pyspark.sql.streaming.DataStreamReader.text¶

DataStreamReader.text(path: str, wholetext: bool = False, lineSep: Optional[str] = None, pathGlobFilter: Union[bool, str, None] = None, recursiveFileLookup: Union[bool, str, None] = None) → DataFrame[source]¶

Loads a text file stream and returns a DataFrame whose schema starts with a string column named “value”, and followed by partitioned columns if there are any. The text files must be encoded as UTF-8.

By default, each line in the text file is a new row in the resulting DataFrame.

New in version 2.0.0.

Changed in version 3.5.0: Supports Spark Connect.

Parameters

pathstr or list: string, or list of strings, for input path(s).

Other Parameters

Extra options: For the extra options, refer to Data Source Option in the version you use.

Notes

This API is evolving.

Examples

Load a data stream from a temporary text file.

>>> import tempfile
>>> import time
>>> with tempfile.TemporaryDirectory() as d:
...     # Write a temporary text file to read it.
...     spark.createDataFrame(
...         [("hello",), ("this",)]).write.mode("overwrite").format("text").save(d)
...
...     # Start a streaming query to read the text file.
...     q = spark.readStream.text(d).writeStream.format("console").start()
...     time.sleep(3)
...     q.stop()

pyspark.sql.streaming.DataStreamReader.table

pyspark.sql.streaming.DataStreamWriter.foreach