Comparison of Flink application scenarios and other real-time computing frameworks
1. Flink application scenarios
In the actual production process, a large amount of data is continuously generated, such as financial transaction data, Internet order data, GPS positioning data, sensor signals, data generated by mobile terminals, communication signal data, etc., as well as network traffic monitoring and server data that we are familiar with. The generated log data, the biggest commonality of these data is that they are generated from different data sources in real time, and then transmitted to the downstream analysis system. For these data types, it mainly includes real-time business scenarios such as real-time intelligent recommendation, complex event processing, real-time fraud detection, real-time data warehouse and ETL type, stream data analysis type, real-time report type, etc., and Flink is very good at these types of scenarios support.
1. Real-time intelligent recommendation
Intelligent recommendation will train the model through the recommendation algorithm based on the user's historical purchase behavior&#x