Public bug reported:
During some investigations regarding segments we may have noticed
performance issues related to the current algorithm that schedules
network segments on hosts.
When an agent is reporting a change in segment, the process goes to the
function `auto_schedule_new_network_segments` with the list of the
segments that this host handles.
This function is retrieving from the segments the related networks, then
we can notice that the algorithm is running a double for loop. That one
iterates through network and per segments to schedule network segments
on all hosts.
for network_id in network_ids:
for segment in segments:
self._schedule_network(
payload.context, network_id, dhcp_notifier,
candidate_hosts=segment['hosts'])
Depending on the design chosen, in a setup that has hundred segments per
host with hundred networks and potentially segments that share the same
list of hosts, we will endup by calling _schedule_network 10000 times
with duplication.
To avoid such duplication and unnecessary calls of _schedule_network for
the same hosts we may want to provide a datastructure that is storing
for each network the hosts already scheduled.
for network_id in network_ids:
for segment in segments:
if not _already_scheduled(network_id, segment['hosts']):
self._schedule_network(
payload.context, network_id, dhcp_notifier,
candidate_hosts=segment['hosts'])
With this same scenario, and by using such algorithm we may reduce the
number of call per the number of networks, 100.
Thanks,
s.
** Affects: neutron
Importance: Undecided
Status: New
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https://bugs.launchpad.net/bugs/1959750
Title:
potential performance issue when scheduling network segments
Status in neutron:
New
Bug description:
During some investigations regarding segments we may have noticed
performance issues related to the current algorithm that schedules
network segments on hosts.
When an agent is reporting a change in segment, the process goes to
the function `auto_schedule_new_network_segments` with the list of the
segments that this host handles.
This function is retrieving from the segments the related networks,
then we can notice that the algorithm is running a double for loop.
That one iterates through network and per segments to schedule network
segments on all hosts.
for network_id in network_ids:
for segment in segments:
self._schedule_network(
payload.context, network_id, dhcp_notifier,
candidate_hosts=segment['hosts'])
Depending on the design chosen, in a setup that has hundred segments
per host with hundred networks and potentially segments that share the
same list of hosts, we will endup by calling _schedule_network 10000
times with duplication.
To avoid such duplication and unnecessary calls of _schedule_network
for the same hosts we may want to provide a datastructure that is
storing for each network the hosts already scheduled.
for network_id in network_ids:
for segment in segments:
if not _already_scheduled(network_id, segment['hosts']):
self._schedule_network(
payload.context, network_id, dhcp_notifier,
candidate_hosts=segment['hosts'])
With this same scenario, and by using such algorithm we may reduce the
number of call per the number of networks, 100.
Thanks,
s.
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