pyspark.sql.streaming.DataStreamReader.text

DataStreamReader.text(path, wholetext=False, lineSep=None, pathGlobFilter=None, recursiveFileLookup=None)[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.

Note

Evolving.

Parameters

  • paths – string, or list of strings, for input path(s).

  • wholetext – if true, read each file from input path(s) as a single row.

  • lineSep – defines the line separator that should be used for parsing. If None is set, it covers all \r, \r\n and \n.

  • pathGlobFilter – an optional glob pattern to only include files with paths matching the pattern. The syntax follows org.apache.hadoop.fs.GlobFilter. It does not change the behavior of `partition discovery`_.

  • recursiveFileLookup – recursively scan a directory for files. Using this option disables `partition discovery`_.

>>> text_sdf = spark.readStream.text(tempfile.mkdtemp())
>>> text_sdf.isStreaming
True
>>> "value" in str(text_sdf.schema)
True

New in version 2.0.

pyspark.sql.streaming.DataStreamReader.schema pyspark.sql.streaming.DataStreamWriter.foreach