Use states to compute metrics in a real-time data stream. Review how state variables behave during processing operations.
- [Instructor] In this video, … we will continue with the example … in the previous video, … and use the state setup to monitor delete alerts. … Given that the output table has a number … of no-alert messages too, … we will first use a filter function … to filter out these alerts. … We check if the first attribute is equal to null alerts. … If so, we ignore them. … Else, we print the alert that the delete happened … for a given user within ten seconds. … There are multiple ways to achieve this alert. … We could have also published these alert messages … through a site output, if we are doing other processing … with a regular map. … Now, let's execute this code and look at the results. … Given that we are generating operations … and timestamps randomly, it may take some time to get a user … with two delete operations within ten seconds. … We have a delete alert received for user Bob, … because he had two deletes within 313 milliseconds. … …
- Streaming with Apache Flink
- Using the DataStream API for basic stream processing
- Working with process functions
- Windowing and joins
- Setting up event-time processing
- State management in Flink
Skill Level Advanced
1. Apache Flink
2. DataStream API
4. Event Time Processing
5. State Management
6. Use Case Project
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