CN112214495B - Data execution tracking method, device and equipment - Google Patents

Data execution tracking method, device and equipment Download PDF

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CN112214495B
CN112214495B CN202011142750.4A CN202011142750A CN112214495B CN 112214495 B CN112214495 B CN 112214495B CN 202011142750 A CN202011142750 A CN 202011142750A CN 112214495 B CN112214495 B CN 112214495B
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execution data
recording
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CN112214495A (en
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庞冬
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Shanghai Yibao Health Management Co ltd
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    • G—PHYSICS
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    • G06F16/245—Query processing
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    • G06F16/2474—Sequence data queries, e.g. querying versioned data
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    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
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    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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Abstract

The application provides a data execution tracking method, a device and equipment, wherein the method comprises the following steps: acquiring class information of current execution data; judging whether a monitoring mark exists in the execution data or not based on the class information; if the monitoring mark exists in the execution data, acquiring the identification information of the execution data; and recording the execution attribute information of the execution data to a time sequence database by taking the identification information as an index according to the monitoring mark. The application realizes real-time data tracking record of the current execution data so as to monitor the data change flow of the execution data.

Description

Data execution tracking method, device and equipment
Technical Field
The present application relates to the field of information processing technologies, and in particular, to a method, an apparatus, and a device for tracking data execution.
Background
Online payment refers to a service for which a bank provides an online funds settlement service when a seller and a buyer conduct transactions through an e-commerce website on the internet. The system provides a safe, quick and convenient electronic commerce application environment and an online fund settlement tool for enterprises and individuals.
With the gradual expansion of the application field of online payment, online payment is also becoming the most popular settlement mode in internet medical and insurance policy settlement. However, various settlement rules also become complicated with the complexity of business rules. For example, when an insurance company settles a policy of a customer, different settlement modes can appear due to different actual insurance services, so that the corresponding policy settlement work needs to be realized by a settlement system with complex calculation rules and operation flows.
However, in an actual scene, the operation rule and real-time data of the management case are often difficult to master, and especially for the problem investigation of the abnormal management case, the complete data change flow and the abnormal root cause cannot be intuitively mastered through the final management result.
Disclosure of Invention
The embodiment of the application aims to provide a data execution tracking method, a device and equipment, which are used for realizing real-time data tracking record of current execution data so as to monitor the data change flow of the execution data.
A first aspect of the embodiment of the present application provides a data execution tracking method, including: acquiring class information of current execution data; judging whether a monitoring mark exists in the execution data or not based on the class information; if the monitoring mark exists in the execution data, acquiring the identification information of the execution data; and recording the execution attribute information of the execution data to a time sequence database by taking the identification information as an index according to the monitoring mark.
In an embodiment, the recording the execution attribute information of the execution data to the time sequence database according to the monitoring mark with the identification information as an index includes: acquiring a data name of the execution data; judging whether the node name of the execution data is configured in the monitoring mark; if the node name of the execution data is not configured in the monitoring mark, setting the node name as the data name, and recording the name node of the execution data to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the name node.
In an embodiment, the recording the execution attribute information of the execution data to the time sequence database according to the monitoring mark with the identification information as an index includes: judging whether the monitoring mark requires recording request parameters or not; and if the request parameters are required to be recorded in the monitoring marks, acquiring request parameter information of the execution data, and recording parameter nodes of the execution data to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the parameter nodes.
In an embodiment, the recording the execution attribute information of the execution data to the time sequence database according to the monitoring mark with the identification information as an index includes: if an abnormality occurs in the running process of the execution data, judging whether the monitoring mark is required to record the execution abnormality or not; and if the monitoring mark is required to record the execution abnormality, acquiring the execution abnormality information of the execution data, and recording abnormal nodes to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the abnormal nodes.
In an embodiment, the recording the execution attribute information of the execution data to the time sequence database according to the monitoring mark with the identification information as an index includes: acquiring a return value for running the execution data; judging whether the execution data is successfully executed or not based on the return value; if the execution data is successfully executed, judging whether the execution success information is required to be recorded in the monitoring mark; and if the monitoring mark is required to record the execution success information, recording an execution success node to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the execution success node.
In an embodiment, the recording the execution attribute information of the execution data to the time sequence database according to the monitoring mark with the identification information as an index further includes: if the execution data fails to be executed, judging whether the execution failure information is required to be recorded in the monitoring mark; and if the monitoring mark is required to record the execution failure information, recording an execution failure node to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the execution failure node.
In an embodiment, the recording the execution attribute information of the execution data to the time sequence database according to the monitoring mark with the identification information as an index further includes: judging whether the monitoring mark requires recording the return value or not; and if the monitoring mark is required to record the return value, recording a return value node to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the return value node.
In an embodiment, the recording the execution attribute information of the execution data to the time sequence database according to the monitoring mark with the identification information as an index includes: and if the execution attribute information carries entity class, selecting a target entity class with preset annotation information in the execution attribute information, and recording the target entity class to the time sequence database by taking the identification information as an index according to the monitoring mark.
A second aspect of an embodiment of the present application provides a data execution tracking apparatus, including: the first acquisition module is used for acquiring class information of the current execution data; the judging module is used for judging whether the monitoring mark exists in the execution data or not based on the class information; the second acquisition module is used for acquiring the identification information of the execution data if the monitoring mark exists in the execution data; and the recording module is used for recording the execution attribute information of the execution data to a time sequence database by taking the identification information as an index according to the monitoring mark.
In one embodiment, the recording module is configured to: acquiring a data name of the execution data; judging whether the node name of the execution data is configured in the monitoring mark; if the node name of the execution data is not configured in the monitoring mark, setting the node name as the data name, and recording the name node of the execution data to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the name node.
In one embodiment, the recording module is configured to: judging whether the monitoring mark requires recording request parameters or not; and if the request parameters are required to be recorded in the monitoring marks, acquiring request parameter information of the execution data, and recording parameter nodes of the execution data to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the parameter nodes.
In one embodiment, the recording module is configured to: if an abnormality occurs in the running process of the execution data, judging whether the monitoring mark is required to record the execution abnormality or not; and if the monitoring mark is required to record the execution abnormality, acquiring the execution abnormality information of the execution data, and recording abnormal nodes to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the abnormal nodes.
In one embodiment, the recording module is configured to: acquiring a return value for running the execution data; judging whether the execution data is successfully executed or not based on the return value; if the execution data is successfully executed, judging whether the execution success information is required to be recorded in the monitoring mark; and if the monitoring mark is required to record the execution success information, recording an execution success node to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the execution success node.
In an embodiment, the recording module is further configured to: if the execution data fails to be executed, judging whether the execution failure information is required to be recorded in the monitoring mark; and if the monitoring mark is required to record the execution failure information, recording an execution failure node to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the execution failure node.
In an embodiment, the recording module is further configured to: judging whether the monitoring mark requires recording the return value or not; and if the monitoring mark is required to record the return value, recording a return value node to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the return value node.
In one embodiment, the recording module is configured to: and if the execution attribute information carries entity class, selecting a target entity class with preset annotation information in the execution attribute information, and recording the target entity class to the time sequence database by taking the identification information as an index according to the monitoring mark.
A third aspect of an embodiment of the present application provides an electronic device, including: a memory for storing a computer program; a processor, configured to execute the method according to the first aspect of the embodiment and any of the embodiments of the present application, to record the execution attribute information of the current execution data into the time sequence database.
According to the data execution tracking method, device and equipment provided by the application, the monitoring mark is added in the class information of the execution data in advance, when the execution data is executed, the current execution data is intercepted, the class information of the current execution data is obtained, when the monitoring mark exists in the class information, the execution attribute information of the execution data is recorded to the time sequence database by taking the identification information as an index based on the specific mark content of the monitoring mark, so that the tracking of the change process of the current execution data is completed, and the execution process of the execution data is monitored in real time.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope, and other related drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of an electronic device according to an embodiment of the application;
FIG. 2 is a flow chart of a data execution tracking method according to an embodiment of the application;
FIG. 3 is a flowchart of a data execution tracking method according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a data execution tracking device according to an embodiment of the application.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings in the embodiments of the present application. In the description of the present application, the terms "first," "second," and the like are used merely to distinguish between descriptions and are not to be construed as indicating or implying relative importance.
As shown in fig. 1, the present embodiment provides an electronic apparatus 1 including: at least one processor 11 and a memory 12, one processor being exemplified in fig. 1. The processor 11 and the memory 12 are connected by the bus 10, and the memory 12 stores instructions executable by the processor 11, which instructions are executed by the processor 11 to enable the electronic device 1 to perform all or part of the flow of the method in the embodiments described below for data tracking of currently executed data.
In an embodiment, the electronic device 1 may be a mobile phone, a notebook computer, a desktop computer, or an operation system composed of multiple computers.
Referring to fig. 2, a data execution tracking method according to an embodiment of the present application may be executed by the electronic device 1 shown in fig. 1, and may be applied to a scenario of a settlement system for online settlement of a policy, so as to monitor and track settlement information of the policy in real time. The method comprises the following steps:
step 201: class information of the current execution data is obtained.
In this step, the execution data may be an execution method in a series of execution codes, and the class information is used to annotate various attribute information of the execution data. And in the process of executing the data, acquiring class information of the current execution data in real time.
Step 202: and judging whether the monitoring mark exists in the execution data or not based on the class information. If so, step 203 may be entered, otherwise, the process may end, or proceed directly to the next trace of execution data.
In the step, the monitoring mark is an annotation class which is added in the class information in advance, and before the data is executed, the class information can be added to the monitoring mark by a user based on actual needs, and the class information to be tracked can be added in the form of the monitoring mark. It is possible to determine whether or not the monitoring flag is present in the execution data based on the class information.
In one embodiment, the monitor tag may be a meta annotation, which may be implemented using AOP (Aspect Oriented Programming, section-oriented programming) techniques, such as:
1. defining annotation class Metrics
2. Tangent plane MetricsAspect realizing Metrics annotation function
1) Defining a tangent point Pointcut, which is used for defining a matching rule of the tangent plane, namely taking the annotation class Metrics as the tangent point:
@Pointcut("@annotation(net.ebaolife.tpa.adjustment.aspect.Metrics)")
public void withMetricsAnnotation(){
}
2) A surrounding notification interception method is defined, namely, a method defined by the point Pointcut is used as a focus point, and interception and log recording are carried out.
In this way, for all execution data added with @ Metrics comments, the priority of the Metrics aspect interception method is set to be the highest, so that the operation of the section execution is performed in the latest mode, and finally the operation of the section execution is performed out, thereby avoiding the situation that the transaction rollback fails because of incapability of capturing exceptions. The annotated data enters the interception method during execution, and then class information and other information of the current execution data can be obtained. In step 2020, it may be determined whether the class information of the current execution data includes a meta annotation, if so, it is indicated that the execution data includes a monitoring tag, and step 203 is entered, if the current execution data does not include the meta annotation, it is indicated that the execution data does not include a monitoring tag, and the current execution data is directly operated without log record. Tracking of the next execution data may also be entered directly.
Step 203: identification information of the execution data is acquired.
In this step, if the monitoring flag exists in the execution data, it indicates that the current execution data is configured to need to track the data change process, in order to facilitate recording the execution process, the identification information of the execution data is obtained in real time, and the identification information of the current execution data, such as the file number of the current execution data, may be obtained through the current thread context.
Step 204: recording the execution attribute information of the execution data to a time sequence database by taking the identification information as an index according to the monitoring mark.
In this step, the content type of the specific record to be tracked of the current execution data may be marked in the monitoring mark, and in the recording process, i have facilitated the subsequent query of the track record, the identification information of each execution data may be used as an index, and then the specific execution attribute information may be recorded in the time sequence database, so as to facilitate the generation of the log of each execution data.
According to the data execution tracking method, the monitoring marks are added to the class information of the execution data in advance, when the execution data is executed, the current execution data is intercepted, the class information of the current execution data is obtained, when the monitoring marks exist in the class information, the execution attribute information of the execution data is recorded to the time sequence database by taking the identification information as an index based on the specific mark content of the monitoring marks, and therefore tracking of the change process of the current execution data is completed, and the execution process of the execution data is monitored in real time.
Referring to fig. 3, a data execution tracking method according to an embodiment of the present application may be executed by the electronic device 1 shown in fig. 1, and may be applied to a scenario of a settlement system for online settlement of a policy, so as to monitor and track settlement information of the policy in real time. The method comprises the following steps:
step 301: class information of the current execution data is obtained. See the description of step 201 in the above embodiments for details.
Step 302: and judging whether the monitoring mark exists in the execution data or not based on the class information. If yes, go to step 303, otherwise go to step 310. See the description of step 202 in the above embodiments for details.
Step 303: and if the monitoring mark exists in the execution data, acquiring the identification information of the execution data. See for details the description of step 203 in the above embodiments.
Step 304: a data name of the execution data is acquired.
In this step, the data name may be a specific name of the currently executed data, for example, the currently executed data is the main program of the management flow, and the name may be "the management main program", and the specific data name may be set in the actual scenario by the data developer.
In one embodiment, step 304 may be performed simultaneously with step 301.
Step 305: it is determined whether the node name of the execution data is configured in the monitor flag. If yes, go to step 307, otherwise go to step 306.
In this step, the @ Metrics annotation (monitoring flag) may be added uniformly in advance to the key data to be logged. The monitoring tag may include an annotation for the node name of the currently executing data, so that the meta annotation of the currently intercepted executing data may be obtained, and it is determined whether the node name in the meta annotation is configured, if yes, step 307 is entered, and if not step 306 is entered.
Step 306: setting a node name as a data name.
In this step, if the node name of the execution data is not configured in the monitor flag, the data name acquired in step 304 is set as the node name.
In one embodiment, for convenience in distinguishing nodes, the node name may be added to the @ Metrics annotation in advance. For example, for a rational procedure entry, the notes are: @ Metrics (memo= "rational main program").
Step 307: and recording name nodes of the execution data to a time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the name nodes.
In this step, the name node of the current execution data is recorded to the time sequence database according to the node name, wherein the case number can be used as an indexable tag, and the node name can be used as field.
Step 308: and judging whether the monitoring mark requires recording request parameters or not. If yes, go to step 309, otherwise, go to step 310.
In this step, in the actual scenario, if the request parameter needs to be recorded, the parameterMetrics may be set to true, for example, for policy check, the annotation is: @ methods (memo= "policy check", parametermerics = true). Then, whether the request parameters need to be recorded or not can be judged based on the mark of the currently intercepted Metrics notes on the request parameters. If not, the present step is skipped and step 310 is entered. If so, step 309 may be entered.
Step 309: acquiring request parameter information of the execution data, recording parameter nodes of the execution data to a time sequence database by taking the identification information as an index, and executing attribute information comprises the parameter nodes.
In this step, if the request parameter is required to be recorded in the monitoring flag, the request parameter node in the monitoring flag that requires recording of the current execution data is described. Request parameter information of the execution data is acquired. Because the request parameter information may include various types of data, the request parameter information may be formatted, for example, by uniformly formatting the date as "yyyy-MM-dd" and other information as a character string. And then recording the request parameter node into a time sequence database, taking the case number as an indexable tag, and taking the request parameter information as field.
Step 310: running the current execution data. And may obtain its return value.
Step 311: if an abnormality occurs in the running process of the execution data, judging whether the record execution abnormality is required in the monitoring mark. If yes, go to step 312, otherwise go to step 313.
In this step, during the execution of the data, an operation exception may be encountered, and if an exception occurs during the operation of the current execution method, an exception record flag of the current intercepted Metrics annotation is first obtained, and whether the exception needs to be recorded is determined. If not, the step is skipped. If so, step 312 is entered.
In an embodiment, in an actual scenario, if it is not necessary to record exception information, the extranmmetrics may be set to false in advance, for example, for a successful mail notification, the annotation is: @ Metrics (memory= "successfully calculated, send mail", extranmmetrics = false).
Step 312: and acquiring execution abnormal information of the execution data, recording abnormal nodes to a time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the abnormal nodes.
In this step, if the record execution abnormality is required in the monitoring flag, the execution abnormality information of the current execution data in the running process is acquired, and the abnormality information is formatted. Based on the anomaly information, recording the anomaly node to a time sequence database, wherein the case number can be used as an indexable tag, and the anomaly information is requested to be used as field.
Step 313: and judging whether the execution data is successfully executed or not based on the return value. If yes, go to step 314, otherwise go to step 316.
Step 314: and judging whether recording execution success information is required in the monitoring mark. If yes, go to step 315, otherwise go to step 318.
In this step, if the execution of the execution data is successful, the execution success flag of the currently intercepted metadata annotation is obtained, and whether the recording of the data execution success node is required is determined. If not, the present step is skipped and step 318 is entered. If yes, step 315 is entered.
In an embodiment, in an actual scenario, if it is not required to record whether the data is executed successfully, the method SuccessMetrics may be set to false, for example, for ticket ordering, note: @ methods (memo= "ticket ordering", method SuccessMetrics = false).
Step 315: if record execution success information is required in the monitoring mark, recording an execution success node to a time sequence database by taking the identification information as an index, and executing attribute information comprises the execution success node. Step 318 is then entered.
In this step, if the record of the execution success information is required in the monitoring tag, the execution success node is recorded in the time sequence database, the case number is used as the indexable tag, and the execution success tag is used as the field.
Step 316: if the execution of the execution data fails, judging whether the record of the execution failure information is required in the monitoring mark. If yes, go to step 317, otherwise go to step 318.
In this step, if the execution fails, the execution failure flag of the currently intercepted Metrics annotation may be obtained, and it may be determined whether the recording of the data execution failure flag is required. If not, the present step is skipped and step 318 is entered. If yes, go to step 317.
Step 317: recording the execution failure node to a time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the execution failure node. Step 318 is then entered.
In this step, if the record of the execution failure information is required in the monitoring flag, the execution failure node is recorded in the time sequence database, and the case number can be used as an indexable tag of the execution failure node, and the execution failure flag is used as field.
Step 318: and judging whether the monitoring mark requires recording a return value or not.
In this step, after the operation of the current execution data is finished, a return value is provided, and the return value also belongs to the execution attribute information of the current execution data. At this time, the return value record mark of the currently intercepted Metrics annotation can be obtained, and whether the return value record is needed in the annotation is judged. If not, then it may end. If so, step 319 is entered.
In one embodiment, if a return value needs to be recorded, return metrics may be set to true, such as for bill amount calculation, annotated as: @ methods (memory= "calculate billing amount according to rules", parameters methods = true, return methods = true).
Step 319: and recording the return value node to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the return value node.
In this step, if the record of the return value is required in the monitoring flag, the return value information is obtained, and the return value information may be formatted. And then the return value information node is recorded to a time sequence database, the case number is used as an indexable tag, and the return value information is used as field. And then returning the return value of the current execution data, and ending.
In an embodiment, if the execution attribute information carries an entity class, selecting a target entity class with preset annotation information in the execution attribute information, and recording the target entity class to the time sequence database according to the monitoring mark by taking the identification information as an index.
In a practical scenario, since there may be an entity class in the method parameters and return values, not all fields in the entity class need to be saved to the time-series database, the user may further process the entity class that needs to be saved. The preset annotation information is set, and the specific processing logic is to uniformly add @ Expose annotation to the field (target entity class) to be saved, so that when the field information with @ Expose annotation is saved in the time sequence database, only the field information with @ Expose annotation can be saved.
For example, the preset annotation information may be as follows:
balance//
@Expose
privateBigDecimal balance；
Freezing amount of// sheets
@Expose
privateBigDecimalfrozenFund；
Rate/consumption limit
@Expose
private Boolean limitPay＝false；
The method records the program operation parameters, the return values, the abnormal information and the like which need to be stored into the time sequence database, takes the case number as an indexable tag, and simultaneously, the time sequence database can automatically add a time stamp timestamp as a main key of the record, so that the calculation flow of each case, the circulation of the data state, the operation time of each key method and the like can be conveniently inquired, and the tracking and monitoring of the data execution process are realized.
Referring to fig. 4, a data execution tracking apparatus 400 according to an embodiment of the application is applicable to the electronic device shown in fig. 1 and can be applied to a settlement system scenario of online settlement of a policy for real-time monitoring and tracking of settlement information of the policy. The device comprises: the functional principles among the first acquisition module 401, the judgment module 402, the second acquisition module 403 and the recording module 404 are as follows:
the first obtaining module 401 is configured to obtain class information of the current execution data. See the description of step 201 in the above embodiments for details.
A judging module 402, configured to judge whether the monitoring mark exists in the execution data based on the class information. See the description of step 202 in the above embodiments for details.
The second obtaining module 403 is configured to obtain the identification information of the execution data if the monitoring mark exists in the execution data. See for details the description of step 203 in the above embodiments.
And the recording module 404 is configured to record the execution attribute information of the execution data to the time sequence database according to the monitoring mark with the identification information as an index. See the description of step 204 in the above embodiments for details.
In one embodiment, the recording module 404 is configured to: a data name of the execution data is acquired. It is determined whether the node name of the execution data is configured in the monitor flag. If the node name of the execution data is not configured in the monitoring mark, setting the node name as a data name, and recording the name node of the execution data to a time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the name node. See for details the description of the related method in the embodiment shown in fig. 3 above.
In one embodiment, the recording module 404 is configured to: and judging whether the monitoring mark requires recording request parameters or not. If the request parameters are required to be recorded in the monitoring mark, request parameter information of the execution data is obtained, the parameter nodes of the execution data are recorded to the time sequence database by taking the identification information as an index, and the execution attribute information comprises the parameter nodes. See for details the description of the related method in the embodiment shown in fig. 3 above.
In one embodiment, the recording module 404 is configured to: if an abnormality occurs in the running process of the execution data, judging whether the record execution abnormality is required in the monitoring mark. If the monitoring mark is required to record the execution abnormality, the execution abnormality information of the execution data is obtained, the abnormal node is recorded to the time sequence database by taking the identification information as an index, and the execution attribute information comprises the abnormal node. See for details the description of the related method in the embodiment shown in fig. 3 above.
In one embodiment, the recording module 404 is configured to: and acquiring a return value of the running execution data. And judging whether the execution data is successfully executed or not based on the return value. If the execution of the execution data is successful, judging whether the record of the execution success information is required in the monitoring mark. If record execution success information is required in the monitoring mark, recording an execution success node to a time sequence database by taking the identification information as an index, and executing attribute information comprises the execution success node. See for details the description of the related method in the embodiment shown in fig. 3 above.
In one embodiment, the recording module 404 is further configured to: if the execution of the execution data fails, judging whether the record of the execution failure information is required in the monitoring mark. If recording of execution failure information is required in the monitoring mark, recording of the execution failure node to the time sequence database is carried out by taking the identification information as an index, and the execution attribute information comprises the execution failure node. See for details the description of the related method in the embodiment shown in fig. 3 above.
In one embodiment, the recording module 404 is further configured to: and judging whether the monitoring mark requires recording a return value or not. If the monitoring mark is required to record the return value, recording the return value node to the time sequence database by taking the identification information as an index, and executing the attribute information comprises the return value node. See for details the description of the related method in the embodiment shown in fig. 3 above.
In one embodiment, the recording module 404 is configured to: if the execution attribute information carries entity class, selecting target entity class with preset annotation information in the execution attribute information, and recording the target entity class to the time sequence database by taking the identification information as an index according to the monitoring mark. See for details the description of the related method in the embodiment shown in fig. 3 above.
For a detailed description of the data execution tracking device 400, please refer to the description of the relevant method steps in the above embodiment.
The embodiment of the application also provides a non-transitory electronic device readable storage medium, which comprises: a program which, when run on an electronic device, causes the electronic device to perform all or part of the flow of the method in the above-described embodiments. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a Flash Memory (Flash Memory), a Hard Disk (HDD), or a Solid State Drive (SSD), etc. The storage medium may also comprise a combination of memories of the kind described above.
Although embodiments of the present application have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the application, and such modifications and variations are within the scope of the application as defined by the appended claims.

Claims (9)

1. A method for tracking data execution, wherein the method is used for real-time monitoring of policy management information, and the method comprises the following steps:
acquiring class information of current execution data; the current execution data specifically comprises an execution method in the execution code, and the class information is used for annotating various attribute information of the execution data;
judging whether a monitoring mark exists in the execution data or not based on the class information; the monitoring mark is an annotation class which is added in the class information in advance, wherein the annotation class specifically comprises annotation class Metrics defined by adopting an AOP technology;
if the monitoring mark exists in the execution data, acquiring the identification information of the execution data;
recording the execution attribute information of the execution data to a time sequence database by taking the identification information as an index according to the monitoring mark;
wherein, according to the monitoring mark, the recording the execution attribute information of the execution data to a time sequence database by taking the identification information as an index includes:
judging whether the monitoring mark requires recording request parameters or not;
and if the request parameters are required to be recorded in the monitoring marks, acquiring request parameter information of the execution data, and recording parameter nodes of the execution data to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the parameter nodes.
2. The method according to claim 1, wherein recording the execution attribute information of the execution data to a time-series database according to the monitoring flag with the identification information as an index, comprises:
acquiring a data name of the execution data;
judging whether the node name of the execution data is configured in the monitoring mark;
if the node name of the execution data is not configured in the monitoring mark, setting the node name as the data name, and recording the name node of the execution data to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the name node.
3. The method according to claim 1, wherein recording the execution attribute information of the execution data to a time-series database according to the monitoring flag with the identification information as an index, comprises:
if an abnormality occurs in the running process of the execution data, judging whether the monitoring mark is required to record the execution abnormality or not;
and if the monitoring mark is required to record the execution abnormality, acquiring the execution abnormality information of the execution data, and recording abnormal nodes to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the abnormal nodes.
4. The method according to claim 1, wherein recording the execution attribute information of the execution data to a time-series database according to the monitoring flag with the identification information as an index, comprises:
acquiring a return value for running the execution data;
judging whether the execution data is successfully executed or not based on the return value;
if the execution data is successfully executed, judging whether the execution success information is required to be recorded in the monitoring mark;
and if the monitoring mark is required to record the execution success information, recording an execution success node to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the execution success node.
5. The method of claim 4, wherein recording the execution attribute information of the execution data to a time-series database according to the monitoring flag with the identification information as an index, further comprises:
if the execution data fails to be executed, judging whether the execution failure information is required to be recorded in the monitoring mark;
and if the monitoring mark is required to record the execution failure information, recording an execution failure node to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the execution failure node.
6. The method of claim 4, wherein recording the execution attribute information of the execution data to a time-series database according to the monitoring flag with the identification information as an index, further comprises:
judging whether the monitoring mark requires recording the return value or not;
and if the monitoring mark is required to record the return value, recording a return value node to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the return value node.
7. The method according to claim 1, wherein recording the execution attribute information of the execution data to a time-series database according to the monitoring flag with the identification information as an index, comprises:
and if the execution attribute information carries entity class, selecting a target entity class with preset annotation information in the execution attribute information, and recording the target entity class to the time sequence database by taking the identification information as an index according to the monitoring mark.
8. A data execution tracking device for real-time monitoring of policy management information, the device comprising:
the first acquisition module is used for acquiring class information of the current execution data; the current execution data specifically comprises an execution method in the execution code, and the class information is used for annotating various attribute information of the execution data;
the judging module is used for judging whether the monitoring mark exists in the execution data or not based on the class information; the monitoring mark is an annotation class which is added in the class information in advance, wherein the annotation class specifically comprises annotation class Metrics defined by adopting an AOP technology;
the second acquisition module is used for acquiring the identification information of the execution data if the monitoring mark exists in the execution data;
the recording module is used for recording the execution attribute information of the execution data to a time sequence database by taking the identification information as an index according to the monitoring mark;
wherein, according to the monitoring mark, the recording the execution attribute information of the execution data to a time sequence database by taking the identification information as an index includes:
judging whether the monitoring mark requires recording request parameters or not;
and if the request parameters are required to be recorded in the monitoring marks, acquiring request parameter information of the execution data, and recording parameter nodes of the execution data to the time sequence database by taking the identification information as an index, wherein the execution attribute information comprises the parameter nodes.
9. An electronic device, comprising:
a memory for storing a computer program;
a processor configured to perform the method according to any one of claims 1 to 7, so as to record the execution attribute information of the current execution data into the time-series database.
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