That's great to hear! I see now that Swift's implementation has some
additional rebalancing logic that Ironic (and the code example from
Gregory's blog) lacked.
Cheers,
Nejc
On 09/08/2014 05:39 AM, John Dickinson wrote:
To test Swift directly, I used the CLI tools that Swift provides for managing
rings. I wrote the following short script:
$ cat remakerings
#!/bin/bash
swift-ring-builder object.builder create 16 3 0
for zone in {1..4}; do
for server in {200..224}; do
for drive in {1..12}; do
swift-ring-builder object.builder add
r1z${zone}-10.0.${zone}.${server}:6010/d${drive} 3000
done
done
done
swift-ring-builder object.builder rebalance
This adds 1200 devices. 4 zones, each with 25 servers, each with 12 drives
(4*25*12=1200). The important thing is that instead of adding 1000 drives in
one zone or in one server, I'm splaying across the placement hierarchy that
Swift uses.
After running the script, I added one drive to one server to see what the
impact would be and rebalanced. The swift-ring-builder tool detected that less
than 1% of the partitions would change and therefore didn't move anything (just
to avoid unnecessary data movement).
--John
On Sep 7, 2014, at 11:20 AM, Nejc Saje <ns...@redhat.com> wrote:
Hey guys,
in Ceilometer we're using consistent hash rings to do workload
partitioning[1]. We've considered using Ironic's hash ring implementation, but
found out it wasn't actually consistent (ML[2], patch[3]). The next thing I
noticed that the Ironic implementation is based on Swift's.
The gist of it is: since you divide your ring into a number of equal sized
partitions, instead of hashing hosts onto the ring, when you add a new host, an
unbound amount of keys get re-mapped to different hosts (instead of the
1/#nodes remapping guaranteed by hash ring).
Swift's hash ring implementation is quite complex though, so I took the
conceptually similar code from Gregory Holt's blogpost[4] (which I'm guessing
is based on Gregory's efforts on Swift's hash ring implementation) and tested
that instead. With a simple test (paste[5]) of first having 1000 nodes and then
adding 1, 99.91% of the data was moved.
I have no way to test this in Swift directly, so I'm just throwing this out
there, so you guys can figure out whether there actually is a problem or not.
Cheers,
Nejc
[1] https://review.openstack.org/#/c/113549/
[2]
http://lists.openstack.org/pipermail/openstack-dev/2014-September/044566.html
[3] https://review.openstack.org/#/c/118932/4
[4] http://greg.brim.net/page/building_a_consistent_hashing_ring.html
[5] http://paste.openstack.org/show/107782/
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