Register now to learn Fabric in free live sessions led by the best Microsoft experts. From Apr 16 to May 9, in English and Spanish.
Hi All,
I am having a table visual and I am seeing slow performance while adding the measure "test_acc" and it seems to load very slow.
Solved! Go to Solution.
@alexa_0028 , try like
test_acc =
var test_1 = calculate(sum('Sales'[Volumes]), left('Product'[Code],3)="ACC")
RETURN
calculate( test_1,'Calendar'[cytd_flag]=1)
or
test_acc =
var test_1 = calculate(sum('Sales'[Volumes]), filter('Product', left('Product'[Code],3)="ACC"))
RETURN
calculate( test_1,filter('Calendar','Calendar'[cytd_flag]=1))
Hi All,
With some retrying, I figured out the way to optimise. The formula I pasted above indeed worked, I was looking the performance along with old measures therefore it was showing high values.
Thank you so much @amitchandak for pointing me to right direction.
Hi All,
With some retrying, I figured out the way to optimise. The formula I pasted above indeed worked, I was looking the performance along with old measures therefore it was showing high values.
Thank you so much @amitchandak for pointing me to right direction.
I tried to rewrite my measure like below , it didn't improve performance much but gave right result:
Hi @amitchandak ,
Thanks for your reply, it did improved performance a lil more.
But this solution doesn't give me the right results. I am looking for the results like highlighted in green but I am getting the value of the volume measure only in test_acc
@alexa_0028 , try like
test_acc =
var test_1 = calculate(sum('Sales'[Volumes]), left('Product'[Code],3)="ACC")
RETURN
calculate( test_1,'Calendar'[cytd_flag]=1)
or
test_acc =
var test_1 = calculate(sum('Sales'[Volumes]), filter('Product', left('Product'[Code],3)="ACC"))
RETURN
calculate( test_1,filter('Calendar','Calendar'[cytd_flag]=1))
Covering the world! 9:00-10:30 AM Sydney, 4:00-5:30 PM CET (Paris/Berlin), 7:00-8:30 PM Mexico City
Check out the April 2024 Power BI update to learn about new features.
User | Count |
---|---|
110 | |
96 | |
77 | |
63 | |
55 |
User | Count |
---|---|
143 | |
109 | |
89 | |
84 | |
66 |