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Sep 23, 2024
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document run_asynchronously #206

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8 changes: 8 additions & 0 deletions best-practices.mdx
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Expand Up @@ -134,6 +134,14 @@ Don't worry about converting Chalk DataFrames to [Pandas](https://pandas.pydata.

The Chalk CLI should be used to run simple online queries. For more complex use cases, you should use one of Chalk's API clients.

### Run large queries asynchronously

When sending large or long-running queries, use
[`run_asynchronously`](/api-docs#ChalkClient.offline_query.run_asynchronously) to set up a separate Kubernetes pod for
running your query separately from your production and branch servers. You can configure resources for asynchronous
offline queries in your dashboard settings. You can also terminate asynchronous queries through the dashboard by
terminating the pod or canceling the query within the dashboard, which is not possible for synchronous queries.

### Create named queries for your commonly executed queries

With Chalk, you can alias your complex queries using a [NamedQuery](/api-docs#NamedQuery). Named queries help simplify and document your
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