Patch memory leak when saving to Zarr #915
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| @@ -703,6 +704,10 @@ def _write_zarr_chunk(segment_index, start_frame, end_frame, worker_ctx): | |||
| traces = traces.astype(dtype) | |||
| zarr_dataset[start_frame:end_frame, :] = traces | |||
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| # fix memory leak by forcing garbage collection | |||
| del traces | |||
| gc.collect() | |||
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does it works without the gc.collect() ?
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I mean it works but the jobs keep accumulating RAM
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This is also something that I think we encountered with hdf5 or memap arrays. You need to regularly force the destruction of the objects to clear the built-in caches that they have, in order to prevent memory leaks
samuelgarcia
approved these changes
Aug 29, 2022
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When saving to ZARR with parallel writing, somehow the RAM usage of each job kept increasing, causing out-of-memory error.
After some debugging, I found that deleting the traces and forcing garbage collection fixes it. It's a patch, but it doesn't seem to affect speed..