Fokko opened a new pull request #28554:
URL: https://github.com/apache/spark/pull/28554


   For example, dates are missing from the export:
   
   ```
   from datetime import datetime, timedelta, timezone
   from pyspark.sql import types as T
   from pyspark.sql import Row
   from pyspark.sql import functions as F
   
   START = datetime(2014, 1, 1, tzinfo=timezone.utc)
   
   n_days = 22
   
   date_range = [Row(date=(START + timedelta(days=n))) for n in range(0, 
n_days)]
   
   schema = T.StructType([T.StructField(name="date", dataType=T.DateType(), 
nullable=False)])
   
   rdd = spark.sparkContext.parallelize(date_range)
   
   df = spark.createDataFrame(data=rdd, schema=schema)
   
   df.agg(F.max("date")).show()
   
   df.summary().show()
   +-------+
   |summary|
   +-------+
   |  count|
   |   mean|
   | stddev|
   |    min|
   |    25%|
   |    50%|
   |    75%|
   |    max|
   +-------+
   ```
   
   Even something less common such as arrays are sortable:
   
   ```
   elcome to
         ____              __
        / __/__  ___ _____/ /__
       _\ \/ _ \/ _ `/ __/  '_/
      /___/ .__/\_,_/_/ /_/\_\   version 2.4.5
         /_/
            
   Using Scala version 2.11.12 (Java HotSpot(TM) 64-Bit Server VM, Java 
1.8.0_172)
   Type in expressions to have them evaluated.
   Type :help for more information.
   
   scala> 
   
   scala> val singersDF = Seq(
        |   ("beatles", "help|hey jude"),
        |   ("romeo", "eres mia")
        | ).toDF("name", "hit_songs")
   singersDF: org.apache.spark.sql.DataFrame = [name: string, hit_songs: string]
   
   scala> 
   
   scala> val actualDF = singersDF.withColumn(
        |   "hit_songs",
        |   split(col("hit_songs"), "\\|")
        | )
   actualDF: org.apache.spark.sql.DataFrame = [name: string, hit_songs: 
array<string>]
   
   scala> actualDF.show()
   +-------+----------------+
   |   name|       hit_songs|
   +-------+----------------+
   |beatles|[help, hey jude]|
   |  romeo|      [eres mia]|
   +-------+----------------+
   
   
   scala> df.max("hit_songs")
   <console>:24: error: not found: value df
          df.max("hit_songs")
          ^
   
   scala> actualDF.max("hit_songs")
   <console>:26: error: value max is not a member of 
org.apache.spark.sql.DataFrame
          actualDF.max("hit_songs")
                   ^
   
   scala> actualDF.agg(min("hit_songs"), max("hit_songs"))
   res3: org.apache.spark.sql.DataFrame = [min(hit_songs): array<string>, 
max(hit_songs): array<string>]
   
   scala> actualDF.agg(min("hit_songs"), max("hit_songs")).show()
   +--------------+----------------+                                            
   
   |min(hit_songs)|  max(hit_songs)|
   +--------------+----------------+
   |    [eres mia]|[help, hey jude]|
   +--------------+----------------+
   ```
   
   Signed-off-by: Fokko Driesprong <[email protected]>
   
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   ### What changes were proposed in this pull request?
   
   Not filtering the columns to compute statistics on.
   
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   ### Why are the changes needed?
   
   Something as simple as DateTypes are not showing up in the output.
   
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   ### Does this PR introduce _any_ user-facing change?
   
   Might be, as their output will change of the summary if they have columns 
that aren't part of the summary right now.
   
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   ### How was this patch tested?
   
   Existing tests.
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