Help Center> MapReduce Service> Developer Guide (2.x and Earlier)> Flink Application Development> Application Development> Stream SQL Join Application> Scenario Description
Scenario Description
Assume that a Flink service receives a message every second. The message records the basic information about a user, including the name, gender, and age. Another Flink service (service 2) receives a message irregularly, and the message records the name and career information about the user.
To meet the requirements of some services, a Flink application is developed to achieve the following function: uses the username recorded in the message received by service 2 as a keyword to jointly query service data.
Data Planning
- The data of service 1 is stored in the Kafka component. Data is sent to and received from Kafka (user with Kafka permission required). For details about Kafka configuration, see Data Planning.
- Service 2 receives messages using the socket. You can run the netcat command to input the analog data source.
- Run the Linux command netcat -l -p <port> to start a simple text server.
- After starting the application to connect to the port monitored by netcat, enter the data information to the netcat terminal.
Development Guidelines
- Start the Flink Kafka Producer application to send data to Kafka.
- Start the Flink Kafka Consumer application to receive data from Kafka and create Table1. Ensure that topics of Kafka Consumer are consistent with that of Kafka Producer.
- Read data from the socket and create Table2.
- Use Flink SQL to jointly query Table1 and Table2 and print the result.
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