This segment will cover the various types of transformations available with the Datastream API.
In the upcoming video, our expert will demonstrate the transformations using a Flink program in Java.
Let’s summarise your learnings from this video.
Transformations
The table given below presents some of the transformations available in the DataStream API.
| Name | Use |
| Map | Takes an element in one format and transforms it into another one |
| FlatMap | Takes one element and produces zero, one or more elements in the same or a different format |
| Filter | Filters values for which the expression returns a false value |
| Union | Produces the union of two data sets |
| Join | Joins two data sets in a manner similar to SQL |
| KeyBy | Logically partitions a stream into disjoint partitions based on keys |
| Reduce | Combines the current element with the last reduced value and emits the new value |
Additional Reading
- Transformations – This is the official documentation link in which all the DataStream API transformation functions have been explained. Refer to this link before attempting the in-segment questions.
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