Pinpointing the Python Code Paths with High Disk I/O (using OpenResty XRay)
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Drizzle Nginx Module
Yichun Zhang , 17 Oct 2013 (created 21 Jun 2011)This is an nginx upstream module that talks to MySQL and/or Drizzle database servers by libdrizzle.
This ngx_drizzle module is not enabled by default. You should specify the --with-http_drizzle_module
option
while configuring OpenResty.
The libdrizzle C library is no longer bundled by OpenResty. You need to download the drizzle server tarball from https://launchpad.net/drizzle.
Latest drizzle7 release does not support building libdrizzle 1.0 separately
and requires a lot of external dependencies like Boost and Protobuf which are
painful to install. The last version supporting building libdrizzle 1.0 separately
is 2011.07.21
. You can download it from here:
https://openresty.org/download/drizzle7-2011.07.21.tar.gz
When you get the drizzle7 2011.07.21 release tarball, you can install libdrizzle-1.0 like this:
tar xzvf drizzle7-2011.07.21.tar.gz
cd drizzle7-2011.07.21/
./configure --without-server
make libdrizzle-1.0
make install-libdrizzle-1.0
Please ensure that you have the python
command point to a python2
interpreter.
It's known that on recent Arch Linux distribution, python
is linked to python3
by
default, and while running make libdrizzle-1.0
will yield the following error:
File "config/pandora-plugin", line 185
print "Dependency loop detected with %s" % plugin['name']
^
SyntaxError: invalid syntax
make: *** [.plugin.scan] Error 1
You can fix this by pointing python
temporarily to python2
.
When you install the libdrizzle-1.0 library to a custom path prefix, you can specify the libdrizzle prefix to OpenResty like this:
cd /path/to/ngx_openresty-VERSION/
./configure --with-libdrizzle=/path/to/drizzle --with-http_drizzle_module
Documentation page: https://github.com/openresty/drizzle-nginx-module#readme
Project page: https://github.com/openresty/drizzle-nginx-module
When used in conjunction with LuaNginxModule, it is recommended to use LuaRestyMySQLLibrary instead of this one, since it is more flexible and more memory-efficient.