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Jonas Winkler 2020-11-23 00:35:06 +01:00
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17
docs/faq.rst
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@ -43,21 +43,8 @@ in your browser and paperless has to do much less work to serve the data.
.. note:: .. note::
Consider setting ``PAPERLESS_OPTIMIZE_THUMBNAILS`` to false to speed up You can adjust some of the settings so that paperless uses less processing
the consumption process. This takes quite a bit of time on Raspberry Pi. power. See :ref:`setup-less_powerful_devices` for details.
.. note::
Updating the :ref:`automatic matching algorithm <advanced-automatic_matching>`
takes quite a bit of time. However, the update mechanism checks if your
data has changed before doing the heavy lifting. If you experience the
algorithm taking too much cpu time, consider changing the schedule in the
admin interface to daily or weekly. You can also manually invoke the task
by changing the date and time of the next run to today/now.
The actual matching of the algorithm is fast and works on Raspberry Pi as
well as on any other device.
**Q:** *How do I install paperless-ng on Raspberry Pi?* **Q:** *How do I install paperless-ng on Raspberry Pi?*

16
docs/setup.rst
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@ -358,6 +358,9 @@ management commands as below.
7. Start paperless. 7. Start paperless.
.. _setup-less_powerful_devices:
Considerations for less powerful devices Considerations for less powerful devices
######################################## ########################################
@ -383,5 +386,18 @@ configuring some options in paperless can help improve performance immensely:
For details, refer to :ref:`configuration`. For details, refer to :ref:`configuration`.
.. note::
Updating the :ref:`automatic matching algorithm <advanced-automatic_matching>`
takes quite a bit of time. However, the update mechanism checks if your
data has changed before doing the heavy lifting. If you experience the
algorithm taking too much cpu time, consider changing the schedule in the
admin interface to daily. You can also manually invoke the task
by changing the date and time of the next run to today/now.
The actual matching of the algorithm is fast and works on Raspberry Pi as
well as on any other device.
.. _redis: https://redis.io/ .. _redis: https://redis.io/