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

We've captured the moments from FabCon & SQLCon that everyone is talking about, and we are bringing them to the community, live and on-demand. Starts on April 14th. Register now

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
New to Fabric survey Carousel

New to Fabric Survey

If you have recently started exploring Fabric, we'd love to hear how it's going. Your feedback can help with product improvements.

Power BI DataViz World Championships carousel

Power BI DataViz World Championships - June 2026

A new Power BI DataViz World Championship is coming this June! Don't miss out on submitting your entry.

Join our Fabric User Panel

Join our Fabric User Panel

Share feedback directly with Fabric product managers, participate in targeted research studies and influence the Fabric roadmap.

March Power BI Update Carousel

Power BI Community Update - March 2026

Check out the March 2026 Power BI update to learn about new features.