pyspark.sql.DataFrameReader.text

DataFrameReader.text(paths: Union[str, List[str]], wholetext: bool = False, lineSep: Optional[str] = None, pathGlobFilter: Union[bool, str, None] = None, recursiveFileLookup: Union[bool, str, None] = None, modifiedBefore: Union[bool, str, None] = None, modifiedAfter: Union[bool, str, None] = None) → DataFrame

Loads text files 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 1.6.0.

Parameters

pathsstr 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.

Examples

>>> df = spark.read.text('python/test_support/sql/text-test.txt')
>>> df.collect()
[Row(value='hello'), Row(value='this')]
>>> df = spark.read.text('python/test_support/sql/text-test.txt', wholetext=True)
>>> df.collect()
[Row(value='hello\nthis')]

pyspark.sql.DataFrameReader.table pyspark.sql.DataFrameWriter.bucketBy