A data processing method and device

Abstract

A data processing method and device provided by an embodiment of the present invention belong to the field of data processing. The method includes obtaining an index value instruction; obtaining the identification information corresponding to the index value instruction; parsing the key set corresponding to the identification information; storing the current key corresponding to the current moment in the key set in the distributed The historical key set corresponding to the cache and the historical moment is stored in the local cache; the value corresponding to the current key is obtained from the distributed cache and each key in the historical key set is obtained from the local cache The corresponding value, and generate the target set. In order to achieve the technical effect of reducing the amount of network transmission and saving the calculation amount of distributed cache.

Description

technical field [0001] The present invention relates to the field of data processing, in particular to a data processing method and device. Background technique [0002] At present, in the indicator calculation of the distributed real-time risk control system, the rules of the strategy exist in many forms. Indicators are one of them. Indicators are usually accompanied by a large number of complex calculations, and the data is continuously added to the indicators for calculation, and the duration is variable. Some only last for a few seconds, while others take several months. , or even longer. At present, in order to prevent malicious acts of black production, the duration of indicators is usually divided into time slices one by one, but this is followed by the management of time slices one by one. The distributed risk control system needs to identify the business system in real time. The request risk has very strict requirements on efficiency and response, so business clas...

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Problems solved by technology

At present, in order to prevent malicious acts of black production, the duration of indicators is usually divided into time slices one by one, but this is followed by the management of time slices one by one. The distributed risk control system needs to identify the business system in real time. The request risk has very strict requirements on efficiency and response, so business classes usually store all time slices and corresponding data in the distributed cache, but this will cause a large amount of network transmission on the indicator server, and the need to process the key every time is huge CPU consumption, and easily lead to network congestion, resulting in high response delay

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