Skip to main content
cancel
Showing results for 
Search instead for 
Did you mean: 

Register now to learn Fabric in free live sessions led by the best Microsoft experts. From Apr 16 to May 9, in English and Spanish.

Reply
Budfudder
Helper IV
Helper IV

Loading Large Tables

I'm connecting successfully to our postgresql database. I then select the tables I want and attempt to Load them. Power BI fails with the error message about running out of memory - one of the tables has over 100,000,000 rows.

 

Is there any way I can get around this? Can I somehow configure Power BI to only download a subset of the rows somehow? What am I missing?

5 REPLIES 5
alanhodgson
Solution Supplier
Solution Supplier

Hey @Budfudder,

 

I think the best practice for loading large datasets is using the Direct Query method instead of Import.

Also, are you running on a 32-bit or 64-bit machine? And do you have atleast 8GB of RAM?

 

I would also recommend looking at your current Connection Timeout configuration.

 

Cheers,

 

Alan

I'm running Windows 10 64-bit, with 8GB of RAM.

 

I'm using the Direct Query method, not Import. My mistake - we are using Import, we have no choice - Direct Query for postgresql is not supported.

 

I'm unable to find the Connection Timeout configuration - where is it?

Hi @Budfudder,

Does your postgre database store in this computer? Is this error from database side? With DirectQuery, each chart just loads maximum 1 mil rows when you interactive( https://powerbi.microsoft.com/en-us/documentation/powerbi-desktop-use-directquery) so I don't think it's problem from PBI.

Unfortunately (from what I can see) postgresql isn't one of the databases supported by DirectQuery - so I can ONLY import. Does importing actually create a copy of the whole table locally?

 

I've had similar problems connecting to our CRM database (not timeouts or failures, but just HUGE load times) - again, it's not supported by DirectQuery.

Hi @Budfudder,

 

To improve query performance, here are two tips for you.

 

  • Tall, narrow tables are faster. Reduce the unused columns in order to improve performance.
  • Integers are faster than strings. Strings are stored in a hash table, they are effectively referenced twice, once for the hash value and once to fetch the string associated with that value.

Reference
http://blog.pragmaticworks.com/power-bi-performance-tips-and-techniques
http://promx.net/en/2016/09/optimizing-power-bi-query-performance-with-crm-2016-online-odata-v4-serv...

 

Regards,

Charlie Liao

Helpful resources

Announcements
Microsoft Fabric Learn Together

Microsoft Fabric Learn Together

Covering the world! 9:00-10:30 AM Sydney, 4:00-5:30 PM CET (Paris/Berlin), 7:00-8:30 PM Mexico City

PBI_APRIL_CAROUSEL1

Power BI Monthly Update - April 2024

Check out the April 2024 Power BI update to learn about new features.

April Fabric Community Update

Fabric Community Update - April 2024

Find out what's new and trending in the Fabric Community.