Github user adrian-wang commented on a diff in the pull request:
https://github.com/apache/spark/pull/2901#discussion_r19329014
--- Diff: python/pyspark/sql.py ---
@@ -1084,10 +1096,11 @@ def applySchema(self, rdd, schema):
... StructField("null", DoubleType(), True)])
>>> srdd = sqlCtx.applySchema(rdd, schema)
>>> results = srdd.map(
- ... lambda x: (x.byte1, x.byte2, x.short1, x.short2, x.int,
x.float, x.time,
- ... x.map["a"], x.struct.b, x.list, x.null))
- >>> results.collect()[0]
- (127, -128, -32768, 32767, 2147483647, 1.0, ...(2010, 1, 1, 1, 1,
1), 1, 2, [1, 2, 3], None)
+ ... lambda x: (x.byte1, x.byte2, x.short1, x.short2, x.int,
x.float, x.date,
+ ... x.time, x.map["a"], x.struct.b, x.list, x.null))
+ >>> results.collect()[0] # doctest: +NORMALIZE_WHITESPACE
+ (127, -128, -32768, 32767, 2147483647, 1.0,
datetime.datetime(2010, 1, 1, 0, 0),
--- End diff --
@davies because of using pyrolite, `java.sql.Date` is serialized in the
same way as `java.sql.Timestamp`, since they are all subtype of
`java.util.Date`. And this make the `dumps()` function to generate datetime
instead of date for `java.util.Date`. I think this is related to your comments
in JIRA SPARK-2674
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