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https://issues.apache.org/jira/browse/KUDU-3290?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17359134#comment-17359134
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shenxingwuying commented on KUDU-3290:
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Realtime replicate data(maybe it called duplication) to another storage system 
is very common requirement.

We need realtime replication, not use mini-batch increment to appoach realtime.
 # By two pipeline to write two system, is very hard to do with the consistency 
and request sequence or failover.
 # We hope commit the scheme and community can maintenance the function. and 
our kudu will easily synchronize with community kudu version.

At this, kafka is just a target system example, kafka may replaced by a kudu 
complete replica, just a non-voter, or other storage system.

Because kafka as a mq system can do system decoupling. Kafka is very popular mq 
symbol system, maybe the most popular mq system. By kafka, users can replicate 
data to any other storage system. So supporting kafka is significant.

In summary,the above two scheme, the more suitable is the first——add a 
Learner(temp called its role).

Kafka is a state machine like KuduEngine. For a Kudu replica(together with new 
replica(its state machine is kafka or other)), all state machine exec cmd ops 
sequentially. So the consistency is not a problem. The code need changes in 
Apply, the Learner need Apply to Kafka.

Apply to Kafka, is an optional function when compiling set.

> Implement Replicate table's data to Kafka(or other Storage System)
> ------------------------------------------------------------------
>
>                 Key: KUDU-3290
>                 URL: https://issues.apache.org/jira/browse/KUDU-3290
>             Project: Kudu
>          Issue Type: New Feature
>          Components: tserver
>            Reporter: shenxingwuying
>            Priority: Critical
>
> h1. background & problem
> We use kudu to store the user profile data, because business requirements, 
> exchange and share data from multi-tenant users, which is reasonable in our 
> application scene, we need replicate data from one system to another. The 
> destination storage system we pick kafka, because of our company's 
> architecture at now.
> At this time, we have two ideas to solve it.
> h1. two replication scheme
> Generally, Raft group has three replicas, one is leader and the other two are 
> followers. We’ll add a replica, its role is Learner. Learner only receive all 
> the data, but not pariticipart in ther leadership election.
> The learner replica, its state machine will be a plugin system, eg:
>  # We can support KuduEngine, which just a data backup like mongodb’s hidden 
> replica.
>  # We can write to the thirdparty store system, like kafka or any other 
> system we need. Then we can replicate data to another system use its client.
> At Paxos has a learner role, which only receive data. we need such a role for 
> new membership.
> But it Kudu Learner has been used for the copying(recovering) tablet replica. 
> Maybe we need a new role name, at this, we still use Learner to represent the 
> new role. (We should think over new role name)
> In our application scene, we will replicate data to kafka, and I will explain 
> the method.
> h2. Learner replication
>  # Add a new replica role, maybe we call it learner, because Paxos has a 
> learner role, which only receive data. We need such a role for new 
> membership. But at Kudu Learner has been used for the copying(recovering) 
> tablet replica. Maybe we need a new role name, at this, we still use Learner 
> to represent the new role. (We should think over new role name)
>  # The voters's safepoint of clean obsoleted wal is min(leader’ max wal 
> sequence number, followers max wal sequence number, learner’ max wal sequence 
> number)
>  # The learner not voter, not partitipant in elections
>  # Raft can replication data to the learner
>  # The process of learner applydb, just like raft followers, the logs before 
> committed index will replicate to kafka, kafka’s response ok. the apply index 
> will increase.
>  # We need kafka client, it will be added to kudu as an option, maybe as an 
> compile option
>  # When a kudu-tserver decomission or corrupted, the learner must move to new 
> kudu-tserver. So the leader should save learner apply OpId, and replicate to 
> followers, when learner's failover when leader down.
>  # The leader must save the learners apply OpId and replicate it to 
> followers, when learner's recovery can make sure no data loss when leader 
> down. If leader no save the applyIndex, learner maybe loss data
>  # Followers save the learners applyindex and term, coz followers maybe 
> become leader.
>  # When load balancer running,we shoud support move learner another 
> kudu-tserver
>  # Table should add a switch option to determine whether raft group has 
> learner, can support setting it when creating table.
>  # Support altering table to add learners maybe an idea, but need solve the 
> base data migrate problem.
>  # Base data migrate. The simple but heavy cost, when learner's max_OpId < 
> committed_OpId (maybe data loss, maybe we alter table add learner replication 
> for a existing table), we can trigger a full scan at the timestamp and 
> replicate data to learner, and then recover the appendEntries flow.
>  # Kudu not support split and merge, we not discuss it now. If KuduSupport 
> split or merge, we can implement it use 12, of course we can use more better 
> method.
>  # If we need the funtion, our cluster should at least 4 tservers.
> If kafka fail or topic not exist, the learner will stop replicate wal, that 
> will occupt more disk space. if learner loss or corrupted, it can recover 
> from the leader. We need make sure the safepoint.
> h2. Leader replication
> We can replication data to kafka or any other storage system from leader 
> directly.
>  # We need not set a role, but the dest is kafka, PeerManager's one peer is 
> different from the others, that will make something complex.
>  # Reuse the leader’s wal, save a output network bandwidth compare to above 
> method.
>  # All replica should maintenance a point to save the apply OpId at kafka.
>  # Safepoint of clean obsoleted wal is min( voters’ max wal sequence number, 
> applyIndex at kafka), which leader save it.
>  # Any leader transfer must recover the apply OpId at kafka.
>  # We need kafka client, it will be added to kudu as an option, may be as an 
> compile option
>  # If kafka's topic or kafka failure, print errorlog. and wal holds
>  # Some process the same as Learner replication. such as base data replicate.
>  # If we need the funtion, our cluster should at least 3 tservers.
> If kafka fail or topic not exist, the leader will stop replicate wal to 
> kafka, that will occupt more disk space. We need make sure the safepoint.



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