couchbase cluster document not replicating but splitting up - couchbase

I've set up a couchbase cluster with 2 nodes containing 300k docs on 4 buckets. the option replicas is forced to 1 as there are only 2 machines.
But documents are splitted half in one node half in the other, I need to have double copy of each document so if a node goes down the other one che still supply all data to my app.
Is there a setting I missed in creating the cluster?
can I still set the cluster to replicate all documents?
I hope someone can help.
thanks
PS: I'm using couchbase community 4.5
UPDATE:
I add screenshots of cluster web interface and cbstast output:
the following is the state with one node only
next the one with both node up:
then cbstats results on both node when both are up and running:
AS you can see with only one node there are half items displayed. Does it mean that the other half resides as replicas but are not shown???
can I still run consistenly my app with only one node???
UPDATE:
I had to click fail-over manually to see replicas become active on the remaining node. As with just two cluster auto fail-over is disabled!!!

Couchbase Server will partition or shard the documents across the two nodes, as you observed. It will also place replicas on those nodes, based on your one-replica configuration.
To access a replica, you must use one of the Client SDKs.
For example, this Java code will attempt to retrieve a replica (getFromReplica("id", ReplicaMode.ALL)) if the active document retrieval fails (get("id")).
bucket.async()
.get("id")
.onErrorResumeNext(bucket.async().getFromReplica("id", ReplicaMode.ALL))
.subscribe();
The ReplicaMode.ALL tells Couchbase to try all nodes with replicas and the active node.

So what was happening with only two nodes in the cluster was that auto fail-over didn't start automatically as specified here:
https://developer.couchbase.com/documentation/server/current/clustersetup/automatic-failover.html
this means data replicas where not activated in the remaining node unless fail-over was triggerd manullay.
The best thing is to have more than TWO nodes in the cluster before going in production.
To be honest I should have ridden documentation very carefully before asking any question.
thanks Jeff Kurtz for your help, you pushed me towards the solution. (the understanding of how couchbase replicas policy works).

Related

Having as many Pods as Nodes

We are currently using 2 Nodes, but we may need more in the future.
The StatefulSets is a mariadb-galera is current replica is at 2.
When we'll had a new Nodes we want the replica to be a 3, f we don't need it anymore and we delete it or a other Node we want it to be a 2.
In fact, if we have 3 Nodes we want 3 replica one on each Nodes.
I could use Pod Topology Spread Constraints but we'll have a bunch of "notScheduled" pods.
Is there a way to adapt the number of Replica automatically, every time a nodes is add or remove?
When we'll had a new Nodes we want the replica to be a 3, f we don't need it anymore and we delete it or a other Node we want it to be a 2.
I would recommend to do it the other way around. Manage the replicas of your container workload and let the number of nodes be adjusted after that.
See e.g. Cluster Autoscaler for how this can be done, it depends on what cloud provider or environment your cluster is using.
It is also important to specify your CPU and Memory requests such that it occupy the whole nodes.
For MariaDB and similar workload, you should use StatefulSet and not DaemonSet.
You could use a Daemon Set https://kubernetes.io/docs/concepts/workloads/controllers/daemonset/
Which will ensure there is one pod per node.
A DaemonSet ensures that all (or some) Nodes run a copy of a Pod. As nodes are added to the cluster, Pods are added to them. As nodes are removed from the cluster, those Pods are garbage collected. Deleting a DaemonSet will clean up the Pods it created.
Also, its not advised to run a database in anything else than a statefulset due to the pod identity concept as statefulsets have.
Due to all the database administration it is advisable to use any cloud provider managed databases or managing it, specially inside the cluster will incur in multiple issues

How to remove Couchbase node, having non replicated ephemeral bucket

I am having 2 Couchbase node, having 3 ephemeral buckets. The buckets are non replicated.
Lets name the nodes as A and B. Now I want to keep node B and remove node A.
Our client services is having the IP of node B, so I want to remove node A.
Can I remove node A directly from the Couchbase console and perform rebalancing. Am I going to lose data.
Any help will be appreciated.
I just tried this locally:
I created an ephemeral bucket with 0 replicas on a 2-node cluster.
I put 6 total documents in the bucket.
I removed one node.
I rebalanced the cluster.
After the rebalance was complete, I still had 6 documents in the ephemeral bucket.
So it appears that you will NOT lose data. HOWEVER, I would highly recommend taking advantage of the distributed nature of Couchbase and turn on replication in order to get high availability (in case something goes wrong with one of the nodes that you didn't plan for).

Couchbase - what happens if a node dies after writing data to disk but before it gets replicated

Here is the scenario.
I have two nodes under my couchbase server, Node A and B.I have replication on, so B will act as the node where replicated data of A should go.
Lets say that I try adding a new record and it happen to get saved at node A. Node A saves this data on RAM and on its disk successfully but UNFORTUNATELY, it crashes even before this data could get replicated to Node B
If I have configured automatic failover, Then all requests for Node A data will now go to Node B.
My question is Will I be able to get this new data which could not get replicated to node B but was successfully written over Node A's Disk? considering that Node A is down and all i have is Node B to communicate with
If yes, Please explain how. if no, Is there any official couchbase doc mentioning this behavior.
I tried looking for an answer in the official document and mostly it look like that answer is no, But thought of discussing this here before concluding that its data loss for sure.
Thanks in advance
In the scenario you described, yes the data will not be available, assuming you didn't check that the data had been successfully replicated. However note that replication will typically complete before perisistance, as the network is typically faster than disk.
Couchbase provides an observe API which allows you to verify that a particular mutation has been replicated and/or persisted. See Monitoring data using observe in the Couchbase developer guide.

Mysql cluster for dummies

So what's the idea behind a cluster?
You have multiple machines with the same copy of the DB where you spread the read/write? Is this correct?
How does this idea work? When I make a select query the cluster analyzes which server has less read/writes and points my query to that server?
When you should start using a cluster, I know this is a tricky question, but mabe someone can give me an example like, 1 million visits and a 100 million rows DB.
1) Correct. Every data node does not hold a full copy of the cluster data, but every single bit of data is stored on at least two nodes.
2) Essentially correct. MySQL Cluster supports distributed transactions.
3) When vertical scaling is not possible anymore, and replication becomes impractical :)
As promised, some recommended readings:
Setting Up Multi-Master Circular Replication with MySQL (simple tutorial)
Circular Replication in MySQL (higher-level warnings about conflicts)
MySQL Cluster Multi-Computer How-To (step-by-step tutorial, it assumes multiple physical machines, but you can run your test with all processes running on the same machine by following these instructions)
The MySQL Performance Blog is a reference in this field
1->your 1st point is correct in a way.But i think if multiple machines would share the same data it would be replication instead of clustering.
In clustering the data is divided among the various machines and there is horizontal partitioning means the dividing of the data is based on the rows,the records are divided by using some algorithm among those machines.
the dividing of data is done in such a way that each record will get a unique key just as in case of a key-value pair and each machine also has a unique machine_id related which is used to define which key value pair would go to which machine.
we call each machine a cluster and each cluster consists of an individual mysql-server, individual data and a cluster manager.and also there is a data sharing between all the cluster nodes so that all the data is available to the every node at any time.
the retrieval of data is done through memcached devices/servers for fast retrieval and
there is also a replication server for a particular cluster to save the data.
2->yes, there is a possibility because there is a sharing of all the data among all the cluster nodes. and also you can use a load balancer to balance the load.But the idea of load balancer is quiet common because they are being used by most of the servers. but if you are trying you just for your knowledge then there is no need because you will not get to notice the type of load that creates the requirement of a load balancer the cluster manager itself can do the whole thing.
3->RandomSeed is right. you do feel the need of a cluster when your replication becomes impractical means if you are using the master server for writes and slave for reads then at some time when the traffic becomes huge such that the sever would not be able to work smoothly then you will feel the need of clustering. simply to speed up the whole process.
this is not the only case, this is just one of the scenario this is only just a case.
hope this is helpful for you!!

Does the MySQL NDB Cluster consider node distance? Will it use the replicates if they are nearer?

I'm building a very small NDB cluster with only 3 machines. This means that machine 1 will serve as both MGM Server, MySQL Server, and NDB data node. The database is only 7 GB so I plan to replicate each node at least once. Now, since a query might end up using data that is cached in the NDB node on machine one, even if it isn't node the primary source for that data, access would be much faster (for obvious reasons).
Does the NDB cluster work like that? Every example I see has at least 5 machines. The manual doesn't seem to mention how to handle node differences like this one.
There are a couple of questions here :
Availability / NoOfReplicas
MySQL Cluster can give high availability when data is replicated across 2 or more data node processes. This requires that the NoOfReplicas configuration parameter is set to 2 or greater. With NoOfReplicas=1, each row is stored in only one data node, and a data node failure would mean that some data is unavailable and therefore the database as a whole is unavailable.
Number of machines / hosts
For HA configurations with NoOfReplicas=2, there should be at least 3 separate hosts. 1 is needed for each of the data node processes, which has a copy of all of the data. A third is needed to act as an 'arbitrator' when communication between the 2 data node processes fails. This ensures that only one of the data nodes continues to accept write transactions, and avoids data divergence (split brain). With only two hosts, the cluster will only be resilient to the failure of one of the hosts, if the other host fails instead, the whole cluster will fail. The arbitration role is very lightweight, so this third machine can be used for almost any other task as well.
Data locality
In a 2 node configuration with NoOfReplicas=2, each data node process stores all of the data. However, this does not mean that only one data node process is used to read/write data. Both processes are involved with writes (as they must maintain copies), and generally, either process could be involved in a read.
Some work to improve read locality in a 2-node configuration is under consideration, but nothing is concrete.
This means that when MySQLD (or another NdbApi client) is colocated with one of the two data nodes, there will still be quite a lot of communication with the other data node.