However this returns a single column of c, without showing the original col1
.
On Thu, May 21, 2015 at 11:25 PM Ram Sriharsha sriharsha@gmail.com
wrote:
df.groupBy($col1).agg(count($col1).as(c)).show
On Thu, May 21, 2015 at 3:09 AM, SLiZn Liu sliznmail...@gmail.com wrote:
Hi Spark
Despite the odd usage, it does the trick, thanks Reynold!
On Fri, May 22, 2015 at 2:47 PM Reynold Xin r...@databricks.com wrote:
In 1.4 it actually shows col1 by default.
In 1.3, you can add col1 to the output, i.e.
df.groupBy($col1).agg($col1, count($col1).as(c)).show()
On Thu, May 21,
In 1.4 it actually shows col1 by default.
In 1.3, you can add col1 to the output, i.e.
df.groupBy($col1).agg($col1, count($col1).as(c)).show()
On Thu, May 21, 2015 at 11:22 PM, SLiZn Liu sliznmail...@gmail.com wrote:
However this returns a single column of c, without showing the original
Hi Spark Users Group,
I’m doing groupby operations on my DataFrame *df* as following, to get
count for each value of col1:
df.groupBy(col1).agg(col1 - count).show // I don't know if I should
write like this.
col1 COUNT(col1#347)
aaa2
bbb4
ccc4
...
and more...
As I ‘d like to
df.groupBy($col1).agg(count($col1).as(c)).show
On Thu, May 21, 2015 at 3:09 AM, SLiZn Liu sliznmail...@gmail.com wrote:
Hi Spark Users Group,
I’m doing groupby operations on my DataFrame *df* as following, to get
count for each value of col1:
df.groupBy(col1).agg(col1 - count).show // I
