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Hi
I'm trying to return value from another table by checking uneven parity of counting row with calculations of conditions.
Currently i have to use multiple colum to check for each name wich ID is corresponding.
Is there a way to optimize this calculation which is too heavy to be publish with a large dataset ?
Here is the actual formula for each column :
VAR ID = Table1[ID]
RETURN
IF(
ISEVEN(
SUMX(
ADDCOLUMNS(
GENERATE(FILTER(Table1, Table1[ID] = ID ),
Table2 ),"@", INT ( (Table2[Name]="X") && (Table1[Col1]-Table2[A]=Table1[Col2]))),
[@]
)
),
"No","Yes")
And the formula for deduce the name
Name = IF(Table1[Check X]="Yes","X",IF(Table1[Check Y]="Yes","Y",IF(Table1[Check Z]="Yes","Z","/")))
Thx
Solved! Go to Solution.
Thank's for Ahmedx for you solution. In the meantime I've found a solution that seems to perform better when refreshing.
Name =
VAR __ID = 'Desired Tablet'[ID]
VAR __datas = ADDCOLUMNS(GENERATE ( FILTER ( Table1, 'Table1'[ID] = __ID ), FILTER(Table2, Table1[Col1]-Table2[A]=Table1[Соl2])),"@",1)
VAR __datassummerize = GROUPBY(__datas,Table1[ID],[Name],"@",SUMX(CURRENTGROUP(),[@]))
RETURN
MAXX(
FILTER(__datassummerize,
ISODD([@])
),
[Name]
)
Thank's for Ahmedx for you solution. In the meantime I've found a solution that seems to perform better when refreshing.
Name =
VAR __ID = 'Desired Tablet'[ID]
VAR __datas = ADDCOLUMNS(GENERATE ( FILTER ( Table1, 'Table1'[ID] = __ID ), FILTER(Table2, Table1[Col1]-Table2[A]=Table1[Соl2])),"@",1)
VAR __datassummerize = GROUPBY(__datas,Table1[ID],[Name],"@",SUMX(CURRENTGROUP(),[@]))
RETURN
MAXX(
FILTER(__datassummerize,
ISODD([@])
),
[Name]
)