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Is your feature request related to a problem? Please describe.
Many of the current Scala unit and integration tests check that queries (or subsets of queries) are going to run on the GPU by inspecting the execution plan made available from the DataFrame API. This approach does not work when Adaptive Query Execution (AQE) is enabled, because the execution plan is determined during query execution. This means we cannot currently test the plugin with AQE to see what issues need to be resolved to fully support it.
Describe the solution you'd like
The tests should be updated to register a listener with the Spark context so that the listenener can receive the executed plan after query execution has been completed and then use that to determine which parts of the query ran on CPU or GPU.
Describe alternatives you've considered
N/A
Additional context
N/A
The text was updated successfully, but these errors were encountered:
Is your feature request related to a problem? Please describe.
Many of the current Scala unit and integration tests check that queries (or subsets of queries) are going to run on the GPU by inspecting the execution plan made available from the DataFrame API. This approach does not work when Adaptive Query Execution (AQE) is enabled, because the execution plan is determined during query execution. This means we cannot currently test the plugin with AQE to see what issues need to be resolved to fully support it.
Describe the solution you'd like
The tests should be updated to register a listener with the Spark context so that the listenener can receive the executed plan after query execution has been completed and then use that to determine which parts of the query ran on CPU or GPU.
Describe alternatives you've considered
N/A
Additional context
N/A
The text was updated successfully, but these errors were encountered: