Prevent threaded Dask workers in DistRDF backend#22393
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Test Results 22 files 22 suites 3d 12h 10m 36s ⏱️ Results for commit 5bb11cb. |
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| self.client = (daskclient if daskclient is not None else | ||
| Client(LocalCluster(n_workers=os.cpu_count(), threads_per_worker=1, processes=True))) | ||
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| workers = self.client.scheduler_info()["workers"] |
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| workers = self.client.scheduler_info()["workers"] | |
| workers = self.client.scheduler_info().get("workers", None) | |
| if workers is None: | |
| return |
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Thanks for the suggestion. I updated the code to safely handle the case where scheduler_info() does not contain worker information yet.
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This PR prevents unsupported threaded Dask workers in DistRDF.
Distributed RDataFrame with Dask threads may lead to crashes and does not provide advantages due to Python GIL limitations. This change validates worker configuration at backend initialization and raises a RuntimeError when threaded workers are detected.
Suggested configuration: