Lazy-Stacker summary: I am doing some work on Neutron IPAM code for IP Allocation, and I need to found whether it's better to use db locking queries (SELECT ... FOR UPDATE) or some sort of non-blocking algorithm. Some measures suggest that for this specific problem db-level locking is more efficient even when using multi-master DB clusters, which kind of counters recent findings by other contributors ... but also backs those from others .
The long and boring thing: In the past few months there's been a fair amount of discussion concerning the use of locking queries (ie: SELECT ... FOR UPDATE) in various OpenStack projects, especially in connection with the fact that this kind of queries is likely to trigger write set certification failures in synchronous db replication engines such as MySQL Galera - as pointed out in  and thoroughly analysed in . Neutron, in particular, uses this construct often - and the correctness of the whole IPAM logic depends on it. On this regard Neutron is also guilty of not implementing any sort of retry mechanism. Eugene, Rossella, and others have been working towards fixing this issue. Some examples of their work can be found at  and . However, techniques such as "compare and swap" described in  can be used for implementing non-blocking algorithms which avoid at all the write-set certification issue. A neutron example of such technique can be found in . However, a bug in this process found by Attila , and the subsequent gerrit discussion , raised further questions on locking vs non-blocking solutions. At this stage, we know that using database-level locks triggers write-set certification failures in synchronous multi master modes. This failures are reported as deadlock errors. Such errors can be dealt with retrying the transaction. However, this is claimed as not efficient in , whereas Attila in  argues the opposite. As I'm rewriting Neutron's IPAM logic as a part of , which heavily relies on this construct, I decided to spend some time to put everything to the test. To this aim I devised 3 algorithms. A-1) The classic one which locks the availability ranges for a subnet until allocation is complete, augmented with a simple and brutal retry mechanism . A-2) A wait-free 2 step process, in which the first one creates the IP allocation entry, and the second completes it by adjusting availability ranges . Primary key violations will trigger retries. A-3) A wait-free, lock-free 3 step process , which adopts compare-and-swap  and the same election process as the bully algorithm . Unfortunately neutron does not create IP records for every address in a subnet's CIDR - this would be fairly bad for IPv6 networks. Therefore we cannot simply apply the simple CAS technique introduced in . I then tested them under arbitrary concurrent load from multiple workers. The tests were performed first on a single node backend, and then a 3-node mysql Galera cluster, installed and configured using the official documentation . The single-node tests showed, as it might have been expected, that the algorithm leveraging db-level locks is way more efficient  While it's pointless discussing the full results, one important aspect here is that with db-level locks are a lot more "gentle" with the database, and this result in consistently faster execution times. With 20 concurrent threads, every thread completed in about 0.06 seconds with db-level locks (A-1). With A-2 it took about 0.45 seconds, and with A-3 0.32. With A-2 we saw over 500 queries, a little more than 200 with A-3, and just a bit more than 100 with A-1. It's worth noting that what makes A-3 faster than A-2 is a random allocation strategy which drastically reduces collisions. A-3's performance with sequential allocations are much worse (the avg. thread runtime with 20 concurrent threads is about 0.75 seconds) With the test on the Galera cluster I was expecting a terrible slowdown in A-1 because of deadlocks caused by certification failures. I was extremely disappointed that the slowdown I measured however does not make any of the other algorithms a viable alternative. On the Galera cluster I did not run extensive collections for A-2. Indeed primary key violations seem to triggers db deadlock because of failed write set certification too (but I have not yet tested this). I run tests with 10 threads on each node, for a total of 30 workers. Some results are available at . There was indeed a slow down in A-1 (about 20%), whereas A-3 performance stayed pretty much constant. Regardless, A-1 was still at least 3 times faster than A-3. As A-3's queries are mostly select (about 75% of them) use of caches might make it a lot faster; also the algorithm is probably inefficient and can be optimised in several areas. Still, I suspect it can be made faster than A-1. At this stage I am leaning towards adoption db-level-locks with retries for Neutron's IPAM. However, since I never trust myself, I wonder if there is something important that I'm neglecting and will hit me down the road. In the medium term, there are a few things we might consider for Neutron's "built-in IPAM". 1) Move the allocation logic out of the driver, thus making IPAM an independent service. The API workers will then communicate with the IPAM service through a message bus, where IP allocation requests will be "naturally serialized" 2) Use 3-party software as dogpile, zookeeper but even memcached to implement distributed coordination. I have nothing against it, and I reckon Neutron can only benefit for it (in case you're considering of arguing that "it does not scale", please also provide solid arguments to support your claim!). Nevertheless, I do believe API request processing should proceed undisturbed as much as possible. If processing an API requests requires distributed coordination among several components then it probably means that an asynchronous paradigm is more suitable for that API request. Thanks for reading through this email. Salvatore  http://lists.openstack.org/pipermail/openstack-dev/2014-May/035264.html  http://www.joinfu.com/2015/01/understanding-reservations-concurrency-locking-in-nova/  https://review.openstack.org/#/c/149261  https://review.openstack.org/#/c/100963  https://github.com/openstack/neutron/blob/master/neutron/plugins/ml2/drivers/helpers.py#L112  https://launchpad.net/bugs/1410854  https://review.openstack.org/#/c/147540  http://specs.openstack.org/openstack/neutron-specs/specs/kilo/reference-ipam-driver.html  https://github.com/salv-orlando/ip_allocation_poc/blob/master/algorithms/db_lock.py  https://github.com/salv-orlando/ip_allocation_poc/blob/master/algorithms/two_step_with_retry.py  https://github.com/salv-orlando/ip_allocation_poc/blob/master/algorithms/three_steps.py  http://www.cs.colostate.edu/~cs551/CourseNotes/Synchronization/BullyExample.html  http://galeracluster.com/documentation-webpages/gettingstarted.html#node-initialization  https://github.com/salv-orlando/ip_allocation_poc/blob/master/results.json (you can read it with the parse_results.py utility available in the same repo)  https://github.com/salv-orlando/ip_allocation_poc/blob/master/results_node_3.json (check results_node_1.json and results_node_2.json as well)
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