sqltap helps you quickly understand:
- how many times a sql query is executed
- how much time your sql queries take
- where your application is issuing sql queries from
http://sqltap.inconshreveable.com
If you want to use this lib with nova you should do follow steps:
- Go to the nova/service.py
- Go to the init block of class WSGIService
- Replace line
self.app = self.loader.load_app(name)
with
loaded_app = self.loader.load_app(name)
dir_path = '/path/to/dir/with/reports/' # This dir should exist
wsgi_app = sqltap.wsgi.SQLTapMiddleware(loaded_app, dir_path)
self.app = wsgi_app
- Run nova-api
After that reports for each API request will be saved in the directory that you provided
When you work at a high level of abstraction, it’s more common for your code to be inefficient and cause performance problems. SQLAlchemy’s ORM is excellent and gives you the flexibility to fix these inefficiencies if you know where to look! sqltap is a library that hooks into SQLAlchemy to collect metrics on all queries you send to your databases. sqltap can help you find where in your application you are generating slow or redundant queries so that you can fix them with minimal effort.
import sqltap
profiler = sqltap.start()
session.query(Knights).filter_by(who_say = 'Ni').all()
statistics = profiler.collect()
sqltap.report(statistics, "report.html")
You can easily integrate SQLTap into any WSGI application. This will create an up-to-date report page at /__sqltap__ where you can dynamically enable/disable the profiling so you can easily run it selectively in production. Integrating is super-easy:
import sqltap.wsgi
wsgi_app = sqltap.wsgi.SQLTapMiddleware(wsgi_app)
For example, to integrate with a Flask application:
import sqltap.wsgi
app = sqltap.wsgi.SQLTapMiddleware(app.wsgi_app)
import sqltap
def context_fn(*args):
""" Associate the request path, unique id with each query statistic """
return (framework.current_request().path,
framework.current_request().id)
# start the profiler immediately
profiler = sqltap.start(user_context_fn=context_fn)
def generate_reports():
""" call this at any time to generate query reports reports """
all_stats = []
per_request_stats = collections.defaultdict(list)
per_page_stats = collections.defaultdict(list)
qstats = profiler.collect()
for qs in qstats:
all_stats.append(qs)
page = qstats.user_context[0]
per_page_stats[page].append(qs)
request_id = qstats.user_context[1]
per_request_stats[request_id].append(qs)
# report with all queries
sqltap.report(all_stats, "report_all.html")
# a report per page
for page, stats:
sqltap.report(stats, "report_page_%s.html" % page)
# a report per request
for request_id, stats:
sqltap.report(stats, "report_request_%s.html" % request_id)
Run the sqltap tests:
nosetests tests/
Apache