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  • pyflink.datastream.stream_execution_environment.StreamExecutionEnvironment.from_source

pyflink.datastream.stream_execution_environment.StreamExecutionEnvironment.from_source#

StreamExecutionEnvironment.from_source(source: Source, watermark_strategy: WatermarkStrategy, source_name: str, type_info: TypeInformation | None = None) → DataStream[source]#

Adds a data Source to the environment to get a DataStream.

The result will be either a bounded data stream (that can be processed in a batch way) or an unbounded data stream (that must be processed in a streaming way), based on the boundedness property of the source.

This method takes an explicit type information for the produced data stream, so that callers can define directly what type/serializer will be used for the produced stream. For sources that describe their produced type, the parameter type_info should not be specified to avoid specifying the produced type redundantly.

Added in version 1.13.0.

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