Github user davies commented on a diff in the pull request: https://github.com/apache/spark/pull/2901#discussion_r19346201 --- 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 -- Oh, I see. After the data was deserialized in Python, we need to some data coversions, so we can convert datetime to date if DataType is DateType.
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