pyspark.sql.DataFrameReader.text#

DataFrameReader.text(paths, wholetext=False, lineSep=None, pathGlobFilter=None, recursiveFileLookup=None, modifiedBefore=None, modifiedAfter=None)[source]#

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.

Added in version 1.6.0.

Changed in version 3.4.0: Supports Spark Connect.

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 for the version you use.

Examples

Write a DataFrame into a text file and read it back.

>>> import tempfile
>>> with tempfile.TemporaryDirectory(prefix="text") as d:
...     # Write a DataFrame into a text file
...     df = spark.createDataFrame([("a",), ("b",), ("c",)], schema=["alphabets"])
...     df.write.mode("overwrite").format("text").save(d)
...
...     # Read the text file as a DataFrame.
...     spark.read.schema(df.schema).text(d).sort("alphabets").show()
+---------+
|alphabets|
+---------+
|        a|
|        b|
|        c|
+---------+