Traffic conversion analysis method and device, storage medium and electronic equipment

Abstract

The specification discloses a traffic conversion analysis method and device, a storage medium and an electronic device, and relates to the technical field of computers. The method comprises the following steps: obtaining a traffic query instruction for a service path link graph, determining a service path tree structure corresponding to the service path link graph through the traffic query instruction, traversing each service path node based on the service path tree structure, obtaining a reference attribution node, a path constraint node and a traffic query parameter corresponding to the service path node, obtaining a traffic query statement corresponding to the service path node according to the reference attribution node, the path constraint node and the traffic query parameter, executing the traffic query statement to obtain traffic query data corresponding to the service path node, and performing traffic conversion analysis processing to obtain a service conversion analysis result.

Description

Technical Field

[0001] This specification relates to the field of computer technology, and in particular to a flow conversion analysis method, apparatus, storage medium, and electronic device. Background Technology

[0002] In the fields of digital operations and user data analytics, monitoring and analyzing the user conversion funnel is a core means of assessing service health. Conversion leakage refers to the phenomenon of users dropping out before proceeding to the next stage in the process of completing the target service. Conversion leakage analysis aims to track user drop-off at each stage of the service process and calculate conversion rates to guide service optimization strategies.

[0003] In related technologies, common conversion leakage analysis typically relies on modeling the transaction chain, such as the direct calculation of single-node query methods and the hierarchical constraint-based single-link strict leakage model. While these two methods can achieve basic monitoring functions in simple linear conversion chains, they are prone to problems such as conversion rate distortion and multi-source data conflicts when facing the complex mesh topology of modern services. Therefore, improving the accuracy of user conversion analysis data is a technical problem that urgently needs to be solved. Summary of the Invention

[0004] This specification provides a flow conversion analysis method, apparatus, storage medium, and electronic device, the technical solution of which is as follows: Firstly, this specification provides a traffic conversion analysis method, the method comprising: Obtain traffic query instructions for the service path link graph, and determine the service path tree structure corresponding to the service path link graph based on the traffic query instructions; Based on the service path tree structure, traverse each service path node to determine the base node, path constraint node and traffic query parameters corresponding to the service path node. The traffic query statement corresponding to the service path node is determined based on the baseline home node, path constraint node, and traffic query parameters. Execute the traffic query statement to obtain the traffic query data corresponding to the service path node, and perform traffic conversion analysis based on the traffic query data to obtain the service conversion analysis results.

[0005] Secondly, this specification provides a flow conversion analysis device, the device comprising: The structure data determination module is used to obtain traffic query instructions for the service path link graph and determine the service path tree structure corresponding to the service path link graph based on the traffic query instructions. The node data acquisition module is used to traverse each service path node based on the service path tree structure and determine the baseline home node, path constraint node and traffic query parameters corresponding to the service path node. The query statement determination module is used to determine the traffic query statement corresponding to the service path node based on the baseline home node, path constraint node, and traffic query parameters. The conversion analysis and processing module is used to execute traffic query statements to obtain traffic query data corresponding to service path nodes, and to perform traffic conversion analysis and processing based on the traffic query data to obtain service conversion analysis results.

[0006] Thirdly, this specification provides a computer storage medium having multiple instructions adapted to be loaded by a processor and executed by the method described above.

[0007] Fourthly, this specification provides a computer program product that stores at least one instruction, which is loaded by a processor and executes the method described above.

[0008] Fifthly, this specification provides an electronic device that may include: a memory and a processor; wherein the memory stores a computer program adapted to be loaded by the memory and to execute the methods described above.

[0009] The beneficial effects of the technical solutions provided in this specification include at least the following: The traffic conversion analysis method provided in this specification involves obtaining a traffic query command for a service path link graph, determining the service path tree structure corresponding to the service path link graph based on the traffic query command, traversing each service path node based on the service path tree structure to obtain the baseline home node, path constraint node, and traffic query parameters corresponding to each service path node, determining the traffic query statement corresponding to each service path node based on the baseline home node, path constraint node, and traffic query parameters, executing the traffic query statement to obtain the traffic query data corresponding to the service path node, and performing traffic conversion analysis processing based on the traffic query data to obtain the service conversion analysis result. Therefore, by determining the traffic query statement through the baseline home node, path constraint node, and traffic query parameters corresponding to each service path node, the accuracy of the traffic query statement is improved, thereby ensuring the accuracy of the traffic query data obtained from executing the traffic query statement, and ultimately improving the accuracy of the service conversion analysis result. Attached Figure Description

[0010] 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, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a flowchart illustrating a traffic conversion analysis method provided in the embodiments of this specification; Figure 2 This is a flowchart illustrating another traffic conversion analysis method provided in the embodiments of this specification; Figure 3 This is a schematic diagram of the structure of a flow conversion and analysis device provided in the embodiments of this specification; Figure 4 This is a schematic diagram of the structure of a query statement determination module provided in the embodiments of this specification; Figure 5 This is a schematic diagram of the structure of an electronic device provided in the embodiments of this specification. Detailed Implementation

[0012] To make the inventive objectives, features, and advantages of the embodiments in this specification more apparent and understandable, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments in this specification, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments in this specification without creative effort are within the scope of protection of this specification.

[0013] In the description of this specification, it should be understood that the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. In the description of this specification, it should be noted that, unless otherwise expressly specified and limited, "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices. Those skilled in the art can understand the specific meaning of the above terms in this specification based on the specific circumstances. Furthermore, in the description of this specification, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship.

[0014] The present specification will now be described in detail with reference to specific embodiments.

[0015] In one embodiment, such as Figure 1 As shown, a traffic conversion analysis method is proposed. This method can be implemented using a computer program and can run on a traffic conversion analysis device based on the von Neumann architecture. This computer program can be integrated into applications or run as a standalone utility application.

[0016] Specifically, this traffic conversion analysis method includes: S102, obtain the traffic query command for the service path link graph, and determine the service path tree structure corresponding to the service path link graph based on the traffic query command. The service path link graph is a directed graph structure used to represent all possible operation trajectories throughout the entire lifecycle of a specific functional service. The service path link graph consists of state nodes, connection nodes, and flow edges, fully mapping all the preceding logic and branching paths from the user initiating an operation, experiencing intermediate processing stages, to finally achieving the goal. Nodes in the service path link graph represent specific behaviors or processing stages of the user during the use of a specific functional service, and edges represent logical dependencies or temporal transition relationships between nodes. The service path link graph is pre-configured and stored in a link graph configuration library.

[0017] The traffic query command is a command used to perform traffic transformation analysis and processing on all nodes in the service path link graph.

[0018] In one embodiment, a traffic query command input by a user is received through a traffic analysis interface. This traffic query command includes at least a query type, a target link graph identifier, and a query time window. The query type is used to distinguish different analysis scenarios such as full-link leakage analysis, single-target node traffic query, flow-edge leakage query, or user detail sampling query. The target link graph identifier is used to uniquely identify the service path link graph to be analyzed. The query time window is used to limit the start and end time range of traffic statistics.

[0019] Optionally, the traffic query command can also carry user attribute filtering conditions, such as application version, region, device type, etc., to generate additional filtering query clauses, which can be merged into the traffic query statement when generating the traffic query statement later.

[0020] The service path tree structure refers to a memory hash mapping structure with the target node identifier as the key and the service path configuration object as the value. The service path configuration object includes at least the identifier of the base node, the identifier of the path constraint node, and the identifier of the direct upstream node. The target node identifier can be any service path node in the service path tree structure. The base node is the upstream source node used for traffic statistics on the specified service path node. The path constraint node is the necessary preceding node required for traffic statistics on a specific service flow path containing the service path node. The direct upstream node is the preceding node in the service path link graph that is directly connected to the service path node via an edge and whose data flow points to the service path node. The base node and path constraint node are pre-configured and stored in the service path link graph. At least one service path node is configured with a corresponding service path configuration object. Through the service path configuration object, a local service path can be obtained with the base node as the root node, the path constraint node as the intermediate node, and the service path node as the leaf node. For a service path node, there can be one base node, one path constraint node, and one or more direct upstream nodes. For example, taking a payment service as an example, the service path link corresponding to this payment service can be: the user first enters homepage A, then enters activity page B from homepage A and then arrives at payment page D, or enters search page C from homepage A and then arrives at payment page D; in this service path link, homepage A is the root node, activity page B and search page C are both intermediate nodes, and payment page D is a leaf node. Then, when payment page D is a service path node, activity page B and search page C are both direct upstream nodes of payment page D, homepage A can be configured as the base node of payment page D, and activity page B or search page C can be configured as the path constraint node of payment page D.

[0021] In one embodiment, the service path tree structure is not generated by real-time traversal of the service path link graph during each query. Instead, the service path link graph is pre-structured and stored in a tree structure configuration library in memory-mapped form. After the traffic query command is parsed, the service path tree structure corresponding to the service path link graph is read from the tree structure configuration library according to the target link graph identifier.

[0022] If the service path tree structure corresponding to the service path link graph does not exist in the tree structure configuration library, for example, during the first query or when the configuration has been updated, the node configuration table and edge configuration table of the service path link graph are read from the link graph configuration library. Each service path node is traversed, and the baseline home node and path constraint node configured for it are extracted. Its direct upstream node is identified, and the baseline home node, path constraint node, and direct upstream node are assembled into a path configuration object. This object is written into a memory-mapped structure indexed by the identifier of the service path node to form a complete service path tree structure, which is then cached for reuse in subsequent queries.

[0023] Optionally, during the query process, if a user adjusts the baseline home node or path constraint node of a target service path node through the interactive interface, the adjusted baseline home node or path constraint node is written to the session-level temporary storage space. A session-level path configuration override object is generated based on the adjusted baseline home node or path constraint node, and the session-level path configuration override object is associated with the service path tree structure. Subsequently, the latest corresponding baseline home node and path constraint node of the service path node are determined through the service path tree structure and its associated session-level path configuration override object. When a confirmation operation is received that the user has saved the adjusted baseline home node or path constraint node as a global default value, the service path tree structure is updated based on the adjusted baseline home node or path constraint node to obtain the latest service path tree structure.

[0024] S104. Based on the service path tree structure, traverse each service path node to determine the base node, path constraint node, and traffic query parameters corresponding to the service path node.

[0025] The baseline originating node is the upstream source node used for traffic statistics when specifying a service path node. When querying user traffic for a service path node, the traffic originating from the baseline originating node and arriving at the service path node is counted. When a service path node has multiple direct upstream nodes, the common ancestor node of all direct upstream nodes is configured as the baseline originating node.

[0026] Path constraint nodes are essential preceding nodes required for traffic statistics on a specific service flow path where a service path node resides. When querying user traffic for a service path node, users who simultaneously flow through both the path constraint node and the service path node are further filtered from the user set determined by the baseline node. Bypass traffic that directly reaches the service path node without passing through the path constraint node is excluded from the statistical scope, thus determining the effective traffic of the service path node on a specific service flow path. It is understandable that path constraint nodes are configured based on the actual application scenario.

[0027] Traffic query parameters include the identifier of the service path node, the identifier of the direct upstream node of the service path node, and query condition parameters. Among them, the query condition parameters may include the query time window and user attribute filtering conditions carried in the traffic query command.

[0028] In one embodiment, during the traversal of the service path tree structure, for each service path node, the baseline home node and path constraint node corresponding to the service path node are extracted from the path configuration object of each service path node, and the direct upstream node of the service path node is extracted. The query time window and user attribute filtering conditions are parsed from the traffic query instruction, and the identifier of the direct upstream node, the query time window, and the user attribute filtering conditions are determined as the traffic query parameters corresponding to the service path node.

[0029] Understandably, the above query time window is used to limit the start and end time of traffic events, and the above user attribute filtering conditions are used to further filter user groups that meet specific characteristics.

[0030] S106, determine the traffic query statement corresponding to the service path node based on the baseline home node, path constraint node and traffic query parameters.

[0031] Among them, the traffic query statement is a structured query language statement executed in the database to obtain traffic query data, and is simply referred to as an SQL statement.

[0032] In one embodiment, the flow query type corresponding to the service path node can be determined by the baseline home node, the path constraint node, and the direct upstream node in the flow query parameters. The flow query template corresponding to the service path node is obtained according to the flow query type. The flow query statement is obtained by directly filling the identifier of the baseline home node, the identifier of the path constraint node, and the flow query parameters into the flow query template. Alternatively, a reference flow query statement is obtained by directly filling the identifier of the baseline home node, the identifier of the path constraint node, and the flow query parameters into the flow query template. The flow query statement is obtained by rewriting the reference flow query statement.

[0033] S108, execute the traffic query statement to obtain the traffic query data corresponding to the service path node, and perform traffic conversion analysis processing based on the traffic query data to obtain the service conversion analysis result.

[0034] Traffic query data refers to the raw query results obtained from executing traffic query statements. For aggregated traffic queries, the traffic query data includes at least the traffic statistics for each service path node, such as the number of unique user identifiers flowing through the service path nodes, the number of event triggers, the earliest arrival timestamp, and the latest arrival timestamp. For detailed traffic queries, the traffic query data includes at least a list of user identifiers, the specific timestamps of each event, and user attribute information. It can be understood that traffic query data is the raw query result returned by the database without transaction logic processing, directly reflecting the actual traffic scale of each service path node under the attribution criteria determined by a specific baseline attribution node and / or the filtering conditions imposed by specific path constraint nodes.

[0035] Service conversion analysis results refer to the structured analysis results formed after processing and calculating traffic query data using transaction logic. These results may include, but are not limited to, the effective traffic values ​​of each service path node, the leakage amount and leakage rate between adjacent service path nodes, the conversion rate distribution of each node on the conversion path, and deviation information for statistical results of abnormal nodes. The service conversion analysis results are presented in a readable format, allowing users to view the entire conversion funnel through the traffic analysis interface, click on a single node to view its traffic details, and click on an edge to view a list of users experiencing single-edge leakage.

[0036] In one embodiment, traffic query statements corresponding to each service path node can be executed in parallel using a thread pool to obtain traffic query data.

[0037] Optionally, traffic conversion analysis processing may include end-to-end leakage analysis processing. Specifically, it can traverse each flow edge in the service path link graph, read the traffic query data corresponding to the service path node upstream of the flow edge and the traffic query data corresponding to the service path node downstream of the flow edge, determine the first effective traffic value of the service path node under the constraint conditions formed by the baseline home node and / or path constraint nodes in the traffic query data corresponding to the service path node upstream of the flow edge, and determine the second effective traffic value of the service path node under the constraint conditions formed by the baseline home node and / or path constraint nodes in the traffic query data corresponding to the service path node downstream of the flow edge, and calculate the leakage amount of the flow edge by subtracting the first effective traffic value from the second effective traffic value. Further, the leakage amount is divided by the first effective traffic value to obtain the leakage rate of the flow edge. The leakage amount and leakage rate of each flow edge can be part of the service conversion analysis results.

[0038] Optionally, traffic conversion analysis processing may include single-node traffic analysis processing. Specifically, the aggregated value in the traffic query data corresponding to the service path node can be determined as the effective traffic value of the service path node. The effective traffic value is associated with the baseline attribution node identifier and the path constraint node identifier corresponding to the service path node to form a traffic analysis result with constraint annotations. This traffic analysis result may be part of the service conversion analysis result.

[0039] The traffic conversion analysis method provided in this specification involves obtaining a traffic query command for a service path link graph, determining the service path tree structure corresponding to the service path link graph based on the traffic query command, traversing each service path node based on the service path tree structure to determine the baseline home node, path constraint node, and traffic query parameters corresponding to each service path node, determining the traffic query statement corresponding to each service path node based on the baseline home node, path constraint node, and traffic query parameters, executing the traffic query statement to obtain the traffic query data corresponding to the service path node, and performing traffic conversion analysis processing based on the traffic query data to obtain the service conversion analysis result. Therefore, by determining the traffic query statement through the baseline home node, path constraint node, and traffic query parameters corresponding to each service path node, the accuracy of the traffic query statement is improved, thereby ensuring the accuracy of the traffic query data obtained from executing the traffic query statement, and ultimately improving the accuracy of the service conversion analysis result.

[0040] Please see Figure 2 This is a flowchart illustrating another embodiment of a traffic conversion analysis method provided in this specification. Specifically, the traffic conversion analysis method may include the following steps: S202, obtain the traffic query command for the service path link graph.

[0041] Specifically, the implementation method of step S202 can be found in [reference needed]. Figure 1 The descriptions of the relevant steps in the illustrated embodiments will not be repeated here.

[0042] S204, determine whether there are node configuration adjustment logs before the traffic query time indicated by the traffic query command.

[0043] The node configuration adjustment log refers to the persistent record generated when a user makes a change to the path configuration object of a service path node. The node configuration adjustment log records at least the following information: the identifier of the service path node whose configuration was adjusted, the identifier of the base node before the adjustment, the identifier of the path constraint node before the adjustment, the identifier of the base node after the adjustment, the identifier of the path constraint node after the adjustment, the timestamp of the configuration adjustment, and the source identifier of the adjustment operation.

[0044] Understandably, the source identifier of an adjustment operation can indicate whether it's a global save update initiated by an administrator in the configuration backend, or a session-level configuration update triggered and confirmed by a user in a query session. For global save updates initiated by an administrator in the configuration backend, the service path tree structure regenerated based on the node configuration adjustment logs will be stored as the latest service path tree structure. For session-level configuration updates, the service path structure regenerated based on the node configuration logs will be used as the service path tree structure for this query, rather than being stored as the latest service path tree structure.

[0045] When a user or administrator modifies the baseline home node or path constraint node of a node in the service path link diagram and chooses to save the modification as the global default configuration, the configuration information of this change is written to the node configuration adjustment log. At the same time, the current service path tree structure corresponding to the service path link diagram is marked as pending update. At this time, the path configuration objects of each node stored inside the current service path tree structure still reflect the old data before the adjustment.

[0046] In one embodiment, after obtaining the traffic query instruction, the traffic query time indicated by the traffic query instruction is first read, and it is then retrieved whether there are node configuration adjustment logs for the service path link graph before the traffic query time.

[0047] S206. If node configuration adjustment logs exist, the current service path tree structure corresponding to the service path link graph is updated based on the node configuration adjustment logs to obtain the service path tree structure.

[0048] If node configuration adjustment logs exist, it indicates that the current service path tree structure in memory can no longer accurately reflect the latest node configuration relationships. Therefore, it is necessary to update the affected service path nodes in the current service path tree structure based on the changes recorded in the node configuration adjustment logs. This update can be an incremental update, i.e., updating only the path configuration objects of the adjusted node and its downstream dependent nodes, or a full update. The resulting service path tree structure after the update will be used as the service path tree structure for this query.

[0049] In one embodiment, the method for obtaining the service path tree structure in step S206 can be: extracting the node configuration update data corresponding to the service path node to be updated based on the node configuration adjustment log, and using the node configuration update data to update the service path configuration object of the service path node to be updated in the current service path tree structure corresponding to the service path link graph to obtain the service path tree structure.

[0050] Optionally, when the node configuration update data includes updating the baseline home node, the baseline home node included in the service path configuration object of the service path node to be updated is replaced with the updated baseline home node; when the node configuration update data includes updating the path constraint node, the path constraint node included in the service path configuration object of the service path node to be updated is replaced with the updated path constraint node; when the node configuration update data includes updating the home node and updating the path constraint node, the baseline home node and path constraint node included in the service path configuration object of the service path node to be updated are replaced with the updated baseline home node and the updated path constraint node, respectively.

[0051] S208 If there is no node configuration adjustment log, the current service path tree structure corresponding to the service path link diagram will be used as the service path tree structure.

[0052] Optionally, when executing the process of using the current service path tree structure corresponding to the service path link graph as the service path tree structure, the following steps may be included: determining whether a current service path tree structure corresponding to the service path link graph exists; if no current service path tree structure exists, determining the traffic query starting point in the service path link graph based on the traffic query instruction, constructing a current service path tree structure with the traffic query starting point as the root node based on the service path link graph, and determining the current service path tree structure as the service path tree structure; if a current service path tree structure exists, then determining the current service path tree structure as the service path tree structure.

[0053] Understandably, the absence of node configuration adjustment logs indicates that the node configuration relationships in the service path link graph have not changed globally since the last construction of the service path tree structure. If the current service path tree structure already exists, it will be used directly as the service path tree structure for this query without triggering additional structure update processing, thereby reducing the computational overhead when starting the query. If the current service path tree structure does not exist, it will be constructed and used as the service path tree structure for this query.

[0054] The aforementioned traffic query starting point refers to the service path node that serves as the initial entry point for the service conversion path in the service path chain diagram. In conversion funnel analysis scenarios, the traffic query starting point typically corresponds to the initial touchpoint of user behavior, such as the application homepage, landing page, or registration entry page. As the root node of the service path tree structure, the node identifier of the traffic query starting point is used to define the upstream boundary of the entire link traffic statistics.

[0055] Optionally, the above-mentioned determination of the traffic query starting point in the service path link graph based on the traffic query command, and the construction of the current service path tree structure with the traffic query starting point as the root node based on the service path link graph, can be as follows: First, read the target service path link graph identifier carried in the traffic query command, and load all node configuration records and edge configuration records of the service path link graph indicated by the target service path link graph identifier from the link graph configuration library; wherein, the node configuration record at least includes the node identifier, the identifier of the preset baseline belonging node for the node, and / or the identifier of the path constraint node; the edge configuration record at least includes the upstream node identifier, the downstream node identifier, and the edge type; traverse all node configuration records, count the number of times each node appears as a downstream node in the edge configuration record, and determine the node with zero counts as the traffic query starting point. If there are multiple nodes with zero counts, select the traffic query starting point from multiple nodes according to the preset priority rules or according to the node creation time. Subsequently, starting from the traffic query origin, each service path node is traversed. For each service path node, the identifier of the preset base node in the node configuration record is read. If this field is null, its direct upstream node identifier is used as the base node identifier. The identifier of the preset path constraint node in the node configuration record is read. If this field is null, the identifier of the path constraint node is determined to be null. The identifier of the direct upstream node associated with the node as a downstream node in the edge configuration record is extracted. The identifiers of the base node, path constraint node, and direct upstream node are assembled into a service path configuration object. For the traffic query origin itself, its base node identifier, path constraint node identifier, and direct upstream node identifier are all set to null. Then, using the service path configuration object of each service path node as the value and the node identifier of each service path node as the key, an in-memory hash map is written to form the current service path tree structure.

[0056] S210: Based on the service path tree structure, traverse each service path node to determine the base node, path constraint node, and traffic query parameters corresponding to the service path node.

[0057] Specifically, the implementation method of step S210 can be found in [reference needed]. Figure 1 The descriptions of the relevant steps in the illustrated embodiments will not be repeated here.

[0058] S212, determine the traffic query type corresponding to the service path node based on the baseline home node and path constraint node, and obtain the traffic query template corresponding to the traffic query type.

[0059] Traffic query type refers to the category to which the query language generation logic belongs, determined by the configuration status of the baseline attribution node and path constraint nodes. Traffic query types can include, but are not limited to, direct upstream query type, ancestor-based query type, direct constraint query type, and composite constraint query type. The query logic for the upstream query type is to count the traffic flowing from the direct upstream node to the target node; the query logic for the ancestor-based query type is to count the traffic originating from the common ancestor node and reaching the target node via any path, requiring the definition of the user set range through a baseline attribution subquery; the query logic for the direct constraint query type is to verify, based on the direct upstream attribution, that the user must pass through the path constraint node through an existence subquery; the query logic for the composite constraint query path is to verify, based on the ancestor attribution, that the user must pass through a path constraint node at a higher upstream level through an existence subquery.

[0060] It is understood that the traffic query type in the embodiments of this specification does not refer to the request-level query type initiated by the user through the front-end interface, such as end-to-end leakage analysis, single-node traffic query, or user detail sampling query, but rather to the technical implementation type of generating query statements determined by the configuration status of the service path node itself during the query statement generation stage. Different traffic query types correspond to different data scanning range definition logic and set operation methods. The traffic query type is used to characterize the query logic paradigm adopted by the service path node during traffic statistics, determining the nested structure of subqueries, the combination of filtering conditions, and the relationship form between data tables in the traffic query statement.

[0061] Optionally, if the baseline home node is a direct upstream node and the identifier of the path constraint node is null, then the traffic query type corresponding to the service path node is determined to be a direct upstream query type; if the baseline home node is not a direct upstream node and the identifier of the path constraint node is null, then the traffic query type corresponding to the service path node is determined to be an ancestor type; if the identifier of the path constraint node is not null and the path constraint node is a direct upstream node, then the traffic query type corresponding to the service path node is determined to be a direct constraint query type; if the identifier of the path constraint node is not null and the path constraint node is not a direct upstream node, then the traffic query type corresponding to the service path node is determined to be a composite constraint query type.

[0062] Here, a traffic query template refers to the template used to generate traffic query statements for the corresponding traffic query type. Different traffic query templates have different query structures used to generate traffic query statements for different traffic query types.

[0063] Optionally, after obtaining the traffic query type, the corresponding traffic query template is retrieved and loaded from the preset template library using the traffic query type as the index key. Each traffic query type corresponds to a unique template identifier.

[0064] S214, Generate traffic query statements corresponding to service path nodes based on traffic query templates and traffic query parameters.

[0065] Optionally, step S214 can be performed as follows: when both the identifier of the base home node and the identifier of the path constraint node are empty, the traffic query parameters are filled into the corresponding positions in the traffic query template to obtain the traffic query statement corresponding to the service path node; when at least one of the identifier of the base home node and the identifier of the path constraint node is not empty, the traffic query parameters, the identifier of the base home node and / or the identifier of the path constraint node are filled into the corresponding positions in the traffic query template to obtain the traffic query statement corresponding to the service path node.

[0066] Optionally, step S214 may also include the following steps A2-A4: A2: Generate a reference traffic query statement corresponding to the service path node based on the traffic query template and traffic query parameters; A4: Determine the data source distribution characteristic indicators corresponding to the service path node, and rewrite the reference traffic query statement based on the data source distribution characteristic indicators to obtain the traffic query statement.

[0067] It is understood that the method of obtaining the reference traffic query statement in step A2 can refer to the method of obtaining the traffic query statement in the first embodiment of step S214 above, and will not be described in detail here.

[0068] Optionally, when determining the data source distribution characteristic indicators corresponding to the service path node in step A4, it may specifically include: determining time filtering conditions based on traffic query instructions, obtaining at least one storage data table where the data source corresponding to the service path node is located based on the time filtering conditions, generating the storage data table distribution variance based on the data volume statistics of the storage data table, and determining the data source distribution characteristic indicators corresponding to the service path node based on the storage data table distribution variance.

[0069] It is understandable that time filtering conditions refer to time parameters extracted from traffic query commands to limit the scanning range of traffic query data. Time filtering conditions include at least the start and end timestamps of the query time window.

[0070] A storage data table refers to an independent data table unit formed by partitioning the data source corresponding to a service path node according to preset table partitioning rules in the underlying storage logic. These partitioning rules are typically based on dimensions such as time period, transaction identifier, or hash value, splitting the originally logically unified data source into multiple storage data tables with independent table names. Each storage data table maintains independent data volume statistics metadata. When executing structured query language statements, the system routes the data to the corresponding physical storage location based on the table name for data scanning.

[0071] The variance of a stored data table distribution refers to the variance metric calculated based on the statistical values ​​of the data volume across the stored data tables covered by time-based filtering conditions. This variance quantifies the dispersion of data distribution across related stored data tables. When the statistical values ​​of the data volume across the stored data tables tend to be consistent, the variance is small, indicating that the data is evenly distributed across the table dimensions. Conversely, when the statistical values ​​of the data volume in a few stored data tables are significantly higher than those in other stored data tables, the variance is large, indicating data skew.

[0072] The data source distribution characteristic index is a feature metric directly determined by the variance of the stored data tables. This index characterizes the degree of uneven distribution of the data sources corresponding to service path nodes across the stored data table dimensions. A higher data source distribution characteristic index indicates a greater degree of skewness in the distribution of the queried data across the various stored data tables, and a higher risk of excessive single-table scan pressure and uneven allocation of computing resources when executing the original reference traffic query statement.

[0073] Specifically, based on the table partitioning rules adopted by the data source corresponding to the service path node, at least one storage data table covered by the time filtering conditions is determined. This table partitioning rule includes at least a table partitioning dimension identifier and a table partitioning naming format. The start and end timestamps in the time filtering conditions are discretized according to the table partitioning dimension to obtain discrete time periods, generating a list of storage data table names corresponding to each discrete time period. For example, when the table partitioning rule is daily partitioning, the start and end timestamps are discretized to obtain each natural day, determining a list of daily-level storage data table names corresponding to each natural day.

[0074] Furthermore, for each of the aforementioned determined storage data tables, the data volume statistics for each storage data table are read. These data volume statistics include at least the number of record rows or the number of storage bytes for each storage data table. If the data volume statistics for a storage data table are zero, then that storage data table is removed from the list of storage data table names, or its data volume statistics are set to zero and a flag is retained.

[0075] Next, based on the data volume statistics of each stored data table obtained above, the arithmetic mean of each data volume statistics is calculated. Then, the difference between the data volume statistics of each stored data table and the arithmetic mean is calculated. The squares of each difference are then summed to obtain the sum of squared deviations. The sum of squared deviations is divided by the number of stored data tables involved in the calculation to obtain the variance of the stored data table distribution. If only one stored data table remains after elimination, the variance of the stored data table distribution is set to zero.

[0076] The variance of the storage data table distribution calculated above is assigned to the data source distribution characteristic index. When the data source distribution characteristic index is less than or equal to a preset index threshold, the reference traffic query statement is not rewritten, and the reference traffic query statement is determined as the traffic query statement. When the data source distribution characteristic index is greater than the preset index threshold, the logical table query description statement in the reference traffic query statement is rewritten into a multi-table join query statement to obtain the traffic query statement. For example, rewriting the logical table query description statement into a multi-table join query statement can be done by splitting the single table query description statement into explicit join references to multiple storage data table names corresponding to each day. Specifically, it can be done by replacing the logical table name in the single table query description statement with a table sequence formed by connecting multiple daily-level storage data table names through a join query keyword, so that the queryer can clearly perceive that the data is distributed on multiple independent physical storage units, thereby generating an execution plan for parallel scanning of each daily-level storage data table.

[0077] Therefore, by using data source distribution characteristic indicators to quantify the uneven distribution of data sources across physical tables, the reference traffic query statement is adaptively rewritten accordingly. When the data source distribution characteristic indicator is in a low-skew scenario (i.e., the data source distribution characteristic indicator is less than or equal to the preset indicator threshold), the data volume statistics of each storage table tend to be balanced. The query engine can automatically complete table pruning and parallel scheduling based on a single logical table reference. In this case, forcibly rewriting it into an explicit multi-table union would increase the parsing overhead and execution plan complexity of the query engine. Therefore, keeping the original statement unchanged can achieve better execution efficiency. However, when a high-skew scenario is detected (i.e., the data source distribution characteristic indicator is greater than the preset indicator threshold), the data volume statistics of some storage tables are significantly higher than those of others. If stored data tables are still executed using a single logical table reference, the query engine often generates an execution plan based on the assumption of uniform distribution. Large-volume stored data tables are concentrated on a few computing nodes, causing the amount of data processed by these computing nodes to far exceed their memory capacity, triggering disk overflow or even memory overflow failures. This results in actual execution time being much longer than theoretical computation time, and poor query stability. In this case, by rewriting the reference traffic query statement into an explicit multi-table union and hierarchical aggregation structure, since each stored data table is scheduled as an independent scanning unit, the single-node resource overload caused by multiple hot data tables being squeezed onto the same computing node is avoided. This avoids the additional performance loss and failure risk caused by single-node resource overload, thereby enhancing query stability and improving resource utilization efficiency.

[0078] S216, execute the traffic query statement to obtain the traffic query data corresponding to the service path node, and perform traffic conversion analysis processing based on the traffic query data to obtain the service conversion analysis result.

[0079] The implementation method of step S216 can be found in [reference needed]. Figure 1The descriptions of the relevant steps in the illustrated embodiments will not be repeated here.

[0080] The traffic conversion analysis method provided in the embodiments of this specification obtains a traffic query command for a service path link graph, determines whether there is a node configuration adjustment log before the traffic query time indicated by the traffic query command, and if there is a node configuration adjustment log, updates the current service path tree structure corresponding to the service path link graph based on the node configuration adjustment log to obtain the service path tree structure. If there is no node configuration adjustment log, the current service path tree structure corresponding to the service path link graph is used as the service path tree structure, thereby ensuring that the service path tree structure used for traffic query is an accurate tree structure. Then, based on the service path tree structure, each service path node is traversed to determine the baseline corresponding to the service path node. Based on the baseline home node, path constraint node, and traffic query parameters, the traffic query type corresponding to the service path node is determined. A traffic query template corresponding to the traffic query type is obtained. Based on the traffic query template and traffic query parameters, a traffic query statement corresponding to the service path node is generated. This improves the efficiency of generating traffic query statements. Executing the traffic query statement yields the traffic query data corresponding to the service path node. Based on the traffic query data, traffic conversion analysis is performed to obtain service conversion analysis results. This ensures the accuracy of the traffic query data generated by executing the traffic query statement, thereby improving the accuracy of the service conversion analysis results.

[0081] The following will combine Figure 3 This specification provides a detailed description of the flow conversion and analysis device provided in the embodiments. It should be noted that... Figure 3 The flow conversion analysis device shown is used to perform the functions described in this manual. Figures 1-2 The methods shown in the embodiments are illustrated for ease of explanation, showing only the parts related to the embodiments of this specification. For specific technical details not disclosed, please refer to this specification. Figures 1-2 The example shown.

[0082] Please see Figure 3 This diagram illustrates the structure of a traffic conversion analysis device according to an embodiment of this specification. This traffic conversion analysis device can be implemented as all or part of a device through software, hardware, or a combination of both. According to some embodiments, the traffic conversion analysis device 30 includes a structure data determination module 310, a node data acquisition module 320, a query statement determination module 330, and a conversion analysis processing module 340, specifically used for: The structure data determination module 310 is used to obtain a traffic query instruction for the service path link graph and determine the service path tree structure corresponding to the service path link graph based on the traffic query instruction. The node data acquisition module 320 is used to traverse each service path node based on the service path tree structure and determine the baseline home node, path constraint node and traffic query parameters corresponding to the service path node. The query statement determination module 330 is used to determine the traffic query statement corresponding to the service path node based on the baseline home node, the path constraint node and the traffic query parameters. The conversion analysis and processing module 340 is used to execute the traffic query statement to obtain the traffic query data corresponding to the service path node, and perform traffic conversion analysis processing based on the traffic query data to obtain the service conversion analysis result.

[0083] Optionally, the structure data determination module 310 includes: The first processing unit is used to determine whether there is a node configuration adjustment log before the traffic query time indicated by the traffic query command; The second processing unit is used to perform structural update processing on the current service path tree structure corresponding to the service path link diagram based on the node configuration adjustment log if there is a node configuration adjustment log to obtain the service path tree structure. The third processing unit is used to determine the current service path tree structure corresponding to the service path link graph as the service path tree structure if there is no node configuration adjustment log.

[0084] Optionally, the second processing unit is specifically used for: Based on the node configuration adjustment log, extract the node configuration update data corresponding to the service path node to be updated, and use the node configuration update data to update the service path configuration object of the service path node to be updated in the current service path tree structure corresponding to the service path link graph to obtain the service path tree structure.

[0085] Optionally, the third processing unit is specifically used for: Determine whether a current service path tree structure corresponding to the service path link graph exists; If the current service path tree structure does not exist, the starting point of the traffic query is determined in the service path link graph based on the traffic query instruction, and the current service path tree structure with the starting point of the traffic query as the root node is constructed based on the service path link graph. The current service path tree structure is then determined as the service path tree structure. If the current service path tree structure exists, then the current service path tree structure is determined as the service path tree structure.

[0086] Optionally, please see Figure 4The diagram shows a structural schematic of a query statement determination module. The query statement determination module 330 includes a query template determination unit 3310 and a query statement generation unit 3320, specifically used for: The query template determination unit 3310 is used to determine the traffic query type corresponding to the service path node based on the baseline home node and the path constraint node, and obtain the traffic query template corresponding to the traffic query type. The query statement generation unit 3320 is used to generate a traffic query statement corresponding to the service path node based on the traffic query template and the traffic query parameters.

[0087] Optionally, the query template determination unit 3310 includes: The statement generation subunit is used to generate a reference traffic query statement corresponding to the service path node based on the traffic query template and the traffic query parameters. The statement rewriting subunit is used to determine the data source distribution characteristic indicators corresponding to the service path node, and rewrite the reference traffic query statement based on the data source distribution characteristic indicators to obtain the traffic query statement.

[0088] Optionally, the statement rewrites the sub-unit, specifically for: Based on the traffic query command, time filtering conditions are determined. Based on the time filtering conditions, at least one storage data table containing the data source corresponding to the service path node is obtained. Based on the data volume statistics of the storage data table, the distribution variance of the storage data table is generated. Based on the distribution variance of the storage data table, the distribution characteristic index of the data source corresponding to the service path node is determined.

[0089] Please refer to Figure 5 This diagram illustrates the structure of an electronic device provided in an exemplary embodiment of this specification. The electronic device in this specification may include one or more components such as a processor 110, a memory 120, an input device 130, an output device 140, and a bus 150. The processor 110, memory 120, input device 130, and output device 140 may be connected via the bus 150.

[0090] Processor 110 may include one or more processing cores. Processor 110 connects to various parts of the terminal using various interfaces and lines, and performs various functions and processes data of terminal 100 by running or executing instructions, programs, code sets, or instruction sets stored in memory 120, and by calling data stored in memory 120. Optionally, processor 110 may be implemented using at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). Processor 110 may integrate one or more of a central processing unit (CPU), graphics processing unit (GPU), and modem. The CPU mainly handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the displayed content; and the modem is used for wireless communication. It is understood that the modem may also not be integrated into processor 110, but implemented separately through a communication chip.

[0091] The memory 120 may include random access memory (RAM) or read-only memory (ROM). Optionally, the memory 120 may include a non-transitory computer-readable storage medium. The memory 120 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 120 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (e.g., touch function, sound playback function, image playback function, etc.), instructions for implementing the various method embodiments described below, etc. The operating system may be the Android system, including systems deeply developed based on the Android system, the iOS system developed by Apple Inc., including systems deeply developed based on the iOS system, or other systems.

[0092] In order for the operating system to distinguish the specific application scenarios of third-party applications, it is necessary to establish data communication between the third-party applications and the operating system. This would allow the operating system to obtain the current scenario information of the third-party applications at any time, and then perform targeted system resource adaptation based on the current scenario.

[0093] The input device 130 is used to receive input instructions or data, and includes, but is not limited to, a keyboard, mouse, camera, microphone, or touch device. The output device 140 is used to output instructions or data, and includes, but is not limited to, a display device and a speaker. In one example, the input device 130 and the output device 140 can be combined, and the input device 130 and the output device 140 can be a touch display screen.

[0094] The touch display screen can be designed as a full-screen, curved screen, or irregularly shaped screen. It can also be designed as a combination of a full-screen and a curved screen, or a combination of an irregularly shaped screen and a curved screen; however, this specification does not limit the specific design of the embodiments described herein.

[0095] In addition, those skilled in the art will understand that the structure of the electronic device shown in the above figures does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements. For example, the electronic device may also include radio frequency circuits, input units, sensors, audio circuits, Wireless Fidelity (WiFi) modules, power supplies, Bluetooth modules, etc., which will not be described in detail here.

[0096] In some embodiments, Figure 5 In the illustrated electronic device, the processor 110 can be used to call a program for a traffic conversion analysis method stored in the memory 120, and specifically perform the following operations: Obtain a traffic query instruction for the service path link graph, and determine the service path tree structure corresponding to the service path link graph based on the traffic query instruction; Based on the service path tree structure, traverse each service path node to determine the baseline home node, path constraint node and traffic query parameters corresponding to the service path node. The traffic query statement corresponding to the service path node is determined based on the baseline home node, the path constraint node, and the traffic query parameters. The traffic query statement is executed to obtain the traffic query data corresponding to the service path node. Based on the traffic query data, traffic conversion analysis is performed to obtain the service conversion analysis result.

[0097] In one embodiment, when the processor 110 executes the step of determining the service path tree structure corresponding to the service path link graph based on the traffic query instruction, it specifically performs the following operations: Determine whether there are node configuration adjustment logs before the traffic query time indicated by the traffic query command; If node configuration adjustment logs exist, the current service path tree structure corresponding to the service path link graph is updated based on the node configuration adjustment logs to obtain the service path tree structure. If no node configuration adjustment log exists, the current service path tree structure corresponding to the service path link diagram will be determined as the service path tree structure.

[0098] In one embodiment, when the processor 110 performs the step of updating the current service path tree structure corresponding to the service path link graph based on the node configuration adjustment log to obtain the service path tree structure, it specifically performs the following operations: Based on the node configuration adjustment log, extract the node configuration update data corresponding to the service path node to be updated, and use the node configuration update data to update the service path configuration object of the service path node to be updated in the current service path tree structure corresponding to the service path link graph to obtain the service path tree structure.

[0099] In one embodiment, when the processor 110 performs the step of determining the current service path tree structure corresponding to the service path link graph as a service path tree structure, it specifically performs the following operations: Determine whether a current service path tree structure corresponding to the service path link graph exists; If the current service path tree structure does not exist, the starting point of the traffic query is determined in the service path link graph based on the traffic query instruction, and the current service path tree structure with the starting point of the traffic query as the root node is constructed based on the service path link graph. The current service path tree structure is then determined as the service path tree structure. If the current service path tree structure exists, then the current service path tree structure is determined as the service path tree structure.

[0100] In one embodiment, when the processor 110 executes the step of determining the traffic query statement corresponding to the service path node based on the baseline home node, the path constraint node, and the traffic query parameters, it specifically performs the following operations: Based on the baseline home node and the path constraint node, determine the traffic query type corresponding to the service path node, and obtain the traffic query template corresponding to the traffic query type; Based on the traffic query template and the traffic query parameters, a traffic query statement corresponding to the service path node is generated.

[0101] In one embodiment, when the processor 110 executes the step of generating a traffic query statement corresponding to the service path node based on the traffic query template and the traffic query parameters, it specifically performs the following operations: Based on the traffic query template and the traffic query parameters, a reference traffic query statement corresponding to the service path node is generated. Determine the data source distribution characteristic indicators corresponding to the service path nodes, and rewrite the reference traffic query statement based on the data source distribution characteristic indicators to obtain the traffic query statement.

[0102] In one embodiment, when the processor 110 performs the step of determining the data source distribution characteristic indicators corresponding to the service path node, it specifically performs the following operations: Based on the traffic query command, time filtering conditions are determined. Based on the time filtering conditions, at least one storage data table containing the data source corresponding to the service path node is obtained. Based on the data volume statistics of the storage data table, the distribution variance of the storage data table is generated. Based on the distribution variance of the storage data table, the distribution characteristic index of the data source corresponding to the service path node is determined.

[0103] This specification also provides a computer-readable storage medium storing at least one instruction that is executed by a processor to implement the traffic conversion analysis method as described in the above embodiments.

[0104] This specification also provides a computer program product that stores at least one instruction, which is loaded and executed by the processor to implement the traffic conversion analysis method described in the above embodiments.

[0105] Those skilled in the art will recognize that the functions described in the embodiments of this specification in one or more of the above examples can be implemented using hardware, software, firmware, or any combination thereof. When implemented in software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transfer of a computer program from one place to another. Storage media can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0106] The above description is merely an optional embodiment of this specification and is not intended to limit this specification. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this specification shall be included within the protection scope of this specification.

[0107] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

Claims

1. A traffic conversion analysis method, the method comprising: Obtain a traffic query instruction for the service path link graph, and determine the service path tree structure corresponding to the service path link graph based on the traffic query instruction; Based on the service path tree structure, traverse each service path node to determine the baseline home node, path constraint node and traffic query parameters corresponding to the service path node. The traffic query statement corresponding to the service path node is determined based on the baseline home node, the path constraint node, and the traffic query parameters. The traffic query statement is executed to obtain the traffic query data corresponding to the service path node. Based on the traffic query data, traffic conversion analysis is performed to obtain the service conversion analysis result.

2. The method according to claim 1, wherein determining the service path tree structure corresponding to the service path link graph based on the traffic query instruction includes: Determine whether there are node configuration adjustment logs before the traffic query time indicated by the traffic query command; If node configuration adjustment logs exist, the current service path tree structure corresponding to the service path link graph is updated based on the node configuration adjustment logs to obtain the service path tree structure. If no node configuration adjustment log exists, the current service path tree structure corresponding to the service path link diagram will be determined as the service path tree structure.

3. The method according to claim 2, wherein the step of updating the current service path tree structure corresponding to the service path link graph based on the node configuration adjustment log to obtain the service path tree structure includes: Based on the node configuration adjustment log, extract the node configuration update data corresponding to the service path node to be updated, and use the node configuration update data to update the service path configuration object of the service path node to be updated in the current service path tree structure corresponding to the service path link graph to obtain the service path tree structure.

4. The method according to claim 2, wherein determining the current service path tree structure corresponding to the service path link graph as the service path tree structure includes: Determine whether a current service path tree structure corresponding to the service path link graph exists; If the current service path tree structure does not exist, the starting point of the traffic query is determined in the service path link graph based on the traffic query instruction, and the current service path tree structure with the starting point of the traffic query as the root node is constructed based on the service path link graph. The current service path tree structure is then determined as the service path tree structure. If the current service path tree structure exists, then the current service path tree structure is determined as the service path tree structure.

5. The method according to claim 1, wherein determining the traffic query statement corresponding to the service path node based on the baseline home node, the path constraint node, and the traffic query parameters comprises: Based on the baseline home node and the path constraint node, determine the traffic query type corresponding to the service path node, and obtain the traffic query template corresponding to the traffic query type; Based on the traffic query template and the traffic query parameters, a traffic query statement corresponding to the service path node is generated.

6. The method according to claim 5, wherein generating the traffic query statement corresponding to the service path node based on the traffic query template and the traffic query parameters includes: Based on the traffic query template and the traffic query parameters, a reference traffic query statement corresponding to the service path node is generated. Determine the data source distribution characteristic indicators corresponding to the service path nodes, and rewrite the reference traffic query statement based on the data source distribution characteristic indicators to obtain the traffic query statement.

7. The method according to claim 6, wherein determining the data source distribution characteristic index corresponding to the service path node includes: Based on the traffic query command, time filtering conditions are determined. Based on the time filtering conditions, at least one storage data table containing the data source corresponding to the service path node is obtained. Based on the data volume statistics of the storage data table, the distribution variance of the storage data table is generated. Based on the distribution variance of the storage data table, the distribution characteristic index of the data source corresponding to the service path node is determined.

8. A flow conversion analysis device, the device comprising: The structure data determination module is used to obtain a traffic query instruction for the service path link graph and determine the service path tree structure corresponding to the service path link graph based on the traffic query instruction. The node data acquisition module is used to traverse each service path node based on the service path tree structure and determine the baseline home node, path constraint node and traffic query parameters corresponding to the service path node. The query statement determination module is used to determine the traffic query statement corresponding to the service path node based on the baseline attribution node, the path constraint node, and the traffic query parameters. The conversion analysis and processing module is used to execute the traffic query statement to obtain the traffic query data corresponding to the service path node, and perform traffic conversion analysis and processing based on the traffic query data to obtain the service conversion analysis result.

9. A computer storage medium storing a plurality of instructions adapted for loading by a processor and executing the method as claimed in any one of claims 1 to 7.

10. A computer program product storing at least one instruction, the at least one instruction being loaded by a processor and executing the method as described in any one of claims 1 to 7.

11. An electronic device, comprising: A processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and executed as described in any one of claims 1 to 7.

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