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Merge pull request #4276 from Ralith/performance-advice
Improve advice regarding poor performance
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commit
8fcd2ca907
@ -72,3 +72,6 @@ Jason Robinson <jasonr at matrix.org>
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Joseph Weston <joseph at weston.cloud>
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Joseph Weston <joseph at weston.cloud>
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+ Add admin API for querying HS version
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+ Add admin API for querying HS version
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Benjamin Saunders <ben.e.saunders at gmail dot com>
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* Documentation improvements
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32
README.rst
32
README.rst
@ -340,8 +340,11 @@ log lines and looking for any 'Processed request' lines which take more than
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a few seconds to execute. Please let us know at #synapse:matrix.org if
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a few seconds to execute. Please let us know at #synapse:matrix.org if
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you see this failure mode so we can help debug it, however.
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you see this failure mode so we can help debug it, however.
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Help!! Synapse eats all my RAM!
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Help!! Synapse is slow and eats all my RAM/CPU!
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-------------------------------
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-----------------------------------------------
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First, ensure you are running the latest version of Synapse, using Python 3
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with a PostgreSQL database.
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Synapse's architecture is quite RAM hungry currently - we deliberately
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Synapse's architecture is quite RAM hungry currently - we deliberately
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cache a lot of recent room data and metadata in RAM in order to speed up
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cache a lot of recent room data and metadata in RAM in order to speed up
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@ -352,14 +355,29 @@ variable. The default is 0.5, which can be decreased to reduce RAM usage
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in memory constrained enviroments, or increased if performance starts to
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in memory constrained enviroments, or increased if performance starts to
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degrade.
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degrade.
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However, degraded performance due to a low cache factor, common on
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machines with slow disks, often leads to explosions in memory use due
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backlogged requests. In this case, reducing the cache factor will make
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things worse. Instead, try increasing it drastically. 2.0 is a good
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starting value.
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Using `libjemalloc <http://jemalloc.net/>`_ can also yield a significant
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Using `libjemalloc <http://jemalloc.net/>`_ can also yield a significant
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improvement in overall amount, and especially in terms of giving back RAM
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improvement in overall memory use, and especially in terms of giving back
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to the OS. To use it, the library must simply be put in the LD_PRELOAD
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RAM to the OS. To use it, the library must simply be put in the
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environment variable when launching Synapse. On Debian, this can be done
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LD_PRELOAD environment variable when launching Synapse. On Debian, this
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by installing the ``libjemalloc1`` package and adding this line to
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can be done by installing the ``libjemalloc1`` package and adding this
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``/etc/default/matrix-synapse``::
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line to ``/etc/default/matrix-synapse``::
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LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libjemalloc.so.1
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LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libjemalloc.so.1
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This can make a significant difference on Python 2.7 - it's unclear how
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This can make a significant difference on Python 2.7 - it's unclear how
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much of an improvement it provides on Python 3.x.
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much of an improvement it provides on Python 3.x.
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If you're encountering high CPU use by the Synapse process itself, you
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may be affected by a bug with presence tracking that leads to a
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massive excess of outgoing federation requests (see `discussion
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<https://github.com/matrix-org/synapse/issues/3971>`_). If metrics
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indicate that your server is also issuing far more outgoing federation
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requests than can be accounted for by your users' activity, this is a
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likely cause. The misbehavior can be worked around by setting
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``use_presence: false`` in the Synapse config file.
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1
changelog.d/4276.misc
Normal file
1
changelog.d/4276.misc
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@ -0,0 +1 @@
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Improve README section on performance troubleshooting.
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