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# ask-ai
a

Alexis Charrier

02/08/2024, 4:04 PM
I got an error: All leaf nodes within graph 'graph' must generate outputs which are mapped to outputs of the graph, and produce assets. is it possible to call ops without using its return ?
s

Scout

02/08/2024, 4:04 PM
Based on the documentation, it is important to ensure that all leaf nodes within a graph-backed asset produce outputs that are mapped to the outputs of the graph and generate assets. If you encounter an error stating that all leaf nodes must generate outputs which are mapped to outputs of the graph and produce assets, it indicates that there is a leaf node in your graph that does not conform to this requirement. The documentation does not provide a direct way to call ops without using their return values within the context of a graph-backed asset. In Dagster, the design of graph-backed assets is such that the outputs of ops are expected to be used to form the assets that the graph produces. If you have an op that does not produce an asset or an output that should be mapped to a graph output, you may need to reconsider the structure of your graph. It might be necessary to ensure that all ops contribute to the creation of assets, or to refactor your graph so that non-asset-producing ops are not leaf nodes. If you need further assistance with this issue, it would be helpful to provide more context or the specific code that is causing the error, so that we can give more targeted advice.
a

Alexis Charrier

02/08/2024, 4:10 PM
@Scout is there way to indicate which particular return of the graph will generate the asset ?
s

Scout

02/08/2024, 4:10 PM
Yes, in Dagster, you can indicate which particular outputs of a graph will generate assets by using the
@graph_multi_asset
decorator. This decorator allows you to define multiple assets that are computed using the same graph of ops and specify which outputs correspond to which assets. Here's an example from the documentation on how to use
@graph_multi_asset
to define a graph that produces multiple assets:
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python from dagster import AssetOut, graph_multi_asset  @graph_multi_asset(outs={"first_asset": AssetOut(), "second_asset": AssetOut()}) def two_assets(upstream_asset):     one, two = two_outputs(upstream_asset)     return {"first_asset": one, "second_asset": two}
In this example, the
two_assets
graph takes an
upstream_asset
as input and produces two outputs,
one
and
two
. The
@graph_multi_asset
decorator is used to map these outputs to two separate assets,
first_asset
and
second_asset
. When you define your graph, you can specify the outputs that should be mapped to assets using the
outs
parameter of the
@graph_multi_asset
decorator. Each key in the
outs
dictionary corresponds to an asset, and the value is an instance of
AssetOut
, which indicates that the output will generate an asset. This way, you can control which outputs of your graph are used to create assets and ensure that the graph's leaf nodes are properly mapped to asset outputs as required by Dagster's execution model.
a

Alexis Charrier

02/08/2024, 4:29 PM
@Scout it's not possible in graph to not capture assign the return of an operator ?
s

Scout

02/08/2024, 4:29 PM
In Dagster, when you define a graph, it is expected that the outputs of the ops (operations) within the graph are either used by downstream ops or mapped to the graph's outputs. If an op within a graph does not have its output captured or assigned, and it is a leaf node (i.e., it does not feed into any other ops), this can lead to an error because Dagster's execution model relies on understanding the dependencies between ops and the assets they produce. However, if an op's output is not needed as an asset or for downstream computation, you can choose to ignore it by not assigning it to a variable or by not including it in the return statement of the graph. Here's a simple example:
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python from dagster import op, graph  @op def do_something():     # Perform some action     return "result"  @op def do_something_else():     # Perform some other action     pass  # This op does not return anything  @graph def my_graph():     do_something()     do_something_else()  # The return value of do_something is not captured or used  my_job = my_graph.to_job()
In the example above,
do_something
returns a value, but within the
my_graph
graph, this return value is not captured or used by any other ops, and it is not mapped to the graph's outputs. This is allowed because
do_something
is not a leaf node; it is followed by
do_something_else
in the graph. However, if
do_something
were the only op in the graph or the last op in the graph (making it a leaf node), and you wanted to ignore its output, you would need to ensure that the graph still produces an asset or output that is mapped to the graph's outputs to satisfy Dagster's requirements for graph execution. If you encounter issues with leaf nodes not producing assets or outputs that are mapped to the graph's outputs, you may need to refactor your graph to ensure that all leaf nodes contribute to the creation of assets or are connected to the graph's outputs. If you have a specific use case or error message, providing more details could help in giving a more targeted response.
a

Alexis Charrier

02/08/2024, 7:03 PM
@Scout what you just suggested is not working when you create an asset from the graph
s

Scout

02/08/2024, 7:03 PM
I apologize for any confusion. When you create an asset from a graph in Dagster, it is indeed required that all leaf nodes in the graph produce outputs that are mapped to the graph's outputs, as assets are expected to be the result of computations within the graph. If you have an op that does not produce an output that is used as an asset, and it is a leaf node in the graph, you will encounter the error you mentioned. To resolve this, you must ensure that all leaf nodes in the graph either: 1. Produce an output that is captured as an asset. 2. Feed into another op that eventually leads to an asset. Here's an example of how you might structure a graph where all leaf nodes contribute to an asset:
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python from dagster import op, graph, AssetOut, Out  @op(out=Out(asset_key="intermediate_asset")) def generate_intermediate_data():     # Perform some action     return "intermediate result"  @op(out=Out(asset_key="final_asset")) def generate_final_asset(intermediate_data):     # Use the intermediate data to produce the final asset     return f"final result based on {intermediate_data}"  @graph def my_asset_graph():     intermediate = generate_intermediate_data()     return generate_final_asset(intermediate)  my_asset_job = my_asset_graph.to_job()
In this example,
generate_intermediate_data
is not a leaf node because its output is used by
generate_final_asset
. The
generate_final_asset
op is a leaf node, but it produces an output that is captured as an asset, satisfying the requirement. If you have an op that should not produce an asset and is currently a leaf node, you will need to adjust your graph structure to either remove the op from the graph or to use its output in a way that contributes to an asset. If you need further assistance with a specific graph structure or error, please provide additional details or code snippets, and I'll do my best to help you resolve the issue.
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