![]() Specifying a WatermarkStrategy directly on the Then track watermarks at a finer level and the overall watermark produced by a The first option is preferable, because it allows sources to exploit knowledgeĪbout shards/partitions/splits in the watermarking logic. Used: 1) directly on sources and 2) after non-source operation. There are two places in Flink applications where a WatermarkStrategy can be Attention: Both timestamps and watermarksĪre specified as milliseconds since the Java epoch of. We will look at the WatermarkGenerator interface later in Writing Would get timestamps directly from the Kafka/Kinesis records. For example, when using Kafka or Kinesis you Specifying a TimestampAssigner is optional and in most cases you don’tĪctually want to specify one. with_timestamp_assigner ( FirstElementTimestampAssigner ()) Here is the interface for completeness’ sake:Ĭlass FirstElementTimestampAssigner ( TimestampAssigner ): def extract_timestamp ( self, value, record_timestamp ): return value WatermarkStrategy \ Users can also build their own strategies when required. A number of common strategiesĪre available out of the box as static methods on WatermarkStrategy, but TimestampAssigner and WatermarkGenerator. The Flink API expects a WatermarkStrategy that contains both a Timestamp assignment goes hand-in-hand with generating watermarks, which tell Timestamp from some field in the element by using a TimestampAssigner. This is usually done by accessing/extracting the Timestamps, meaning each element in the stream needs to have its event In order to work with event time, Flink needs to know the events Time, processing time, and ingestion time, please refer to the With event time timestamps and watermarks. In this section you will learn about the APIs that Flink provides for working ![]() We recommend you use the latest stable version. This documentation is for an unreleased version of Apache Flink. The Deprecated AssignerWithPeriodicWatermarks and AssignerWithPunctuatedWatermarks.Watermark Strategies and the Kafka Connector.Writing a Punctuated WatermarkGenerator.Hadoop MapReduce compatibility with Flink.Conversions between Table and DataStream.Conversions between PyFlink Table and Pandas DataFrame. ![]()
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