Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/1598#discussion_r15714150
--- Diff: python/pyspark/sql.py ---
@@ -522,71 +866,112 @@ def _ssql_ctx(self):
return self._scala_SQLContext
def inferSchema(self, rdd):
- """Infer and apply a schema to an RDD of L{dict}s.
+ """Infer and apply a schema to an RDD of L{Row}s.
+
+ We peek at the first row of the RDD to determine the fields' names
+ and types. Nested collections are supported, which include array,
+ dict, list, Row, tuple, namedtuple, or object.
--- End diff --
Can we add a note about the complications with us only looking at the first
row. In particular, the type can't change in future rows and this breaks if
there are `None` in the first row. Also do we throw an exceptions for `None`s?
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