting the specific cloud application-related data stored in the first cluster, and sends a feedback message to the first cluster. The feedback message carries information indicating that the first cluster can clear the specific cloud application-related data or carries information indicating that the first cluster cannot clear the specific cloud application-related data. After receiving the feedback message, the first cluster will clear the specific cloud application-related data indicated in the feedback message or not process it according to the content of the feedback message. For another example, when the storage space of the first cluster reaches the warning value, the first cluster can send a clear query request for all cloud application-related data stored in it to the central scheduling node. After receiving the clear query request, the central scheduling node determines, for each cloud application-related data among some or all of the cloud application-related data stored in the first cluster, whether the number of copies of the cloud application-related data of the cloud application stored in the first cluster is greater than the first value after the cloud application-related data of the cloud application stored in the first cluster is deleted. After the cloud application-related data of each cloud application among some or all of the cloud application-related data stored in the first cluster are judged, a feedback message is sent to the first cluster. The feedback message carries information indicating that the first cluster can clear the cloud application-related data (the number of copies corresponding to the cloud application-related data that can be cleared is greater than the first value during the judgment process) or carries information indicating that the first cluster cannot clear the cloud application-related data. After receiving the feedback message, the first cluster will clear the cloud application-related data indicated in the feedback message or not process it according to the content of the feedback message.

[0028] Reference Figure 2 As shown, an embodiment of the present application provides a flow chart of a data storage and distribution method based on cloud applications, the method being applied to a first cluster, including: S20, sending a scheduling application request to the central scheduling node, wherein the scheduling application request is used to request to obtain information of a cluster storing cloud application related data; S21. Receive information of the second cluster sent by the central scheduling node, determine the target node based on the information of the second cluster, and download corresponding files from the target node, wherein the first cluster, the central scheduling node and the second cluster belong to a cluster system, the first cluster and the second cluster are deployed in different Internet data centers (IDC) computer rooms, and the target node is at least one node in the second cluster.

[0029] The data storage and distribution method based on cloud applications provided in the embodiment of the present application no longer uses a third-party storage server to store and distribute cloud application related data, but instead uses a cluster belonging to a cluster system and deployed in an IDC computer room to store and distribute cloud application related data, thereby making full use of the bandwidth of each IDC computer room, reducing the cost of data storage and transmission, and improving efficiency.

[0030] Based on the foregoing method embodiment, the method may further include: Send a purge query request to the central scheduling node; A feedback message sent by the central scheduling node is received, and if the feedback message carries information indicating that the first cluster can clear the specified data, the stored specified data is cleared.

[0031] Reference Figure 3 FIG. 1 is a schematic diagram of a data storage and distribution device based on cloud applications provided in an embodiment of the present application. The device is applied to a central scheduling node and includes: The determining unit 30 is used to receive a scheduling application request sent by the first cluster, and determine a second cluster from the cluster system according to the scheduling application request, wherein the scheduling application request is used to request to obtain information of a cluster storing cloud application related data, the cluster system includes a central scheduling node and multiple clusters, the first cluster and the second cluster are different, the first cluster and the second cluster are each a cluster among the multiple clusters, each cluster is deployed in an Internet data center IDC computer room, and each cluster includes at least one node; The first sending unit 31 is configured to send the information of the second cluster to the first cluster, so that the first cluster determines a target node based on the information of the second cluster and downloads a corresponding file from the target node, wherein the target node is at least one node in the second cluster.

[0032] The data storage and distribution device based on cloud applications provided in the embodiment of the present application no longer stores and distributes cloud application related data through a third-party storage server, but stores and distributes cloud application related data through a cluster belonging to a cluster system and deployed in an IDC computer room, thereby making full use of the bandwidth of each IDC computer room, reducing the cost of data storage and transmission, and improving efficiency.

[0033] Based on the above device embodiment, the determining unit may be used to: Determine at least one candidate cluster from the cluster system according to the scheduling application request, wherein the data requested by the scheduling application request is stored in each candidate cluster in the form of slices; If the number of the candidate clusters is 1, the candidate cluster is determined to be the second cluster; or If the number of candidate clusters is greater than 1, for each candidate cluster, the scheduling priority of the candidate cluster is calculated based on the number of scheduling tasks completed by the candidate cluster, the number of scheduling tasks currently being performed by the candidate cluster, and the number of scheduling times of the scheduling tasks corresponding to the scheduling application request in the candidate cluster, and the candidate cluster with the highest scheduling priority is determined as the second cluster.

[0034] Based on the above device embodiment, the determining unit may be used to: Calculate the first index, the second index, the third index and the fourth index, where the first index T1 = n1 / N, the second index T2 = (P1-n2) / P1, the third index T3 = (M-n3) / M, and the fourth index T4 = (P2-t) / P2, n1 is the number of scheduling tasks completed by the candidate cluster, N is the number of scheduling tasks completed by all clusters in the cluster system, P1 is the set parameter, n2 is the number of scheduling tasks being performed by the candidate cluster, M is the number of all clusters in the cluster system, n3 is the number of scheduling times of the scheduling task corresponding to the scheduling application request in the candidate cluster, P2 is the set parameter, and t is the round-trip delay between the candidate cluster and the first cluster; A weighted sum is taken for the first indicator, the second indicator, the third indicator, and the fourth indicator, and a result of the weighted sum is used as the scheduling priority of the candidate cluster.

[0035] Reference Figure 4 , which is a schematic diagram of a data storage and distribution device based on cloud applications provided in an embodiment of the present application, and is applied to a first cluster, including: A second sending unit 40 is used to send a scheduling application request to the central scheduling node, wherein the scheduling application request is used to request to obtain information of a cluster storing cloud application related data; The download unit 41 is used to receive information of the second cluster sent by the central scheduling node, determine the target node based on the information of the second cluster, and download the corresponding file from the target node, wherein the first cluster, the central scheduling node and the second cluster belong to a cluster system, the first cluster and the second cluster are deployed in different Internet data centers IDC computer rooms, and the target node is at least one node in the second cluster.

[0036] The data storage and distribution device based on cloud applications provided in the embodiment of the present application no longer stores and distributes cloud application related data through a third-party storage server, but stores and distributes cloud application related data through a cluster belonging to a cluster system and deployed in an IDC computer room, thereby making full use of the bandwidth of each IDC computer room, reducing the cost of data storage and transmission, and improving efficiency.

[0037] The data storage and distribution device based on cloud applications provided in the embodiment of the present application has an implementation process that is consistent with the data storage and distribution method based on cloud applications provided in the embodiment of the present application, and the effect that can be achieved is also the same as the data storage and distribution method based on cloud applications provided in the embodiment of the present application, which will not be repeated here.

[0038] like Figure 5 As shown, an electronic device provided by an embodiment of the present application includes: a processor 50, a memory 51 and a bus 52, wherein the memory 51 stores machine-readable instructions executable by the processor 50, and when the electronic device is running, the processor 50 communicates with the memory 51 through the bus 52, and the processor 50 executes the machine-readable instructions to perform the steps of the above-mentioned cloud application-based data storage and distribution method.

[0039] Specifically, the above-mentioned memory 51 and processor 50 can be general-purpose memory and processor, which are not specifically limited here. When the processor 50 runs the computer program stored in the memory 51, it can execute the above-mentioned cloud application-based data storage and distribution method.

[0040] Corresponding to the above-mentioned data storage and distribution method based on cloud applications, an embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned data storage and distribution method based on cloud applications are executed.

[0041] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A data storage and distribution method based on cloud applications, characterized in that: Applied to central dispatching nodes, including: Receive a scheduling application request sent by the first cluster, and determine a second cluster from the cluster system according to the scheduling application request, wherein the scheduling application request is used to request to obtain information of a cluster storing cloud application related data, the cluster system includes a central scheduling node and multiple clusters, the first cluster and the second cluster are different, the first cluster and the second cluster are each one of the multiple clusters, each cluster is deployed in an Internet data center IDC computer room, and each cluster includes at least one node; The information of the second cluster is sent to the first cluster, so that the first cluster determines a target node based on the information of the second cluster and downloads a corresponding file from the target node, wherein the target node is at least one node in the second cluster.

2. The method according to claim 1, characterized in that The step of determining the second cluster from the cluster system according to the scheduling application request includes: Determine at least one candidate cluster from the cluster system according to the scheduling application request, wherein the data requested by the scheduling application request is stored in each candidate cluster in the form of slices; If the number of the candidate clusters is 1, the candidate cluster is determined to be the second cluster; or If the number of candidate clusters is greater than 1, for each candidate cluster, the scheduling priority of the candidate cluster is calculated based on the number of scheduling tasks completed by the candidate cluster, the number of scheduling tasks currently being performed by the candidate cluster, and the number of scheduling times of the scheduling tasks corresponding to the scheduling application request in the candidate cluster, and the candidate cluster with the highest scheduling priority is determined as the second cluster.

3. The method according to claim 2, characterized in that The calculating the scheduling priority of the candidate cluster according to the number of completed scheduling tasks of the candidate cluster, the number of ongoing scheduling tasks of the candidate cluster, and the number of scheduling times of the scheduling tasks corresponding to the scheduling application request in the candidate cluster includes: Calculate the first index, the second index, the third index and the fourth index, where the first index T1 = n1 / N, the second index T2 = (P1-n2) / P1, the third index T3 = (M-n3) / M, and the fourth index T4 = (P2-t) / P2, n1 is the number of scheduling tasks completed by the candidate cluster, N is the number of scheduling tasks completed by all clusters in the cluster system, P1 is the set parameter, n2 is the number of scheduling tasks being performed by the candidate cluster, M is the number of all clusters in the cluster system, n3 is the number of scheduling times of the scheduling task corresponding to the scheduling application request in the candidate cluster, P2 is the set parameter, and t is the round-trip delay between the candidate cluster and the first cluster; A weighted sum is taken for the first indicator, the second indicator, the third indicator, and the fourth indicator, and a result of the weighted sum is used as the scheduling priority of the candidate cluster.

4. The method according to claim 1, characterized in that Also includes: receiving a clear query request sent by the first cluster; After the first cluster clears the specified data, it is determined whether the number of copies of the specified data is greater than a first value. If so, a feedback message is sent to the first cluster, wherein the feedback message carries information indicating that the first cluster can clear the specified data.

5. A data storage and distribution method based on cloud applications, characterized in that: Applied to the first cluster, including: Sending a scheduling application request to the central scheduling node, wherein the scheduling application request is used to request information of a cluster storing cloud application related data; Receive information of the second cluster sent by the central scheduling node, determine the target node based on the information of the second cluster, and download the corresponding file from the target node, wherein the first cluster, the central scheduling node and the second cluster belong to a cluster system, the first cluster and the second cluster are deployed in different Internet data centers (IDC) computer rooms, and the target node is at least one node in the second cluster.

6. The method according to claim 5, characterized in that Also includes: Sending a purge query request to the central dispatch node; A feedback message sent by the central scheduling node is received, and if the feedback message carries information indicating that the first cluster can clear the specified data, the stored specified data is cleared.

7. A data storage and distribution device based on cloud applications, characterized in that: Applied to central dispatching nodes, including: A determination unit is configured to receive a scheduling application request sent by a first cluster, and determine a second cluster from the cluster system according to the scheduling application request, wherein the scheduling application request is used to request information of a cluster storing cloud application related data, the cluster system includes a central scheduling node and multiple clusters, the first cluster and the second cluster are different, the first cluster and the second cluster are each a cluster among multiple clusters, each cluster is deployed in an Internet data center IDC computer room, and each cluster includes at least one node; The first sending unit is used to send the information of the second cluster to the first cluster, so that the first cluster determines a target node based on the information of the second cluster and downloads a corresponding file from the target node, wherein the target node is at least one node in the second cluster.

8. The device according to claim 7, characterized in that The determining unit is used for: Determine at least one candidate cluster from the cluster system according to the scheduling application request, wherein the data requested by the scheduling application request is stored in each candidate cluster in the form of slices; If the number of the candidate clusters is 1, the candidate cluster is determined to be the second cluster; or If the number of candidate clusters is greater than 1, for each candidate cluster, the scheduling priority of the candidate cluster is calculated based on the number of scheduling tasks completed by the candidate cluster, the number of scheduling tasks currently being performed by the candidate cluster, and the number of scheduling times of the scheduling tasks corresponding to the scheduling application request in the candidate cluster, and the candidate cluster with the highest scheduling priority is determined as the second cluster.

9. The device according to claim 8, characterized in that The determining unit is used for: Calculate the first index, the second index, the third index and the fourth index, where the first index T1 = n1 / N, the second index T2 = (P1-n2) / P1, the third index T3 = (M-n3) / M, and the fourth index T4 = (P2-t) / P2, n1 is the number of scheduling tasks completed by the candidate cluster, N is the number of scheduling tasks completed by all clusters in the cluster system, P1 is the set parameter, n2 is the number of scheduling tasks being performed by the candidate cluster, M is the number of all clusters in the cluster system, n3 is the number of scheduling times of the scheduling task corresponding to the scheduling application request in the candidate cluster, P2 is the set parameter, and t is the round-trip delay between the candidate cluster and the first cluster; A weighted sum is taken for the first indicator, the second indicator, the third indicator, and the fourth indicator, and a result of the weighted sum is used as the scheduling priority of the candidate cluster.

10. A data storage and distribution device based on cloud applications, characterized in that: Applied to the first cluster, including: A second sending unit is used to send a scheduling application request to the central scheduling node, wherein the scheduling application request is used to request to obtain information of a cluster storing cloud application related data; A download unit is used to receive information of the second cluster sent by the central scheduling node, determine a target node based on the information of the second cluster, and download corresponding files from the target node, wherein the first cluster, the central scheduling node and the second cluster belong to a cluster system, the first cluster and the second cluster are deployed in different Internet data center IDC computer rooms, and the target node is at least one node in the second cluster.

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