Hello All,
I wanted to ask for some explanation on something that i see.
I have a simple OpenFlow pipeline which first does a match on inport + dst
MAC address, (table 1)
then match on subnets ranges (with go to Controller) and on single IP's
(table 2)
for example: priority 100 match 10.0.0.0/24 go to controller
priority 100 match 10.0.0.1 go to next table
And a default rule in this table to go to the egress table (table 3) with
priority 1:
priority 1 goto egress table
I am sending a generated packet using ovs-appctl with destination IP that
doesnt match
any subnet or specific IP in table 2 :
ovs-appctl ofproto/trace br-int
in_port=2,dl_src=00:00:00:00:00:01,dl_dst=fa:16:3e:e2:16:63,eth_type=0x800,nw_dst=8.8.8.8,nw_src=192.1.1.1
-generate
The installed megaflow i see is this:
Megaflow: recirc_id=0,ip,in_port=2,dl_dst=fa:16:3e:e2:16:63,nw_dst=
0.0.0.0/2.0.0.0,nw_frag=no
The question is how does the nw_dst is calculated in this megaflow ?
is it finding a mask that doesnt fit any IP or subnet in table 2 and
calculate it? (it seems
like a hard task, especially with combined IP's and subnets matchers).
If i add a learning flow to this table with nw_dst of 8.8.8.8 (for example
do learning for every miss in table 2) is it going to be more efficient
performance wise? (because the megaflow would then be able to have nw_dst
of 8.8.8.8)
Thanks
Gal.
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