OPTION C or OPTION A? Which one are you referring to?
Both have separate DCs to keep the workload separate. - OPTION A) - Node DC RACK AZ 1 read ONE us-east-1a 2 read ONE us-east-1a - 3 read ONE us-east-1a - 4 write TWO us-east-1b 5 write TWO us-east-1b - 6 write TWO us-east-1b Here we have 2 DC read and write One Rack per DC One Availability Zone per DC Thanks, Sergio On Wed, Oct 23, 2019, 1:11 PM Jon Haddad <j...@jonhaddad.com> wrote: > Personally, I wouldn't ever do this. I recommend separate DCs if you want > to keep workloads separate. > > On Wed, Oct 23, 2019 at 4:06 PM Sergio <lapostadiser...@gmail.com> wrote: > >> I forgot to comment for >> >> OPTION C) >> 1. Node DC RACK AZ 1 read ONE us-east-1a 2 read ONE us-east-1b >> 2. 3 read ONE us-east-1c >> 3. 4 write TWO us-east-1a 5 write TWO us-east-1b >> 4. 6 write TWO us-east-1c I would expect that I need to decrease the >> Consistency Level in the reads if one of the AZ goes down. Please consider >> the below one as the real OPTION A. The previous one looks to be wrong >> because the same rack is assigned to 2 different DC. >> 5. OPTION A) >> 6. Node DC RACK AZ 1 read ONE us-east-1a 2 read ONE us-east-1a >> 7. 3 read ONE us-east-1a >> 8. 4 write TWO us-east-1b 5 write TWO us-east-1b >> 9. 6 write TWO us-east-1b >> >> >> >> Thanks, >> >> Sergio >> >> Il giorno mer 23 ott 2019 alle ore 12:33 Sergio < >> lapostadiser...@gmail.com> ha scritto: >> >>> Hi Reid, >>> >>> Thank you very much for clearing these concepts for me. >>> https://community.datastax.com/comments/1133/view.html I posted this >>> question on the datastax forum regarding our cluster that it is unbalanced >>> and the reply was related that the *number of racks should be a >>> multiplier of the replication factor *in order to be balanced or 1. I >>> thought then if I have 3 availability zones I should have 3 racks for each >>> datacenter and not 2 (us-east-1b, us-east-1a) as I have right now or in the >>> easiest way, I should have a rack for each datacenter. >>> >>> >>> >>> 1. Datacenter: live >>> ================ >>> Status=Up/Down >>> |/ State=Normal/Leaving/Joining/Moving >>> -- Address Load Tokens Owns Host ID >>> Rack >>> UN 10.1.20.49 289.75 GiB 256 ? >>> be5a0193-56e7-4d42-8cc8-5d2141ab4872 us-east-1a >>> UN 10.1.30.112 103.03 GiB 256 ? >>> e5108a8e-cc2f-4914-a86e-fccf770e3f0f us-east-1b >>> UN 10.1.19.163 129.61 GiB 256 ? >>> 3c2efdda-8dd4-4f08-b991-9aff062a5388 us-east-1a >>> UN 10.1.26.181 145.28 GiB 256 ? >>> 0a8f07ba-a129-42b0-b73a-df649bd076ef us-east-1b >>> UN 10.1.17.213 149.04 GiB 256 ? >>> 71563e86-b2ae-4d2c-91c5-49aa08386f67 us-east-1a >>> DN 10.1.19.198 52.41 GiB 256 ? >>> 613b43c0-0688-4b86-994c-dc772b6fb8d2 us-east-1b >>> UN 10.1.31.60 195.17 GiB 256 ? >>> 3647fcca-688a-4851-ab15-df36819910f4 us-east-1b >>> UN 10.1.25.206 100.67 GiB 256 ? >>> f43532ad-7d2e-4480-a9ce-2529b47f823d us-east-1b >>> So each rack label right now matches the availability zone and we >>> have 3 Datacenters and 2 Availability Zone with 2 racks per DC but the >>> above is clearly unbalanced >>> If I have a keyspace with a replication factor = 3 and I want to >>> minimize the number of nodes to scale up and down the cluster and keep it >>> balanced should I consider an approach like OPTION A) >>> 2. Node DC RACK AZ 1 read ONE us-east-1a 2 read ONE us-east-1a >>> 3. 3 read ONE us-east-1a >>> 4. 4 write ONE us-east-1b 5 write ONE us-east-1b >>> 5. 6 write ONE us-east-1b >>> 6. OPTION B) >>> 7. Node DC RACK AZ 1 read ONE us-east-1a 2 read ONE us-east-1a >>> 8. 3 read ONE us-east-1a >>> 9. 4 write TWO us-east-1b 5 write TWO us-east-1b >>> 10. 6 write TWO us-east-1b >>> 11. *7 read ONE us-east-1c 8 write TWO us-east-1c* >>> 12. *9 read ONE us-east-1c* Option B looks to be unbalanced and I >>> would exclude it OPTION C) >>> 13. Node DC RACK AZ 1 read ONE us-east-1a 2 read ONE us-east-1b >>> 14. 3 read ONE us-east-1c >>> 15. 4 write TWO us-east-1a 5 write TWO us-east-1b >>> 16. 6 write TWO us-east-1c >>> 17. >>> >>> >>> so I am thinking of A if I have the restriction of 2 AZ but I guess >>> that option C would be the best. If I have to add another DC for reads >>> because we want to assign a new DC for each new microservice it would >>> look >>> like: >>> OPTION EXTRA DC For Reads >>> 1. Node DC RACK AZ 1 read ONE us-east-1a 2 read ONE us-east-1b >>> 2. 3 read ONE us-east-1c >>> 3. 4 write TWO us-east-1a 5 write TWO us-east-1b >>> 4. 6 write TWO us-east-1c 7 extra-read THREE us-east-1a >>> 5. 8 extra-read THREE us-east-1b >>> 6. >>> 7. >>> >>> >>> 1. 9 extra-read THREE us-east-1c >>> 2. >>> The DC for *write* will replicate the data in the other datacenters. >>> My scope is to keep the *read* machines dedicated to serve reads and >>> *write* machines to serve writes. Cassandra will handle the >>> replication for me. Is there any other option that is I missing or wrong >>> assumption? I am thinking that I will write a blog post about all my >>> learnings so far, thank you very much for the replies Best, Sergio >>> >>> >>> Il giorno mer 23 ott 2019 alle ore 10:57 Reid Pinchback < >>> rpinchb...@tripadvisor.com> ha scritto: >>> >>>> No, that’s not correct. The point of racks is to help you distribute >>>> the replicas, not further-replicate the replicas. Data centers are what do >>>> the latter. So for example, if you wanted to be able to ensure that you >>>> always had quorum if an AZ went down, then you could have two DCs where one >>>> was in each AZ, and use one rack in each DC. In your situation I think I’d >>>> be more tempted to consider that. Then if an AZ went away, you could fail >>>> over your traffic to the remaining DC and still be perfectly fine. >>>> >>>> >>>> >>>> For background on replicas vs racks, I believe the information you want >>>> is under the heading ‘NetworkTopologyStrategy’ at: >>>> >>>> http://cassandra.apache.org/doc/latest/architecture/dynamo.html >>>> >>>> >>>> >>>> That should help you better understand how replicas distribute. >>>> >>>> >>>> >>>> As mentioned before, while you can choose to do the reads in one DC, >>>> except for concerns about contention related to network traffic and >>>> connection handling, you can’t isolate reads from writes. You can _ >>>> *mostly*_ insulate the write DC from the activity within the read DC, >>>> and even that isn’t an absolute because of repairs. However, your mileage >>>> may vary, so do what makes sense for your usage pattern. >>>> >>>> >>>> >>>> R >>>> >>>> >>>> >>>> *From: *Sergio <lapostadiser...@gmail.com> >>>> *Reply-To: *"user@cassandra.apache.org" <user@cassandra.apache.org> >>>> *Date: *Wednesday, October 23, 2019 at 12:50 PM >>>> *To: *"user@cassandra.apache.org" <user@cassandra.apache.org> >>>> *Subject: *Re: Cassandra Rack - Datacenter Load Balancing relations >>>> >>>> >>>> >>>> *Message from External Sender* >>>> >>>> Hi Reid, >>>> >>>> Thanks for your reply. I really appreciate your explanation. >>>> >>>> We are in AWS and we are using right now 2 Availability Zone and not 3. >>>> We found our cluster really unbalanced because the keyspace has a >>>> replication factor = 3 and the number of racks is 2 with 2 datacenters. >>>> We want the writes spread across all the nodes but we wanted the reads >>>> isolated from the writes to keep the load on that node low and to be able >>>> to identify problems in the consumers (reads) or producers (writes) >>>> applications. >>>> It looks like that each rack contains an entire copy of the data so >>>> this would lead to replicate for each rack and then for each node the >>>> information. If I am correct if we have a keyspace with 100GB and >>>> Replication Factor = 3 and RACKS = 3 => 100 * 3 * 3 = 900GB >>>> If I had only one rack across 2 or even 3 availability zone I would >>>> save in space and I would have 300GB only. Please correct me if I am wrong. >>>> >>>> Best, >>>> >>>> Sergio >>>> >>>> >>>> >>>> Il giorno mer 23 ott 2019 alle ore 09:21 Reid Pinchback < >>>> rpinchb...@tripadvisor.com> ha scritto: >>>> >>>> Datacenters and racks are different concepts. While they don't have to >>>> be associated with their historical meanings, the historical meanings >>>> probably provide a helpful model for understanding what you want from them. >>>> >>>> When companies own their own physical servers and have them housed >>>> somewhere, the questions arise on where you want to locate any particular >>>> server. It's a balancing act on things like network speed of related >>>> servers being able to talk to each other, versus fault-tolerance of having >>>> many servers not all exposed to the same risks. >>>> >>>> "Same rack" in that physical world tended to mean something like "all >>>> behind the same network switch and all sharing the same power bus". The >>>> morning after an electrical glitch fries a power bus and thus everything in >>>> that rack, you realize you wished you didn't have so many of the same type >>>> of server together. Well, they were servers. Now they are door stops. >>>> Badness and sadness. >>>> >>>> That's kind of the mindset to have in mind with racks in Cassandra. >>>> It's an artifact for you to separate servers into pools so that the >>>> disparate pools have hopefully somewhat independent infrastructure risks. >>>> However, all those servers are still doing the same kind of work, are the >>>> same version, etc. >>>> >>>> Datacenters are amalgams of those racks, and how similar or different >>>> they are from each other depends on what you want to do with them. What is >>>> true is that if you have N datacenters, each one of them must have enough >>>> disk storage to house all the data. The actual physical footprint of that >>>> data in each DC depends on the replication factors in play. >>>> >>>> Note that you sorta can't have "one datacenter for writes" because the >>>> writes will replicate across the data centers. You could definitely choose >>>> to have only one that takes read queries, but best to think of writing as >>>> being universal. One scenario you can have is where the DC not taking live >>>> traffic read queries is the one you use for maintenance or performance >>>> testing or version upgrades. >>>> >>>> One rack makes your life easier if you don't have a reason for multiple >>>> racks. It depends on the environment you deploy into and your fault >>>> tolerance goals. If you were in AWS and wanting to spread risk across >>>> availability zones, then you would likely have as many racks as AZs you >>>> choose to be in, because that's really the point of using multiple AZs. >>>> >>>> R >>>> >>>> >>>> On 10/23/19, 4:06 AM, "Sergio Bilello" <lapostadiser...@gmail.com> >>>> wrote: >>>> >>>> Message from External Sender >>>> >>>> Hello guys! >>>> >>>> I was reading about >>>> https://urldefense.proofpoint.com/v2/url?u=https-3A__cassandra.apache.org_doc_latest_architecture_dynamo.html-23networktopologystrategy&d=DwIBaQ&c=9Hv6XPedRSA-5PSECC38X80c1h60_XWA4z1k_R1pROA&r=OIgB3poYhzp3_A7WgD7iBCnsJaYmspOa2okNpf6uqWc&m=xmgs1uQTlmvCtIoGJKHbByZZ6aDFzS5hDQzChDPCfFA&s=9ZDWAK6pstkCQfdbwLNsB-ZGsK64RwXSXfAkOWtmkq4&e= >>>> >>>> I would like to understand a concept related to the node load >>>> balancing. >>>> >>>> I know that Jon recommends Vnodes = 4 but right now I found a >>>> cluster with vnodes = 256 replication factor = 3 and 2 racks. This is >>>> unbalanced because the racks are not a multiplier of the replication >>>> factor. >>>> >>>> However, my plan is to move all the nodes in a single rack to >>>> eventually scale up and down the node in the cluster once at the time. >>>> >>>> If I had 3 racks and I would like to keep the things balanced I >>>> should scale up 3 nodes at the time one for each rack. >>>> >>>> If I would have 3 racks, should I have also 3 different datacenters >>>> so one datacenter for each rack? >>>> >>>> Can I have 2 datacenters and 3 racks? If this is possible one >>>> datacenter would have more nodes than the others? Could it be a problem? >>>> >>>> I am thinking to split my cluster in one datacenter for reads and >>>> one for writes and keep all the nodes in the same rack so I can scale up >>>> once node at the time. >>>> >>>> >>>> >>>> Please correct me if I am wrong >>>> >>>> >>>> >>>> Thanks, >>>> >>>> >>>> >>>> Sergio >>>> >>>> >>>> >>>> >>>> --------------------------------------------------------------------- >>>> >>>> To unsubscribe, e-mail: user-unsubscr...@cassandra.apache.org >>>> >>>> For additional commands, e-mail: user-h...@cassandra.apache.org >>>> >>>> >>>> >>>> >>>>
