Starts an asynchronous job that generates a snapshot of a dashboard's output. You can request one or several of the following format configurations in each API call.
- 1 Paginated PDF
- 1 Excel workbook that includes up to 5 table or pivot table visuals
- 5 CSVs from table or pivot table visuals
The status of a submitted job can be polled with the
DescribeDashboardSnapshotJob API. When you call the
DescribeDashboardSnapshotJob API, check the
JobStatus field in the response. Once the job reaches a
COMPLETED or
FAILED status, use the
DescribeDashboardSnapshotJobResult API to obtain the URLs for the generated files. If the job fails, the
DescribeDashboardSnapshotJobResult API returns detailed information about the error that occurred.
StartDashboardSnapshotJob API throttling Amazon QuickSight utilizes API throttling to create a more consistent user experience within a time span for customers when they call the
StartDashboardSnapshotJob. By default, 12 jobs can run simlutaneously in one Amazon Web Services account and users can submit up 10 API requests per second before an account is throttled. If an overwhelming number of API requests are made by the same user in a short period of time, Amazon QuickSight throttles the API calls to maintin an optimal experience and reliability for all Amazon QuickSight users.
Common throttling scenarios The following list provides information about the most commin throttling scenarios that can occur.
- A large number of SnapshotExport API jobs are running simultaneously on an Amazon Web Services account. When a new StartDashboardSnapshotJob is created and there are already 12 jobs with the RUNNING status, the new job request fails and returns a LimitExceededException error. Wait for a current job to comlpete before you resubmit the new job.
- A large number of API requests are submitted on an Amazon Web Services account. When a user makes more than 10 API calls to the Amazon QuickSight API in one second, a ThrottlingException is returned.
If your use case requires a higher throttling limit, contact your account admin or
Amazon Web ServicesSupport to explore options to tailor a more optimal expereince for your account.
Best practices to handle throttling If your use case projects high levels of API traffic, try to reduce the degree of frequency and parallelism of API calls as much as you can to avoid throttling. You can also perform a timing test to calculate an estimate for the total processing time of your projected load that stays within the throttling limits of the Amazon QuickSight APIs. For example, if your projected traffic is 100 snapshot jobs before 12:00 PM per day, start 12 jobs in parallel and measure the amount of time it takes to proccess all 12 jobs. Once you obtain the result, multiply the duration by 9, for example
(12 minutes * 9 = 108 minutes). Use the new result to determine the latest time at which the jobs need to be started to meet your target deadline.
The time that it takes to process a job can be impacted by the following factors:
- The dataset type (Direct Query or SPICE).
- The size of the dataset.
- The complexity of the calculated fields that are used in the dashboard.
- The number of visuals that are on a sheet.
- The types of visuals that are on the sheet.
- The number of formats and snapshots that are requested in the job configuration.
- The size of the generated snapshots.