You can also specify the delimiter character(s). Merge Columns concatenates columns to each other in the order of selection of columns. Example? Merge Columns! Fortunately there are workarounds for this situation.
There are also some Transformations in Power Query that Query Folding doesn’t support them. So sometimes you have to step beyond query folding, and there might be no better way of doing that. You would need to bring data from different data sources in Power BI, and this is the ability that Power Query gives to you. then before joining to web query it will be fetched into cache and then rest of steps happens by M engine. That means transformations will happen on the data of SQL Server table. For example if you are doing some transformations on a SQL Server table in Power Query and then join it with a web query query folding stops from the time you bring the external data source. However in some cases it is not supported. If Query Folding is supported on a step, you can right click on that step and click on View Native Query. The question that might comes into your mind right now is that Can I see the Native Query that M script translates to it? The answer is Yes. You have to avoid this option as much as possible. and data will be loaded in the local cache, and rest of transformations happens on M engine side. In this case T-SQL brings the data before that step. The second diagram shows Query Folding partially supported (only up to specific step). Server side operation apply all transformations on the data set and returns only desired result set. The first diagram shows a M script fully folded (translated to T-SQL). Why? because performance is much higher to run transformations on billions of records in the data source, rather than bringing millions of records into cache and applying some transformations on it. You can see as an example how the conditional column script in M translated to Case statement in T-SQL. #"Added Conditional Column" = Table.AddColumn(Sales_SalesOrderHeader, "Custom", each if >= 100 then "0" else "1" )Īnd here is the folded version of that translated to native T-SQL query: select. In other words when you run Power Query script on top of a SQL Server database, query folding will translate the M script into T-SQL statements, and fetch the final results.ĪdventureWorks2012 = Source, Query Folding means translating Power Query (M) transformations into native query language of the data source (for example T-SQL). I can’t start talking about the issue without explaining what Query Folding is, so let’s start with that. If you like to learn more about Power BI read the Power BI online book from Rookie to Rock Star. Note that Merge Columns is an example here ,this situation might happens with some other transformations as well. In this post I’ll show you how this cause the performance issue, and how it can be solved. This easiness does come with a price, a high price I’d say, price of reducing the performance of Power Query and as a result Power BI! Merge Columns doesn’t support query folding and it means it will affect performance badly. Now with the new Merge Column this are much easier, you select columns and apply Merge Columns. Previously you could do the concatenation with adding concatenation simply with & character, what you’ve done was adding a new custom column, and writing M expression to concatenate columns. Merge Columns concatenate columns to each other to either create a new column, or replace them with the new concatenated result. as an example recently (I believe from last few releases) Power BI Desktop added a feature called Merge Columns. Some transformations can be translated to query language of the data source, some not. Have you ever thought does your Power Query Transformations happens in the data source side (server side), or on the local memory (client side)? When you use a relational data source, query can be run on the data source, but it depends on transformations.