DataFrame's pivot doesn't see column created in groupBy

Related to https://stackoverflow.com/questions/39817993/pivoting-with-missing-values. I'm not completely sure if this is a bug or expected behavior.

When you `groypBy` by a column generated inside of it, the `pivot` method apparently doesn't find this column during the analysis.

E.g.

df = (sc.parallelize([(1.0, "2016-03-30 01:00:00"), 
                      (30.2, "2015-01-02 03:00:02")])
        .toDF(["amount", "Date"])
        .withColumn("Date", col("Date").cast("timestamp")))

(df.withColumn("hour",hour("date"))
   .groupBy(dayofyear("date").alias("date"))
   .pivot("hour").sum("amount").show())

Shows the following exception.

AnalysisException: u'resolved attribute(s) date#140688 missing from dayofyear(date)#140994,hour#140977,sum(`amount`)#140995 in operator !Aggregate [dayofyear(cast(date#140688 as date))], [dayofyear(cast(date#140688 as date)) AS dayofyear(date)#140994, pivotfirst(hour#140977, sum(`amount`)#140995, 1, 3, 0, 0) AS __pivot_sum(`amount`) AS `sum(``amount``)`#141001];'

To solve it you have to add the column date before grouping and pivoting.