When should I return MaterializeResult of a scalar...
# ask-ai
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When should I return MaterializeResult of a scalar value from an asset and when should I return a scalar value
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When deciding whether to return a
MaterializeResult
or a scalar value from an asset, you should consider the following based on the documentation: 1. Returning `MaterializeResult`: This is useful when you want to explicitly report to Dagster that an asset has been materialized without necessarily using an I/O manager. This can be particularly helpful when the asset materialization is conditional or when the asset does not use an I/O manager, such as when executing queries directly in a database. If you want to emit events to the event log prior to the completion of the asset's execution function, especially for long-running computations, you might use
MaterializeResult
to yield intermediate results. 2. Returning a scalar value: If your asset function is designed to compute and return a simple scalar value that should be stored or passed to downstream assets, you can return this value directly. The scalar value will be handled by the default I/O manager or the one specified in your asset definition. The documentation also mentions that there is an ongoing discussion about the use of
MaterializeResult
and how to access its value or metadata in downstream assets. There is a feature request to support a
value
in
MaterializeResult
to store scalar values that can be accessed in downstream assets, indicating that this is a recognized use case that may be addressed in future versions of Dagster. In summary, use
MaterializeResult
when you need to report materialization events explicitly, especially under conditional or complex scenarios, and return a scalar value when your asset function's primary purpose is to compute and pass that value to other parts of your Dagster job. Keep in mind that the handling of scalar values and
MaterializeResult
may evolve, so it's a good idea to stay updated with the latest Dagster documentation and release notes for any changes in best practices.