This documentation is for an unreleased version of Apache Flink. We recommend you use the latest stable version.

Note: DataStream API V2 is a new set of APIs, to gradually replace the original DataStream API. It is currently in the experimental stage and is not fully available for production.

Watermark #

Before introducing Watermark, users should be aware that Watermark in DataStream V2 does not refer to the original Watermark that measure progress in event time, but is a special event that can be customized by the user and can be propagated along the streams.

Using Watermark in Flink involves three key steps:

1. Define and Declare the Watermark
2. Emit the Watermark
3. Handle the Watermark

Let’s follow these steps to understand how to use Watermark in Flink.

Define and Declare Watermark #

A watermark is a special event that carries data. It can be emitted from a Source or ProcessFunction, propagating along streams, received by downstream ProcessFunction. When defining a Watermark, there are four aspects need to consider:

1. [Required] Watermark Identifier

   Since multiple types of Watermarks can propagate in streams, it’s essential to assign an identifier to each Watermark for differentiation.

   Note that the identifier must be a String, is case-sensitive, and must be globally unique within the entire job.

2. [Required] Watermark Data Type

   It is important to specify the data type of the Watermark. Currently, Flink supports two types: Long and Bool.

3. [Required] Combine Function and combineWaitForAllChannels

   A ProcessFunction may receive multiple Watermarks from different input channels due to having multiple upstream inputs, each potentially with varying degrees of parallelism. In such cases, users often wish to combine Watermarks from input channels before outputting to the ProcessFunction.

   Flink supports the following combination functions:

   • For Long type Watermark:
     • MIN: Retains and outputs the minimum value of all received watermarks.
     • MAX: Retains and outputs the maximum value of all received watermarks.
   • For Bool type Watermark:
     • AND: Retains and outputs the logical AND result of all received watermarks.
     • OR: Retains and outputs the logical OR result of all received watermarks.

   Additionally, users can configure whether the combining process should wait until the ProcessFunction has received Watermarks from all upstream channels. This is particularly useful in some scenarios. For example, the event time watermark need to wait receives the watermarks from all inputs and then combine them. This ensures that the time carried by the event time watermark does not decrease. By default, the combineWaitForAllChannels setting is false.

4. [Optional] WatermarkHandlingStrategy by Framework

   The WatermarkHandlingStrategy determines whether the framework should send the watermark to downstream ProcessFunction when the user-defined ProcessFunction does pop the Watermark. There are two options of this setting:

   • IGNORE: The framework shouldn’t take any action.
   • FORWARD: The framework should send the watermark to downstream.

   This optional setting is useful in some cases. For example, setting it to IGNORE can indicate that the framework does not need to propagate this Watermark, but rather that it is up to the user to control its sending.

To simplify the process of defining a Watermark, Flink offer a WatermarkBuilder. This builder ultimately creates a WatermarkDeclaration object. Below is an example demonstrating how to use it to defining a Watermark:

LongWatermarkDeclaration watermarkDeclaration = WatermarkDeclarations  .newBuilder("MY_CUSTOM_WATERMARK_IDENTIFIER")  .typeLong()  .combineFunctionMax()  .combineWaitForAllChannels(true)  .defaultHandlingStrategyForward()  .build(); 

Once users have defined the Watermark, it is essential to declare it in the ProcessFunction#declareWatermarks or Source#declareWatermarks. This step allows the framework to recognize it properly. Here’s an example of how to declare the Watermark in the ProcessFunction:

public class CustomProcessFunction  implements OneInputStreamProcessFunction<Long, Long> {   LongWatermarkDeclaration watermarkDeclaration = ...;   @Override  public Set<? extends WatermarkDeclaration> declareWatermarks() {  return Set.of(watermarkDeclaration);  } } 

Please note that each type of Watermark only needs to be declared once in a job.

Emit Watermark #

Users can utilize the Watermark declaration to create a watermark. Below is an example of how to generate a Long type watermark with a value of 1:

LongWatermarkDeclaration watermarkDeclaration = ...; LongWatermark watermark = watermarkDeclaration.newWatermark(1); 

And users can emit Watermark in ProcessFunction by calling nonPartitionedContext.getWatermarkManager().emitWatermark(watermark), it is also support emit Watermark in Source by calling sourceReaderContext.emitWatermark(watermark). Here is an example of how to emit a Watermark in a ProcessFunction:

public class CustomProcessFunction  implements OneInputStreamProcessFunction<Long, Long> {   LongWatermarkDeclaration watermarkDeclaration = ...;   @Override  public Set<? extends WatermarkDeclaration> declareWatermarks() {  return Set.of(watermarkDeclaration);  }   @Override  public void processRecord(Long record, Collector<Long> output, PartitionedContext<Long> ctx)  throws Exception {  // do something as needed   // generate and emit Watermark  LongWatermark watermark = watermarkDeclaration.newWatermark(1);  ctx.getNonPartitionedContext().getWatermarkManager().emitWatermark(watermark);  } } 

Handle Watermark #

Once the ProcessFunction receives a Watermark, the framework will invoke the ProcessFunction#onWatermark method to process it. Therefore, users will need to override ProcessFunction#onWatermark in order to handle the Watermark appropriately.

The return value of the ProcessFunction#onWatermark method is of type WatermarkHandlingResult, which has two possible options:

• PEEK: ProcessFunction only peek the Watermark, and it’s framework’s responsibility to handle this watermark.

  The framework will forward/ignore the Watermark according to the WatermarkHandlingStrategy associated with it.

• POLL: This Watermark should be sent to downstream by process function itself. The framework does no additional processing.

By default, the ProcessFunction#onWatermark method returns WatermarkHandlingResult.PEEK.

Here is an example of how to handle Watermarks in ProcessFunction:

 public static final String CUSTOM_WATERMARK_IDENTIFIER = "CUSTOM_WATERMARK_IDENTIFIER";  public class CustomProcessFunction  implements OneInputStreamProcessFunction<Long, Long> {   ...   @Override  public WatermarkHandlingResult onWatermark(  Watermark watermark, Collector<Long> output, NonPartitionedContext<Long> ctx) {  // For Watermark that this ProcessFunction is interested in, process the watermark  if (watermark.getIdentifier().equals(CUSTOM_WATERMARK_IDENTIFIER)) {  // do something as needed  }   // For other Watermarks, return PEEK  return WatermarkHandlingResult.PEEK;  } } 

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