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:
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):
I’ve written about a method to dynamically flatten parent-child-hierarchies also with multiple parents some while ago here. I’ve actually used this approach for Bill-of-materials cases and refined that approach in a series starting here. There, the quantities are aggregated in M already, as they are not supposed to change. But if one wants to use the hierarchical structure to report on transaction tables where several filters shall be applied, one has to adjust the data model a bit:
If you have parent-child-hierarchy with multiple parents, my function will a table like below, where the children with multiple parents still reside in different rows:
Today I read the (as always) great article by Matthew Roche “Governing Power BI just got a little easier” and couldn’t find a description on how to get to this promising window with all the admin goodness. So here it comes how to build your Power BI REST API custom connector then 😉 :
Create a custom connector for the Power BI REST API
Miguel Escobar has done a fantastic job to make it super-easy for you here.
Edit 30th September 2019: This repo has just been updated and includes a version with API secret. So if you’ve downloaded that content before and got an authorization error, please get the new files.
Get data from your connector
After you’ve stored the .mez-file in the correct folder (C:\Users\<YourUserNameGoesHere>\Documents\Power BI Desktop\Custom Connectors) and open Power BI Desktop again, you will be greeted with this warning message: Read more
Have you ever wanted to compare a version of a Power BI file with a previous one? … In the unlikely case that you haven’t yet, just wait until the auditors are in again – my new Power BI Comparer tool will save your day then 😉
Or maybe even before you uploade a new version of a report that has already been published to the service. How do you communicate the changes to your colleagues? Wouldn’t it be nice to have a tool that performs that comparison and documentation fully automagically?
Power BI Comparer
Fortunately my Power BI Comparer-tool makes it super easy to compare all properties of 2 Power BI files with each other: Just convert your pbix-files to pbit (as we need to access the data model properties as well) and drop the paths to these new files in my Excel-file like so:
While Power Query has a native function to fetch text between 2 delimiters in Power Query, there is no such function that removes the text instead. Therefore I’ve created a custom function Text.RemoveBetweenDelimiter. It even lets you choose to remove the delimiters themselves as well via the optional 4th parameter. (“Text.RemoveBetweenDelimiters “- function)
The code for the Text.RemoveBetweenDelimiters -function
When you’re dealing with a beast like DAX you can use any help there is, right? So here I show you how you can debug DAX variables who contain tables or show the result of multiple variables at once. So you can easily compare them with each other to spot the reason for problems fast.
Please note, that currently only comma separated DAX code is supported.
Watch this measure from Gerhard Brueckl’s brilliant solution for dynamic TopN clustering with others. It contains 5 variables who return tables and one variable with a scalar:
Measure with variables who contain tables and scalars
If you want to follow along how this calculation is evolving for each value in a matrix, my VarDebugMeasure will show details of every variable like so:
Measure to debug DAX variables