I was surprised recently to discover that MySQL uses repeatable read for
transactions by default. Postgres uses read committed by default, and
SQLite uses serializable. We don't set the isolation level explicitly
anywhere, so our applications are running under different isolation
levels depending on backend. This doesn't sound like a good idea to me.
It's one thing to support multiple sql syntaxes, but different isolation
levels have different semantics. Supporting that is much harder, and
currently we're not even trying.

I'm aware that the same isolation level on different databases will
still have subtly different semantics, but at least they should agree on
the big things. I think we should pick one, and it should be read committed.

Also note that 'repeatable read' on both MySQL and Postgres is actually
snapshot isolation, which isn't quite the same thing. For example, it
doesn't get phantom reads.

The most important reason I think we need read committed is recovery
from concurrent changes within the scope of a single transaction. To
date, in Nova at least, this hasn't been an issue as transactions have
had an extremely small scope. However, we're trying to expand that scope
with the new enginefacade in oslo.db:
https://review.openstack.org/#/c/138215/ . With this expanded scope,
transaction failure in a library function can't simply be replayed
because the transaction scope is larger than the function.

So, 3 concrete examples of how repeatable read will make Nova worse:

* https://review.openstack.org/#/c/140622/

This was committed to Nova recently. Note how it involves a retry in the
case of concurrent change. This works fine, because the retry is creates
a new transaction. However, if the transaction was larger than the scope
of this function this would not work, because each iteration would
continue to read the old data. The solution to this is to create a new
transaction. However, because the transaction is outside of the scope of
this function, the only thing we can do locally is fail. The caller then
has to re-execute the whole transaction, or fail itself.

This is a local concurrency problem which can be very easily handled
locally, but not if we're using repeatable read.

*
https://github.com/openstack/nova/blob/master/nova/db/sqlalchemy/api.py#L4749

Nova has multiple functions of this type which attempt to update a
key/value metadata table. I'd expect to find multiple concurrency issues
with this if I stopped to give it enough thought, but concentrating just
on what's there, notice how the retry loop starts a new transaction. If
we want to get to a place where we don't do that, with repeatable read
we're left failing the whole transaction.

* https://review.openstack.org/#/c/136409/

This one isn't upstream, yet. It's broken, and I can't currently think
of a solution if we're using repeatable read.

The issue is atomic creation of a shared resource. We want to handle a
creation race safely. This patch:

* Attempts to reads the default (it will normally exist)
* Creates a new one if it doesn't exist
* Goes back to the start if creation failed due to a duplicate

Seems fine, but it will fail because the re-read will continue to not
return the new value under repeatable read (no phantom reads). The only
way to see the new row is a new transaction. Is this will no longer be
in the scope of this function, the only solution will be to fail. Read
committed could continue without failing.

Incidentally, this currently works by using multiple transactions, which
we are trying to avoid. It has also been suggested that in this specific
instance the default security group could be created with the project.
However, that would both be more complicated, because it would require
putting a hook into another piece of code, and less robust, because it
wouldn't recover if somebody deleted the default security group.


To summarise, with repeatable read we're forced to abort the current
transaction to deal with certain relatively common classes of
concurrency issue, whereas with read committed we can safely recover. If
we want to reduce the number of transactions we're using, which we do,
the impact of this is going to dramatically increase. We should
standardise on read committed.

Matt
-- 
Matthew Booth
Red Hat Engineering, Virtualisation Team

Phone: +442070094448 (UK)
GPG ID:  D33C3490
GPG FPR: 3733 612D 2D05 5458 8A8A 1600 3441 EA19 D33C 3490

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