Problemas de performance no Amazon QuickSight com grandes volumes de dados no SPICE

Hi @thais ,

So with 73 million rows and 100GB, you may be pushing what SPICE can handle, especially with the way your dashboard is set up. I think the issue may not just be regarding the data size, but also that you’ve got two layers of filtering happening: the date range filter plus the UUID filtering through card actions. Honestly without working in your environment, it is hard to tell if this problem is related to SPICE volume, how you are interacting with the data on the dashboard (i.e. filters), or could be a mix of both.

A few things to note for data volume is check if you’re loading columns you don’t actually need. High-cardinality text fields especially can kill performance, so if there’s anything you’re not using in those 46 visuals, cut it out (Quicksight Spice Capacity & data load - Q&A - Amazon Quick Community).

Additionally, one thing to note is that there is a 50 visual limit for each sheet in Quick Sight. Now while you are not at the limit, the closer you are to the limit can sometimes make your dashboard act wonky.

Another potential solution could be breaking this up. One big dashboard with 46 cards is a lot to ask from a single dataset. Maybe split it into a few smaller ones like KPIs in one, detailed tables in another. This can sometimes increase performance.

Additionally, one thing to note is to make sure you’ve got enough SPICE capacity allocated. Auto-purchase can save you from hitting limits during refreshes (Configure SPICE memory capacity - Amazon Quick).

Honestly though, with that many rows and the UUID filtering happening when people click cards, you might just be hitting the limits of what SPICE can handle smoothly. While SPICE technically supports up to 2 billion rows now, performance at that scale really depends on how the data is structured and queried. Sometimes the answer isn’t optimizing what you have, it’s restructuring how you’re approaching the problem. Moreover, if these don’t help enough, might be worth looking at whether direct query could work for some of this; however, direct query may offer different issues.

Hope something here helps!

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