Multiple independent streams may need to be merged to deliver new insights. Use Flink to merge multiple streams and process merged data.
- [Instructor] In the next video, … I will show you how to combine two streams … of different formats with the connect operator. … Please note that this is a real time streaming scenario, … the content of two streams are not deterministic … and cannot be assumed to have any kind of synchronization. … Hence, a real horizontal combine … like a SQL join type operation is not possible … unless there is a window. … But we can combine two streams vertically … using the connect operator. … For this example, we will use the data streams … we created in the earlier example. … Customer trail and sales rep trail. … Both streams are of different formats. … One is a POJO object called audit trail … and the other is a tuple. … We can combine them together … and push them in the same format using the connect function. … We use the connect function on the first data stream … to connect it to the second data stream … and deliver a connected streams object called merge trail. … This object has both the data types, …
- 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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