In redis master-slave architecture, when a master fails a slave is promoted to master. As only master can perform write operations, What happens to data in the window period when slave is promoted to master. Does my system remain unresponsive?
Define "data":)
Client connections to the master will be closed upon its failure, so your system will be notified of that. Any data that was not written to the master and the replicas before the failure will therefore still reside in your application/system.
Once your system tries using a replica it will be able to read the data in it up to the point it was synchronized before failure. Once the replica is promoted to masterhood, your system will be able to continue writing data.
Note that Redis' synchronization is asynchronous. That means that slaves may lag behind the master and therefore lose some updates in case of failure. Refer to the WAIT command for more information about ensure the consistency.
Related
I need to load static data one time in redis in the master node and only when the synchronization is finished for all slaves I am going to be able to read. This is because we are going to have a lot reading and a few writing, and the data is not going to change for a long time.
I read from oficial documentation https://docs.redis.com/latest/rs/concepts/data-access/consistency-durability/, https://docs.redis.com/latest/rs/concepts/data-access/consistency-durability/ and https://redis.io/topics/cluster-tutorial in Redis Cluster consistency guarantees.
I read also Can the WAIT command provide strong consistency in Redis? but without to get a conclusion.
If I use synchronous replication and wait command to check if the replication was successful, do I have some guarantees about consistency ?
By default, a Redis Cluster is not able to guarantee strong consistency. It means that under certain conditions it is possible that Redis Cluster will lose writes that were acknowledged by the system to the client.
The reason why Redis Cluster can lose writes is because it uses asynchronous replication, however, you can improve consistency by forcing the database to flush data to disk before replying to the client, but this usually results in prohibitively low performance. That would be the equivalent of synchronous replication in the case of Redis Cluster. Basically, there is a trade-off to be made between performance and consistency, if you are fine with that!
Redis Cluster has support for synchronous writes when absolutely needed, implemented via the WAIT command. This makes losing writes a lot less likely. However, note that Redis Cluster does not implement strong consistency even when synchronous replication is used: it is always possible, under more complex failure scenarios, that a replica that was not able to receive the write will be elected as master.
There is another notable scenario where Redis Cluster will lose writes, that happens during a network partition where a client is isolated with a minority of instances including at least a master.
For example, imagine a 6 nodes cluster composed of A, B, C, A1, B1, C1, with 3 masters and 3 replicas. There is also a client, let's call it Z1.
After a partition occurs, it is possible that in one side of the partition we have A, C, A1, B1, C1, and in the other side we have B and Z1.
Z1 is still able to write to B, which will accept its writes. If the partition heals in a very short time, the cluster will continue normally. However, if the partition lasts enough time for B1 to be promoted to master on the majority side of the partition, the writes that Z1 has sent to B in the meantime will be lost.
Note that there is a maximum window to the amount of writes Z1 will be able to send to B: if enough time has elapsed for the majority side of the partition to elect a replica as master, every master node in the minority side will have stopped accepting writes.
This amount of time is a very important configuration directive of Redis Cluster, and is called the node timeout.
After node timeout has elapsed, a master node is considered to be failing, and can be replaced by one of its replicas. Similarly, after node timeout has elapsed without a master node to be able to sense the majority of the other master nodes, it enters an error state and stops accepting writes.
I am very new in REDIS cache implementation.
Could you please let me know what is the replication factor means?
How it works or What is the impact?
Thanks.
At the base of Redis replication (excluding the high availability features provided as an additional layer by Redis Cluster or Redis Sentinel) there is a very simple to use and configure leader follower (master-slave) replication: it allows replica Redis instances to be exact copies of master instances. The replica will automatically reconnect to the master every time the link breaks, and will attempt to be an exact copy of it regardless of what happens to the master.
This system works using three main mechanisms:
When a master and a replica instances are well-connected, the master keeps the replica updated by sending a stream of commands to the replica, in order to replicate the effects on the dataset happening in the master side due to: client writes, keys expired or evicted, any other action changing the master dataset.
When the link between the master and the replica breaks, for network issues or because a timeout is sensed in the master or the replica, the replica reconnects and attempts to proceed with a partial resynchronization: it means that it will try to just obtain the part of the stream of commands it missed during the disconnection.
When a partial resynchronization is not possible, the replica will ask for a full resynchronization. This will involve a more complex process in which the master needs to create a snapshot of all its data, send it to the replica, and then continue sending the stream of commands as the dataset changes.
Redis uses by default asynchronous replication, which being low latency and high performance, is the natural replication mode for the vast majority of Redis use cases.
Synchronous replication of certain data can be requested by the clients using the WAIT command. However WAIT is only able to ensure that there are the specified number of acknowledged copies in the other Redis instances, it does not turn a set of Redis instances into a CP system with strong consistency: acknowledged writes can still be lost during a failover, depending on the exact configuration of the Redis persistence. However with WAIT the probability of losing a write after a failure event is greatly reduced to certain hard to trigger failure modes.
I'm currently exploring Redis cluster. I've started 6 instances on 3 physical servers(3 master and 3 slaves) with persistence enabled.
I've noticed that when I kill one of the master instances then it's slave is promoted to master after some time. However, it remains as master even when I start the killed instance.
Since, Redis does asynchronous replication, therefore, I was thinking of a scenario where the master, immediately after flushing the data is killed i.e. it wasn't able to replicate that data.
Will this data get replicated to the new master(initially slave), once
the instance comes back up?
NO. If the master haven't replicate data to slave, the data will be lost. When the old master recovers, it will be become a slave of some other node based on some rules. Then the old master will replicate data from its new master.
I am new to Redis. I read their documentation on Sentinel and Replication in which they talk about how the replicas try to remain in sync with the master as much as possible, but it is still possible that if the master fails after a successful write, the replica might not receive that write. If Sentinel then marks this replica as the new master, it is possible that the replica serves stale data.
If I cannot afford to lose consistency and prefer it over availability, how can I turn off replication so that when Sentinel marks a new replica as master, all the first requests would be cache misses and my cache can slowly warm up instead of returning potentially stale data?
Also, is that a good idea? Are there other good alternatives?
I cannot afford to lose consistency and prefer it over availability
It's not clear that redis automated failover is appropriate for your application. It looks like each client would need to carefully keep track of server availability.
Suppose you have a few clients, a master, M1, and three replicas, R2, R3, R4. Client C5 writes a new bank account balance to M1, which immediately permanently fails, and R2 is promoted to become master M2. Master did not obtain an acknowledge from a replica before replying to client. No paxos-like consensus protocol happens between servers prior to the reply being sent to C5.
C5 could remember counters / timestamps embedded in each write request, forget the write payload, and detect stale reads. But client C6 could not, unless you supply such data quickly and reliably outside the protocol. Nathan Fritz observes that your app could issue a write and then a PUBLISH event, and monitor multiple replicas with a LISTEN for that event, delaying its report of success to end user. Consider incorporating derecho into your app if the solid promises of virtual synchrony are necessary. Production releases of redis are targeted at a different part of the problem space than your primary interest.
the redis.conf says:
1) Disk-backed: The Redis master creates a new process that writes the RDB
file on disk. Later the file is transferred by the parent
process to the slaves incrementally
I just dont know what does "transferred by the parent process to the slaves" mean?
thank you
It is simple. First read the RDB file into a buffer, and use socket.write to send this to salve's port which is listenning this.
The implemention is more complex than what I said. But this is what redis do. You can refer the replication.c in redis/src for more details.
EDITED:
Yes, the disk-less mechanism just use the child process directly sends the RDB over the wire to slaves, without using the disk as intermediate storage.
Actually, if you use disk to save the RDB and redis master can serve many slaves at the same time without queuing. Once the disk-less replication serve on slave, and if another slave comes and want do a full sync, it need to be queued to wait for the first slave to finish. So there are another settings repl-diskless-sync-delay to wait more slave to do this parallel.
And these two method only occur after something wrong happens. In the normal case, the redis master and salve through a well connected wire to replicate the redis command the slave to keep the same between the master and slave. And if the wire is break or the slave fall down, then need do a partial resync action to obtain the part slave missed. If the psync is not possible to achieve, it will try do full resync. The full resync is what we talked about.
This is how a full synchronization works in more details:
The master starts a background saving process in order to produce an RDB file. At the same time it starts to buffer all new write commands received from the clients. When the background saving is complete, the master transfers the database file to the slave, which saves it on disk, and then loads it into memory. The master will then send all buffered commands to the slave. This is done as a stream of commands and is in the same format of the Redis protocol itself.
And the disk-less replication is just a new feature which supports the full-resync in that case to deal with the slow disk stress. More about it refer to https://redis.io/topics/replication. such as how do psync and why psync will fail, you can find answer from this article.