pyspark.sql.streaming.DataStreamReader.parquet¶

DataStreamReader.parquet(path: str, mergeSchema: Optional[bool] = None, pathGlobFilter: Union[bool, str, None] = None, recursiveFileLookup: Union[bool, str, None] = None, datetimeRebaseMode: Union[bool, str, None] = None, int96RebaseMode: Union[bool, str, None] = None) → DataFrame[source]¶

Loads a Parquet file stream, returning the result as a DataFrame.

New in version 2.0.0.

Parameters

pathstr: the path in any Hadoop supported file system

Other Parameters

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

Examples

Load a data stream from a temporary Parquet file.

>>> import tempfile
>>> import time
>>> with tempfile.TemporaryDirectory() as d:
...     # Write a temporary Parquet file to read it.
...     spark.range(10).write.mode("overwrite").format("parquet").save(d)
...
...     # Start a streaming query to read the Parquet file.
...     q = spark.readStream.schema(
...         "id LONG").parquet(d).writeStream.format("console").start()
...     time.sleep(3)
...     q.stop()

pyspark.sql.streaming.DataStreamReader.orc pyspark.sql.streaming.DataStreamReader.schema