How to implement a custom data transformation function in Apache Beam?

In Apache Beam, you can implement custom data transformation functions by inheriting from the DoFn class. Here is a simple example demonstrating how to implement a custom data transformation function:

import org.apache.beam.sdk.transforms.DoFn;
import org.apache.beam.sdk.values.KV;

public class CustomTransform extends DoFn<KV<String, Integer>, String> {
  
  @ProcessElement
  public void processElement(ProcessContext c) {
    KV<String, Integer> input = c.element();
    String key = input.getKey();
    Integer value = input.getValue();
    
    String output = "Key: " + key + ", Value: " + value;
    
    c.output(output);
  }
}

In the example above, we defined a custom transformation function called CustomTransform, which inherits from the DoFn class and implements the processElement method. Within the processElement method, we have access to the input data and can apply any custom processing to it. Finally, we output the transformed data by calling the output method of ProcessContext.

To use a custom transformation function in an Apache Beam pipeline, you can apply the function by using the ParDo transform, for example:

PCollection<KV<String, Integer>> input = ... // input PCollection

PCollection<String> output = input.apply(ParDo.of(new CustomTransform()));

In the example above, we apply a custom transformation function CustomTransform to the input PCollection, using the ParDo.of method to create the ParDo transform. Finally, we get an output PCollection containing the data processed by CustomTransform.