Re: [DISCUSS] KIP-925: rack aware task assignment in Kafka Streams
Hi Colt, Thanks for the feedback. > most deployments have three racks, RF=3, and one replica for each partition in each rack This KIP is mainly targeting the case where the client won't always be in the same rack as any replica. There's some proposal to make RF=2 and use other tiered storage to do backup. If all TopicPartitions have replicas which can be in same rack as clients, this KIP will not take effect and rack aware assignment will be turned off. As for setting the leader of replicas, I think this is something clients don't have control over. Also as you mentioned, if there are multiple clients, there's no "set the leader and fit all" solution. On Thu, Jun 1, 2023 at 10:20 AM Colt McNealy wrote: > Hi all, > > I've got a rather naive question here. The spiritual goal of this KIP is to > reduce cross-rack traffic (normally, this manifests itself in terms of a > higher AWS/Azure bill as cloud providers charge for cross-AZ traffic). > > To generalize, most deployments have three racks, RF=3, and one replica for > each partition in each rack. Therefore, in the steady state (absent any > cluster anomalies such as broker failure, etc) we are pretty confident that > there should be a replica for every partition (input, changelog, > repartition, output topic) on the same rack as a given Streams instance. > > Why not just let Sophie's High-Availability Task Assignor do its thing, and > then *set the preferred leader* for each replica to a broker in the same > rack/AZ as the Active Task? This would solve two problems: > > 1. The current KIP can't make any improvements in the case where a Task has > three involved partitions (eg. input, changelog, output) and the leader for > each partition is in a different rack. With this approach, we could get > pretty close to having zero cross-AZ traffic in a healthy cluster. > 2. There needs to be a lot of work done to balance availability, data > movement, and cross-AZ traffic in the current proposal. My proposal doesn't > actually involve any additional data movement; simply reassignment of > partition leadership. > > The biggest argument against this proposal is that there could be two > Streams apps using the same topic, which would cause some bickering. > Secondly, some have observed that changing partition leadership can trigger > ProducerFencedExceptions in EOS, which causes a state restoration. > > Colt McNealy > > *Founder, LittleHorse.dev* > > > On Thu, Jun 1, 2023 at 10:02 AM Hao Li wrote: > > > Hi Bruno, > > > > dropping config rack.aware.assignment.enabled > > and add value NONE to the enum for the possible values of config > > rack.aware.assignment.strategy sounds good to me. > > > > On Thu, Jun 1, 2023 at 12:39 AM Bruno Cadonna > wrote: > > > > > Hi Hao, > > > > > > Thanks for the updates! > > > > > > What do you think about dropping config rack.aware.assignment.enabled > > > and add value NONE to the enum for the possible values of config > > > rack.aware.assignment.strategy? > > > > > > Best, > > > Bruno > > > > > > On 31.05.23 23:31, Hao Li wrote: > > > > Hi all, > > > > > > > > I've updated the KIP based on the feedback. Major changes I made: > > > > 1. Add rack aware assignment to `StickyTaskAssignor` > > > > 2. Reject `Prefer reliability and then find optimal cost` option in > > > standby > > > > task assignment. > > > > > > > > > > > > On Wed, May 31, 2023 at 12:09 PM Hao Li wrote: > > > > > > > >> Hi all, > > > >> > > > >> Thanks for the feedback! I will update the KIP accordingly. > > > >> > > > >> *For Sophie's comments:* > > > >> > > > >> 1 and 2. Good catch. Fixed these. > > > >> > > > >> 3 and 4 Yes. We can make this public config and call out the > > > >> clientConsumer config users need to set. > > > >> > > > >> 5. It's ideal to take the previous assignment in HAAssignor into > > > >> consideration when we compute our target assignment, the > complications > > > come > > > >> with making sure the assignment can eventually converge and we don't > > do > > > >> probing rebalance infinitely. It's not only about storing the > previous > > > >> assignment or get it somehow. We can actually get the previous > > > assignment > > > >> now like we do in StickyAssignor. But the previous assignment will > > > change > > > >> in each round of probing rebalance. The proposal which added some > > > weight to > > > >> make the rack aware assignment lean towards the original HAA's > target > > > >> assignment will add benefits of stability in some corner cases in > case > > > of > > > >> tie in cross rack traffic cost. But it's not sticky. But the bottom > > > line is > > > >> it won't be worse than current HAA's stickiness. > > > >> > > > >> 6. I'm fine with changing the assignor config to public. Actually, I > > > think > > > >> we can min-cost algorithm with StickyAssignor as well to mitigate > the > > > >> problem of 5. So we can have one public config to choose an assignor > > and > > > >> one public config to enable the rack aware
Re: [DISCUSS] KIP-925: rack aware task assignment in Kafka Streams
Hi all, I've got a rather naive question here. The spiritual goal of this KIP is to reduce cross-rack traffic (normally, this manifests itself in terms of a higher AWS/Azure bill as cloud providers charge for cross-AZ traffic). To generalize, most deployments have three racks, RF=3, and one replica for each partition in each rack. Therefore, in the steady state (absent any cluster anomalies such as broker failure, etc) we are pretty confident that there should be a replica for every partition (input, changelog, repartition, output topic) on the same rack as a given Streams instance. Why not just let Sophie's High-Availability Task Assignor do its thing, and then *set the preferred leader* for each replica to a broker in the same rack/AZ as the Active Task? This would solve two problems: 1. The current KIP can't make any improvements in the case where a Task has three involved partitions (eg. input, changelog, output) and the leader for each partition is in a different rack. With this approach, we could get pretty close to having zero cross-AZ traffic in a healthy cluster. 2. There needs to be a lot of work done to balance availability, data movement, and cross-AZ traffic in the current proposal. My proposal doesn't actually involve any additional data movement; simply reassignment of partition leadership. The biggest argument against this proposal is that there could be two Streams apps using the same topic, which would cause some bickering. Secondly, some have observed that changing partition leadership can trigger ProducerFencedExceptions in EOS, which causes a state restoration. Colt McNealy *Founder, LittleHorse.dev* On Thu, Jun 1, 2023 at 10:02 AM Hao Li wrote: > Hi Bruno, > > dropping config rack.aware.assignment.enabled > and add value NONE to the enum for the possible values of config > rack.aware.assignment.strategy sounds good to me. > > On Thu, Jun 1, 2023 at 12:39 AM Bruno Cadonna wrote: > > > Hi Hao, > > > > Thanks for the updates! > > > > What do you think about dropping config rack.aware.assignment.enabled > > and add value NONE to the enum for the possible values of config > > rack.aware.assignment.strategy? > > > > Best, > > Bruno > > > > On 31.05.23 23:31, Hao Li wrote: > > > Hi all, > > > > > > I've updated the KIP based on the feedback. Major changes I made: > > > 1. Add rack aware assignment to `StickyTaskAssignor` > > > 2. Reject `Prefer reliability and then find optimal cost` option in > > standby > > > task assignment. > > > > > > > > > On Wed, May 31, 2023 at 12:09 PM Hao Li wrote: > > > > > >> Hi all, > > >> > > >> Thanks for the feedback! I will update the KIP accordingly. > > >> > > >> *For Sophie's comments:* > > >> > > >> 1 and 2. Good catch. Fixed these. > > >> > > >> 3 and 4 Yes. We can make this public config and call out the > > >> clientConsumer config users need to set. > > >> > > >> 5. It's ideal to take the previous assignment in HAAssignor into > > >> consideration when we compute our target assignment, the complications > > come > > >> with making sure the assignment can eventually converge and we don't > do > > >> probing rebalance infinitely. It's not only about storing the previous > > >> assignment or get it somehow. We can actually get the previous > > assignment > > >> now like we do in StickyAssignor. But the previous assignment will > > change > > >> in each round of probing rebalance. The proposal which added some > > weight to > > >> make the rack aware assignment lean towards the original HAA's target > > >> assignment will add benefits of stability in some corner cases in case > > of > > >> tie in cross rack traffic cost. But it's not sticky. But the bottom > > line is > > >> it won't be worse than current HAA's stickiness. > > >> > > >> 6. I'm fine with changing the assignor config to public. Actually, I > > think > > >> we can min-cost algorithm with StickyAssignor as well to mitigate the > > >> problem of 5. So we can have one public config to choose an assignor > and > > >> one public config to enable the rack aware assignment. > > >> > > >> *For Bruno's comments:* > > >> > > >> The proposal was to implement all the options and use configs to > choose > > >> them during runtime. We can make those configs public as suggested. > > >> 1, 2, 3, 4, 5: agree and will fix those. > > >> 6: subscription protocol is not changed. > > >> 7: yeah. Let me fix the notations. > > >> 8: It meant clients. In the figure, it maps to `c1_1`, `c1_2`, `c1_3` > > etc. > > >> 9: I'm also ok with just optimizing reliability for standby tasks. Or > we > > >> could simply run the "balance reliability over cost" greedy algorithm > to > > >> see if any cost could be reduced. > > >> 10: Make sense. Will fix the wording. > > >> 11: Make sense. Will update the test part. > > >> > > >> *For Walker's comments:* > > >> 1. Stability for HAA is an issue. See my comments for Sophie's > feedback > > 5 > > >> and 6. I think we could use the rack aware assignment for > >
Re: [DISCUSS] KIP-925: rack aware task assignment in Kafka Streams
Hi Bruno, dropping config rack.aware.assignment.enabled and add value NONE to the enum for the possible values of config rack.aware.assignment.strategy sounds good to me. On Thu, Jun 1, 2023 at 12:39 AM Bruno Cadonna wrote: > Hi Hao, > > Thanks for the updates! > > What do you think about dropping config rack.aware.assignment.enabled > and add value NONE to the enum for the possible values of config > rack.aware.assignment.strategy? > > Best, > Bruno > > On 31.05.23 23:31, Hao Li wrote: > > Hi all, > > > > I've updated the KIP based on the feedback. Major changes I made: > > 1. Add rack aware assignment to `StickyTaskAssignor` > > 2. Reject `Prefer reliability and then find optimal cost` option in > standby > > task assignment. > > > > > > On Wed, May 31, 2023 at 12:09 PM Hao Li wrote: > > > >> Hi all, > >> > >> Thanks for the feedback! I will update the KIP accordingly. > >> > >> *For Sophie's comments:* > >> > >> 1 and 2. Good catch. Fixed these. > >> > >> 3 and 4 Yes. We can make this public config and call out the > >> clientConsumer config users need to set. > >> > >> 5. It's ideal to take the previous assignment in HAAssignor into > >> consideration when we compute our target assignment, the complications > come > >> with making sure the assignment can eventually converge and we don't do > >> probing rebalance infinitely. It's not only about storing the previous > >> assignment or get it somehow. We can actually get the previous > assignment > >> now like we do in StickyAssignor. But the previous assignment will > change > >> in each round of probing rebalance. The proposal which added some > weight to > >> make the rack aware assignment lean towards the original HAA's target > >> assignment will add benefits of stability in some corner cases in case > of > >> tie in cross rack traffic cost. But it's not sticky. But the bottom > line is > >> it won't be worse than current HAA's stickiness. > >> > >> 6. I'm fine with changing the assignor config to public. Actually, I > think > >> we can min-cost algorithm with StickyAssignor as well to mitigate the > >> problem of 5. So we can have one public config to choose an assignor and > >> one public config to enable the rack aware assignment. > >> > >> *For Bruno's comments:* > >> > >> The proposal was to implement all the options and use configs to choose > >> them during runtime. We can make those configs public as suggested. > >> 1, 2, 3, 4, 5: agree and will fix those. > >> 6: subscription protocol is not changed. > >> 7: yeah. Let me fix the notations. > >> 8: It meant clients. In the figure, it maps to `c1_1`, `c1_2`, `c1_3` > etc. > >> 9: I'm also ok with just optimizing reliability for standby tasks. Or we > >> could simply run the "balance reliability over cost" greedy algorithm to > >> see if any cost could be reduced. > >> 10: Make sense. Will fix the wording. > >> 11: Make sense. Will update the test part. > >> > >> *For Walker's comments:* > >> 1. Stability for HAA is an issue. See my comments for Sophie's feedback > 5 > >> and 6. I think we could use the rack aware assignment for > StickyAssignor as > >> well. For HAA assignments, it's less sticky and we can only shoot for > >> minimizing the cross rack traffic eventually when everything is stable. > >> 2. Yeah. This is a good point and we can also turn it on for > >> StickyAssignor. > >> > >> Thanks, > >> Hao > >> > >> > >> On Tue, May 30, 2023 at 2:28 PM Sophie Blee-Goldman < > >> ableegold...@gmail.com> wrote: > >> > >>> Hey Hao, thanks for the KIP! > >>> > >>> 1. There's a typo in the "internal.rack.aware.assignment.strategry" > >>> config, > >>> this > >>> should be internal.rack.aware.assignment.strategy. > >>> > >>> 2. > >>> > For O(E^2 * (CU)) complexity, C and U can be viewed as constant. > >>> Number of > edges E is T * N where T is the number of clients and N is the number > of > Tasks. This is because a task can be assigned to any client so there > >>> will > be an edge between every task and every client. The total complexity > >>> would > be O(T * N) if we want to be more specific. > >>> > >>> I feel like I'm missing something here, but if E = T * N and the > >>> complexity > >>> is ~O(E^2), doesn't > >>> this make the total complexity order of O(T^2 * N^2)? > >>> > >>> 3. > >>> > Since 3.C.I and 3.C.II have different tradeoffs and work better in > different workloads etc, we > >>> > >>> could add an internal configuration to choose one of them at runtime. > > >>> Why only an internal configuration? Same goes for > >>> internal.rack.aware.assignment.standby.strategry (which also has the > typo) > >>> > >>> 4. > >>> > There are no changes in public interfaces. > >>> > >>> I think it would be good to explicitly call out that users can utilize > >>> this > >>> new feature by setting the > >>> ConsumerConfig's CLIENT_RACK_CONFIG, possibly with a brief example > >>> > >>> 5. > >>> > The idea is that if we always try to make it
Re: [DISCUSS] KIP-925: rack aware task assignment in Kafka Streams
Hi Hao, Thanks for the updates! What do you think about dropping config rack.aware.assignment.enabled and add value NONE to the enum for the possible values of config rack.aware.assignment.strategy? Best, Bruno On 31.05.23 23:31, Hao Li wrote: Hi all, I've updated the KIP based on the feedback. Major changes I made: 1. Add rack aware assignment to `StickyTaskAssignor` 2. Reject `Prefer reliability and then find optimal cost` option in standby task assignment. On Wed, May 31, 2023 at 12:09 PM Hao Li wrote: Hi all, Thanks for the feedback! I will update the KIP accordingly. *For Sophie's comments:* 1 and 2. Good catch. Fixed these. 3 and 4 Yes. We can make this public config and call out the clientConsumer config users need to set. 5. It's ideal to take the previous assignment in HAAssignor into consideration when we compute our target assignment, the complications come with making sure the assignment can eventually converge and we don't do probing rebalance infinitely. It's not only about storing the previous assignment or get it somehow. We can actually get the previous assignment now like we do in StickyAssignor. But the previous assignment will change in each round of probing rebalance. The proposal which added some weight to make the rack aware assignment lean towards the original HAA's target assignment will add benefits of stability in some corner cases in case of tie in cross rack traffic cost. But it's not sticky. But the bottom line is it won't be worse than current HAA's stickiness. 6. I'm fine with changing the assignor config to public. Actually, I think we can min-cost algorithm with StickyAssignor as well to mitigate the problem of 5. So we can have one public config to choose an assignor and one public config to enable the rack aware assignment. *For Bruno's comments:* The proposal was to implement all the options and use configs to choose them during runtime. We can make those configs public as suggested. 1, 2, 3, 4, 5: agree and will fix those. 6: subscription protocol is not changed. 7: yeah. Let me fix the notations. 8: It meant clients. In the figure, it maps to `c1_1`, `c1_2`, `c1_3` etc. 9: I'm also ok with just optimizing reliability for standby tasks. Or we could simply run the "balance reliability over cost" greedy algorithm to see if any cost could be reduced. 10: Make sense. Will fix the wording. 11: Make sense. Will update the test part. *For Walker's comments:* 1. Stability for HAA is an issue. See my comments for Sophie's feedback 5 and 6. I think we could use the rack aware assignment for StickyAssignor as well. For HAA assignments, it's less sticky and we can only shoot for minimizing the cross rack traffic eventually when everything is stable. 2. Yeah. This is a good point and we can also turn it on for StickyAssignor. Thanks, Hao On Tue, May 30, 2023 at 2:28 PM Sophie Blee-Goldman < ableegold...@gmail.com> wrote: Hey Hao, thanks for the KIP! 1. There's a typo in the "internal.rack.aware.assignment.strategry" config, this should be internal.rack.aware.assignment.strategy. 2. For O(E^2 * (CU)) complexity, C and U can be viewed as constant. Number of edges E is T * N where T is the number of clients and N is the number of Tasks. This is because a task can be assigned to any client so there will be an edge between every task and every client. The total complexity would be O(T * N) if we want to be more specific. I feel like I'm missing something here, but if E = T * N and the complexity is ~O(E^2), doesn't this make the total complexity order of O(T^2 * N^2)? 3. Since 3.C.I and 3.C.II have different tradeoffs and work better in different workloads etc, we could add an internal configuration to choose one of them at runtime. Why only an internal configuration? Same goes for internal.rack.aware.assignment.standby.strategry (which also has the typo) 4. There are no changes in public interfaces. I think it would be good to explicitly call out that users can utilize this new feature by setting the ConsumerConfig's CLIENT_RACK_CONFIG, possibly with a brief example 5. The idea is that if we always try to make it overlap as much with HAAssignor’s target assignment, at least there’s a higher chance that tasks won’t be shuffled a lot if the clients remain the same across rebalances. This line definitely gave me some pause -- if there was one major takeaway I had after KIP-441, one thing that most limited the feature's success, it was our assumption that clients are relatively stable across rebalances. This was mostly true at limited scale or for on-prem setups, but unsurprisingly broke down in cloud environments or larger clusters. Not only do clients naturally fall in and out of the group, autoscaling is becoming more and more of a thing. Lastly, and this is more easily solved but still worth calling out, an assignment is only deterministic as long as the client.id is persisted. Currently in Streams, we only write
Re: [DISCUSS] KIP-925: rack aware task assignment in Kafka Streams
Thanks Sophie! I've just made the updates :) On Wed, May 31, 2023 at 2:29 PM Sophie Blee-Goldman wrote: > Thanks Hao -- I really like Walker's idea to separate the assignment > strategy from the rack awareness option. > Having two different configs for these makes a lot of sense to me and seems > like it will benefit the most users. > > Given your KIP already has a lot going on with it, I would be happy to > write up a quick KIP just for the public > assignor config to take that aspect off your hands. We can discuss that > separately and keep this thread focused > on the rack awareness algorithm. If that sounds good I'll kick off a KIP > tonight, then you can just update the > "Current Task Assignment Logic" section to mention that either assignor may > be plugged in, and the rack > awareness can be configured independently. > > If users are able to plug in the StickyAssignor if they experience > problems, this is good enough for me w.r.t my > other concern regarding task shuffling > > On Wed, May 31, 2023 at 12:09 PM Hao Li wrote: > > > Hi all, > > > > Thanks for the feedback! I will update the KIP accordingly. > > > > *For Sophie's comments:* > > > > 1 and 2. Good catch. Fixed these. > > > > 3 and 4 Yes. We can make this public config and call out the > clientConsumer > > config users need to set. > > > > 5. It's ideal to take the previous assignment in HAAssignor into > > consideration when we compute our target assignment, the complications > come > > with making sure the assignment can eventually converge and we don't do > > probing rebalance infinitely. It's not only about storing the previous > > assignment or get it somehow. We can actually get the previous assignment > > now like we do in StickyAssignor. But the previous assignment will change > > in each round of probing rebalance. The proposal which added some weight > to > > make the rack aware assignment lean towards the original HAA's target > > assignment will add benefits of stability in some corner cases in case of > > tie in cross rack traffic cost. But it's not sticky. But the bottom line > is > > it won't be worse than current HAA's stickiness. > > > > 6. I'm fine with changing the assignor config to public. Actually, I > think > > we can min-cost algorithm with StickyAssignor as well to mitigate the > > problem of 5. So we can have one public config to choose an assignor and > > one public config to enable the rack aware assignment. > > > > *For Bruno's comments:* > > > > The proposal was to implement all the options and use configs to choose > > them during runtime. We can make those configs public as suggested. > > 1, 2, 3, 4, 5: agree and will fix those. > > 6: subscription protocol is not changed. > > 7: yeah. Let me fix the notations. > > 8: It meant clients. In the figure, it maps to `c1_1`, `c1_2`, `c1_3` > etc. > > 9: I'm also ok with just optimizing reliability for standby tasks. Or we > > could simply run the "balance reliability over cost" greedy algorithm to > > see if any cost could be reduced. > > 10: Make sense. Will fix the wording. > > 11: Make sense. Will update the test part. > > > > *For Walker's comments:* > > 1. Stability for HAA is an issue. See my comments for Sophie's feedback 5 > > and 6. I think we could use the rack aware assignment for StickyAssignor > as > > well. For HAA assignments, it's less sticky and we can only shoot for > > minimizing the cross rack traffic eventually when everything is stable. > > 2. Yeah. This is a good point and we can also turn it on for > > StickyAssignor. > > > > Thanks, > > Hao > > > > > > On Tue, May 30, 2023 at 2:28 PM Sophie Blee-Goldman < > > ableegold...@gmail.com> > > wrote: > > > > > Hey Hao, thanks for the KIP! > > > > > > 1. There's a typo in the "internal.rack.aware.assignment.strategry" > > config, > > > this > > > should be internal.rack.aware.assignment.strategy. > > > > > > 2. > > > > > > > For O(E^2 * (CU)) complexity, C and U can be viewed as constant. > > Number > > > of > > > > edges E is T * N where T is the number of clients and N is the number > > of > > > > Tasks. This is because a task can be assigned to any client so there > > will > > > > be an edge between every task and every client. The total complexity > > > would > > > > be O(T * N) if we want to be more specific. > > > > > > I feel like I'm missing something here, but if E = T * N and the > > complexity > > > is ~O(E^2), doesn't > > > this make the total complexity order of O(T^2 * N^2)? > > > > > > 3. > > > > > > > Since 3.C.I and 3.C.II have different tradeoffs and work better in > > > > different workloads etc, we > > > > > > could add an internal configuration to choose one of them at runtime. > > > > > > > Why only an internal configuration? Same goes for > > > internal.rack.aware.assignment.standby.strategry (which also has the > > typo) > > > > > > 4. > > > > > > > There are no changes in public interfaces. > > > > > > I think it would be good to explicitly call out that users can
Re: [DISCUSS] KIP-925: rack aware task assignment in Kafka Streams
Hi all, I've updated the KIP based on the feedback. Major changes I made: 1. Add rack aware assignment to `StickyTaskAssignor` 2. Reject `Prefer reliability and then find optimal cost` option in standby task assignment. On Wed, May 31, 2023 at 12:09 PM Hao Li wrote: > Hi all, > > Thanks for the feedback! I will update the KIP accordingly. > > *For Sophie's comments:* > > 1 and 2. Good catch. Fixed these. > > 3 and 4 Yes. We can make this public config and call out the > clientConsumer config users need to set. > > 5. It's ideal to take the previous assignment in HAAssignor into > consideration when we compute our target assignment, the complications come > with making sure the assignment can eventually converge and we don't do > probing rebalance infinitely. It's not only about storing the previous > assignment or get it somehow. We can actually get the previous assignment > now like we do in StickyAssignor. But the previous assignment will change > in each round of probing rebalance. The proposal which added some weight to > make the rack aware assignment lean towards the original HAA's target > assignment will add benefits of stability in some corner cases in case of > tie in cross rack traffic cost. But it's not sticky. But the bottom line is > it won't be worse than current HAA's stickiness. > > 6. I'm fine with changing the assignor config to public. Actually, I think > we can min-cost algorithm with StickyAssignor as well to mitigate the > problem of 5. So we can have one public config to choose an assignor and > one public config to enable the rack aware assignment. > > *For Bruno's comments:* > > The proposal was to implement all the options and use configs to choose > them during runtime. We can make those configs public as suggested. > 1, 2, 3, 4, 5: agree and will fix those. > 6: subscription protocol is not changed. > 7: yeah. Let me fix the notations. > 8: It meant clients. In the figure, it maps to `c1_1`, `c1_2`, `c1_3` etc. > 9: I'm also ok with just optimizing reliability for standby tasks. Or we > could simply run the "balance reliability over cost" greedy algorithm to > see if any cost could be reduced. > 10: Make sense. Will fix the wording. > 11: Make sense. Will update the test part. > > *For Walker's comments:* > 1. Stability for HAA is an issue. See my comments for Sophie's feedback 5 > and 6. I think we could use the rack aware assignment for StickyAssignor as > well. For HAA assignments, it's less sticky and we can only shoot for > minimizing the cross rack traffic eventually when everything is stable. > 2. Yeah. This is a good point and we can also turn it on for > StickyAssignor. > > Thanks, > Hao > > > On Tue, May 30, 2023 at 2:28 PM Sophie Blee-Goldman < > ableegold...@gmail.com> wrote: > >> Hey Hao, thanks for the KIP! >> >> 1. There's a typo in the "internal.rack.aware.assignment.strategry" >> config, >> this >> should be internal.rack.aware.assignment.strategy. >> >> 2. >> >> > For O(E^2 * (CU)) complexity, C and U can be viewed as constant. >> Number of >> > edges E is T * N where T is the number of clients and N is the number of >> > Tasks. This is because a task can be assigned to any client so there >> will >> > be an edge between every task and every client. The total complexity >> would >> > be O(T * N) if we want to be more specific. >> >> I feel like I'm missing something here, but if E = T * N and the >> complexity >> is ~O(E^2), doesn't >> this make the total complexity order of O(T^2 * N^2)? >> >> 3. >> >> > Since 3.C.I and 3.C.II have different tradeoffs and work better in >> > different workloads etc, we >> >> could add an internal configuration to choose one of them at runtime. >> > >> Why only an internal configuration? Same goes for >> internal.rack.aware.assignment.standby.strategry (which also has the typo) >> >> 4. >> >> > There are no changes in public interfaces. >> >> I think it would be good to explicitly call out that users can utilize >> this >> new feature by setting the >> ConsumerConfig's CLIENT_RACK_CONFIG, possibly with a brief example >> >> 5. >> >> > The idea is that if we always try to make it overlap as much with >> > HAAssignor’s target >> >> assignment, at least there’s a higher chance that tasks won’t be shuffled >> a >> > lot if the clients >> >> remain the same across rebalances. >> > >> This line definitely gave me some pause -- if there was one major takeaway >> I had after KIP-441, >> one thing that most limited the feature's success, it was our assumption >> that clients are relatively >> stable across rebalances. This was mostly true at limited scale or for >> on-prem setups, but >> unsurprisingly broke down in cloud environments or larger clusters. Not >> only do clients naturally >> fall in and out of the group, autoscaling is becoming more and more of a >> thing. >> >> Lastly, and this is more easily solved but still worth calling out, an >> assignment is only deterministic >> as long as the client.id is persisted.
Re: [DISCUSS] KIP-925: rack aware task assignment in Kafka Streams
Thanks Hao -- I really like Walker's idea to separate the assignment strategy from the rack awareness option. Having two different configs for these makes a lot of sense to me and seems like it will benefit the most users. Given your KIP already has a lot going on with it, I would be happy to write up a quick KIP just for the public assignor config to take that aspect off your hands. We can discuss that separately and keep this thread focused on the rack awareness algorithm. If that sounds good I'll kick off a KIP tonight, then you can just update the "Current Task Assignment Logic" section to mention that either assignor may be plugged in, and the rack awareness can be configured independently. If users are able to plug in the StickyAssignor if they experience problems, this is good enough for me w.r.t my other concern regarding task shuffling On Wed, May 31, 2023 at 12:09 PM Hao Li wrote: > Hi all, > > Thanks for the feedback! I will update the KIP accordingly. > > *For Sophie's comments:* > > 1 and 2. Good catch. Fixed these. > > 3 and 4 Yes. We can make this public config and call out the clientConsumer > config users need to set. > > 5. It's ideal to take the previous assignment in HAAssignor into > consideration when we compute our target assignment, the complications come > with making sure the assignment can eventually converge and we don't do > probing rebalance infinitely. It's not only about storing the previous > assignment or get it somehow. We can actually get the previous assignment > now like we do in StickyAssignor. But the previous assignment will change > in each round of probing rebalance. The proposal which added some weight to > make the rack aware assignment lean towards the original HAA's target > assignment will add benefits of stability in some corner cases in case of > tie in cross rack traffic cost. But it's not sticky. But the bottom line is > it won't be worse than current HAA's stickiness. > > 6. I'm fine with changing the assignor config to public. Actually, I think > we can min-cost algorithm with StickyAssignor as well to mitigate the > problem of 5. So we can have one public config to choose an assignor and > one public config to enable the rack aware assignment. > > *For Bruno's comments:* > > The proposal was to implement all the options and use configs to choose > them during runtime. We can make those configs public as suggested. > 1, 2, 3, 4, 5: agree and will fix those. > 6: subscription protocol is not changed. > 7: yeah. Let me fix the notations. > 8: It meant clients. In the figure, it maps to `c1_1`, `c1_2`, `c1_3` etc. > 9: I'm also ok with just optimizing reliability for standby tasks. Or we > could simply run the "balance reliability over cost" greedy algorithm to > see if any cost could be reduced. > 10: Make sense. Will fix the wording. > 11: Make sense. Will update the test part. > > *For Walker's comments:* > 1. Stability for HAA is an issue. See my comments for Sophie's feedback 5 > and 6. I think we could use the rack aware assignment for StickyAssignor as > well. For HAA assignments, it's less sticky and we can only shoot for > minimizing the cross rack traffic eventually when everything is stable. > 2. Yeah. This is a good point and we can also turn it on for > StickyAssignor. > > Thanks, > Hao > > > On Tue, May 30, 2023 at 2:28 PM Sophie Blee-Goldman < > ableegold...@gmail.com> > wrote: > > > Hey Hao, thanks for the KIP! > > > > 1. There's a typo in the "internal.rack.aware.assignment.strategry" > config, > > this > > should be internal.rack.aware.assignment.strategy. > > > > 2. > > > > > For O(E^2 * (CU)) complexity, C and U can be viewed as constant. > Number > > of > > > edges E is T * N where T is the number of clients and N is the number > of > > > Tasks. This is because a task can be assigned to any client so there > will > > > be an edge between every task and every client. The total complexity > > would > > > be O(T * N) if we want to be more specific. > > > > I feel like I'm missing something here, but if E = T * N and the > complexity > > is ~O(E^2), doesn't > > this make the total complexity order of O(T^2 * N^2)? > > > > 3. > > > > > Since 3.C.I and 3.C.II have different tradeoffs and work better in > > > different workloads etc, we > > > > could add an internal configuration to choose one of them at runtime. > > > > > Why only an internal configuration? Same goes for > > internal.rack.aware.assignment.standby.strategry (which also has the > typo) > > > > 4. > > > > > There are no changes in public interfaces. > > > > I think it would be good to explicitly call out that users can utilize > this > > new feature by setting the > > ConsumerConfig's CLIENT_RACK_CONFIG, possibly with a brief example > > > > 5. > > > > > The idea is that if we always try to make it overlap as much with > > > HAAssignor’s target > > > > assignment, at least there’s a higher chance that tasks won’t be > shuffled a > > > lot if the clients > > > > remain
Re: [DISCUSS] KIP-925: rack aware task assignment in Kafka Streams
Hi all, Thanks for the feedback! I will update the KIP accordingly. *For Sophie's comments:* 1 and 2. Good catch. Fixed these. 3 and 4 Yes. We can make this public config and call out the clientConsumer config users need to set. 5. It's ideal to take the previous assignment in HAAssignor into consideration when we compute our target assignment, the complications come with making sure the assignment can eventually converge and we don't do probing rebalance infinitely. It's not only about storing the previous assignment or get it somehow. We can actually get the previous assignment now like we do in StickyAssignor. But the previous assignment will change in each round of probing rebalance. The proposal which added some weight to make the rack aware assignment lean towards the original HAA's target assignment will add benefits of stability in some corner cases in case of tie in cross rack traffic cost. But it's not sticky. But the bottom line is it won't be worse than current HAA's stickiness. 6. I'm fine with changing the assignor config to public. Actually, I think we can min-cost algorithm with StickyAssignor as well to mitigate the problem of 5. So we can have one public config to choose an assignor and one public config to enable the rack aware assignment. *For Bruno's comments:* The proposal was to implement all the options and use configs to choose them during runtime. We can make those configs public as suggested. 1, 2, 3, 4, 5: agree and will fix those. 6: subscription protocol is not changed. 7: yeah. Let me fix the notations. 8: It meant clients. In the figure, it maps to `c1_1`, `c1_2`, `c1_3` etc. 9: I'm also ok with just optimizing reliability for standby tasks. Or we could simply run the "balance reliability over cost" greedy algorithm to see if any cost could be reduced. 10: Make sense. Will fix the wording. 11: Make sense. Will update the test part. *For Walker's comments:* 1. Stability for HAA is an issue. See my comments for Sophie's feedback 5 and 6. I think we could use the rack aware assignment for StickyAssignor as well. For HAA assignments, it's less sticky and we can only shoot for minimizing the cross rack traffic eventually when everything is stable. 2. Yeah. This is a good point and we can also turn it on for StickyAssignor. Thanks, Hao On Tue, May 30, 2023 at 2:28 PM Sophie Blee-Goldman wrote: > Hey Hao, thanks for the KIP! > > 1. There's a typo in the "internal.rack.aware.assignment.strategry" config, > this > should be internal.rack.aware.assignment.strategy. > > 2. > > > For O(E^2 * (CU)) complexity, C and U can be viewed as constant. Number > of > > edges E is T * N where T is the number of clients and N is the number of > > Tasks. This is because a task can be assigned to any client so there will > > be an edge between every task and every client. The total complexity > would > > be O(T * N) if we want to be more specific. > > I feel like I'm missing something here, but if E = T * N and the complexity > is ~O(E^2), doesn't > this make the total complexity order of O(T^2 * N^2)? > > 3. > > > Since 3.C.I and 3.C.II have different tradeoffs and work better in > > different workloads etc, we > > could add an internal configuration to choose one of them at runtime. > > > Why only an internal configuration? Same goes for > internal.rack.aware.assignment.standby.strategry (which also has the typo) > > 4. > > > There are no changes in public interfaces. > > I think it would be good to explicitly call out that users can utilize this > new feature by setting the > ConsumerConfig's CLIENT_RACK_CONFIG, possibly with a brief example > > 5. > > > The idea is that if we always try to make it overlap as much with > > HAAssignor’s target > > assignment, at least there’s a higher chance that tasks won’t be shuffled a > > lot if the clients > > remain the same across rebalances. > > > This line definitely gave me some pause -- if there was one major takeaway > I had after KIP-441, > one thing that most limited the feature's success, it was our assumption > that clients are relatively > stable across rebalances. This was mostly true at limited scale or for > on-prem setups, but > unsurprisingly broke down in cloud environments or larger clusters. Not > only do clients naturally > fall in and out of the group, autoscaling is becoming more and more of a > thing. > > Lastly, and this is more easily solved but still worth calling out, an > assignment is only deterministic > as long as the client.id is persisted. Currently in Streams, we only write > the process UUID to the > state directory if there is one, ie if at least one persistent stateful > task exists in the topology. This > made sense in the context of KIP-441, which targeted heavily stateful > deployments, but this KIP > presumably intends to target more than just the persistent & stateful > subset of applications. To > make matters even worse, "persistent" is defined in a semantically > inconsistent way throughout >
Re: [DISCUSS] KIP-925: rack aware task assignment in Kafka Streams
Hi Hao, Most of the comments I had on this kip are already mentioned, but I did want to share my two major concerns. 1. Stability. I worry about stability. If we only have the HA assignor work with rack awareness we will have a lot of state movement in many cases. Sophie and Bruno have this concern as well. 2. It seems the rack awareness assignment operation can be run after any assignment algorithm. I would think that maybe we can leave it agnostic if it is using the sicky assignor or the HA assignor and let the users choose the strategy. Maybe just have the rack awareness be off or on, independent of the assignment strategy. Walker On Wed, May 31, 2023 at 7:46 AM Bruno Cadonna wrote: > Hi Hao, > > > Thank you for the KIP! Really interesting! > > In general, I think the KIP is a bit too vague. You explain the main > algorithm and different options. It is not clear to me on what option we > will start voting. One way out of this situation would be to cut the KIP > down to the simplest options and evaluate those. Then, we would have a > starting point from which we can move on. > > > 1. > Mention that the KIP optimizes only the read path and does nothing about > the write path. > > > 2. > "U is 1 and C is at most 3 (A task can have at most 3 topics including > changelog topic?)" > where C is max cost and U is max capacity > > C is not at most 3 to answer the question in the KIP. A task can have > any number of topics it reads from. Some examples: > - a processor API operator with multiple state stores reads from > multiple changelog topics > - a cascade of merge operators would result in a task with multiple > input topics > - a cascade of joins would result in a task with multiple input topics > and multiple changelog topics. > I am pretty sure there are also other examples. > > Assuming cost C is 1 for each topic partition is a simplification. > Traffic for tasks can vary significantly. I saw joins that had 100s of > bytes/s on one side and 10s of MB/s on the other side. I guess the > cross-rack traffic depends on the data rate. Please correct me if I am > wrong. I am fine with simplifying but then we also need to explicitly > state the simplification and its limitation in the KIP to manage > expectations. > > C is just a factor in the complexity but we should be clear about the > simplification we made. How much C influences the actual performance we > do not know and we should evaluate this as part of the implementation of > the KIP. Maybe add this aspect to the performance experiments in the > test plan section. > > > 3. > I second Sophie's question about the complexity being O(T^2 * N^2) > instead of O(T*N). > > > 4. > The improved algorithm in "Min cost with balanced sub-topology" contains > a bunch more edges and the complexity of the algorithm depends on the > square of the number of edges. Can you say something about the trade-off > or even quantify it? How does does the complexity change from O(T^2 * N^2)? > > > 5. > If you propose to implement multiple algorithms, the KIP should add > public configs as Sophie proposed. > > > 6. > Does any of the algorithm change the subscription protocol? Usually we > describe those changes in a KIP. > > > 7. > I have a couple of minor comment about notation: > > 7.1 For the complexity, I think it would be better to either use |T| and > |C| or define new variables like for example N_task = |T| and N_client = > |C| for the formula to be consistent with the mapping function you > define in the previous section. > > 7.2 Using C for the set of clients and the cost is confusing. Maybe use > Cost or $ for cost. > > > 8. > In the "Graph construction" section in the "Min cost with balanced > sub-topology" section, you write > "Create new set of nodes which has same number as clients" > Shouldn't this be number of tasks. > > > 9. > Regarding standby assignment, have you considered to simplify the setup > by defining if rack-aware configs are set, the standby assignment is > optimized for reliability and if they are not set costs are optimized. I > think that would be a good starting point on which we can iterate in > future. > > > 10. > Just a clarification and something that you should corrected in the KIP. > In "Assignment of stateless tasks" you contrast stateless tasks with > active task. However, active tasks can be stateless or stateful. So > "Rack awareness assignment algorithm for active tasks" should actually > be "Rack awareness assignment algorithm for active stateful tasks". > Please use the terms accordingly otherwise, it gets confusing. > > > 11. > In the testing plan, I think it would be useful to also have performance > experiments along other dimension like number of topic partitions a task > reads from, i.e., basically the varying costs per task. > > > Best, > Bruno > > On 30.05.23 23:28, Sophie Blee-Goldman wrote: > > Hey Hao, thanks for the KIP! > > > > 1. There's a typo in the "internal.rack.aware.assignment.strategry" > config, > > this > >
Re: [DISCUSS] KIP-925: rack aware task assignment in Kafka Streams
Hi Hao, Thank you for the KIP! Really interesting! In general, I think the KIP is a bit too vague. You explain the main algorithm and different options. It is not clear to me on what option we will start voting. One way out of this situation would be to cut the KIP down to the simplest options and evaluate those. Then, we would have a starting point from which we can move on. 1. Mention that the KIP optimizes only the read path and does nothing about the write path. 2. "U is 1 and C is at most 3 (A task can have at most 3 topics including changelog topic?)" where C is max cost and U is max capacity C is not at most 3 to answer the question in the KIP. A task can have any number of topics it reads from. Some examples: - a processor API operator with multiple state stores reads from multiple changelog topics - a cascade of merge operators would result in a task with multiple input topics - a cascade of joins would result in a task with multiple input topics and multiple changelog topics. I am pretty sure there are also other examples. Assuming cost C is 1 for each topic partition is a simplification. Traffic for tasks can vary significantly. I saw joins that had 100s of bytes/s on one side and 10s of MB/s on the other side. I guess the cross-rack traffic depends on the data rate. Please correct me if I am wrong. I am fine with simplifying but then we also need to explicitly state the simplification and its limitation in the KIP to manage expectations. C is just a factor in the complexity but we should be clear about the simplification we made. How much C influences the actual performance we do not know and we should evaluate this as part of the implementation of the KIP. Maybe add this aspect to the performance experiments in the test plan section. 3. I second Sophie's question about the complexity being O(T^2 * N^2) instead of O(T*N). 4. The improved algorithm in "Min cost with balanced sub-topology" contains a bunch more edges and the complexity of the algorithm depends on the square of the number of edges. Can you say something about the trade-off or even quantify it? How does does the complexity change from O(T^2 * N^2)? 5. If you propose to implement multiple algorithms, the KIP should add public configs as Sophie proposed. 6. Does any of the algorithm change the subscription protocol? Usually we describe those changes in a KIP. 7. I have a couple of minor comment about notation: 7.1 For the complexity, I think it would be better to either use |T| and |C| or define new variables like for example N_task = |T| and N_client = |C| for the formula to be consistent with the mapping function you define in the previous section. 7.2 Using C for the set of clients and the cost is confusing. Maybe use Cost or $ for cost. 8. In the "Graph construction" section in the "Min cost with balanced sub-topology" section, you write "Create new set of nodes which has same number as clients" Shouldn't this be number of tasks. 9. Regarding standby assignment, have you considered to simplify the setup by defining if rack-aware configs are set, the standby assignment is optimized for reliability and if they are not set costs are optimized. I think that would be a good starting point on which we can iterate in future. 10. Just a clarification and something that you should corrected in the KIP. In "Assignment of stateless tasks" you contrast stateless tasks with active task. However, active tasks can be stateless or stateful. So "Rack awareness assignment algorithm for active tasks" should actually be "Rack awareness assignment algorithm for active stateful tasks". Please use the terms accordingly otherwise, it gets confusing. 11. In the testing plan, I think it would be useful to also have performance experiments along other dimension like number of topic partitions a task reads from, i.e., basically the varying costs per task. Best, Bruno On 30.05.23 23:28, Sophie Blee-Goldman wrote: Hey Hao, thanks for the KIP! 1. There's a typo in the "internal.rack.aware.assignment.strategry" config, this should be internal.rack.aware.assignment.strategy. 2. For O(E^2 * (CU)) complexity, C and U can be viewed as constant. Number of edges E is T * N where T is the number of clients and N is the number of Tasks. This is because a task can be assigned to any client so there will be an edge between every task and every client. The total complexity would be O(T * N) if we want to be more specific. I feel like I'm missing something here, but if E = T * N and the complexity is ~O(E^2), doesn't this make the total complexity order of O(T^2 * N^2)? 3. Since 3.C.I and 3.C.II have different tradeoffs and work better in different workloads etc, we could add an internal configuration to choose one of them at runtime. Why only an internal configuration? Same goes for internal.rack.aware.assignment.standby.strategry (which also has the typo) 4.
Re: [DISCUSS] KIP-925: rack aware task assignment in Kafka Streams
Hey Hao, thanks for the KIP! 1. There's a typo in the "internal.rack.aware.assignment.strategry" config, this should be internal.rack.aware.assignment.strategy. 2. > For O(E^2 * (CU)) complexity, C and U can be viewed as constant. Number of > edges E is T * N where T is the number of clients and N is the number of > Tasks. This is because a task can be assigned to any client so there will > be an edge between every task and every client. The total complexity would > be O(T * N) if we want to be more specific. I feel like I'm missing something here, but if E = T * N and the complexity is ~O(E^2), doesn't this make the total complexity order of O(T^2 * N^2)? 3. > Since 3.C.I and 3.C.II have different tradeoffs and work better in > different workloads etc, we could add an internal configuration to choose one of them at runtime. > Why only an internal configuration? Same goes for internal.rack.aware.assignment.standby.strategry (which also has the typo) 4. > There are no changes in public interfaces. I think it would be good to explicitly call out that users can utilize this new feature by setting the ConsumerConfig's CLIENT_RACK_CONFIG, possibly with a brief example 5. > The idea is that if we always try to make it overlap as much with > HAAssignor’s target assignment, at least there’s a higher chance that tasks won’t be shuffled a > lot if the clients remain the same across rebalances. > This line definitely gave me some pause -- if there was one major takeaway I had after KIP-441, one thing that most limited the feature's success, it was our assumption that clients are relatively stable across rebalances. This was mostly true at limited scale or for on-prem setups, but unsurprisingly broke down in cloud environments or larger clusters. Not only do clients naturally fall in and out of the group, autoscaling is becoming more and more of a thing. Lastly, and this is more easily solved but still worth calling out, an assignment is only deterministic as long as the client.id is persisted. Currently in Streams, we only write the process UUID to the state directory if there is one, ie if at least one persistent stateful task exists in the topology. This made sense in the context of KIP-441, which targeted heavily stateful deployments, but this KIP presumably intends to target more than just the persistent & stateful subset of applications. To make matters even worse, "persistent" is defined in a semantically inconsistent way throughout Streams. All this is to say, it may sound more complicated to remember the previous assignment, but (a) imo it only introduces a lot more complexity and shaky assumptions to continue down this path, and (b) we actually already do persist some amount of state, like the process UUID, and (c) it seems like this is the perfect opportunity to finally rid ourselves of the determinism constraint which has frankly caused more trouble and time lost in sum than it would have taken us to just write the HighAvailabilityTaskAssignor to consider the previous assignment from the start in KIP-441 6. > StickyTaskAssignor users who would like to use rack aware assignment > should upgrade their Kafka Streams version to the version in which HighAvailabilityTaskAssignor > and rack awareness assignment are available. Building off of the above, the HAAssignor hasn't worked out perfectly for everybody up until now, given that we are only adding complexity to it now, on the flipside I would hesitate to try and force everyone to use it if they want to upgrade. We added a "secret" backdoor internal config to allow users to set the task assignor back in KIP-441 for this reason. WDYT about bumping this to a public config on the side in this KIP? On Tue, May 23, 2023 at 11:46 AM Hao Li wrote: > Thanks John! Yeah. The ConvergenceTest looks very helpful. I will add it to > the test plan. I will also add tests to verify the new optimizer will > produce a balanced assignment which has no worse cross AZ cost than the > existing assignor. > > Hao > > On Mon, May 22, 2023 at 3:39 PM John Roesler wrote: > > > Hi Hao, > > > > Thanks for the KIP! > > > > Overall, I think this is a great idea. I always wanted to circle back > > after the Smooth Scaling KIP to put a proper optimization algorithm into > > place. I think this has the promise to really improve the quality of the > > balanced assignments we produce. > > > > Thanks for providing the details about the MaxCut/MinFlow algorithm. It > > seems like a good choice for me, assuming we choose the right scaling > > factors for the weights we add to the graph. Unfortunately, I don't think > > that there's a good way to see how easy or hard this is going to be until > > we actually implement it and test it. > > > > That leads to the only real piece of feedback I had on the KIP, which is > > the testing portion. You mentioned system/integration/unit tests, but > > there's not too much information about what those tests will do. I'd like > > to
Re: [DISCUSS] KIP-925: rack aware task assignment in Kafka Streams
Thanks John! Yeah. The ConvergenceTest looks very helpful. I will add it to the test plan. I will also add tests to verify the new optimizer will produce a balanced assignment which has no worse cross AZ cost than the existing assignor. Hao On Mon, May 22, 2023 at 3:39 PM John Roesler wrote: > Hi Hao, > > Thanks for the KIP! > > Overall, I think this is a great idea. I always wanted to circle back > after the Smooth Scaling KIP to put a proper optimization algorithm into > place. I think this has the promise to really improve the quality of the > balanced assignments we produce. > > Thanks for providing the details about the MaxCut/MinFlow algorithm. It > seems like a good choice for me, assuming we choose the right scaling > factors for the weights we add to the graph. Unfortunately, I don't think > that there's a good way to see how easy or hard this is going to be until > we actually implement it and test it. > > That leads to the only real piece of feedback I had on the KIP, which is > the testing portion. You mentioned system/integration/unit tests, but > there's not too much information about what those tests will do. I'd like > to suggest that we invest in more simulation testing specifically, similar > to what we did in > https://github.com/apache/kafka/blob/trunk/streams/src/test/java/org/apache/kafka/streams/processor/internals/assignment/TaskAssignorConvergenceTest.java > . > > In fact, it seems like we _could_ write the simulation up front, and then > implement the algorithm in a dummy way and just see whether it passes the > simulations or not, before actually integrating it with Kafka Streams. > > Basically, I'd be +1 on this KIP today, but I'd feel confident about it if > we had a little more detail regarding how we are going to verify that the > new optimizer is actually going to produce more optimal plans than the > existing assigner we have today. > > Thanks again! > -John > > On 2023/05/22 16:49:22 Hao Li wrote: > > Hi Colt, > > > > Thanks for the comments. > > > > > and I struggle to see how the algorithm isn't at least O(N) where N is > > the number of Tasks...? > > > > For O(E^2 * (CU)) complexity, C and U can be viewed as constant. Number > of > > edges E is T * N where T is the number of clients and N is the number of > > Tasks. This is because a task can be assigned to any client so there will > > be an edge between every task and every client. The total complexity > would > > be O(T * N) if we want to be more specific. > > > > > But if the leaders for each partition are spread across multiple zones, > > how will you handle that? > > > > This is what the min-cost flow solution is trying to solve? i.e. Find an > > assignment of tasks to clients where across AZ traffic can be minimized. > > But there are some constraints to the solution and one of them is we need > > to balance task assignment first ( > > > https://cwiki.apache.org/confluence/display/KAFKA/KIP-925%3A+Rack+aware+task+assignment+in+Kafka+Streams#KIP925:RackawaretaskassignmentinKafkaStreams-Designforrackawareassignment > ). > > So in your example of three tasks' partitions being in the same AZ of a > > client, if there are other clients, we still want to balance the tasks to > > other clients even if putting all tasks to a single client can result in > 0 > > cross AZ traffic. In > > > https://cwiki.apache.org/confluence/display/KAFKA/KIP-925%3A+Rack+aware+task+assignment+in+Kafka+Streams#KIP925:RackawaretaskassignmentinKafkaStreams-Algorithm > > section, the algorithm will try to find a min-cost solution based on > > balanced assignment instead of pure min-cost. > > > > Thanks, > > Hao > > > > On Tue, May 9, 2023 at 5:55 PM Colt McNealy wrote: > > > > > Hello Hao, > > > > > > First of all, THANK YOU for putting this together. I had been hoping > > > someone might bring something like this forward. A few comments: > > > > > > **1: Runtime Complexity > > > > Klein’s cycle canceling algorithm can solve the min-cost flow > problem in > > > O(E^2CU) time where C is max cost and U is max capacity. In our > particular > > > case, C is 1 and U is at most 3 (A task can have at most 3 topics > including > > > changelog topic?). So the algorithm runs in O(E^2) time for our case. > > > > > > A Task can have multiple input topics, and also multiple state stores, > and > > > multiple output topics. The most common case is three topics as you > > > described, but this is not necessarily guaranteed. Also, math is one > of my > > > weak points, but to me O(E^2) is equivalent to O(1), and I struggle to > see > > > how the algorithm isn't at least O(N) where N is the number of > Tasks...? > > > > > > **2: Broker-Side Partition Assignments > > > Consider the case with just three topics in a Task (one input, one > output, > > > one changelog). If all three partition leaders are in the same Rack (or > > > better yet, the same broker), then we could get massive savings by > > > assigning the Task to that Rack/availability zone. But if
Re: [DISCUSS] KIP-925: rack aware task assignment in Kafka Streams
Hi Hao, Thanks for the KIP! Overall, I think this is a great idea. I always wanted to circle back after the Smooth Scaling KIP to put a proper optimization algorithm into place. I think this has the promise to really improve the quality of the balanced assignments we produce. Thanks for providing the details about the MaxCut/MinFlow algorithm. It seems like a good choice for me, assuming we choose the right scaling factors for the weights we add to the graph. Unfortunately, I don't think that there's a good way to see how easy or hard this is going to be until we actually implement it and test it. That leads to the only real piece of feedback I had on the KIP, which is the testing portion. You mentioned system/integration/unit tests, but there's not too much information about what those tests will do. I'd like to suggest that we invest in more simulation testing specifically, similar to what we did in https://github.com/apache/kafka/blob/trunk/streams/src/test/java/org/apache/kafka/streams/processor/internals/assignment/TaskAssignorConvergenceTest.java . In fact, it seems like we _could_ write the simulation up front, and then implement the algorithm in a dummy way and just see whether it passes the simulations or not, before actually integrating it with Kafka Streams. Basically, I'd be +1 on this KIP today, but I'd feel confident about it if we had a little more detail regarding how we are going to verify that the new optimizer is actually going to produce more optimal plans than the existing assigner we have today. Thanks again! -John On 2023/05/22 16:49:22 Hao Li wrote: > Hi Colt, > > Thanks for the comments. > > > and I struggle to see how the algorithm isn't at least O(N) where N is > the number of Tasks...? > > For O(E^2 * (CU)) complexity, C and U can be viewed as constant. Number of > edges E is T * N where T is the number of clients and N is the number of > Tasks. This is because a task can be assigned to any client so there will > be an edge between every task and every client. The total complexity would > be O(T * N) if we want to be more specific. > > > But if the leaders for each partition are spread across multiple zones, > how will you handle that? > > This is what the min-cost flow solution is trying to solve? i.e. Find an > assignment of tasks to clients where across AZ traffic can be minimized. > But there are some constraints to the solution and one of them is we need > to balance task assignment first ( > https://cwiki.apache.org/confluence/display/KAFKA/KIP-925%3A+Rack+aware+task+assignment+in+Kafka+Streams#KIP925:RackawaretaskassignmentinKafkaStreams-Designforrackawareassignment). > So in your example of three tasks' partitions being in the same AZ of a > client, if there are other clients, we still want to balance the tasks to > other clients even if putting all tasks to a single client can result in 0 > cross AZ traffic. In > https://cwiki.apache.org/confluence/display/KAFKA/KIP-925%3A+Rack+aware+task+assignment+in+Kafka+Streams#KIP925:RackawaretaskassignmentinKafkaStreams-Algorithm > section, the algorithm will try to find a min-cost solution based on > balanced assignment instead of pure min-cost. > > Thanks, > Hao > > On Tue, May 9, 2023 at 5:55 PM Colt McNealy wrote: > > > Hello Hao, > > > > First of all, THANK YOU for putting this together. I had been hoping > > someone might bring something like this forward. A few comments: > > > > **1: Runtime Complexity > > > Klein’s cycle canceling algorithm can solve the min-cost flow problem in > > O(E^2CU) time where C is max cost and U is max capacity. In our particular > > case, C is 1 and U is at most 3 (A task can have at most 3 topics including > > changelog topic?). So the algorithm runs in O(E^2) time for our case. > > > > A Task can have multiple input topics, and also multiple state stores, and > > multiple output topics. The most common case is three topics as you > > described, but this is not necessarily guaranteed. Also, math is one of my > > weak points, but to me O(E^2) is equivalent to O(1), and I struggle to see > > how the algorithm isn't at least O(N) where N is the number of Tasks...? > > > > **2: Broker-Side Partition Assignments > > Consider the case with just three topics in a Task (one input, one output, > > one changelog). If all three partition leaders are in the same Rack (or > > better yet, the same broker), then we could get massive savings by > > assigning the Task to that Rack/availability zone. But if the leaders for > > each partition are spread across multiple zones, how will you handle that? > > Is that outside the scope of this KIP, or is it worth introducing a > > kafka-streams-generate-rebalance-proposal.sh tool? > > > > Colt McNealy > > *Founder, LittleHorse.io* > > > > > > On Tue, May 9, 2023 at 4:03 PM Hao Li wrote: > > > > > Hi all, > > > > > > I have submitted KIP-925 to add rack awareness logic in task assignment > > in > > > Kafka Streams and would like to
Re: [DISCUSS] KIP-925: rack aware task assignment in Kafka Streams
Hi Colt, Thanks for the comments. > and I struggle to see how the algorithm isn't at least O(N) where N is the number of Tasks...? For O(E^2 * (CU)) complexity, C and U can be viewed as constant. Number of edges E is T * N where T is the number of clients and N is the number of Tasks. This is because a task can be assigned to any client so there will be an edge between every task and every client. The total complexity would be O(T * N) if we want to be more specific. > But if the leaders for each partition are spread across multiple zones, how will you handle that? This is what the min-cost flow solution is trying to solve? i.e. Find an assignment of tasks to clients where across AZ traffic can be minimized. But there are some constraints to the solution and one of them is we need to balance task assignment first ( https://cwiki.apache.org/confluence/display/KAFKA/KIP-925%3A+Rack+aware+task+assignment+in+Kafka+Streams#KIP925:RackawaretaskassignmentinKafkaStreams-Designforrackawareassignment). So in your example of three tasks' partitions being in the same AZ of a client, if there are other clients, we still want to balance the tasks to other clients even if putting all tasks to a single client can result in 0 cross AZ traffic. In https://cwiki.apache.org/confluence/display/KAFKA/KIP-925%3A+Rack+aware+task+assignment+in+Kafka+Streams#KIP925:RackawaretaskassignmentinKafkaStreams-Algorithm section, the algorithm will try to find a min-cost solution based on balanced assignment instead of pure min-cost. Thanks, Hao On Tue, May 9, 2023 at 5:55 PM Colt McNealy wrote: > Hello Hao, > > First of all, THANK YOU for putting this together. I had been hoping > someone might bring something like this forward. A few comments: > > **1: Runtime Complexity > > Klein’s cycle canceling algorithm can solve the min-cost flow problem in > O(E^2CU) time where C is max cost and U is max capacity. In our particular > case, C is 1 and U is at most 3 (A task can have at most 3 topics including > changelog topic?). So the algorithm runs in O(E^2) time for our case. > > A Task can have multiple input topics, and also multiple state stores, and > multiple output topics. The most common case is three topics as you > described, but this is not necessarily guaranteed. Also, math is one of my > weak points, but to me O(E^2) is equivalent to O(1), and I struggle to see > how the algorithm isn't at least O(N) where N is the number of Tasks...? > > **2: Broker-Side Partition Assignments > Consider the case with just three topics in a Task (one input, one output, > one changelog). If all three partition leaders are in the same Rack (or > better yet, the same broker), then we could get massive savings by > assigning the Task to that Rack/availability zone. But if the leaders for > each partition are spread across multiple zones, how will you handle that? > Is that outside the scope of this KIP, or is it worth introducing a > kafka-streams-generate-rebalance-proposal.sh tool? > > Colt McNealy > *Founder, LittleHorse.io* > > > On Tue, May 9, 2023 at 4:03 PM Hao Li wrote: > > > Hi all, > > > > I have submitted KIP-925 to add rack awareness logic in task assignment > in > > Kafka Streams and would like to start a discussion: > > > > > > > https://cwiki.apache.org/confluence/display/KAFKA/KIP-925%3A+Rack+aware+task+assignment+in+Kafka+Streams > > > > -- > > Thanks, > > Hao > > > -- Thanks, Hao
Re: [DISCUSS] KIP-925: rack aware task assignment in Kafka Streams
Hello Hao, First of all, THANK YOU for putting this together. I had been hoping someone might bring something like this forward. A few comments: **1: Runtime Complexity > Klein’s cycle canceling algorithm can solve the min-cost flow problem in O(E^2CU) time where C is max cost and U is max capacity. In our particular case, C is 1 and U is at most 3 (A task can have at most 3 topics including changelog topic?). So the algorithm runs in O(E^2) time for our case. A Task can have multiple input topics, and also multiple state stores, and multiple output topics. The most common case is three topics as you described, but this is not necessarily guaranteed. Also, math is one of my weak points, but to me O(E^2) is equivalent to O(1), and I struggle to see how the algorithm isn't at least O(N) where N is the number of Tasks...? **2: Broker-Side Partition Assignments Consider the case with just three topics in a Task (one input, one output, one changelog). If all three partition leaders are in the same Rack (or better yet, the same broker), then we could get massive savings by assigning the Task to that Rack/availability zone. But if the leaders for each partition are spread across multiple zones, how will you handle that? Is that outside the scope of this KIP, or is it worth introducing a kafka-streams-generate-rebalance-proposal.sh tool? Colt McNealy *Founder, LittleHorse.io* On Tue, May 9, 2023 at 4:03 PM Hao Li wrote: > Hi all, > > I have submitted KIP-925 to add rack awareness logic in task assignment in > Kafka Streams and would like to start a discussion: > > > https://cwiki.apache.org/confluence/display/KAFKA/KIP-925%3A+Rack+aware+task+assignment+in+Kafka+Streams > > -- > Thanks, > Hao >
[DISCUSS] KIP-925: rack aware task assignment in Kafka Streams
Hi all, I have submitted KIP-925 to add rack awareness logic in task assignment in Kafka Streams and would like to start a discussion: https://cwiki.apache.org/confluence/display/KAFKA/KIP-925%3A+Rack+aware+task+assignment+in+Kafka+Streams -- Thanks, Hao