Hi Levani,
Thanks for the modifications!
I have some follow up questions/comments:
5. Something is not clear to me. If the active is on Node-1 and the
first replica is on Node-5 (different cluster, different zone), why
would the second replica go to Node-4 that has a different cluster than
but the same zone as the active instead of Node-6 which has a different
zone of Node-1? In general wouldn't it be better to guarantee under
Partially Preferred task distribution to distribute active and standby
replicas of the same task over the dimension that has at least as many
values as the number of replicas + 1 and then over the dimensions that
have less values? That would then also be independent on the ordering of
the tags.
7. I agree with you. Could you add a sentence or two about this to the KIP?
New question:
8. How would the assignor react on different numbers and different
orderings of the tags in standby.replicas.awareness across Streams clients?
Best,
Bruno
On 22.02.21 11:46, Levani Kokhreidze wrote:
Hi Bruno,
Thanks for the feedback. Please check my answers below:
1. No objections; sounds good. Updated KIP
2. No objections; sounds good. Updated KIP
3. Thanks for the information; I can change KIP only to expose prefix method
instead of a constant if it’s the way forward.
4. Done. Updated KIP
5. Yes, order in standby.replicas.awareness config counts as stated in the
STANDBY_REPLICA_AWARENESS_DOC.
Actually, it plays a role in Partially Preferred distribution. In the example
presented in the KIP, while one of the standby tasks can be placed in a
different cluster and different zone compared to the active task, we have to
choose either the same cluster or the same zone for the second standby task. In
the first example presented in the KIP, while Node-5 is in the other cluster
and other zone compared to the active task, the second standby task's preferred
options are in different zones than Node-1 and Node-5, but in the same cluster
as active task or the first standby task. Without importance semantics in
standby.replicas.awareness, putting second standby task in Node-4 (different
cluster, same zone as active task) would have been a valid option.
I’ve updated KIP to clarify this a bit more, I hope this helps.
6. Thanks for pointing that out, it was a mistake. I’ve removed that phrase
from the KIP.
7. It shouldn’t affect HighAvailabilityTaskAssignor in a “breaking way” meaning
that all the existing behavior should stay as is (e.g., when new configurations
are not specified). Once required configurations are set, the main change
should happen in HighAvailabilityTaskAssignor#assignStandbyReplicaTasks and
HighAvailabilityTaskAssignor#assignStandbyTaskMovements
I hope this answers your questions.
Regards,
Levani
On 18. Feb 2021, at 15:10, Bruno Cadonna <br...@confluent.io> wrote:
Hi Levani,
Thank you for the KIP.
Really interesting!
Here my comments:
1. To be consistent with the other configs that involve standbys , I would
rename
standby.task.assignment.awareness -> standby.replicas.awareness
2. I would also rename the prefix
instance.tag -> client.tag
3. The following is a question about prefixes in general that maybe somebody
else can answer. In the config it says for other prefixes that it is
recommended to use the method *Prefix(final String prop) instead of the raw
prefix string.
Is the plan to make the raw prefix string private in a future release?
Should we consider making only the prefix method for this KIP public?
4. Could you provide a mathematical formula instead of Java code for absolute
preferred standby task distribution and the other distributtion properties?
Could you also add an example for absolute preffered distribution for the
computation of the formula similar to what you did for the other properties?
5. Does the order of the tags given for standby.task.assignment.awareness
count? You mention it once, but then for the Partially Preferred standby task
distribution property it does not seem to be important.
6. In the section about least preferred standby task distribution, you state that
"and one [zone] will be reserved for active task". What do you mean by that?
All Streams clients will participate in the task assignment of active tasks irrespective
of their tags, right? The statement does also not really fit with the example where
active stateful task 0_0 is on Node-1, does it?
7. Could you also say some words about how this KIP affects the current
HighAvailabilityTaskAssignor?
Best,
Bruno
On 09.02.21 15:54, Levani Kokhreidze wrote:
Hello all,
I’ve updated KIP-708 [1] to reflect the latest discussion outcomes.
I’m looking forward to your feedback.
Regards,
Levani
[1] -
https://cwiki.apache.org/confluence/display/KAFKA/KIP-708%3A+Rack+awarness+for+Kafka+Streams
On 2. Feb 2021, at 22:03, Levani Kokhreidze <levani.co...@gmail.com> wrote:
Hi John.
Thanks a lot for this detailed analysis!
Yes, that is what I had in mind as well.
I also like that idea of having “task.assignment.awareness” configuration
to tell which instance tags can be used for rack awareness.
I may borrow it for this KIP if you don’t mind :)
Thanks again John for this discussion, it’s really valuable.
I’ll update the proposal and share it once again in this discussion thread.
Regards,
Levani
On 2. Feb 2021, at 18:47, John Roesler <vvcep...@apache.org <mailto:vvcep...@apache.org>
<mailto:vvcep...@apache.org <mailto:vvcep...@apache.org>>> wrote:
Hi Levani,
1. Thanks for the details.
I figured it must be something like this two-dimensional definition of "rack".
It does seem like, if we make the config take a list of tags, we can define
the semantics to be that the system will make a best effort to distribute
the standbys over each rack dimension.
In your example, there are two clusters and three AZs. The example
configs would be:
Node 1:
instance.tag.cluster: K8s_Cluster1
instance.tag.zone: eu-central-1a
task.assignment.awareness: cluster,zone
Node 2:
instance.tag.cluster: K8s_Cluster1
instance.tag.zone: eu-central-1b
task.assignment.awareness: cluster,zone
Node 3:
instance.tag.cluster: K8s_Cluster1
instance.tag.zone: eu-central-1c
task.assignment.awareness: cluster,zone
Node 4:
instance.tag.cluster: K8s_Cluster2
instance.tag.zone: eu-central-1a
task.assignment.awareness: cluster,zone
Node 5:
instance.tag.cluster: K8s_Cluster2
instance.tag.zone: eu-central-1b
task.assignment.awareness: cluster,zone
Node 6:
instance.tag.cluster: K8s_Cluster2
instance.tag.zone: eu-central-1c
task.assignment.awareness: cluster,zone
Now, if we have a task 0_0 with an active and two replicas,
there are three total copies of the task to distribute over:
* 6 instances
* 2 clusters
* 3 zones
There is a constraint that we _cannot_ assign two copies of a task
to a single instance, but it seems like the default rack awareness
would permit us to assign two copies of a task to a rack, if (and only
if) the number of copies is greater than the number of racks.
So, the assignment we would get is like this:
* assigned to three different instances
* one copy in each of zone a, b, and c
* two copies in one cluster and one in the other cluster
For example, we might have 0_0 assigned to:
* Node 1 (cluster 1, zone a)
* Node 5 (cluster 2, zone b)
* Node 3 (cluster 1, zone c)
Is that what you were also thinking?
Thanks,
-John
On Tue, Feb 2, 2021, at 02:24, Levani Kokhreidze wrote:
Hi John,
1. Main reason was that it seemed easier change compared to having
multiple tags assigned to each host.
---
Answering your question what use-case I have in mind:
Lets say we have two Kubernetes clusters running the same Kafka Streams
application.
And each Kubernetes cluster is spanned across multiple AZ.
So the setup overall looks something like this:
K8s_Cluster1 [eu-central-1a, eu-central-1b, eu-central-1c]
K8s_Cluster2 [eu-central-1a, eu-central-1b, eu-central-1c]
Now, if Kafka Streams application is launched in K8s_Clister1:
eu-central-1a,
ideally I would want standby task to be created in the different K8s
cluster and region.
So in this example it can be K8s_Cluster2: [eu-central-1b,
eu-central-1c]
But giving it a bit more thought, this can be implemented if we change
semantics of “tags” a bit.
So instead of doing full match with tags, we can do iterative matching
and it should work.
(If this is what you had in mind, apologies for the misunderstanding).
If we consider the same example as mentioned above, for the active task
we would
have following tags: [K8s_Cluster1, eu-central-1a]. In order to
distribute standby task
in the different K8s cluster, plus in the different AWS region, standby
task assignment
algorithm can compare each tag by index. So steps would be something
like:
// this will result in selecting client in the different K8s cluster
1. clientsInDifferentCluster = (tagsOfActiveTask[0] != allClientTags[0])
// this will result in selecting the client in different AWS region
2. selectedClientForStandbyTask = (tagsOfActiveTask[1] !=
clientsInDifferentCluster[1] )
WDYT?
If you agree with the use-case I’ve mentioned, the pluggable assignor
can be differed to another KIP, yes.
As it won’t be required for this KIP and use-cases I had in mind to
work.
Regards,
Levani
On 2. Feb 2021, at 07:55, John Roesler <vvcep...@apache.org <mailto:vvcep...@apache.org>
<mailto:vvcep...@apache.org <mailto:vvcep...@apache.org>>> wrote:
Hello Levani,
Thanks for the reply.
1. Interesting; why did you change your mind?
I have a gut feeling that we can achieve pretty much any rack awareness need
that people have by using purely config, which is obviously much easier to use.
But if you had a case in mind where this wouldn’t work, it would be good to
know.
In fact, if that is true, then perhaps you could just defer the whole idea of a
pluggable interface (point 2) to a separate KIP. I do think a pluggable
assignor would be extremely valuable, but it might be nice to cut the scope of
KIP-708 if just a config will suffice.
What do you think?
Thanks,
John
On Mon, Feb 1, 2021, at 06:07, Levani Kokhreidze wrote:
Hi John,
Thanks a lot for thorough feedback, it’s really valuable.
1. Agree with this. Had the same idea initially.
We can set some upper limit in terms of what’s
the max number of tags users can set to make
sure it’s not overused. By default, we can create
standby tasks where tags are different from active task (full match).
This should mimic default rack awareness behaviour.
2. I like the idea and I’d be happy to work on
refactoring TaskAssignor to accommodate rack awareness use-case.
When I was going through the code, it felt way more natural
to use pluggable TaskAssignor for achieving rack awareness
instead of introducing new interface and contract.
But I thought approach mentioned in the KIP is simpler so
decided to move forward with it as an initial proposal :).
But I agree with you, it will be much better if we can have
TaskAssignor as pluggable interface users can use.
One potential challenge I see with this is that, if we just let
users implement TaskAssignor in its current form, we will be forcing
users to implement functionality for active task assignment, as well as
standby task assignment. This feels like not very clear contract,
because with
just TaskAssignor interface it’s not really clear they one needs to
allocate
standby tasks as well. We can enforce it on some level with the return
object
You’ve mentioned TaskAssignor#assign has to return, but still feels
error prone.
In addition, I suspect in most of the cases users would want
to control standby task assignment and leave active task assignment as
is.
To make implementation of standby task assignment easier for users,
what if
we decouple active and standby task assignment from the `TaskAssignor`?
Idea I have in mind is to split TaskAssignor into ActiveTaskAssignor
and StandbyTaskAssignor
and let users add their own implementation for them separately if they
like via config.
If this approach sounds reasonable, I’ll work on updating KIP this week.
Thanks,
Levani
On 28. Jan 2021, at 19:20, John Roesler <vvcep...@apache.org <mailto:vvcep...@apache.org>
<mailto:vvcep...@apache.org <mailto:vvcep...@apache.org>>> wrote:
Thanks, Levani!
I was reflecting more on your KIP last night.
One thing I should mention is that I have previously used
the rack awareness feature of Elasticsearch, and found it to
be pretty intuitive and also capable of what we needed in
our AWS clusters. As you look at related work, you might
take ES into consideration.
I was also had some thoughts about your proposal.
1. I'm wondering if we instead allow people to add arbitrary
tags to each host, and then have a configuration to specify
a combination of tags to use for rack awareness. This seems
easier to manage than for the use case you anticipate where
people would concatenate rackId = (clusterId + AZ), and then
have to parse the rackId back out to compute the assignment.
2. About the proposed RackAwareStandbyTaskAssignor, I'm
wondering if we can change the level of abstraction a little
bit and capture even more value here. One thing we wanted to
do in KIP-441, but decided to cut from the scope, was to
define a public TaskAssignor interface so that people can
plug in the whole task assignment algorithm.
In fact, there is already an internal config and interface
for this (`internal.task.assignor.class`:
`org.apache.kafka.streams.processor.internals.assignment.Tas
kAssignor`).
We kept that interface and config internal because the
current TaskAssignor interface has a number of flaws, but if
we correct those flaws, we can offer a nice public interface
that people can use to control the standby allocation, but
also active task allocation, based on the tags I suggested
in (1).
I don't think we need too much work to refactor
TaskAssignor, the main problems are that the assign method
mutates its input and that it doesn't expose the full
metadata from the cluster members. Therefore, if you like
this idea, we should propose to refactor TaskAssignor with:
* input: an immutable description of the cluster, including
current lags of all stateful tasks and current stateless
task assignments, as well as metadata for each host.
* output: an object describing the new assignment as well as
a flag on whether to schedule a followup probing rebalance.
An even more stretchy stretch goal would be to include
metadata of the brokers, which could be used to achieve
higher levels of rack awareness. For example, we could co-
locate tasks in the same "rack" (AZ) as the partition leader
for their input or output topics, to minimize cross-AZ
traffic. I'm not sure to what extent clients can learn the
relevant broker metadata, so this stretch might not be
currently feasible, but as long as we design the
TaskAssignor for extensibility, we can do something like
this in the future.
Thanks again for this proposal, I hope the above is more
inspiring than annoying :)
I really think your KIP is super high value in whatever form
you ultimately land on.
Thanks,
John
On Thu, 2021-01-28 at 13:08 +0200, Levani Kokhreidze wrote:
Hi John
Thanks for the feedback (and for the great work on KIP441 :) ).
Makes sense, will add a section in the KIP explaining rack awarenesses on high
level and how it’s implemented in the different distributed systems.
Thanks,
Levani
On 27. Jan 2021, at 16:07, John Roesler <vvcep...@apache.org <mailto:vvcep...@apache.org>
<mailto:vvcep...@apache.org <mailto:vvcep...@apache.org>>> wrote:
Hi Levani,
Thanks for this KIP! I think this is really high value; it was something I was
disappointed I didn’t get to do as part of KIP-441.
Rack awareness is a feature provided by other distributed systems as well. I
wonder if your KIP could devote a section to summarizing what rack awareness
looks like in other distributed systems, to help us put this design in context.
Thanks!
John
On Tue, Jan 26, 2021, at 16:46, Levani Kokhreidze wrote:
Hello all,
I’d like to start discussion on KIP-708 [1] that aims to introduce rack
aware standby task distribution in Kafka Streams.
In addition to changes mentioned in the KIP, I’d like to get some ideas
on additional change I have in mind.
Assuming KIP moves forward, I was wondering if it makes sense to
configure Kafka Streams consumer instances with the rack ID passed with
the new StreamsConfig#RACK_ID_CONFIG property.
In practice, that would mean that when “rack.id <http://rack.id/> <http://rack.id/ <http://rack.id/>>
<http://rack.id/ <http://rack.id/> <http://rack.id/ <http://rack.id/>>>” is
configured in Kafka Streams, it will automatically translate into
ConsumerConfig#CLIENT_RACK_ID config for all the KafkaConsumer clients
that is used by Kafka Streams internally.
[1]
https://cwiki.apache.org/confluence/display/KAFKA/KIP-708%3A+Rack+aware+Kafka+Streams+with+pluggable+StandbyTask+assignor
<https://cwiki.apache.org/confluence/display/KAFKA/KIP-708%3A+Rack+aware+Kafka+Streams+with+pluggable+StandbyTask+assignor>
<https://cwiki.apache.org/confluence/display/KAFKA/KIP-708%3A+Rack+aware+Kafka+Streams+with+pluggable+StandbyTask+assignor
<https://cwiki.apache.org/confluence/display/KAFKA/KIP-708%3A+Rack+aware+Kafka+Streams+with+pluggable+StandbyTask+assignor>>
<https://cwiki.apache.org/confluence/display/KAFKA/KIP-708:+Rack+aware+Kafka+Streams+with+pluggable+StandbyTask+assignor
<https://cwiki.apache.org/confluence/display/KAFKA/KIP-708:+Rack+aware+Kafka+Streams+with+pluggable+StandbyTask+assignor>
<https://cwiki.apache.org/confluence/display/KAFKA/KIP-708:+Rack+aware+Kafka+Streams+with+pluggable+StandbyTask+assignor
<https://cwiki.apache.org/confluence/display/KAFKA/KIP-708:+Rack+aware+Kafka+Streams+with+pluggable+StandbyTask+assignor>>>
P.S
I have draft PR ready, if it helps the discussion moving forward, I can
provide the draft PR link in this thread.
Regards,
Levani
