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I'm using NginX to serve metadata on MDQ queryes like:
# get all the entitities in a single aggregated metadata
/entities
# get a single metadata, related to the hashed entityID in the request URL
# the encoded value is a hashed entity_id
/entities/{sha1}baf9ddc66fa9d6a6077e72cd04e0e292ccbc7676
The rules are the following
location ~ /entities/\{sha1\}(.*) {
default_type "application/xml; charset=utf-8";
alias /opt/pyff/md/$1.xml;
}
location ~ /entities$ {
default_type "application/xml; charset=utf-8";
alias /opt/pyff/md/md-loaded.xml;
}
pyff without a CACHE will take roughly 3 or 4 seconds to get back the result, NginX instead will take 36ms. In addition to this if nginx is unable to find the requested sha1 metadata it will return 404, instead of error 500 as pyff does.
Please share your ideas
The text was updated successfully, but these errors were encountered:
look at scripts/mirror-mdq.sh and also test the new api backend. With the redis backend and config.cache_size turned up to a bit more than your expected volume of entities you should get much better performance.
At the moment I'll be in production with nginx static serve, when I'll have more time I'll try to read the code and understand your suggestions, otherwise I'll wait more time to get for official documentation on these tasks. thank you @leifj
I'm using NginX to serve metadata on MDQ queryes like:
The rules are the following
This experience is related to #171
pyff without a CACHE will take roughly 3 or 4 seconds to get back the result, NginX instead will take 36ms. In addition to this if nginx is unable to find the requested sha1 metadata it will return 404, instead of error 500 as pyff does.
Please share your ideas
The text was updated successfully, but these errors were encountered: