cloud-fan commented on code in PR #38742:
URL: https://github.com/apache/spark/pull/38742#discussion_r1031014545
##########
python/pyspark/sql/connect/dataframe.py:
##########
@@ -797,6 +796,137 @@ def schema(self) -> StructType:
else:
return self._schema
+ @property
+ def isLocal(self) -> bool:
+ """Returns ``True`` if the :func:`collect` and :func:`take` methods
can be run locally
+ (without any Spark executors).
+
+ .. versionadded:: 3.4.0
+
+ Returns
+ -------
+ bool
+ """
+ if self._plan is None:
+ raise Exception("Cannot analyze on empty plan.")
+ query = self._plan.to_proto(self._session)
+ return self._session.is_local(query)
+
+ @property
+ def isStreaming(self) -> bool:
+ """Returns ``True`` if this :class:`DataFrame` contains one or more
sources that
+ continuously return data as it arrives. A :class:`DataFrame` that
reads data from a
+ streaming source must be executed as a :class:`StreamingQuery` using
the :func:`start`
+ method in :class:`DataStreamWriter`. Methods that return a single
answer, (e.g.,
+ :func:`count` or :func:`collect`) will throw an
:class:`AnalysisException` when there
+ is a streaming source present.
+
+ .. versionadded:: 3.4.0
+
+ Notes
+ -----
+ This API is evolving.
+
+ Returns
+ -------
+ bool
+ Whether it's streaming DataFrame or not.
+ """
+ if self._plan is None:
+ raise Exception("Cannot analyze on empty plan.")
+ query = self._plan.to_proto(self._session)
+ return self._session.is_streaming(query)
+
+ def printSchema(self) -> None:
+ """Prints out the schema in the tree format.
+
+ .. versionadded:: 3.4.0
+
+ Returns
+ -------
+ None
+ """
+ if self._plan is None:
+ raise Exception("Cannot analyze on empty plan.")
+ query = self._plan.to_proto(self._session)
+ print(self._session.tree_string(query))
+
+ def semanticHash(self) -> int:
Review Comment:
This is a developer API in Dataset, do we really need to provide it in Spark
connect?
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