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Dual channel replication (valkey-io#60)
In this PR we introduce the main benefit of dual channel replication by continuously steaming the COB (client output buffers) in parallel to the RDB and thus keeping the primary's side COB small AND accelerating the overall sync process. By streaming the replication data to the replica during the full sync, we reduce 1. Memory load from the primary's node. 2. CPU load from the primary's main process. [Latest performance tests](#data) ## Motivation * Reduce primary memory load. We do that by moving the COB tracking to the replica side. This also decrease the chance for COB overruns. Note that primary's input buffer limits at the replica side are less restricted then primary's COB as the replica plays less critical part in the replication group. While increasing the primary’s COB may end up with primary reaching swap and clients suffering, at replica side we’re more at ease with it. Larger COB means better chance to sync successfully. * Reduce primary main process CPU load. By opening a new, dedicated connection for the RDB transfer, child processes can have direct access to the new connection. Due to TLS connection restrictions, this was not possible using one main connection. We eliminate the need for the child process to use the primary's child-proc -> main-proc pipeline, thus freeing up the main process to process clients queries. ## Dual Channel Replication high level interface design - Dual channel replication begins when the replica sends a `REPLCONF CAPA DUALCHANNEL` to the primary during initial handshake. This is used to state that the replica is capable of dual channel sync and that this is the replica's main channel, which is not used for snapshot transfer. - When replica lacks sufficient data for PSYNC, the primary will send `-FULLSYNCNEEDED` response instead of RDB data. As a next step, the replica creates a new connection (rdb-channel) and configures it against the primary with the appropriate capabilities and requirements. The replica then requests a sync using the RDB channel. - Prior to forking, the primary sends the replica the snapshot's end repl-offset, and attaches the replica to the replication backlog to keep repl data until the replica requests psync. The replica uses the main channel to request a PSYNC starting at the snapshot end offset. - The primary main threads sends incremental changes via the main channel, while the bgsave process sends the RDB directly to the replica via the rdb-channel. As for the replica, the incremental changes are stored on a local buffer, while the RDB is loaded into memory. - Once the replica completes loading the rdb, it drops the rdb-connection and streams the accumulated incremental changes into memory. Repl steady state continues normally. ## New replica state machine ![image](https://github.com/user-attachments/assets/38fbfff0-60b9-4066-8b13-becdb87babc3) ## Data <a name="data"></a> ![image](https://github.com/user-attachments/assets/d73631a7-0a58-4958-a494-a7f4add9108f) ![image](https://github.com/user-attachments/assets/f44936ed-c59a-4223-905d-0fe48a6d31a6) ![image](https://github.com/user-attachments/assets/bd333ee2-3c47-47e5-b244-4ea75f77c836) ## Explanation These graphs demonstrate performance improvements during full sync sessions using rdb-channel + streaming rdb directly from the background process to the replica. First graph- with at most 50 clients and light weight commands, we saw 5%-7.5% improvement in write latency during sync session. Two graphs below- full sync was tested during heavy read commands from the primary (such as sdiff, sunion on large sets). In that case, the child process writes to the replica without sharing CPU with the loaded main process. As a result, this not only improves client response time, but may also shorten sync time by about 50%. The shorter sync time results in less memory being used to store replication diffs (>60% in some of the tested cases). ## Test setup Both primary and replica in the performance tests ran on the same machine. RDB size in all tests is 3.7gb. I generated write load using valkey-benchmark ` ./valkey-benchmark -r 100000 -n 6000000 lpush my_list __rand_int__`. --------- Signed-off-by: naglera <anagler123@gmail.com> Signed-off-by: naglera <58042354+naglera@users.noreply.github.com> Co-authored-by: Viktor Söderqvist <viktor.soderqvist@est.tech> Co-authored-by: Ping Xie <pingxie@outlook.com> Co-authored-by: Madelyn Olson <madelyneolson@gmail.com>
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