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Improve performances for Nested.Join
Dear all, I have a two tables: Table 1, which is the main one Table 2's, i.e. a lot of subtables from where I need to recover values to make calculation in the Table 1. I am using a custom f...
Hi Mic1979
After reviewing the dataset, it was found that the file contains a large amount of data, which could impact the performance of the functions. To enhance performance, follow these steps:
- Use Direct Query or Live connection for importing data this will reduce the time and improves the query performance .
- Remove unnecessary rows or columns from tables. This will help speed up operations, especially when performing joins.
- Since you are using custom function due to this the performance will reduced. If possible, try to replace your custom function with built-in functions that are often optimized for performance.
If this post helps, then please consider Accepting as solution to help the other members find it more quickly, don't forget to give a "Kudos".
Hello
here thel link to the sample file:
Basically what I did with Teble.Nestedjoin is:
- From the Table Project_Step_DISTRIBUTION I did the merge with Function_DISTRIBUTION.
- I have rows repeated in the column to merge for the table Function_DISTRIBUTION. I need this as I need to expand the column Function_Description to have this column present in the resulting table. In fact this is not a simple lookup.
- Then I am using custom function Merge_Multiply_Rename, basically doing the same thing, but with always the same structure in the table.
- The final table I have is at the following link: https://docs.google.com/file/d/1KXoWZYEkkqZyASufvHGeVn39gpTzFjfW/edit?usp=docslist_api&filetype=msexcel
Here I need to group by summing the column TOTAL_Volumes. But the GroupBy in Power query is extremely low. So I need to find an alternative to this with a custom function.
Hoping what I wrote is clear enough for you to support me.
THANKS IN ADVANCE!!!
Hi Mic1979
After reviewing the dataset, it was found that the file contains a large amount of data, which could impact the performance of the functions. To enhance performance, follow these steps:
- Use Direct Query or Live connection for importing data this will reduce the time and improves the query performance .
- Remove unnecessary rows or columns from tables. This will help speed up operations, especially when performing joins.
- Since you are using custom function due to this the performance will reduced. If possible, try to replace your custom function with built-in functions that are often optimized for performance.
If this post helps, then please consider Accepting as solution to help the other members find it more quickly, don't forget to give a "Kudos".