agg function not working for multiple aggregations

[FrancisLau]

Data has 2 columns:

|requestDate|requestDuration|

| 2015-06-17| 104|

Here is the code:

avgSaveTimesByDate = gridSaves.groupBy(gridSaves.requestDate).agg({"requestDuration": "min", "requestDuration": "max","requestDuration": "avg"})

avgSaveTimesByDate.show(100)

Summary of Issue

I expect 4 columns of data: date, min, max and average but only the date and average shows. The first 2 aggs do not show up. If I move max to the last position, only date and max shows up. Very weird.

+-----------+--------------------+ |requestDate|AVG(requestDuration)| +-----------+--------------------+

| 2015-06-10| 750.8886326991035|

Am I doing this incorrectly? I am trying to get a dataframe for a box plot.

[rlgarris]

Hi Francis,

Thanks for reaching out.

I just tried this in version 2.0 of Databricks and it appeared to work as expected.

Are you using version 2.0 and Spark 1.4?

If so I would suggest using this alternate syntax:

from pyspark.sql import functions as F

aggs = df.groupBy("cut").agg(df.cut, F.min("carat"), F.max("carat"), F.avg("carat"))

Let me know if that works for you.

[ReKa · Accepted solution]

My guess is that the reason this may not work is the fact that the dictionary input does not have unique keys. With this syntax, column-names are keys and if you have two or more aggregation for the same column, some internal loops may forget the non-uniqueness of the keys.