forked from AkkomaGang/akkoma
Changes to pgtune docs
I experienced that it may be better to tell pgtune you have lower resoures than what you have when you have other services running. I added that now. I also moved the examples as part of the pgtune section.
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@ -6,6 +6,31 @@ Akkoma performance is largely dependent on performance of the underlying databas
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[PgTune](https://pgtune.leopard.in.ua) can be used to get recommended settings. Be sure to set "Number of Connections" to 20, otherwise it might produce settings hurtful to database performance. It is also recommended to not use "Network Storage" option.
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If your server runs other services, you may want to take that into account. E.g. if you have 4G ram, but 1G of it is already used for other services, it may be better to tell PGTune you only have 3G. In the end, PGTune only provides recomended settings, you can always try to finetune further.
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### Example configurations
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Here are some configuration suggestions for PostgreSQL 10+.
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#### 1GB RAM, 1 CPU
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```
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shared_buffers = 256MB
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effective_cache_size = 768MB
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maintenance_work_mem = 64MB
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work_mem = 13107kB
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```
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#### 2GB RAM, 2 CPU
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```
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shared_buffers = 512MB
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effective_cache_size = 1536MB
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maintenance_work_mem = 128MB
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work_mem = 26214kB
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max_worker_processes = 2
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max_parallel_workers_per_gather = 1
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max_parallel_workers = 2
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```
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## Disable generic query plans
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When PostgreSQL receives a query, it decides on a strategy for searching the requested data, this is called a query plan. The query planner has two modes: generic and custom. Generic makes a plan for all queries of the same shape, ignoring the parameters, which is then cached and reused. Custom, on the contrary, generates a unique query plan based on query parameters.
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@ -23,26 +48,3 @@ config :pleroma, Pleroma.Repo,
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```
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A more detailed explaination of the issue can be found at <https://blog.soykaf.com/post/postgresql-elixir-troubles/>.
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## Example configurations
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Here are some configuration suggestions for PostgreSQL 10+.
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### 1GB RAM, 1 CPU
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```
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shared_buffers = 256MB
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effective_cache_size = 768MB
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maintenance_work_mem = 64MB
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work_mem = 13107kB
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```
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### 2GB RAM, 2 CPU
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```
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shared_buffers = 512MB
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effective_cache_size = 1536MB
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maintenance_work_mem = 128MB
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work_mem = 26214kB
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max_worker_processes = 2
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max_parallel_workers_per_gather = 1
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max_parallel_workers = 2
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```
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