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# Problem While introducing Async IO threads(https://github.com/redis/redis/pull/13695) primary and replica clients were left to be handled inside main thread due to data race and synchronization issues. This PR solves this issue with the additional hope it increases performance of replication. # Overview ## Moving the clients to IO threads Since clients first participate in a handshake and an RDB replication phases it was decided they are moved to IO-thread after RDB replication is done. For primary client this was trivial as the master client is created only after RDB sync (+ some additional checks one can see in `isClientMustHandledByMainThread`). Replica clients though are moved to IO threads immediately after connection (as are all clients) so currently in `unstable` replication happens while this client is in IO-thread. In this PR it was moved to main thread after receiving the first `REPLCONF` message from the replica, but it is a bit hacky and we can remove it. I didn't find issues between the two versions. ## Primary client (replica node) We have few issues here: - during `serverCron` a `replicationCron` is ran which periodically sends `REPLCONF ACK` message to the master, also checks for timed-out master. In order to prevent data races we utilize`IOThreadClientsCron`. The client is periodically sent to main thread and during `processClientsFromIOThread` it's checked if it needs to run the replication cron behaviour. - data races with main thread - specifically `lastinteraction` and `read_reploff` members of the primary client that are written to in `readQueryFromClient` could be accessed at the same time from main thread during execution of `INFO REPLICATION`(`genRedisInfoString`). To solve this the members were duplicated so if the client is in IO-thread it writes to the duplicates and they are synced with the original variables each time the client is send to main thread ( that means `INFO REPLICATION` could potentially return stale values). - During `freeClient` the primary client is fetched to main thread but when caching it(`replicationCacheMaster`) the thread id will remain the id of the IO thread it was from. This creates problems when resurrecting the master client. Here the call to `unbindClientFromIOThreadEventLoop` in `freeClient` was rewritten to call `keepClientInMainThread` which automatically fixes the problem. - During `exitScriptTimedoutMode` the master is queued for reprocessing (specifically process any pending commands ASAP after it's unblocked). We do that by putting it in the `server.unblocked_clients` list, which are processed in the next `beforeSleep` cycle in main thread. Since this will create a contention between main and IO thread, we just skip this queueing in `unblocked_clients` and just queue the client to main thread - the `processClientsFromIOThread` will process the pending commands just as main would have. ## Replica clients (primary node) We move the client after RDB replication is done and after replication backlog is fed with its first message. We do that so that the client's reference to the first replication backlog node is initialized before it's read from IO-thread, hence no contention with main thread on it. ### Shared replication buffer Currently in unstable the replication buffer is shared amongst clients. This is done via clients holding references to the nodes inside the buffer. A node from the buffer can be trimmed once each replica client has read it and send its contents. The reference is `client->ref_repl_buf_node`. The replication buffer is written to by main thread in `feedReplicationBuffer` and the refcounting is intrusive - it's inside the replication-buffer nodes themselves. Since the replica client changes the refcount (decreases the refcount of the node it has just read, and increases the refcount of the next node it starts to read) during `writeToClient` we have a data race with main thread when it feeds the replication buffer. Moreover, main thread also updates the `used` size of the node - how much it has written to it, compared to its capacity which the replica client relies on to know how much to read. Obviously replica being in IO-thread creates another data race here. To mitigate these issues a few new variables were added to the client's struct: - `io_curr_repl_node` - starting node this replica is reading from inside IO-thread - `io_bound_repl_node` - the last node in the replication buffer the replica sees before being send to IO-thread. These values are only allowed to be updated in main thread. The client keeps track of how much it has read into the buffer via the old `ref_repl_buf_node`. Generally while in IO-thread the replica client will now keep refcount of the `io_curr_repl_node` until it's processed all the nodes up to `io_bound_repl_node` - at that point its returned to main thread which can safely update the refcounts. The `io_bound_repl_node` reference is there so the replica knows when to stop reading from the repl buffer - imagine that replica reads from the last node of the replication buffer while main thread feeds data to it - we will create a data race on the `used` value (`_writeToClientSlave`(IO-thread) vs `feedReplicationBuffer`(main)). That's why this value is updated just before the replica is being send to IO thread. *NOTE*, this means that when replicas are handled by IO threads they will hold more than one node at a time (i.e `io_curr_repl_node` up to `io_bound_repl_node`) meaning trimming will happen a bit less frequently. Tests show no significant problems with that. (tnx to @ShooterIT for the `io_curr_repl_node` and `io_bound_repl_node` mechanism as my initial implementation had similar semantics but was way less clear) Example of how this works: * Replication buffer state at time N: | node 0| ... | node M, used_size K | * replica caches `io_curr_repl_node`=0, `io_bound_repl_node`=M and `io_bound_block_pos`=K * replica moves to IO thread and processes all the data it sees * Replication buffer state at time N + 1: | node 0| ... | node M, used_size Full | |node M + 1| |node M + 2, used_size L|, where Full > M * replica moves to main thread at time N + 1, at this point following happens - refcount to node 0 (io_curr_repl_node) is decreased - `ref_repl_buf_node` becomes node M(io_bound_repl_node) (we still have size-K bytes to process from there) - refcount to node M is increased (now all nodes from 0 up to M-1 including can be trimmed unless some other replica holds reference to them) - And just before the replica is send back to IO thread the following are updated: - `io_bound_repl_node` ref becomes node M+2 - `io_bound_block_pos` becomes L Note that replica client is only moved to main if it has processed all the data it knows about (i.e up to `io_bound_repl_node` + `io_bound_block_pos`) ### Replica clients kept in main as much as possible During implementation an issue arose - how fast is the replica client able to get knowledge about new data from the replication buffer and how fast can it trim it. In order for that to happen ASAP whenever a replica is moved to main it remains there until the replication buffer is fed new data. At that point its put in the pending write queue and special cased in handleClientsWithPendingWrites so that its send to IO thread ASAP to write the new data to replica. Also since each time the replica writes its whole repl data it knows about that means after it's send to main thread `processClientsFromIOThread` is able to immediately update the refcounts and trim whatever it can. ### ACK messages from primary Slave clients need to periodically read `REPLCONF ACK` messages from client. Since replica can remain in main thread indefinitely if no DB change occurs, a new atomic `pending_read` was added during `readQueryFromClient`. If a replica client has a pending read it's returned back to IO-thread in order to process the read even if there is no pending repl data to write. ### Replicas during shutdown During shutdown the main thread pauses write actions and periodically checks if all replicas have reached the same replication offset as the primary node. During `finishShutdown` that may or may not be the case. Either way a client data may be read from the replicas and even we may try to write any pending data to them inside `flushSlavesOutputBuffers`. In order to prevent races all the replicas from IO threads are moved to main via `fetchClientFromIOThread`. A cancel of the shutdown should be ok, since the mechanism employed by `handleClientsWithPendingWrites` should return the client back to IO thread when needed. ## Notes While adding new tests timing issues with Tsan tests were found and fixed. Also there is a data race issue caught by Tsan on the `last_error` member of the `client` struct. It happens when both IO-thread and main thread make a syscall using a `client` instance - this can happen only for primary and replica clients since their data can be accessed by commands send from other clients. Specific example is the `INFO REPLICATION` command. Although other such races were fixed, as described above, this once is insignificant and it was decided to be ignored in `tsan.sup`. --------- Co-authored-by: Yuan Wang <wangyuancode@163.com> Co-authored-by: Yuan Wang <yuan.wang@redis.com> |
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| .. | ||
| aof-multi-part.tcl | ||
| aof-race.tcl | ||
| aof.tcl | ||
| block-repl.tcl | ||
| convert-ziplist-hash-on-load.tcl | ||
| convert-ziplist-zset-on-load.tcl | ||
| convert-zipmap-hash-on-load.tcl | ||
| corrupt-dump-fuzzer.tcl | ||
| corrupt-dump.tcl | ||
| dismiss-mem.tcl | ||
| failover.tcl | ||
| logging.tcl | ||
| psync2-master-restart.tcl | ||
| psync2-pingoff.tcl | ||
| psync2-reg.tcl | ||
| psync2.tcl | ||
| rdb.tcl | ||
| redis-benchmark.tcl | ||
| redis-cli.tcl | ||
| replication-2.tcl | ||
| replication-3.tcl | ||
| replication-4.tcl | ||
| replication-buffer.tcl | ||
| replication-iothreads.tcl | ||
| replication-psync.tcl | ||
| replication-rdbchannel.tcl | ||
| replication.tcl | ||
| shutdown.tcl | ||