version 1.3.1
scala> auction.printSchema
root
|-- auctionid: string (nullable = true)
|-- bid: float (nullable = false)
|-- bidtime: float (nullable = false)
|-- bidder: string (nullable = true)
|-- bidderrate: integer (nullable = true)
|-- openbid: float (nullable = false)
|-- price: float (nullable = false)
|-- item: string (nullable = true)
|-- daystolive: integer (nullable = true)
scala> auction.groupBy("auctionid", "item").count.show
auctionid item count
3016429446 palm 10
8211851222 xbox 28
On Wed, Oct 21, 2015 at 2:38 PM, Ali Tajeldin EDU <[email protected]>
wrote:
> Which version of Spark are you using? I just tried the example below on
> 1.5.1 and it seems to work as expected:
>
> scala> val res = df.groupBy("key").count.agg(min("count"), avg("count"))
> res: org.apache.spark.sql.DataFrame = [min(count): bigint, avg(count):
> double]
>
> scala> res.show
> +----------+----------+
> |min(count)|avg(count)|
> +----------+----------+
> | 1| 1.0|
> +----------+----------+
>
>
> scala> res.printSchema
> root
> |-- min(count): long (nullable = true)
> |-- avg(count): double (nullable = true)
>
> On Oct 21, 2015, at 11:12 AM, Carol McDonald <[email protected]>
> wrote:
>
> This used to work :
>
> // What's the min number of bids per item? what's the average? what's the
> max?
> auction.groupBy("item", "auctionid").count.agg(min("count"),
> avg("count"),max("count")).show
>
> // MIN(count) AVG(count) MAX(count)
> // 1 16.992025518341308 75
>
> but this now gives an error
>
> val res = auction.groupBy("item", "auctionid").count.agg(min("count"),
> avg("count"),max("count"))
>
> <console>:42: error: Float does not take parameters
>
> val res = auction.groupBy("item", "auctionid").count.agg(min("count"),
> avg("count"),max("count"))
>
> min and max still work .
>
> Do I need to cast the count to a float ?
>
> auction.groupBy("item", "auctionid").count.agg(min("count"),
> max("count")).show
>
> MIN(count) MAX(count)
> 1 75
>
>
>
