User behavior analysis method and system based on streaming calculation

Abstract

The embodiment of the invention provides a user behavior analysis method and system based on streaming calculation. The method and system are used for achieving real-time analysis of user behaviors and improving the accuracy of user behavior analysis. The method comprises the steps that user behavior data is acquired from at least two channels and is converted into JSON data packets in a unified format, wherein the user behavior data comprises user behavior paths, time indexes, user basic label data, transaction data, activation and retention, click behaviors and platform types; a Spark Streaming computing engine is used for carrying out real-time user behavior analysis on the user behavior data, wherein the user behavior analysis comprises event analysis, user retention analysis, funnel analysis, user behavior path analysis, transaction analysis, user portraits and click analysis; user behavior analysis results are stored, and corresponding analysis results are displayed according toquery requests of users.

Description

technical field [0001] The invention relates to the technical field of big data processing, in particular to a user behavior analysis method and system based on stream computing. Background technique [0002] User behavior analysis refers to the collection, sorting, and statistics of all data in the process of users using products, and analyzes the rules of users using products, so as to provide strong data support for subsequent development, optimization or marketing of products. In the era of information explosion, information is increasing at a geometric rate every day, which makes all major Internet companies in the market face severe challenges. [0003] In existing solutions, user behavior data is often collected through a single channel, such as a separate Web terminal or a separate App terminal. The amount of user behavior data collected for a single user is relatively small, which affects the accuracy of user behavior analysis results. Secondly, the existing user b...

AI Technical Summary

Problems solved by technology

[0003] In existing solutions, the collection of user behavior data is often a single channel, such as a separate Web terminal or a separate App terminal. The amount of user behavior data collected for a single user is relatively small, which affects the accuracy of user behavior analysis results

Secondly, the existing user behavior data engine analysis mechanism uses the Map / Reduce batch processing mechanism under the Hadoop architecture, which cannot process user behavior data in real time, resulting in delays in the analysis results of user behavior data

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