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There are several cases where you'll want to do API calls asynchronously. The batching system allows you to push several API calls at once, and then check the status and fetch the results with a separate call. This is helpful if you want to:
There are three endpoints for dealing with Batches:
There are two recommended 'flows' for using this system.
With the basic flow, submit your requests, then periodically poll the Batch's status, providing some sort of progress bar for the user to see things are moving. Once the number of tasks running has gone to zero, use the regular GET endpoint to fetch all the data at once.
With the parallel flow, don't wait to start downloading from the regular GET. Fetch from it repeatedly until you have downloaded all the data. The system will, by default, only return to you requests which have been finished since your last request. This way you can start getting data even before all the requests are done, so that the bottleneck is the slower of network speed and server processing speed, rather than the sum of the two.
Sometimes you just want to do a huge query, say to get a ton of data about a User that just logged in. The normal solution would be to download one piece at a time, chaining cursors from one request to the next. With parallel queries, you POST the query to the system once, and it automatically generates and runs all these individual requests at once. This makes it possible to download all the data your client needs to get going for a given User in a matter of minutes. For particularly learned users, getting the data serially could take hours.
Here's how it works: POST a Batch with a GET query that involves a cursor and set the spawner property to true for the Request object, and the system will automatically generate all requests it needs to run the entire query, using your input as the starting point (including beginning with a cursor), as well as still taking into account any limits you impose. When you access the results, they'll include the auto-generated Requests.