pyspark.sql.DataFrameReader.parquet¶
-
DataFrameReader.parquet(*paths, **options)[source]¶ Loads Parquet files, returning the result as a
DataFrame.New in version 1.4.0.
- Parameters
- pathsstr
- Other Parameters
- **options
For the extra options, refer to Data Source Option in the version you use.
Examples
>>> df = spark.read.parquet('python/test_support/sql/parquet_partitioned') >>> df.dtypes [('name', 'string'), ('year', 'int'), ('month', 'int'), ('day', 'int')]