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SQLAlchemy - Lost connection to MySQL server during query

Here's was my situation:
  • The database was set up behind behind an AWS ELB and HAProxy. 
  • The idle connection timeout on the ELB was set to 60 mins.
  • All the relevant timeouts on HAProxy seemed to be set to 60 mins too. 
  • The pool_recycle in SQLAlchemy was set to 30 mins.
  • I was still seeing the occasional "Lost connection to MySQL server during query" when small queries were running after the connection had some time to sit around.
The solution ended up being setting my pool_recycle down to 5 mins, but I'm still not sure what was causing connections to time out after 5 mins.

There are definitely other things that can cause this problem too. For example, it can happen if your data exceeds max_allowed_packet. See this page for more details:

Most of this also applies for "MySQL server has gone away".

You should also make sure your pool_recycle is set lower than your 'interactive_timeout' and 'wait_timeout' properties in the mysql config file to the values you need.

SQLAlchemy - Unexpected Lazy Loading

If you're seeing unexpected lazy loading on a lazy="joined" relationship in SQLAlchemy, it might be because you're accessing those relationships after you've already run session.commit(). By default, session.commit() will expire the data on your relationships, meaning it will try to fetch it again next time you try to access those attributes.

The relevant section of the docs for session.commit():
By default, the Session also expires all database loaded state on all ORM-managed attributes after transaction commit. This so that subsequent operations load the most recent data from the database. This behavior can be disabled using the expire_on_commit=False option to sessionmaker or the Session constructor.

SQLAlchemy - Is is necessary to commit after session.execute?

The docs for session.execute say:

Execute a SQL expression construct or string statement within the current transaction.

So, the answer is yes, you need to issue a commit after running session.execute().

Here’s a code example along with the output from “echo=True” showing it begins the session but doesn’t end it unless you run session.commit():

SQLAlchemy 1.1.4's New "server_side_cursors" Option

Before SQLAlchemy 1.1.4, if you wanted to stream your MySQL query using server side cursors, you would need to run your query using "execution_options(stream_results=True)" and pass SSCursor into create_engine's connect_args. Now, all you need to do is pass "server_side_cursors=True" into create_engine and it will automatically stream the results for your select queries.

Is it necessary to run SQLAlchemy's session.remove()?

If you're using flask-sqlalchemy, then the answer is no - it's already doing it for you when the request finishes:

If you're using scoped_session and not explicitly running session.remove(), then your connections will only be returned to the pool after your thread finishes and garbage collection occurs. It's not a good idea to leave this to garbage collection, because you can't guarantee your connections will be returned to the pool when your application is busy. This will often lead to errors like this: "TimeoutError: QueuePool limit of size 5 overflow 10 reached, connection timed out, timeout 30"

The solution is to make sure session.remove() runs when the work finishes (like flask-sqlalchemy does), as described here:

Another alternative is not making the session global and using a context manager, as described at the bottom of this section: However, this can make things difficult when you need to access the query results outside of the context manager. If you access the query results outside of the context manager without running session.expunge_all(), you'll see all kinds of errors like this: "DetachedInstanceError: Instance <ReportingJob at 0xa41cd8c> is not bound to a Session; attribute refresh operation cannot proceed"

Another option is setting autocommit to True, but that has quite a few gotchas. Turning on autocommit will acquire connections from the engine on an as-needed basis and return them immediately after their use. You will have to explicitly start transactions with session.begin() if you enable it. It seems like this setting should be called "autotransaction" instead. It's also not very efficient, because it needs to get and return a connection each time you run a query.

PHP - max_execution_time doesn't work for socket operations

In new relic transaction logs, I was seeing some PHP requests last as long as an hour. It turns out that time spent waiting on sockets doesn't apply toward max_execution_time, and loops that involved waiting on sockets could end up taking a really long time without timing out.

PHP docs have this to say about max_execution_time:
"The set_time_limit() function and the configuration directive max_execution_time only affect the execution time of the script itself. Any time spent on activity that happens outside the execution of the script such as system calls using system(), stream operations, database queries, etc. is not included when determining the maximum time that the script has been running. This is not true on Windows where the measured time is real."

The solution ended up being setting request_terminate_timeout in php-fpm.

Python - Cachetools LRUCache KeyError

If your application is threaded and you're getting a "KeyError" while using the non-decorator version of cachetool's LRUCache, then you need to put whatever is manipulating the cache object inside of a lock. Also, since LRUCache is modified when values are gotten from it, you will also need to make sure you're locking when you get values from cache too. If you can use the decorator version of LRUCache, that's preferred since it has built-in locking.

Here's an example of the error:

And an example of the fix: