# How to use “CrossJoin” in DAX

The “CrossJoin” function returns the Cartesian product of all rows from all tables in the arguments. In my sample below I want to have sales per year per city.

```EVALUATE
SUMMARIZE (
CROSSJOIN (
VALUES ( 'Date'[Calendar Year] ),
VALUES ( Geography[City] )
),
'Date'[Calendar Year],
Geography[City]
),
"Sum of Sales", CALCULATE ( SUM ( 'Internet Sales'[Sales Amount] ) )
)```

And the result looks like this

But as you can see I get a lot of empty rows. To remove these empty rows I add a filter to my query. I also moved my calculation outside the main query to make it more readable.

```DEFINE
MEASURE 'Internet Sales'[Sales] =
SUM ( 'Internet Sales'[Sales Amount] )
EVALUATE
FILTER (
SUMMARIZE (
CROSSJOIN (
VALUES ( 'Date'[Calendar Year] ),
VALUES ( Geography[City] )
),
'Date'[Calendar Year],
Geography[City]
),
'Internet Sales'[Sales] <> 0
),
"Sum of Sales", 'Internet Sales'[Sales]
)```

# Basic query optimalization in DAX

What can we do to make queries as fast as possible? Here is some tips ðŸ™‚

In my simple test I want to see the sales for year 2009. To make sure my queries does not hit any cache I’m clearing it using XMLA. In my first query I will try to use the ROW function and sum up the internet sales

```EVALUATE
ROW (
"Sales", CALCULATE (
SUM ( 'Internet Sales'[Sales Amount] ),
'Date'[Calendar Year] = 2008
)
)```

When watching the profiler I can see that this query took 156 milliseconds. The reason why this takes quite long is that we are one the row level.

Lets switch to table level.

```EVALUATE
FILTER (
SUMMARIZE (
'Date',
'Date'[Calendar Year],
"Sales", SUM ( 'Internet Sales'[Sales Amount] )
),
'Date'[Calendar Year] = 2008
)```

This query took 78 milliseconds. Twice as fast as the first query.

What if I move the calculation using ADDCOLUMNS outside the SUMMARIZE?

```EVALUATE
FILTER (
SUMMARIZE ( 'Date', 'Date'[Calendar Year] ),
'Date'[Calendar Year] = 2008
),
"Sales", CALCULATE ( SUM ( 'Internet Sales'[Sales Amount] ) )
)```

This query took 62 milliseconds

Do you have an even better optimalization tip? Feel free to drop me an mail

# Comparable day in DAX

In many companies they want to compare todays sales with the comparable day last year. To find the comparable day we subtract 364 from todays date. In this sample todays date is 15 january 2007.

To see what dates we should get we can run this SQL

```select '2007/01/15' as TodaysDate, DateName(dw, '2007/01/15') As 'DayName',
```

And this will return this result

To check the values for these dates we can run these DAX queries

```EVALUATE
FILTER (
VALUES ('Date'[Date]),
"Sales this day", 'Internet Sales'[Internet Total Sales]
),
'Date'[Date] = DATE ( 2007, 01, 15 )
)

EVALUATE
FILTER (
VALUES ('Date'[Date]),
"Sales this day", 'Internet Sales'[Internet Total Sales]
),
'Date'[Date] = DATE ( 2006, 01, 16 )
)```

The final query where we put all together looks like this

```EVALUATE
FILTER (
VALUES ( 'Date'[Date] ),
"Comparable day", CALCULATE (
'Internet Sales'[Internet Total Sales],
DATEADD ( 'Date'[Date] , -364, Day)
),
"Sales this day", 'Internet Sales'[Internet Total Sales]
),
'Date'[Date] = DATE ( 2007, 01, 15 )
)```

Please note that this sample requires a date dimension that has the date 2006/01/16. If you are unsure about this you will have to change the query. The -364 approach will have issues if last year was a leap years.

# Running total in DAX

To get a running total in DAX you can use the DATESYTD function.

Here is an example that gives running total per day for a given range.

```EVALUATE
FILTER (
VALUES ( 'Date'[Date] ),
"Running total", CALCULATE (
'Internet Sales'[Internet Total Sales],
DATESYTD ( 'Date'[Date] )
),
"Sales per day", 'Internet Sales'[Internet Total Sales]
),
'Date'[Date] < DATE ( 2006, 01, 20 )
&& 'Date'[Date] >= DATE ( 2006, 01, 01 )
)
```

And here is an example on how to get running total per month.

```EVALUATE
FILTER (
SUMMARIZE (
'Date',
'Date'[Month Name],
'Date'[Calendar Year],
"Running total", CALCULATE (
'Internet Sales'[Internet Total Sales],
DATESYTD ( 'Date'[Date] )
),
"Sales per month", 'Internet Sales'[Internet Total Sales]
),
'Date'[Calendar Year] = 2006
)```

# DYNAMIC DATE FILTER IN DAX USING VBA

If you are creating scheduled reports in DAX it might be handy to add some VBA to calculate time periods automatically.

Here is an example that returns yesterday

```EVALUATE
FILTER (
SUMMARIZE (
'Date',
'Date'[Date],
"Sales", 'Internet Sales'[Internet Total Sales]
),
FORMAT('Date'[Date], "yyyy-MM-dd") = FORMAT(NOW() - 1, "yyyy-MM-dd")
)
```

If you want to test a valid date in the sample database you can figure out how many days you have to remove by running this SQL “select DATEDIFF(day, getdate(), ‘2006/05/18’)”. And then subtract this number instead of “NOW() – 1”.

And if you want to have a similar query for year this can look like this

```EVALUATE
FILTER (
SUMMARIZE (
'Date',
'Date'[Calendar Year],
"Sales", 'Internet Sales'[Internet Total Sales]
),
'Date'[Calendar Year] = INT(FORMAT(NOW() - 1, "yyyy"))
)```

# Creating an simple if test in DAX

Here is a sample on how to create an if test in DAX. It is really easy ðŸ™‚ In the sample below we test the sales per month for 2007 versus the sales per month for 2006. If the sales are higher we print “Higher”. If it was lower we print “Lower”.

```DEFINE
MEASURE 'Internet Sales'[Previous Sales per month] =
CALCULATE (
'Internet Sales'[Internet Total Sales],
SAMEPERIODLASTYEAR ( 'Date'[Date] )
)
MEASURE 'Internet Sales'[Sales per month] =
CALCULATE (
'Internet Sales'[Internet Total Sales],
'Date'[Month]
)
MEASURE 'Internet Sales'[MyTest] =
IF (
'Internet Sales'[Sales per month]
>= 'Internet Sales'[Previous Sales per month],
"Higher",
"Lower"
)
EVALUATE
FILTER (
SUMMARIZE (
'Date',
'Date'[Month],
'Date'[Calendar Year],
"Previous Sales per month", FORMAT (
'Internet Sales'[Previous Sales per month],
"Currency"
),
"Sales Sales per month", FORMAT ( 'Internet Sales'[Sales per month], "Currency" ),
"Change", 'Internet Sales'[MyTest]
),
'Date'[Calendar Year] = 2007
)
```

# Get “Year To Date” and “Last Year To Date” in DAX

To get “Year To Date” and “Last year to date” in DAX is really simple. You can use the function TotalYTD and mix this with DATESBETWEEN or SAMEPERIODLASTYEAR.

This is an example with DATESBETWEEN

```DEFINE
MEASURE 'Internet Sales'[Previous Year To Date] =
CALCULATE (
TOTALYTD (
'Internet Sales'[Internet Total Sales],
DATESBETWEEN (
'Date'[Date],
FIRSTDATE ( DATEADD ( 'Date'[Date], -12, MONTH ) ),
LASTDATE ( DATEADD ( 'Date'[Date], -12, MONTH ) )
)
)
)
MEASURE 'Internet Sales'[Year To Date] =
CALCULATE (
TOTALYTD (
'Internet Sales'[Internet Total Sales],
'Date'[Date]
)
)
MEASURE 'Internet Sales'[Change] =
FORMAT (
'Internet Sales'[Year To Date]
/ 'Internet Sales'[Previous Year To Date],
"Percent"
)
EVALUATE
FILTER (
SUMMARIZE (
'Date',
'Date'[Date],
"Previous Year To Date", 'Internet Sales'[Previous Year To Date],
"Sales Year To Date", 'Internet Sales'[Year To Date],
"Change", 'Internet Sales'[Change]
),
'Date'[Date] = DATE ( 2007, 01, 15 )
)
```

And this is an example with SAMEPERIODLASTYEAR

```DEFINE
MEASURE 'Internet Sales'[Previous Year To Date] =
CALCULATE (
TOTALYTD (
'Internet Sales'[Internet Total Sales],
SAMEPERIODLASTYEAR ( 'Date'[Date] )
)
)
MEASURE 'Internet Sales'[Year To Date] =
CALCULATE (
TOTALYTD (
'Internet Sales'[Internet Total Sales],
'Date'[Date]
)
)
MEASURE 'Internet Sales'[Change] =
FORMAT (
'Internet Sales'[Year To Date]
/ 'Internet Sales'[Previous Year To Date],
"Percent"
)
EVALUATE
FILTER (
SUMMARIZE (
'Date',
'Date'[Date],
"Previous Year To Date", 'Internet Sales'[Previous Year To Date],
"Sales Year To Date", 'Internet Sales'[Year To Date],
"Change", 'Internet Sales'[Change]
),
'Date'[Date] = DATE ( 2007, 01, 15 )
)```