Apache Beam 提供了 Splittable DoFn Streaming API，它允许用户创建可拆分的并行处理函数，并在流式数据处理步骤中使用它们。

以下是一个使用 Splittable DoFn 的示例代码：

import org.apache.beam.sdk.transforms.DoFn;
import org.apache.beam.sdk.transforms.splittabledofn.OffsetRange;
import org.apache.beam.sdk.transforms.splittabledofn.RestrictionTracker;
import org.apache.beam.sdk.transforms.splittabledofn.SplitResult;

public class MyDoFn extends DoFn {
  @ProcessElement
  public void processElement(ProcessContext c, RestrictionTracker tracker) {
    OffsetRange range = tracker.currentRestriction();
    for (long i = range.getFrom(); tracker.tryClaim(i) && i < range.getTo(); ++i) {
      // Process input element with index i.
      c.output("Processed element " + i);
    }
  }

  @GetInitialRestriction
  public OffsetRange getInitialRestriction(String element) {
    // Split the global range into subranges and assign one to each worker.
    return new OffsetRange(0L, 100L);
  }

  @SplitRestriction
  public SplitResult splitRestriction(
      String element, OffsetRange restriction) {
    // Split the given range into sub-ranges that can be processed independently.
    long midpoint = (restriction.getFrom() + restriction.getTo()) / 2;
    return SplitResult.of(
        new OffsetRange(restriction.getFrom(), midpoint),
        new OffsetRange(midpoint, restriction.getTo()));
  }

  @NewTracker
  public RestrictionTracker newTracker(OffsetRange range) {
    // Return a new RestrictionTracker suitable for processing a subrange of the input
    // based on the given initial restriction.
    return new MyRestrictionTracker(range);
  }
}

此代码定义了一个可拆分的 DoFn，它从输入字符串流中处理元素，并输出处理后的字符串流。

我们可以使用此 DoFn 在 Apache Beam 流水线中进行流式处理，如下所示：

PipelineOptions options = PipelineOptionsFactory.create();
Pipeline p = Pipeline.create(options);

p.apply("ReadFromSource", TextIO.read().from("inputFile.txt"))
    .apply(ParDo.of(new MyDoFn()))
    .apply("WriteToSink", TextIO.write().to("outputFile.txt"));

p.run();

此代码从输入文件中读取字符串流