Dataset Refresh Failure

I’m encountering issues with data refreshes in Amazon QuickSight. I have four datasets linked to RDS-MySQL, all set up for scheduled hourly refreshes in SPICE. The first dataset, which is 13GB in size, typically takes around 30 minutes to complete its refresh cycle. Could this lengthy refresh process be causing failures for the other datasets as well?

This happened to all my datasets for the last few days. Can anyone advise me on this issue

Hi @Harsheena – Per screenshots, it looks like the backend server is timing out the refresh cycle. This could be because of several reasons and will need a deeper look. Couple of things to validate is the load level on the backend server and timeout configurations on the backend server.
I would recommend filing a case with AWS Support where we can dive into the details so that we can help you further. Here are the steps to open a support case. If your company has someone who manages your AWS account, you might not have direct access to AWS Support and will need to raise an internal ticket to your IT team or whomever manages your AWS account. They should be able to open an AWS Support case on your behalf. Hope this helps!

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@awsvig Thanks for the solution

@awsvig,I have one more concern: could the refresh failures be related to my use of SPICE? Considering my dataset consists of millions of rows in an RDS MySQL database, I’m wondering which approach is more suitable for creating the datasets: SPICE or Direct Query. I intend to use these datasets to build dashboards and enable hourly refreshes in line with my business requirements. Any guidance or advice on the best approach would be greatly appreciated.

Hi @Harsheena -
The answer is “it depends”. :slight_smile: Direct query can get the latest from your data source but will add to the load on your data source.

QuickSight Datasets can work in either Direct query or SPICE mode.
In Direct query mode, queries are executed against backend data source each time a dashboard/analysis (that uses the dataset) is loaded.
In SPICE mode, QuickSight extracts a point in time snap shot of the data - pulling from all tables defined in the dataset per joins specified therein. This extracted data is stored in QuickSight SPICE layer and is used to drive all requests against that dataset. Data in SPICE layer can be refreshed on a schedule (which can be set from UI) or triggered as last step in your data refresh pipeline via create-ingestion API call.

Query mode can be switched back and forth without impacting the meta data defined in the dataset.

Using SPICE mode gets you two benefits.

  • Scale - QuickSight handles all the load without burdening the underlying data source. So, you don’t have to worry if it is 10 users or 10K users hitting a dataset via one or more dashboards.
  • Speed - SPICE layer is built for QuickSight with performance in mind and provides super fast dashboard loads.