HyukjinKwon commented on a change in pull request #27331:
URL: https://github.com/apache/spark/pull/27331#discussion_r445270934
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File path: python/pyspark/sql/readwriter.py
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@@ -1048,6 +1048,128 @@ def jdbc(self, url, table, mode=None, properties=None):
self.mode(mode)._jwrite.jdbc(url, table, jprop)
+class DataFrameWriterV2(object):
+ """
+ Interface used to write a class:`pyspark.sql.dataframe.DataFrame`
+ to external storage using the v2 API.
+
+ .. versionadded:: 3.1.0
+ """
+
+ def __init__(self, df, table):
+ self._df = df
+ self._spark = df.sql_ctx
+ self._jwriter = df._jdf.writeTo(table)
+
+ @since(3.1)
+ def using(self, provider):
+ """
+ Specifies a provider for the underlying output data source.
+ Spark's default catalog supports "parquet", "json", etc.
+ """
+ self._jwriter.using(provider)
+ return self
+
+ @since(3.1)
+ def option(self, key, value):
+ """
+ Add a write option.
+ """
+ self._jwriter.option(key, to_str(value))
+ return self
+
+ @since(3.1)
+ def options(self, **options):
+ """
+ Add write options.
+ """
+ options = {k: to_str(v) for k, v in options.items()}
+ self._jwriter.options(options)
+ return self
+
+ @since(3.1)
+ def partitionedBy(self, col, *cols):
Review comment:
@rdblue, @brkyvz, @cloud-fan, Should we maybe at least use a different
class for these partition column expressions such as `PartitionedColumn` like
we do for `TypedColumn`?
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