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- Which kind of message queue are you using? For example, RabbitMQ allows for clustering. Is that similar to what you need?Greg Burghardt– Greg Burghardt2024-07-13 01:16:17 +00:00Commented Jul 13, 2024 at 1:16
- And by "implementing a message queue" do you mean you are choosing from an existing solution, or are you literally writing the code which will serve as a message queue?Greg Burghardt– Greg Burghardt2024-07-13 01:18:43 +00:00Commented Jul 13, 2024 at 1:18
- In Kafka, changing the number of partitions only affects future messages. Existing messages remain in their partition and aren't moved around. However, brokers (nodes) in a cluster can fetch data from each other. So a client only has to connect to any node in the cluster, not to the node that happens to store the data. Perhaps you could implement a similar mechanism to internally route message reads to the correct node. But Kafka also makes some decisions (messages are immutable, clients pull messages) that make this feasible.amon– amon2024-07-13 04:29:08 +00:00Commented Jul 13, 2024 at 4:29
- 2I am implementing my own queue from scratch, with the semantics of SQS.poundifdef– poundifdef2024-07-13 14:28:23 +00:00Commented Jul 13, 2024 at 14:28
- 1If this is a cloud-first design then storage will be virtualized anyway. You may be able to share storage, or reassign volumes to another compute node with little or no downtime. Actually moving data between nodes would make scaling down more difficult. However, your main problem isn't storing/moving data, but designing a distributed system. Your problems are shared with other databases that support sharding and/or replicas. Solutions will depend on your CAP priorities/ desired consistency model. Aside from "B doesn't have the data yet", also consider "B has crashed/frozen".amon– amon2024-07-13 19:50:03 +00:00Commented Jul 13, 2024 at 19:50
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