Chain table-based node data integration method, system, terminal and storage medium

Abstract

This invention relates to the field of cloud computing and big data technology, specifically providing a linked list-based method, system, terminal, and storage medium for integrating node data. The method includes: exporting node monitoring data from all partitions of a private cloud system; and integrating the node monitoring data from all partitions using a recursive processing model to obtain an integrated linked list with the node data arranged in sequence. This invention achieves rapid and automated integration of node data, improving the speed of application deployment, ensuring data center stability, reducing data center management costs, and enhancing the user experience.

Description

Technical Field

[0001] This invention relates to the fields of cloud computing and big data technology, specifically to a method, system, terminal, and storage medium for integrating node data based on a linked list. Background Technology

[0002] Currently, the digital transformation and upgrading of society cannot be separated from intelligent transformation. With the integration of cloud computing and big data into various industries, we are entering an era of intelligent computing. The total amount of data in society is growing explosively, and the demand for computing power is increasing significantly. Computing power is becoming the core driving force for the development of the digital economy. It is common for data centers in government, state-owned enterprises, and the Internet to have hundreds, thousands, or even tens of thousands of physical nodes. It is also common for the entire system to contain multiple data centers. Common examples include disaster recovery solutions with two sites and three centers, and a partition in each city in a private cloud system. In such systems, different data centers or partitions are relatively physically or logically isolated. The data between these partitions is relatively independent, but in many cases, it is necessary to integrate the full data of the entire system (such as the CPU utilization data of all virtual machines in all partitions) for auditing or problem location. For example, in a private cloud system, there are two partitions, regionone and regiontwo. The virtual machine data (CPU utilization from low to high) in regionone can be exported through monitoring data, and the virtual machine data (CPU utilization from low to high) in regiontwo can also be exported through monitoring data. The ability to quickly and accurately integrate all virtual machine data of the entire system when problems occur in a massive data center or when statistical audits are required is key to accelerating the deployment of cloud computing and big data applications, ensuring data center stability, reducing data center management costs, and improving user experience. Summary of the Invention

[0003] To address the problem that existing technologies can only monitor partitioned data and cannot integrate partitioned monitoring data as a whole, resulting in high management costs for data centers, this invention provides a linked list-based node data integration method, system, terminal, and storage medium to solve the aforementioned technical problems.

[0004] In a first aspect, the present invention provides a method for integrating node data based on a linked list, comprising:

[0005] Export node monitoring data for all partitions from the private cloud system;

[0006] A recursive processing model is used to integrate the node monitoring data of all partitions, resulting in an integrated linked list in which the node data is arranged in sequence.

[0007] Furthermore, export node monitoring data for all partitions from the private cloud system, including:

[0008] Traverse all partitions of the private cloud system and export the node monitoring data linked list for each partition. The node monitoring data linked list stores the monitoring data of all virtual machine nodes in the partition. The virtual machine node monitoring data in the node monitoring data linked list is arranged in ascending order, and the monitoring data includes CPU utilization.

[0009] Furthermore, after exporting node monitoring data for all partitions from the private cloud system, the method further includes:

[0010] The newly acquired node monitoring data linked list for each partition is cached in the specified path of the management node, and the historical data in the specified path is cleared.

[0011] Furthermore, a recursive processing model is used to integrate the node monitoring data of all partitions, resulting in an integrated linked list with the node data arranged in sequence, including:

[0012] The recursive processing model filters out the head node from the node monitoring data of all partitions.

[0013] The execution pointer of the recursive processing model is set to point to a data package, which includes node monitoring data of the partition to which the head node belongs, excluding the head node, and node monitoring data of other partitions, where other partitions refer to partitions other than the partition to which the head node belongs.

[0014] Furthermore, the recursive processing model filters out the head node from the node monitoring data of all partitions, including:

[0015] The recursive processing model is defined as f(x) = x + f(x-1). The recursive function selects the minimum value from all node monitoring data and uses the minimum value as the head node.

[0016] Furthermore, after selecting the head node, the method further includes:

[0017] Save the head node data to the initial position of the integrated linked list;

[0018] The execution pointer is used to re-select the minimum value from the data package as the new sort value, and the new sort value is saved to the next position of the existing data in the integrated linked list;

[0019] Remove the new sort value from the data package to update the data package;

[0020] The execution pointer is used repeatedly to filter and sort values ​​from the latest data package until the data package is empty, and the sort values ​​selected each time are saved to the integrated linked list.

[0021] Furthermore, after selecting the head node, the method further includes:

[0022] Use the monitoring data linked list of the node containing the head node as the base linked list;

[0023] Using a recursive processing model, the node monitoring data from the node monitoring data linked lists of other partitions are inserted into the base linked list in ascending order;

[0024] After the node monitoring data of other partitions is sequentially inserted into the basic linked list, the basic linked list is output as an integrated linked list.

[0025] Secondly, the present invention provides a node data integration system based on a linked list, comprising:

[0026] The data export unit is used to export node monitoring data from all partitions of the private cloud system.

[0027] The data integration unit is used to integrate the node monitoring data of all partitions using a recursive processing model, resulting in an integrated linked list in which the node data is arranged in order.

[0028] Furthermore, the data export unit is specifically used for:

[0029] Traverse all partitions of the private cloud system and export the node monitoring data linked list for each partition. The node monitoring data linked list stores the monitoring data of all virtual machine nodes in the partition. The virtual machine node monitoring data in the node monitoring data linked list is arranged in ascending order, and the monitoring data includes CPU utilization.

[0030] Furthermore, after exporting node monitoring data for all partitions from the private cloud system, the system also performs the following:

[0031] The newly acquired node monitoring data linked list for each partition is cached in the specified path of the management node, and the historical data in the specified path is cleared.

[0032] Furthermore, the data integration unit is specifically used for:

[0033] The recursive processing model filters out the head node from the node monitoring data of all partitions.

[0034] The execution pointer of the recursive processing model is set to point to a data package, which includes node monitoring data of the partition to which the head node belongs, excluding the head node, and node monitoring data of other partitions, where other partitions refer to partitions other than the partition to which the head node belongs.

[0035] Furthermore, the recursive processing model filters out the head node from the node monitoring data of all partitions, including:

[0036] The recursive processing model is defined as f(x) = x + f(x-1). The recursive function selects the minimum value from all node monitoring data and uses the minimum value as the head node.

[0037] Furthermore, after selecting the head node, the following is also executed:

[0038] Save the head node data to the initial position of the integrated linked list;

[0039] The execution pointer is used to re-select the minimum value from the data package as the new sort value, and the new sort value is saved to the next position of the existing data in the integrated linked list;

[0040] Remove the new sort value from the data package to update the data package;

[0041] The execution pointer is used repeatedly to filter and sort values ​​from the latest data package until the data package is empty, and the sort values ​​selected each time are saved to the integrated linked list.

[0042] Furthermore, after selecting the head node, the following is also executed:

[0043] Use the monitoring data linked list of the node containing the head node as the base linked list;

[0044] Using a recursive processing model, the node monitoring data from the node monitoring data linked lists of other partitions are inserted into the base linked list in ascending order;

[0045] After the node monitoring data of other partitions is sequentially inserted into the basic linked list, the basic linked list is output as an integrated linked list.

[0046] Thirdly, a terminal is provided, including:

[0047] Processor, memory, among which,

[0048] This memory is used to store computer programs.

[0049] The processor is used to retrieve and run the computer program from memory, causing the terminal to perform the terminal method described above.

[0050] Fourthly, a computer storage medium is provided, wherein instructions are stored therein, which, when executed on a computer, cause the computer to perform the methods described in the above aspects.

[0051] The beneficial effects of the present invention are that the node data integration method, system, terminal and storage medium based on linked lists provided by the present invention, after exporting the node monitoring data of each partition of the private cloud system, integrates the node monitoring data of each partition using a recursive processing model, realizing the function of quickly and automatically integrating node data, thereby improving the rapid deployment and launch of applications, ensuring the stability of the data center, reducing the investment in data center management costs, and improving the user experience.

[0052] Furthermore, the design principle of this invention is reliable, the structure is simple, and it has a very wide range of application prospects. Attached Figure Description

[0053] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0054] Figure 1 This is a schematic flowchart of a method according to an embodiment of the present invention.

[0055] Figure 2 This is a schematic block diagram of a system according to an embodiment of the present invention.

[0056] Figure 3 This is a schematic diagram of the structure of a terminal provided in an embodiment of the present invention. Detailed Implementation

[0057] To enable those skilled in the art to better understand the technical solutions of this invention, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this invention.

[0058] The key terms used in this invention will be explained below.

[0059] Private clouds are built for the exclusive use of a single customer, thus providing the most effective control over data, security, and quality of service. The company owns the infrastructure and can control how applications are deployed on that infrastructure. Private clouds can be deployed within the firewall of an enterprise data center or in a secure hosting facility; the core attribute of a private cloud is dedicated resources.

[0060] A recursive algorithm in computer science is a method for solving a problem by repeatedly breaking it down into similar subproblems. Recursive methods can be used to solve many computer science problems, making it a very important concept in the field.

[0061] Figure 1 This is a schematic flowchart illustrating a method according to an embodiment of the present invention. Wherein, Figure 1 The executing entity can be a linked list-based node data integration system.

[0062] like Figure 1 As shown, the method includes:

[0063] Step 110: Export node monitoring data for all partitions from the private cloud system;

[0064] Step 120: Use a recursive processing model to integrate the node monitoring data of all partitions to obtain an integrated linked list in which the node data is arranged in order.

[0065] The recursive approach of the recursive processing model is as follows: a function calls itself during runtime; this function is called a recursive function, and the process of calling itself is called recursion. For example, define the function f(x) = x + f(x-1); 1) Start from the linked list with the smaller head node (e.g., l2), and let the next pointer point to a package containing: the rest of the l2 linked list excluding the head node and the entire l1 linked list; 2) Open the package from step 1), starting from the linked list with the smaller head node (e.g., l1), and let the next pointer point to a package containing: the rest of the l1 linked list excluding the head node and the entire l2 linked list; 3) Continue opening packages according to the above pattern until one of the linked lists contains only null in the package, then stop.

[0066] This method, after exporting the node monitoring data of each partition of the private cloud system, uses a recursive processing model to integrate the node monitoring data of each partition, realizing the function of quickly and automatically integrating node data. This improves the rapid deployment and launch of applications, ensures the stability of the data center, reduces the investment in data center management costs, and enhances the user experience.

[0067] To facilitate understanding of the present invention, the following description further illustrates the node data integration method based on linked lists provided by the present invention, using the principle of the linked list-based node data integration method and the process of integrating node data in the embodiments.

[0068] The existing method for integrating node data is to export monitoring data for all virtual machines from the regionone partition, then export the monitoring data for all virtual machines from the regiontwo partition, and then manually process the data using an Excel spreadsheet to obtain the data for all virtual machines (CPU utilization from low to high). However, due to the large number of partitions in the private cloud system, manually processing massive amounts of node monitoring data is inefficient and prone to data omissions.

[0069] To address the aforementioned situation, this invention proposes a linked list-based node data integration method, providing a complete and rapid approach to integrating node data in a data center business environment built on cloud computing and big data. This method utilizes a higher-performance recursive algorithm to achieve rapid and automated node data integration, thereby improving application deployment speed, ensuring data center stability, reducing data center management costs, and enhancing user experience. Specifically, the linked list-based node data integration method includes:

[0070] S1. Export node monitoring data for all partitions from the private cloud system.

[0071] Traverse all partitions of the private cloud system and export the node monitoring data linked list for each partition. The node monitoring data linked list stores the monitoring data of all virtual machine nodes in the partition. The virtual machine node monitoring data in the node monitoring data linked list is arranged in ascending order, and the monitoring data includes CPU utilization.

[0072] Specifically, the management center periodically sends encryption requests to each partition control node, and these requests can be encrypted using a public key. Upon receiving the encryption request, each partition control node decrypts it and uploads the partition's monitoring data list to the management center based on the decrypted request. This prevents malicious requests from arbitrarily obtaining monitoring data.

[0073] The monitoring data in the partition's monitoring data list is arranged in ascending order, and the monitoring data includes CPU utilization. For example, the node monitoring data list for partition 1 is shown in the table below:

[0074] Table 1. Node monitoring data linked list for partition 1

[0075] Virtual machine number CPU utilization Virtual machine k 10％ Virtual machine i 30％ … …

[0076] The data sorting method for the node monitoring data linked list of each partition is the same as that in Table 1. The node monitoring data linked lists of all received partitions are cached in the specified path of the management node. Before storing a new linked list in this path, the historical linked list with the same name as the new linked list is searched in this path, the historical linked list is cleared and the new linked list is stored.

[0077] S2. Use a recursive processing model to integrate the node monitoring data of all partitions to obtain an integrated linked list in which the node data is arranged in order.

[0078] The recursive processing model filters out the head node from the node monitoring data of all partitions. The execution pointer of the recursive processing model is set to point to a data package, which includes node monitoring data of the partition to which the head node belongs (excluding the head node itself) and node monitoring data of other partitions (excluding the partition to which the head node belongs). The function of the recursive processing model is defined as f(x) = x + f(x-1), which filters out the minimum value from all node monitoring data and uses this minimum value as the head node. The head node data is saved to the initial position of the integrated linked list. The execution pointer is used to re-filter the minimum value from the data package as the new sort value, and the new sort value is saved to the position after the existing data in the integrated linked list. The new sort value is removed from the data package to update the data package. The execution pointer is used repeatedly to filter the sort value from the latest data package until the data package is empty, and the sort value selected each time is saved to the integrated linked list.

[0079] Specifically, a function that calls itself during runtime is called a recursive function, and the process of calling itself is called recursion. For example, define the function f(x) = x + f(x - 1); 1) Start from the linked list with the smaller head node (e.g., l2), and let the next pointer point to a package containing: the rest of the l2 linked list excluding the head node and the entire l1 linked list; 2) Open the package from step 1), starting from the linked list with the smaller head node (e.g., l1), and let the next pointer point to a package containing: the rest of the l1 linked list excluding the head node and the entire l2 linked list; 3) Continue opening packages according to the above pattern until one of the linked lists contains only null in the package, then stop.

[0080] The recursive processing model described above can integrate the node monitoring data from all partitions to obtain an integrated list. The entire process requires no manual intervention, making it convenient and fast.

[0081] In another preferred embodiment of the present invention, the node monitoring data linked list containing the head node is used as the base linked list; a recursive processing model is used to insert the node monitoring data from the node monitoring data linked lists of other partitions into the base linked list in ascending order; after the node monitoring data from other partitions is inserted into the base linked list in sequence, the base linked list is output as an integrated linked list. Specifically, the steps include:

[0082] Step 1: Treat the virtual machines in regionone as linked list l1, sorted by CPU utilization from smallest to largest, and treat the virtual machines in regiontwo as linked list l2, sorted by CPU utilization from smallest to largest.

[0083] Step 2: If linked list l1 is null, return linked list l2 as the merge result; or if linked list l2 is null, return linked list l1 as the merge result.

[0084] Step 3: If the head node of linked list l1 is smaller, merge linked list l1.next and linked list l2, and assign the merged result to linked list l1.next (attached to the end of linked list l1); if the head node of linked list l2 is smaller, merge linked list l1 and linked list l2.next, and assign the merged result to linked list l2.next (attached to the end of linked list l2).

[0085] The following is the core code that implements this function using a recursive algorithm:

[0086]

[0087] / / If linked list l2 is empty, return linked list l1.

[0088] if (l2 == NULL) {

[0089] return l1;

[0090] }

[0091] / / If the head node of linked list l1 is smaller, merge linked list l1.next and linked list l2, and assign the merged result to linked list l1.next.

[0092] if (l1->val <= l2->val) {

[0093] l1->next=mergeTwoLists(l1->next,l2);

[0094] return l1;

[0095] }

[0096] / / If the head node of linked list l2 is smaller, then merge linked lists l1 and l2.next, and assign the merged result to linked list l2.next.

[0097] l2->next=mergeTwoLists(l1,l2->next);

[0098] return l2;

[0099] }

[0100] };

[0101] The above three steps complete a method for integrating node data based on a linked list.

[0102] When using this implementation method, there is no need to recreate the linked list. By merging the linked lists of each partition, the integration efficiency is further improved.

[0103] like Figure 2 As shown, the system 200 includes:

[0104] Data export unit 210 is used to export node monitoring data of all partitions from the private cloud system;

[0105] The data integration unit 220 is used to integrate the node monitoring data of all partitions using a recursive processing model to obtain an integrated linked list in which the node data is arranged in order.

[0106] The recursive approach of the data integration unit is as follows: a function calls itself during runtime; this function is called a recursive function, and the calling process is called recursion. For example, define the function f(x) = x + f(x-1); 1) Start from the linked list with the smaller head node (e.g., l2), and the next pointer points to a package containing: the rest of the l2 linked list excluding the head node and the entire l1 linked list; 2) Open the package from step 1), starting from the linked list with the smaller head node (e.g., l1), and the next pointer points to a package containing: the rest of the l1 linked list excluding the head node and the entire l2 linked list; 3) Continue opening packages according to the above pattern until one of the linked lists contains only null in the package, then stop.

[0107] Optionally, as an embodiment of the present invention, the data export unit is specifically used for:

[0108] Traverse all partitions of the private cloud system and export the node monitoring data linked list for each partition. The node monitoring data linked list stores the monitoring data of all virtual machine nodes in the partition. The virtual machine node monitoring data in the node monitoring data linked list is arranged in ascending order, and the monitoring data includes CPU utilization.

[0109] Optionally, as an embodiment of the present invention, after exporting the node monitoring data of all partitions from the private cloud system, the system further performs the following:

[0110] The newly acquired node monitoring data linked list for each partition is cached in the specified path of the management node, and the historical data in the specified path is cleared.

[0111] Optionally, as an embodiment of the present invention, the data integration unit is specifically used for:

[0112] The recursive processing model filters out the head node from the node monitoring data of all partitions.

[0113] The execution pointer of the recursive processing model is set to point to a data package, which includes node monitoring data of the partition to which the head node belongs, excluding the head node, and node monitoring data of other partitions, where other partitions refer to partitions other than the partition to which the head node belongs.

[0114] Optionally, as an embodiment of the present invention, the recursive processing model filters out the head node from the node monitoring data of all partitions, including:

[0115] The recursive processing model is defined as f(x) = x + f(x-1). The recursive function selects the minimum value from all node monitoring data and uses the minimum value as the head node.

[0116] Optionally, as an embodiment of the present invention, after selecting the head node, the following is also performed:

[0117] Save the head node data to the initial position of the integrated linked list;

[0118] The execution pointer is used to re-select the minimum value from the data package as the new sort value, and the new sort value is saved to the next position of the existing data in the integrated linked list;

[0119] Remove the new sort value from the data package to update the data package;

[0120] The execution pointer is used repeatedly to filter and sort values ​​from the latest data package until the data package is empty, and the sort values ​​selected each time are saved to the integrated linked list.

[0121] The recursive processing model described above can integrate the node monitoring data from all partitions to obtain an integrated list. The entire process requires no manual intervention, making it convenient and fast.

[0122] Optionally, as an embodiment of the present invention, after selecting the head node, the following is also performed:

[0123] Use the monitoring data linked list of the node containing the head node as the base linked list;

[0124] Using a recursive processing model, the node monitoring data from the node monitoring data linked lists of other partitions are inserted into the base linked list in ascending order;

[0125] After the node monitoring data of other partitions is sequentially inserted into the basic linked list, the basic linked list is output as an integrated linked list.

[0126] When using this implementation method, there is no need to recreate the linked list. By merging the linked lists of each partition, the integration efficiency is further improved.

[0127] Figure 3This is a schematic diagram of the structure of a terminal 300 provided in an embodiment of the present invention. The terminal 300 can be used to execute the node data integration method based on a linked list provided in an embodiment of the present invention.

[0128] The terminal 300 may include a processor 310, a memory 320, and a communication unit 330. These components communicate via one or more buses. Those skilled in the art will understand that the server structure shown in the figure does not constitute a limitation of the present invention. It may be a bus topology or a star topology, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0129] The memory 320 can be used to store the execution instructions of the processor 310. The memory 320 can be implemented by any type of volatile or non-volatile memory terminal or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. When the execution instructions in the memory 320 are executed by the processor 310, the terminal 300 is able to perform some or all of the steps in the above method embodiments.

[0130] The processor 310 serves as the control center of the storage terminal, connecting various parts of the electronic terminal via various interfaces and lines. It executes software programs and / or modules stored in the memory 320, and calls data stored in the memory to perform various functions of the electronic terminal and / or process data. The processor can be composed of integrated circuits (ICs), such as a single packaged IC or multiple packaged ICs with the same or different functions connected together. For example, the processor 310 may consist only of a central processing unit (CPU). In this embodiment of the invention, the CPU may have a single processing core or include multiple processing cores.

[0131] The communication unit 330 is used to establish a communication channel, enabling the storage terminal to communicate with other terminals. It can receive user data sent by other terminals or send user data to other terminals.

[0132] The present invention also provides a computer storage medium, wherein the computer storage medium may store a program, which, when executed, may include some or all of the steps provided in the embodiments of the present invention. The storage medium may be a magnetic disk, an optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0133] Therefore, after exporting the node monitoring data of each partition of the private cloud system, the present invention uses a recursive processing model to integrate the node monitoring data of each partition, thereby realizing the function of quickly and automatically integrating node data. This improves the rapid deployment and launch of applications, ensures the stability of the data center, reduces the investment in data center management costs, and improves the user experience. The technical effects achieved by this embodiment can be found in the description above, and will not be repeated here.

[0134] Those skilled in the art will clearly understand that the techniques in the embodiments of the present invention can be implemented using software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions in the embodiments of the present invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, or any other medium capable of storing program code. It includes several instructions to cause a computer terminal (which may be a personal computer, a server, or a second terminal, a network terminal, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0135] The same or similar parts between the various embodiments in this specification can be referred to mutually. In particular, the terminal embodiments are basically similar to the method embodiments, so the description is relatively simple, and the relevant parts can be referred to the description in the method embodiments.

[0136] In the embodiments provided by this invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between systems or units may be electrical, mechanical, or other forms.

[0137] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0138] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0139] Although the present invention has been described in detail with reference to the accompanying drawings and preferred embodiments, the invention is not limited thereto. Various equivalent modifications or substitutions can be made to the embodiments of the invention by those skilled in the art without departing from the spirit and essence of the invention, and such modifications or substitutions should all be within the scope of the invention. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the invention should also be covered within the protection scope of the invention. Therefore, the protection scope of the invention should be determined by the scope of the claims.

Claims

1. A method for integrating node data based on a linked list, characterized in that, include: Export node monitoring data for all partitions from the private cloud system; The node monitoring data of all partitions is integrated using a recursive processing model to obtain an integrated linked list in which the node data is arranged in order. Export node monitoring data for all partitions from the private cloud system, including: Traverse all partitions of the private cloud system and export the node monitoring data linked list for each partition. The node monitoring data linked list stores the monitoring data of all virtual machine nodes in the partition. The virtual machine node monitoring data in the node monitoring data linked list is arranged in ascending order, and the monitoring data includes CPU utilization. A recursive processing model is used to integrate the node monitoring data of all partitions, resulting in an integrated linked list in which the node data is arranged sequentially, including: The recursive processing model filters out the head node from the node monitoring data of all partitions. The execution pointer of the recursive processing model is set to point to a data package, which includes node monitoring data of the partition to which the head node belongs, excluding the head node, and node monitoring data of other partitions, where other partitions refer to partitions other than the partition to which the head node belongs.

2. The method according to claim 1, characterized in that, After exporting node monitoring data for all partitions from the private cloud system, the method further includes: The newly acquired node monitoring data linked list for each partition is cached in the specified path of the management node, and the historical data in the specified path is cleared.

3. The method according to claim 1, characterized in that, The recursive processing model filters out the head nodes from the node monitoring data of all partitions, including: The recursive processing model is defined as f(x) = x + f(x-1). The recursive function selects the minimum value from all node monitoring data and uses the minimum value as the head node.

4. The method according to claim 3, characterized in that, After selecting the head node, the method further includes: Save the head node data to the initial position of the integrated linked list; The execution pointer is used to re-select the minimum value from the data package as the new sort value, and the new sort value is saved to the next position of the existing data in the integrated linked list; Remove the new sort value from the data package to update the data package; The execution pointer is used repeatedly to filter and sort values ​​from the latest data package until the data package is empty, and the sort values ​​selected each time are saved to the integrated linked list.

5. The method according to claim 4, characterized in that, After selecting the head node, the method further includes: Use the monitoring data linked list of the node containing the head node as the base linked list; Using a recursive processing model, the node monitoring data from the node monitoring data linked lists of other partitions are inserted into the base linked list in ascending order; After the node monitoring data of other partitions is sequentially inserted into the basic linked list, the basic linked list is output as an integrated linked list.

6. A node data integration system based on a linked list, characterized in that, include: The data export unit is used to export node monitoring data from all partitions of the private cloud system. The data integration unit is used to integrate the node monitoring data of all partitions using a recursive processing model to obtain an integrated linked list in which the node data is arranged in order. Export node monitoring data for all partitions from the private cloud system, including: Traverse all partitions of the private cloud system and export the node monitoring data linked list for each partition. The node monitoring data linked list stores the monitoring data of all virtual machine nodes in the partition. The virtual machine node monitoring data in the node monitoring data linked list is arranged in ascending order, and the monitoring data includes CPU utilization. A recursive processing model is used to integrate the node monitoring data of all partitions, resulting in an integrated linked list in which the node data is arranged sequentially, including: The recursive processing model filters out the head node from the node monitoring data of all partitions. The execution pointer of the recursive processing model is set to point to a data package, which includes node monitoring data of the partition to which the head node belongs, excluding the head node, and node monitoring data of other partitions, where other partitions refer to partitions other than the partition to which the head node belongs.

7. A terminal, characterized in that, include: processor; Memory used to store the processor's execution instructions; The processor is configured to perform the method according to any one of claims 1-5.

8. A computer-readable storage medium storing a computer program, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-5.

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