Alexis Charrier
02/08/2024, 4:04 PMScout
02/08/2024, 4:04 PMAlexis Charrier
02/08/2024, 4:10 PMScout
02/08/2024, 4:10 PM@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: 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.Alexis Charrier
02/08/2024, 4:29 PMScout
02/08/2024, 4:29 PMpython 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.Alexis Charrier
02/08/2024, 7:03 PMScout
02/08/2024, 7:03 PMpython 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.