WIP Experimental integration of nocopy cloudpickle with bytelist API #1643
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I'm glad to see this work happen. Hopefully the Dask test suite can provide some useful feedback! |
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I have to work on other things in the coming days but plan to resume work ASAP. |
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Closing this as cloudpipe/cloudpickle#138 was closed in favor of PEP 574 in upstream python and numpy. |
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This is a work in progress integration of an experimental branch of cloudpickle that allows for nocopy dump and load of nested numpy arrays using a bytelist API.
This relies on: cloudpipe/cloudpickle#138
In particular, this should help make the workers more stable when dealing with large numpy arrays or pandas data frames: spilling to disk (and loading back spilled data structures) should no longer incur large temporary buffer allocations. Also the
_BytelistFilehelper class is not properly tested.There are broken tests (e.g. I just noticed that pickling arrays of objects is broken) but I wanted to do a full run on CI and communicate about the final goal of my work on cloudpickle to other cloudpickle and dask developers.