Data request processing method and device, storage medium and electronic device

Abstract

The invention discloses a data request processing method and device, a storage medium and an electronic device. The method comprises the following steps: receiving a target data request; writing the target data request into a first message queue, wherein the first message queue comprises data requests to be sent to a data source server, the data requests in the first message queue are set to be taken out from the first message queue according to a sending period and sent to the data source server, and the number of the data requests taken out from the first message queue in each sending period is the same; and when the target sending period arrives, taking out a plurality of data requests including the target data request from the first message queue, and sending the plurality of data requests including the target data request to a data source server so as to inform the data source server to obtain the target data requested by the plurality of data requests.

Description

technical field [0001] The present application relates to the technical field of data processing, and in particular, to a data request processing method and device, a storage medium, and an electronic device. Background technique [0002] In some scenarios, it is difficult to obtain server data, and there are limited frequency requirements. For example, only one query interaction within a specified threshold can be checked per second, but the request volume of the application side is very large, far exceeding the query frequency limit. Then when the number of users increases, Or during the peak period of business, there will be problems such as data query failure, call data timeout, or even the service of the data provider. This will seriously affect user experience and business growth, and will also affect the reliability and stability of data provider services. [0003] The solution in the prior art is to alleviate the pressure on the data server by adding a cache server,...

AI Technical Summary

Problems solved by technology

[0002] In some scenarios, it is difficult to obtain server data, and there are limited frequency requirements. For example, only one query interaction within a specified threshold can be checked per second, but the request volume of the application side is very large, far exceeding the query frequency limit. Then when the number of users increases, Or during the peak period of business, there will be problems such as data query failure, call data timeout, or even the service of the data provider.

This will seriously affect user experience and business growth, and will also affect the reliability and stability of data provider services

[0003] The solution in the prior art is to alleviate the pressure on the data server by adding a cache server, but the data in the cache server cannot guarantee the real-time performance of the data, and, when there is no requested data in the cache server, there will still be a large number of The requests are pouring into the data server, and the root problem is not solved

[0004] For the above problems, no effective solution has been proposed

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