kopia lustrzana https://dev.funkwhale.audio/funkwhale/funkwhale
38 wiersze
1.4 KiB
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38 wiersze
1.4 KiB
ReStructuredText
Optimizing your Funkwhale instance
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Depending on your requirements, you may want to reduce as much as possible
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Funkwhale's memory footprint.
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Reduce workers concurrency
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--------------------------
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Asynchronous tasks are handled by a celery worker, which will by default
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spawn a worker process per CPU available. This can lead to a higher
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memory usage.
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You can control this behavior using the ``--concurrency`` flag.
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For instance, setting ``--concurrency=1`` will spawn only one worker.
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This flag should be appended after the ``celery -A funkwhale_api.taskapp
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worker`` command in your :file:`docker-compose.yml` file if your using Docker,
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or in your :file:`/etc/systemd/system/funkwhale-worker.service` otherwise.
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.. note::
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Reducing concurrency comes at a cost: asynchronous tasks will be processed
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more slowly. However, on small instances, this should not be an issue.
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Switch from prefork to solo pool
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--------------------------------
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Using a different pool implementation for Celery tasks may also help.
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Using the ``solo`` pool type should reduce your memory consumption.
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You can control this behavior using the ``--pool=solo`` flag.
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This flag should be appended after the ``celery -A funkwhale_api.taskapp worker``
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command in your :file:`docker-compose.yml` file if you're using Docker, or in
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your :file:`/etc/systemd/system/funkwhale-worker.service` otherwise.
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