I guess I confuse easily...still Either I don't understand what it's doing, or I don't understand why it's doing what it is, or what it's doing is confused.
Sigh.
On 08-Jun-14 14:24, Evan Hunt wrote:
> On Sun, Jun 08, 2014 at 09:45:23AM -0400, Timothe Litt wrote:
>> Consider a continuous stream of queries to a slow server. For the sake
>> of exposition, assume the incremental adjustment is 1 rather than 5.
>>
>> Named drops the 11th query, but increases the limit.
> It only increases the limit if one of the pending queries for that name
> got an answer back. If the authoritative server's not responding at all,
> we just carry on dropping queries, but if *is* answering -- just not
> quickly enough to keep up with demand -- then we adjust our queue
> lengths.
Better, but unless this limit/accounting is per-server, it still doesn't
make sense.
And if it is, it ought to be able to add (# dropped) to the limit rather
than
sneak up on it.
As described, the resolver threads are per name + record type.
I don't see why a server would respond quickly to one record type and
not another.
I don't see why one slow responder should control the max queue depth
for all, unless
one argues that for the faster ones, the excess quota wouldn't be used.
That might
open a DOS attack; If I control a slow responder, I can make other
resolvers allocate
extra resources...
> The code was written before my time, so I'm only guessing here, but I
Not blaming you :-( Just trying to understand.
> suspect the idea was to adapt to the situation where you have a fast
> local network and a slow upstream connection. If we're getting queries
> for popular names faster than we can resolve them, it may make sense to
> buffer more queries.
I suppose - but per name+record type (+class?)?
That does tell us what requests have been issued - no point in making
more than one
request to the same server for the same data. (Modulo UDP lossage.)
From first principles:
If a (client) request arrives that requires data not in the cache:
a) If new data is not already been requested, clearly it needs to
be fetched
So you probably allocate a cache entry marked 'pending' and
queue the
requesting task.
b) The client request must either get queued or dropped.
When should one drop?
-- If too many client resolver tasks are queued (for any
data)
-- If too many client+internal resolver tasks are queued
for this *server*
c) The assumption on dropping is that the client can retry, and
will hit in the cache.
This must get ugly when the record has a TTL of 0 (or <
client retry interval)
If the upstream physical connection (pipe) is slow, it doesn't matter
where the query
goes - if we send a lot, it will get saturated.
Coalescing duplicate queries makes sense, up to some memory limit.
But why
would it be limited per-name with a globally tuned throttle?
If we usually request from more than one NS, a slow pipe might benefit
from dropping back
to less parallelism when congested. But this isn't the right
measurement point for that.
If the pipe is fast, but some *server* is slow, we can expect all
responses from *that server*
to be equally slow. No matter what the name/type/class is.
So in that case, we still want to coalesce the requests if quota allows.
But the quota would want to be 'outstanding requests to *that server*',
not something per-name+type.
As for popular vs. unpopular names - we only know that a name is popular
because
the queue grows. (Or maybe we could have some cache history if this is
a ttl
expired(ing prefetch) case.) The only sensible thing one might do is
drop requests for
unpopular names if a popular one hit a limit... on the theory that
limited resources
should go to satisfy the most requests.
>> For the former, a global threshold makes some sense - an abusive burst
>> of queries can be for multiple zones - or focused on one.
>> But isn't this what response rate limiting is for? Given RRL, does this
>> still make sense?
> RRL is response rate limiting -- it applies to output not input.
Isn't it pretty much the same thing? Dropping a request is
the same as dropping a response - from the client's point of view. It's
better from
named's point of view, since it can avoid internal work.
RRL claims to limit based on 'lots of packets with similar source
addresses asking
for similar or identical information'. Isn't that sufficient to prevent
this case?
To make an internal resolver query, there must be a client request, right?
So limiting the client requests ought to prevent unreasonable numbers of
internal resolver queries...I think.
If not, Request Rate Limiting has the same acronym, and RRL.current
could reasonably extend
to cover this case. If a given client is creating an unacceptable
request rate, the requests
could be dropped. Some people do this with iptables in front of named.
Named could be
smarter - e.g. drop duplicate requests for the same data from a
client(range) at an interval
less than TTL / n. Or something like that.
>> For the latter, separating the measurement/threshold tuning from the
>> decision to drop would seem to produce more sensible behavior than
>> dropping every 5i-th packet. And for it to make any sense at all, it
>> must be adjusted per server, not globally...
> As it happens I'm in the middle of a research project on this very
> subject; future releases will probably have some additional per-server
> throttling and holddown controls and more finely adjustable drop
> policies. Stay tuned.
Of course the 'servers' in this case have to be dynamically discovered;
they're not
'server' in the sense of 'my masters and slaves', they're servers in the
sense of
other authoritative servers consulted for resolving non-local names. Be
careful with
the vocabulary (doc and config items) to avoid adding to my confusion :-)
>> Or I'm missing something, in which case the documentation needs some
>> more/different words :-(
> If the above was helpful and you feel inspired to rephrase it into
> text for the ARM, I'm always happy to take your patches. :)
>
Perhaps when I'm unconfused.
smime.p7s
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