Performance tip for aggregations after joins in Power Query and Power BI

This article was edited on 2nd Nov 2019. JoinKind.Local has been removed to avoid problems with merges on tables with primary keys:

In this article you’ll learn how to speed up the aggregation of joined/merged tables by orders of magnitude (I recorded up to 30 times faster execution times). This method works for merges where both table have multiple rows for each keys. If one of your tables has a primary key, the method Chris Webb describes here works just as good: Chris Webb’s article on how to improve performance on aggregations after joins using primary keys .

You can follow along the different methods in this file:  PerformanceAggregationsAfterMerges1_Upload.zip

Background

When you join a table to another table in Power Query, the UI gives you the option to either expand the columns (default) or aggregate the contents of the joint tables. That’s useful if multiple rows are returned for the rows of the table that has been joined to (left table):

Read more

Query folding on JoinKind.Inner gotcha for Power BI and Power Query

If you query databases who support query folding, you’re probably very aware of every step you take and check if folding happens with every new step like so:

“View Native Query” shows folding query that’s send back to the server (if not greyed out)

Folding will (usually) happen as long as “View Native Query” isn’t greyed out.

So when doing an inner join on tables whithin the same database, I was a bit surprised to see this greyed out actually. As according to the literature, it should fold.

But guess what? After I expanded a column from it, the folding was back again: Read more

Bulk-extract Power Query M-code from multiple Excel files at once

Some time ago I published a function that extracts all M-code from Power BI (.pbix)-files. Today I publish the pendant to Bulk-extract Power Query M-code from multiple Excel-files at once. The code contains many elements from the before mentioned, so please refer to that article for reference.

How to use

The function below has just one parameter where you either fill in a full filename (incl. path) of an Excel file, or a folder path where multiple files reside. The function will automatically detect the right modus and spit out the M-code. Read more

Improve import of Excel sheets with empty rows and columns in Power Query and Power BI

When you import Excel sheets who have empty leading or trailing columns and rows (showing null-values), you can substantially improve the complexity and speed of your import process with a simple trick:

Remove the reasons for the empty trailing rows and columns 😉

Background

Usually, when you import data from an Excel sheet, Power Query will automatically detect the used range in a sheet and will just return those rows and columns who have content in it. So how can it come that in some cases, additional rows or columns are returned who have nothing but empty values in them?

Reason

The reason for it can be cell formatting of empty cells. They often occur in old workbooks where cells have been deleted. These cells will be returned with a null-value during the import process with Power Query. See this blogpost for more details of potential pitfalls that come with it.

Solution

The “Inquire” Excel Add-On lets you clean any excess cell formatting. After you’ve executed this command, Power Query will not import any of those leading or trailing empty rows or columns any more. Often this will reduce the file size of the Excel files dramatically as well.

Effects

You will benefit from:

  • simpler query logic
  • potentially huge improved import speed, due to the reduced file size

Enjoy and stay queryious 😉