CN-121979741-A - Data processing method and device, electronic equipment and storage medium

CN121979741ACN 121979741 ACN121979741 ACN 121979741ACN-121979741-A

Abstract

The invention discloses a data processing method, a data processing device, electronic equipment and a storage medium, and relates to the technical field of data processing. The data processing method comprises the steps of obtaining attribute characteristics of a service interface request, generating an access log according to the attribute characteristics, obtaining a history request log, determining a system fusing strategy according to the access log, the history request log and a preset fusing rule, determining history response data under the condition that the system fusing strategy is fusing, determining a data type of the history response data according to a target classification model, and determining target response data according to the data type and the history response data. The embodiment of the invention improves the rationality of system fusing, simultaneously avoids the incapability of responding to the request in the system fusing process, and improves the robustness and the user experience of the system.

Inventors

ZHOU YAN
TIAN GUOLIANG
ZHANG YU

Assignees

中国移动通信集团江苏有限公司
中国移动通信集团有限公司

Dates

Publication Date: 20260505
Application Date: 20260116

Claims (10)

1. A method of data processing, comprising: acquiring attribute characteristics of a service interface request, and generating an access log according to the attribute characteristics; acquiring a history request log, and determining a system fusing strategy according to the access log, the history request log and a preset fusing rule; When the system fusing strategy is fusing, historical response data are determined, the data type of the historical response data is determined according to a target classification model, and target response data are determined according to the data type and the historical response data.
2. The method of claim 1, wherein the obtaining the attribute characteristics of the service interface request, and generating the access log according to the attribute characteristics, comprises: extracting dimension information of a service interface request in a target dimension, and taking the dimension information as attribute characteristics; and packaging the attribute features into a structured log, and taking the structured log as an access log.
3. The method of claim 1, wherein the obtaining the history request log, determining the system fusing policy based on the access log, the history request log, and a preset fusing rule, comprises: determining attribute dimensions of attribute features in an access log, taking a history request log matched in a current statistical period according to the attribute dimensions as a first target request log, and taking a history request log matched in a history statistical period according to the attribute dimensions as a second target request log; Determining the request success rate and the request call quantity of the first target request log as real-time indexes, and determining the request success rate and the request call quantity of the second target request log as historical indexes; Extracting a preset fusing rule, and determining a difference value between the historical index and the real-time index as a difference value index; and determining a system fusing strategy according to the preset fusing rule, the difference index and the real-time index.
4. A method according to claim 3, wherein the preset fusing rules include at least: Determining that the system fusing strategy is fusing under the condition that the real-time index meets a preset fixed fusing threshold or a preset window fusing threshold and the difference index meets a preset difference fusing threshold; And determining that the system fusing strategy is fusing under the condition that the real-time index does not meet the preset fixed fusing threshold and the real-time index does not meet the preset window fusing threshold, but the difference index meets the preset difference fusing threshold.
5. The method of claim 1, wherein said determining historical response data, determining a data type of said historical response data based on a target classification model, determining target response data based on said data type and said historical response data, comprises: extracting response data stored in a first target request log in the history request log as history response data; inputting historical response data into a target classification model, and determining the data type of the historical response data through the target classification model, wherein the data type comprises unchanged data and changed data; When the data type is determined to be unchanged data, the historical response data is taken as target response data; and when the data type is determined to be the change data, determining a corresponding preset data determination rule of the historical response data, and determining target response data according to the historical response data and the preset data determination rule.
6. The method of claim 1, further comprising, after the obtaining the history request log and determining the system fusing policy according to the access log, the history request log, and a preset fusing rule: And when the system fusing strategy is not fused, sending the service interface request to a target application cluster so that the target application cluster feeds back target response data according to the service interface request.
7. The method of claim 1, wherein determining historical response data when the system blowing policy is blown, determining a data type of the historical response data according to a target classification model, and after determining target response data according to the data type and the historical response data, further comprises: acquiring a preset system recovery test case corresponding to the attribute characteristics, and executing the preset system recovery test case according to the preset execution frequency to obtain a test case result; and when the test case result meets the preset condition and exceeds the preset times, determining that the system is restored, and updating the system fusing strategy to be not fused.
8. A data processing apparatus, comprising: the log determining module is used for acquiring attribute characteristics of the service interface request and generating an access log according to the attribute characteristics; the strategy determining module is used for acquiring a history request log and determining a system fusing strategy according to the access log, the history request log and a preset fusing rule; And the data response module is used for determining historical response data under the condition that the system fusing strategy is fusing, determining the data type of the historical response data according to the target classification model, and determining target response data according to the data type and the historical response data.
9. An electronic device, the electronic device comprising: at least one processor, and A memory communicatively coupled to the at least one processor, wherein, The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the data processing method of any one of claims 1-7.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores computer instructions for causing a processor to implement the data processing method of any one of claims 1-7 when executed.

Description

Data processing method and device, electronic equipment and storage medium Technical Field The present invention relates to the field of data processing technologies, and in particular, to a data processing method, a data processing device, an electronic device, and a storage medium. Background With the widespread use of micro-service architecture in software development, stability of services and user experience become particularly important. When a service fails or a response is delayed, a fusing mechanism is often required to prevent the failure from spreading. However, the conventional fusing mechanism is mostly dependent on a fixed threshold, does not have dynamic adjustment capability, is difficult to adapt to complex and changeable flow conditions, and usually needs to preset fusing return or simple rules, but such rules often cannot bring better experience to users. Currently, fixed threshold fusing mechanisms are the most traditional fusing strategies. It determines whether to trigger a blow based on a preset fixed threshold. When the failure rate or response time of a certain service exceeds a preset threshold, the fuse is opened to prevent further requests for the service and prevent other services from being influenced by the failure of the service. Its advantages are simple implementation, easy understanding and configuration, and stable and predictable flow environment. But lacks flexibility and is difficult to cope with dynamically changing traffic and complex service dependencies. And a fixed threshold may not be applicable to all scenarios, possibly resulting in false triggers or failures. The sliding window fusing mechanism determines whether to trigger fusing by counting the number of requests and failures within a certain time window. It splits the request data in the time dimension, calculates the failure rate, and controls the fusing state with finer granularity. The method can more accurately reflect the performance of the service in different time periods and reduce misjudgment. Flexibility and response capability are improved, and short-term flow fluctuation is adapted. But it is relatively complex to implement and requires maintenance and processing of the time window data. In a high concurrency environment, the selection of a time window may affect performance. The above fusing mechanism focuses on linkage failure caused by service failure and on maintaining the stability of the whole service. The availability of service return data at the time of actual degradation is not adaptable to each system. Therefore, how to reasonably trigger fusing becomes a problem to be solved in the prior art. Disclosure of Invention The invention provides a data processing method, a data processing device, electronic equipment and a storage medium, which are used for solving the problem that the dynamic adjustment capability is low when fusing is triggered in the prior art. According to an aspect of the present invention, there is provided a data processing method, wherein the method includes: acquiring attribute characteristics of a service interface request, and generating an access log according to the attribute characteristics; acquiring a history request log, and determining a system fusing strategy according to the access log, the history request log and a preset fusing rule; When the system fusing strategy is fusing, historical response data are determined, the data type of the historical response data is determined according to a target classification model, and target response data are determined according to the data type and the historical response data. According to another aspect of the present invention, there is provided a data processing apparatus, wherein the apparatus comprises: the log determining module is used for acquiring attribute characteristics of the service interface request and generating an access log according to the attribute characteristics; the strategy determining module is used for acquiring a history request log and determining a system fusing strategy according to the access log, the history request log and a preset fusing rule; And the data response module is used for determining historical response data under the condition that the system fusing strategy is fusing, determining the data type of the historical response data according to the target classification model, and determining target response data according to the data type and the historical response data. According to another aspect of the present invention, there is provided an electronic apparatus including: at least one processor, and A memory communicatively coupled to the at least one processor, wherein, The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the data processing method according to any one of the embodiments of the present invention. According to another aspect of the present invention, there is provided a comput