zhengruifeng commented on code in PR #40402:
URL: https://github.com/apache/spark/pull/40402#discussion_r1134776117
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connector/connect/common/src/main/protobuf/spark/connect/base.proto:
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@@ -272,6 +272,9 @@ message ExecutePlanResponse {
// The metrics observed during the execution of the query plan.
repeated ObservedMetrics observed_metrics = 6;
+ // The Spark schema
+ DataType schema = 7;
Review Comment:
Is it a optional field only available in `df.collect`?
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python/pyspark/sql/connect/dataframe.py:
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@@ -1344,9 +1344,9 @@ def collect(self) -> List[Row]:
if self._session is None:
raise Exception("Cannot collect on empty session.")
query = self._plan.to_proto(self._session.client)
- table = self._session.client.to_table(query)
+ table, schema = self._session.client.to_table(query)
- schema = from_arrow_schema(table.schema)
+ schema = schema or from_arrow_schema(table.schema)
Review Comment:
when I was implementing the collection I was thinking about this dumb
question: is it possible to make arrow schema 100% compatible with spark schema
if we store the different fields in arrow metadata?
e.g. for a spark `MapType`, store the `valueContainsNull` as a metadata in
the `pa.schema`.
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