A breadth-first-based opcua model node search method and system

Abstract

The application provides an opcua model node search method and system based on breadth priority. The opcua model node search method comprises the following steps: acquiring associated nodes connected with a root node corresponding to the opcua model, and adding the associated nodes into a list list to form a node list; performing batch browsing on all the associated nodes in the node list; and storing the nodes that have completed the browsing in sequence by using a HashMap until all the associated nodes complete the browsing. The system comprises modules corresponding to the method steps.

Description

Technical Field

[0001] This invention proposes a method and system for node search in the OPCUA model based on breadth-first search, belonging to the field of Internet technology. Background Technology

[0002] Traditionally, when retrieving the information model of OPCUA, a depth-first search approach is typically used. For each node, all related nodes are recursively examined. This method requires multiple network requests, inevitably resulting in a significant amount of time being spent on network communication. Consequently, this reduces the efficiency of retrieving related nodes from the OPCUA information model. Summary of the Invention

[0003] This invention provides a breadth-first search method and system for OPCUA model node search, to solve the problem of low efficiency in acquiring relevant nodes in the information model of PCUA in the prior art. The technical solution adopted is as follows:

[0004] A breadth-first search method for OPCUA model nodes, the OPCUA model node search method comprising:

[0005] Obtain the associated nodes connected to the root node of the Opcua model, and add the associated nodes to the list to form a node list;

[0006] Batch browse all associated nodes in the node list;

[0007] Use a HashMap to store the nodes that have been browsed until all related nodes have been browsed.

[0008] Further, obtain the associated nodes connected to the root node of the Opcua model, and add the associated nodes to a list to form a node list, including:

[0009] Search the opcua model to obtain all root nodes contained within the opcua model;

[0010] For each root node, search for the associated nodes corresponding to that root node to obtain the associated nodes corresponding to each root node;

[0011] The root node is marked with a unique identifier, and all associated nodes corresponding to the root node are marked with the same identifier as the root node.

[0012] Use the unique identifier corresponding to the root node as the first marker, and use the unique identifier on the associated node corresponding to the root node that is the same as the root node as the second marker;

[0013] The root node and associated nodes are both imported into a list, and each list unit contains associated nodes corresponding to the root node.

[0014] Furthermore, batch browsing of all associated nodes in the node list includes:

[0015] Extract each list cell from the node list, and scan the second marker of the associated node in the list cell and the first marker on the root node corresponding to the list cell;

[0016] By comparing the consistency of the first and second tags, it is detected whether the associated nodes in each list unit completely belong to their corresponding root nodes, and the detected list units are obtained.

[0017] For each of the detected list units, the number of associated nodes is considered, and batch browsing is performed on a unit basis.

[0018] Furthermore, by comparing the consistency of the first and second tags, it is detected whether the associated nodes in each list unit completely belong to their corresponding root nodes, including:

[0019] The second mark is compared with the first mark in turn to determine whether the second mark is the same as the first mark;

[0020] When the second tag is the same as the first tag, the associated node corresponding to the second tag is retained in the list unit;

[0021] When the second tag is different from the first tag, the second tag that is different from the first tag of the root node corresponding to the current list unit is taken as the tag to be tested;

[0022] The first label of all root nodes is extracted by traversing and scanning. The first label is then compared with the label to be tested in turn to obtain the first label that is the same as the label to be tested.

[0023] Retrieve the root node and its list unit corresponding to the first mark that is the same as the mark to be tested, and take the list unit corresponding to the first mark that is the same as the mark to be tested as the target unit;

[0024] The associated nodes corresponding to the marker to be tested are imported into the target unit, and after the associated nodes are imported into the target unit, the associated nodes corresponding to the marker to be tested are deleted from the original list unit where the associated nodes corresponding to the marker to be tested are located.

[0025] A breadth-first search system for OPCUA model nodes, the OPCUA model node search system comprising:

[0026] The node list formation module is used to obtain the associated nodes connected to the root node of the opcua model and add the associated nodes to the list to form a node list;

[0027] The batch browsing module is used to browse all associated nodes in the node list in batches;

[0028] The storage module is used to store the nodes that have been browsed sequentially using a HashMap until all associated nodes have been browsed.

[0029] Furthermore, the node list forming module includes:

[0030] The search module is used to search the opcua model and obtain all root nodes contained within the opcua model.

[0031] The associated node acquisition module is used to search for the associated nodes corresponding to each root node, and obtain the associated nodes corresponding to each root node.

[0032] The tagging module is used to uniquely identify the root node and to tag all associated nodes corresponding to the root node with the same identifier as the root node.

[0033] The marker determination module is used to take the unique identifier code corresponding to the root node as the first marker and the unique identifier code on the associated node corresponding to the root node that is the same as the root node as the second marker.

[0034] The import module is used to import both the root node and the associated nodes into the list, and the root node is a list unit, with each list unit containing the associated nodes corresponding to the root node.

[0035] Furthermore, the batch browsing module includes:

[0036] The list extraction module is used to extract each list cell from the node list, and scan the second marker of the associated node in the list cell and the first marker on the root node corresponding to the list cell.

[0037] The consistency comparison module is used to detect whether the associated nodes in each list unit completely belong to their corresponding root nodes by comparing the consistency of the first tag and the second tag, and to obtain the list unit after detection.

[0038] The browsing module is used to perform batch browsing on a per-list-unit basis, based on the number of associated nodes in each of the detected list units.

[0039] Furthermore, the consistency comparison module includes:

[0040] The comparison module is used to compare the second mark with the first mark sequentially to determine whether the second mark is the same as the first mark;

[0041] The node retention module is used to retain the associated node corresponding to the second tag in the list unit when the second tag is the same as the first tag;

[0042] The test tag module is used to take the second tag, which is different from the first tag of the root node corresponding to the current list unit, as the test tag when the second tag is different from the first tag.

[0043] The traversal module is used to traverse and scan all root nodes and extract the first label of all root nodes. The first label is then compared with the label to be tested in turn to obtain the first label that is the same as the label to be tested.

[0044] The target unit acquisition module is used to retrieve the root node and its list unit corresponding to the first mark that is the same as the mark to be tested, and to take the list unit corresponding to the first mark that is the same as the mark to be tested as the target unit;

[0045] The deletion module is used to import the associated nodes corresponding to the test mark into the target unit, and after the associated nodes are imported into the target unit, delete the associated nodes corresponding to the test mark in the original list unit where the associated nodes corresponding to the test mark are located.

[0046] Beneficial effects of this invention:

[0047] This invention proposes a breadth-first search (BFS) method and system for OPCUA model node search. Based on the BFS idea, it first retrieves nodes connected to the root node and adds them to a List, then performs batch browsing on the nodes in the List. A HashMap is used to store all browsed nodes, thus avoiding duplicate access. Because it uses tail recursion, the compiler can optimize the OPCUA model without causing call stack overflow during program execution. This effectively avoids the problem of low node search efficiency during OPCUA model optimization, while also significantly reducing the node search time and bandwidth consumption of the OPCUA model, thereby saving bandwidth. Attached Figure Description

[0048] Figure 1 This is a flowchart of the method described in this invention;

[0049] Figure 2 This is a system block diagram of the system described in this invention. Detailed Implementation

[0050] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0051] This invention proposes a breadth-first search method for OPCUA model nodes, such as... Figure 1 As shown, the OPCUA model node search method includes:

[0052] S1. Obtain the associated nodes connected to the root node of the opcua model, and add the associated nodes to the list to form a node list;

[0053] S2. Perform batch browsing of all associated nodes in the node list;

[0054] S3. Use a HashMap to store the nodes that have been browsed until all related nodes have been browsed.

[0055] The working principle of the above technical solution is as follows: First, obtain the associated nodes connected to the root node of the opcua model and add the associated nodes to a list to form a node list; then, perform batch browsing of all associated nodes in the node list; finally, use a HashMap to store the nodes that have been browsed until all associated nodes have been browsed.

[0056] The advantages of the above technical solution are as follows: The breadth-first search-based OPCUA model node search method proposed in this embodiment is based on the breadth-first search idea. It first obtains the nodes connected to the root node and adds them to a List, then performs batch browsing on the nodes in the List. A HashMap is used to store all browsed nodes, thus avoiding duplicate access. Because it uses a tail-recursive method, the compiler can optimize the OPCUA model without causing call stack overflow during program execution. This effectively avoids the problem of low node search efficiency during OPCUA model optimization, and simultaneously reduces the node search time and bandwidth usage of the OPCUA model, thereby effectively saving bandwidth.

[0057] In one embodiment of the present invention, the associated nodes connected to the root node of the OPCUA model are obtained, and the associated nodes are added to a list to form a node list, including:

[0058] S101. Search the opcua model to obtain all root nodes contained within the opcua model;

[0059] S102. For each root node, search for the associated nodes corresponding to the root node to obtain the associated nodes corresponding to each root node;

[0060] S103. The root node is marked with a unique identifier, and all associated nodes corresponding to the root node are marked with the same identifier as the root node.

[0061] S104. Use the unique identifier code corresponding to the root node as the first mark, and use the unique identifier code on the associated node corresponding to the root node that is the same as the root node as the second mark.

[0062] S105. Import both the root node and the associated nodes into a list, and use the root node as a list unit, with each list unit containing the associated nodes corresponding to the root node.

[0063] The working principle of the above technical solution is as follows: First, the OPCUA model is searched to obtain all root nodes contained within the OPCUA model; then, for each root node, the associated nodes corresponding to the root node are searched to obtain the associated nodes corresponding to each root node; subsequently, the root node is marked with a unique identifier, and all associated nodes corresponding to the root node are marked with the same identifier as the root node; then, the unique identifier corresponding to the root node is used as the first identifier, and the unique identifier on the associated nodes corresponding to the root node that is the same as the root node is used as the second identifier; finally, the root node and associated nodes are both imported into a list, and each list unit contains associated nodes corresponding to the root node.

[0064] The above technical solution has the following effects: it can effectively improve the accuracy and efficiency of obtaining associated nodes in the OPCUA model, while effectively reducing the node search time and bandwidth consumption of the OPCUA model, thereby effectively saving bandwidth.

[0065] One embodiment of the present invention involves batch browsing of all associated nodes in the node list, including:

[0066] S201. Extract each list cell from the node list, and scan the second marker of the associated node in the list cell and the first marker on the root node corresponding to the list cell;

[0067] S202. By comparing the consistency of the first mark and the second mark, detect whether the associated nodes in each list unit completely belong to their corresponding root node, and obtain the detected list unit.

[0068] S203. For each of the detected list units, perform batch browsing on a per-list-unit basis, considering the number of associated nodes in each list unit.

[0069] The working principle of the above technical solution is as follows: First, extract each list unit in the node list, scan the second marker of the associated nodes in the list unit and the first marker on the root node corresponding to the list unit; then, by comparing the consistency of the first marker and the second marker, detect whether the associated nodes in each list unit completely belong to their corresponding root node, and obtain the detected list unit; finally, based on the number of associated nodes in each detected list unit, perform batch browsing on a unit basis.

[0070] The above technical solution has the following effects: it can effectively improve the accuracy and efficiency of obtaining associated nodes in the OPCUA model, while effectively reducing the node search time and bandwidth consumption of the OPCUA model, thereby effectively saving bandwidth.

[0071] In one embodiment of the present invention, detecting whether an associated node in each list unit completely belongs to its corresponding root node by comparing the consistency of a first tag and a second tag includes:

[0072] S2021. Compare the second mark with the first mark in sequence to determine whether the second mark is the same as the first mark;

[0073] S2022. When the second tag is the same as the first tag, the associated node corresponding to the second tag is retained in the list unit;

[0074] S2023. When the second marker is different from the first marker, the second marker that is different from the first marker of the root node corresponding to the current list unit is taken as the marker to be tested.

[0075] S2024. Traverse and scan all root nodes and extract the first label of each root node. Compare the first label with the label to be tested in turn to obtain the first label that is the same as the label to be tested.

[0076] S2025. Retrieve the root node and its list unit corresponding to the first mark that is the same as the mark to be tested, and take the list unit corresponding to the first mark that is the same as the mark to be tested as the target unit;

[0077] S2026. Import the associated node corresponding to the test mark into the target unit, and after the associated node is imported into the target unit, delete the associated node corresponding to the test mark in the original list unit where the associated node corresponding to the test mark is located.

[0078] The working principle of the above technical solution is as follows: First, the second mark is compared with the first mark in turn to determine whether the second mark is the same as the first mark; then, when the second mark is the same as the first mark, the associated node corresponding to the second mark is retained in the list unit; subsequently, when the second mark is different from the first mark, the second mark that is different from the first mark of the root node corresponding to the current list unit is taken as the mark to be tested; then, the first marks of all root nodes are traversed and extracted, and the first marks are compared with the mark to be tested in turn to obtain the first mark that is the same as the mark to be tested; then, the root node and its list unit corresponding to the first mark that is the same as the mark to be tested are retrieved, and the list unit corresponding to the first mark that is the same as the mark to be tested is taken as the target unit; finally, the associated node corresponding to the mark to be tested is imported into the target unit, and after the associated node is imported into the target unit, the associated node corresponding to the mark to be tested is deleted from the original list unit where the associated node corresponding to the mark to be tested is located.

[0079] The above technical solution has the following effects: it can effectively improve the accuracy and efficiency of obtaining associated nodes in the OPCUA model, while effectively reducing the node search time and bandwidth consumption of the OPCUA model, thereby effectively saving bandwidth.

[0080] This invention proposes a breadth-first search system for OPCUA model nodes, such as... Figure 2 As shown, the OPCUA model node search system includes:

[0081] The node list formation module is used to obtain the associated nodes connected to the root node of the opcua model and add the associated nodes to the list to form a node list;

[0082] The batch browsing module is used to browse all associated nodes in the node list in batches;

[0083] The storage module is used to store the nodes that have been browsed sequentially using a HashMap until all associated nodes have been browsed.

[0084] The working principle of the above technical solution is as follows: First, the associated nodes connected to the root node of the opcua model are obtained through the node list forming module, and the associated nodes are added to the list to form a node list; then, the batch browsing module is used to batch browse all the associated nodes in the node list; finally, the storage module uses a HashMap to sequentially store the nodes that have been browsed until all associated nodes have been browsed.

[0085] The advantages of the above technical solution are as follows: The breadth-first search-based OPCUA model node search system proposed in this embodiment is based on the breadth-first search idea. It first obtains nodes connected to the root node and adds them to a List, then performs batch browsing on the nodes in the List. A HashMap is used to store all browsed nodes, thus avoiding duplicate access. Because it uses a tail-recursive method, the compiler can optimize the OPCUA model without causing call stack overflow during program execution. This effectively avoids the problem of low node search efficiency during OPCUA model optimization, and simultaneously reduces the node search time and bandwidth consumption of the OPCUA model, thereby effectively saving bandwidth.

[0086] In one embodiment of the present invention, the node list forming module includes:

[0087] The search module is used to search the opcua model and obtain all root nodes contained within the opcua model.

[0088] The associated node acquisition module is used to search for the associated nodes corresponding to each root node, and obtain the associated nodes corresponding to each root node.

[0089] The tagging module is used to uniquely identify the root node and to tag all associated nodes corresponding to the root node with the same identifier as the root node.

[0090] The marker determination module is used to take the unique identifier corresponding to the root node as the first marker and the unique identifier on the associated node corresponding to the root node that is the same as the root node as the second marker.

[0091] The import module is used to import both the root node and the associated nodes into the list, and the root node is a list unit, with each list unit containing the associated nodes corresponding to the root node.

[0092] The working principle of the above technical solution is as follows: First, the search module searches the opcua model to obtain all the root nodes contained in the opcua model;

[0093] Then, the associated node acquisition module is used to search for the associated nodes corresponding to each root node to obtain the associated nodes corresponding to each root node;

[0094] Then, the root node is uniquely identified using a tagging module, and all associated nodes corresponding to the root node are identified using the same tagging method as the root node.

[0095] Subsequently, the unique identifier corresponding to the root node is used as the first identifier by the tag determination module, and the unique identifier on the associated node corresponding to the root node that is the same as the root node is used as the second identifier.

[0096] Finally, the root node and associated nodes are imported into the list using the import module. Each list unit contains associated nodes corresponding to the root node.

[0097] The above technical solution has the following effects: it can effectively improve the accuracy and efficiency of obtaining associated nodes in the OPCUA model, while effectively reducing the node search time and bandwidth consumption of the OPCUA model, thereby effectively saving bandwidth.

[0098] In one embodiment of the present invention, the batch browsing module includes:

[0099] The list extraction module is used to extract each list cell from the node list, and scan the second marker of the associated node in the list cell and the first marker on the root node corresponding to the list cell.

[0100] The consistency comparison module is used to detect whether the associated nodes in each list unit completely belong to their corresponding root nodes by comparing the consistency of the first tag and the second tag, and to obtain the list unit after detection.

[0101] The browsing module is used to perform batch browsing on a per-list-unit basis, based on the number of associated nodes in each of the detected list units.

[0102] The working principle of the above technical solution is as follows: First, the list extraction module extracts each list unit from the node list, and scans the second marker of the associated nodes in the list unit and the first marker on the root node corresponding to the list unit; then, the consistency comparison module detects whether the associated nodes in each list unit completely belong to their corresponding root node by comparing the consistency of the first marker and the second marker, and obtains the detected list unit; finally, the browsing module performs batch browsing on a unit basis, based on the number of associated nodes in each detected list unit.

[0103] The above technical solution has the following effects: it can effectively improve the accuracy and efficiency of obtaining associated nodes in the OPCUA model, while effectively reducing the node search time and bandwidth consumption of the OPCUA model, thereby effectively saving bandwidth.

[0104] In one embodiment of the present invention, the consistency comparison module includes:

[0105] The comparison module is used to compare the second mark with the first mark sequentially to determine whether the second mark is the same as the first mark;

[0106] The node retention module is used to retain the associated node corresponding to the second tag in the list unit when the second tag is the same as the first tag;

[0107] The test tag module is used to take the second tag, which is different from the first tag of the root node corresponding to the current list unit, as the test tag when the second tag is different from the first tag.

[0108] The traversal module is used to traverse and scan all root nodes and extract the first label of all root nodes. The first label is then compared with the label to be tested in turn to obtain the first label that is the same as the label to be tested.

[0109] The target unit acquisition module is used to retrieve the root node and its list unit corresponding to the first mark that is the same as the mark to be tested, and to take the list unit corresponding to the first mark that is the same as the mark to be tested as the target unit;

[0110] The deletion module is used to import the associated nodes corresponding to the test mark into the target unit, and after the associated nodes are imported into the target unit, delete the associated nodes corresponding to the test mark in the original list unit where the associated nodes corresponding to the test mark are located.

[0111] The working principle of the above technical solution is as follows: First, the comparison module compares the second mark with the first mark in sequence to determine whether the second mark is the same as the first mark;

[0112] Then, using the node retention module, when the second tag is the same as the first tag, the associated node corresponding to the second tag is retained in the list unit;

[0113] Subsequently, when the second mark is different from the first mark, the test mark module takes the second mark, which is different from the first mark of the root node corresponding to the current list unit, as the test mark.

[0114] Then, the traversal module is used to scan and extract the first label of all root nodes. The first label is compared with the label to be tested in turn to obtain the first label that is the same as the label to be tested.

[0115] Then, the target unit acquisition module retrieves the root node and its list unit corresponding to the first mark that is the same as the mark to be tested, and takes the list unit corresponding to the first mark that is the same as the mark to be tested as the target unit;

[0116] Finally, the deletion module is used to import the associated nodes corresponding to the test mark into the target unit, and after the associated nodes are imported into the target unit, the associated nodes corresponding to the test mark are deleted from the original list unit where the associated nodes corresponding to the test mark are located.

[0117] The above technical solution has the following effects: it can effectively improve the accuracy and efficiency of obtaining associated nodes in the OPCUA model, while effectively reducing the node search time and bandwidth consumption of the OPCUA model, thereby effectively saving bandwidth.

[0118] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A breadth-first search method for OPCUA model nodes, characterized in that, The OPCUA model node search method includes: Obtain the associated nodes connected to the root node of the Opcua model, and add the associated nodes to the list to form a node list; Batch browse all associated nodes in the node list; Use a HashMap to store the nodes that have been browsed until all related nodes have been browsed; Batch browsing of all associated nodes in the node list includes: Extract each list cell from the node list, and scan the second marker of the associated node in the list cell and the first marker on the root node corresponding to the list cell; By comparing the consistency of the first and second tags, it is detected whether the associated nodes in each list unit completely belong to their corresponding root nodes, and the detected list units are obtained. For each of the detected list units, batch browsing is performed on a unit basis, considering the number of associated nodes in each list unit. Specifically, by comparing the consistency of the first and second tags, it is determined whether the associated nodes in each list unit completely belong to their corresponding root nodes, including: The second mark is compared with the first mark in turn to determine whether the second mark is the same as the first mark; When the second tag is the same as the first tag, the associated node corresponding to the second tag is retained in the list unit; When the second tag is different from the first tag, the second tag, which is different from the first tag of the root node corresponding to the current list unit, is taken as the tag to be tested; The first label of all root nodes is extracted by traversing and scanning. The first label is then compared with the label to be tested in turn to obtain the first label that is the same as the label to be tested. Retrieve the root node and its list unit corresponding to the first mark that is the same as the mark to be tested, and take the list unit corresponding to the first mark that is the same as the mark to be tested as the target unit; The associated nodes corresponding to the marker to be tested are imported into the target unit, and after the associated nodes are imported into the target unit, the associated nodes corresponding to the marker to be tested are deleted from the original list unit where the associated nodes corresponding to the marker to be tested are located.

2. The OPCUA model node search method according to claim 1, characterized in that, Obtain the associated nodes connected to the root node of the OPCUA model, and add the associated nodes to a list to form a node list, including: Search the opcua model to obtain all root nodes contained within the opcua model; For each root node, search for the associated nodes corresponding to that root node to obtain the associated nodes corresponding to each root node; The root node is marked with a unique identifier, and all associated nodes corresponding to the root node are marked with the same identifier as the root node. Use the unique identifier corresponding to the root node as the first marker, and use the unique identifier on the associated node corresponding to the root node that is the same as the root node as the second marker; The root node and associated nodes are both imported into a list, and each list unit contains associated nodes corresponding to the root node.

3. A breadth-first search system for OPCUA model nodes, characterized in that, The Opcua model node search system includes: The node list formation module is used to obtain the associated nodes connected to the root node of the opcua model and add the associated nodes to the list to form a node list; The batch browsing module is used to browse all associated nodes in the node list in batches; The storage module is used to store the nodes that have been browsed sequentially using a HashMap until all associated nodes have been browsed. The batch browsing module includes: The list extraction module is used to extract each list cell from the node list, and scan the second marker of the associated node in the list cell and the first marker on the root node corresponding to the list cell. The consistency comparison module is used to detect whether the associated nodes in each list unit completely belong to their corresponding root nodes by comparing the consistency of the first tag and the second tag, and to obtain the list unit after detection. The browsing module is used to perform batch browsing on a unit basis, based on the number of associated nodes in each of the detected list units. The consistency comparison module includes: The comparison module is used to compare the second mark with the first mark sequentially to determine whether the second mark is the same as the first mark; The node retention module is used to retain the associated node corresponding to the second tag in the list unit when the second tag is the same as the first tag; The test tag module is used to take the second tag, which is different from the first tag of the root node corresponding to the current list unit, as the test tag when the second tag is different from the first tag. The traversal module is used to traverse and scan all root nodes and extract the first label of all root nodes. The first label is then compared with the label to be tested in turn to obtain the first label that is the same as the label to be tested. The target unit acquisition module is used to retrieve the root node and its list unit corresponding to the first mark that is the same as the mark to be tested, and to take the list unit corresponding to the first mark that is the same as the mark to be tested as the target unit; The deletion module is used to import the associated nodes corresponding to the test mark into the target unit, and after the associated nodes are imported into the target unit, delete the associated nodes corresponding to the test mark in the original list unit where the associated nodes corresponding to the test mark are located.

4. The OPCUA model node search system according to claim 3, characterized in that, The node list forming module includes: The search module is used to search the opcua model and obtain all root nodes contained within the opcua model. The associated node acquisition module is used to search for the associated nodes corresponding to each root node, and obtain the associated nodes corresponding to each root node. The tagging module is used to uniquely identify the root node and to tag all associated nodes corresponding to the root node with the same identifier as the root node. The marker determination module is used to take the unique identifier corresponding to the root node as the first marker and the unique identifier on the associated node corresponding to the root node that is the same as the root node as the second marker. The import module is used to import both the root node and the associated nodes into the list, and the root node is a list unit, with each list unit containing the associated nodes corresponding to the root node.

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