Method and device for detecting high-frequency call, electronic equipment and readable storage medium

Abstract

The embodiment of the invention provides a method and device for detecting a high-frequency call, electronic equipment and a readable storage medium. The method comprises the following steps: collecting signaling data of a user call service, and obtaining identification information and latest call time of a user; reading a first user call information bitmap and the last call time of the first user call information bitmap in a preset time window from a memory database according to the identification information of the user, and updating the first user call information bitmap according to the latest call time and the last call time to obtain a second user call information bitmap; determining high-frequency call information of a user in a second user call information bitmap according to a preset high-frequency call rule, and writing the second user call information bitmap into the memory database to replace the first user call information bitmap; and reading the label information of the user from the memory database according to the identification information of the user, and filtering the high-frequency call information of the user to obtain target high-frequency call information. According to the embodiment of the invention, the high-frequency call information can be obtained through one-time real-time calculation.

Description

technical field [0001] The present invention relates to the field of big data technology, in particular to a method for identifying high-frequency calls, a device for identifying high-frequency calls, electronic equipment, and a computer-readable storage medium. Background technique [0002] At present, in real-time applications in the telecommunications industry, it is usually necessary to identify high-frequency calls of users through signaling bills. After analyzing and verifying the high-frequency call numbers, the voice function of suspected fraudulent users is restricted. For example, high-frequency calls can be Make calls more than 5 times within 5 minutes, and use the user's tag information to filter to get the final high-frequency call user. At present, two methods are usually used to identify high-frequency calls of users: one is to process through real-time streaming engine, based on the time window API of the engine, to cache the user's detailed data, and to land...

AI Technical Summary

Problems solved by technology

[0004] For the second solution, HBASE is used to record the time point when the user has a specific behavior within a certain period in a column. Based on the HBASE reading method, it is necessary to take out the complete record from HBASE each time for statistical analysis of the time period. Calculate the behavior of users. In this process, the concurrent throughput of HBASE is huge, and the large-scale data interaction will easily cause pressure on the bandwidth. In addition, because the user's label information needs to be filtered, HIVE / SPARK's Secondary calculations, resulting in data that cannot be processed in real time

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