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@@ -44,8 +44,9 @@ In order to do this you will need to:
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* Ensure all worker processes write the Eliot logs to disk (if you're using the ``multiprocessing`` or ``distributed`` backends).
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* If you're using multiple worker machines, aggregate all log files into a single place, so you can more easily analyze them with e.g. `eliot-tree <https://github.com/jonathanj/eliottree>`_.
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* Replace ``dask.compute()`` with ``eliot.dask.compute_with_trace()``.
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* Replace ``dask.persist()`` with ``eliot.dask.persist_with_trace()``.
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In the following example, you can see how this works for a Dask run using ``distributed``, the recommended Dask scheduler.
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In the following example, you can see how this works for a Dask run using ``distributed``, the recommended Dask scheduler for more sophisticated use cases.
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We'll be using multiple worker processes, but only use a single machine:
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