Consider the following setup:
There a 2 physical servers which are set up as a regular mongodb replication set (including an arbiter process, so automatic failover will work correctly).
now, as far as i understand, most actual work will be done on the primary server, while the slave will mostly just do work to keep its dataset in sync.
Would it be reasonable, to introduce sharding into this setup in a way that one would set up another replication set on the same 2 servers, so that each of them has one mongod process running as primary and one process running as secondary.
The expected result would be that both servers will share the workload of actual querys/inserts while both are up. In the case of one server failing the whole setup should elegantly fail over to continue running, until the other server is restored.
Are there any downsides to this setup, except the overall overhead in setup and number of processes (mongos/configservers/arbiters)?
That would definitely work. I'd asked a question in the #mongodb IRC channel a bit ago as to whether or not it was a bad idea to run multiple mongod processes on a single machine. The answer was "as long as you have the RAM/CPU/bandwidth, go nuts".
It's worth noting that if you're looking for high-performance reads, and don't mind writes being a bit slower, you could:
Do your writes in "safe mode", where the write doesn't return until it's been propagated to N servers (in this case, where N is the number of servers in the replica set, so all of them)
Set the driver-appropriate flag in your connection code to allow reading from slaves.
This would get you a clustered setup similar to MySQL - write once on the master, but any of the slaves is eligible for a read. In a circumstance where you have many more reads than writes (say, an order of magnitude), this may be higher performance, but I don't know how it'd behave when a node goes down (since writes may stall trying to write to 3 nodes, but only 2 are up, etc - that would need testing).
One thing to note is that while both machines are up, your queries are being split between them. When one goes down, all queries will go to the remaining machine thus doubling the demands placed on it. You'd have to make sure your machines could withstand a sudden doubling of queries.
In that situation, I'd reconsider sharding in the first place, and just make it an un-sharded replica set of 2 machines (+1 arbiter).
You are missing one crucial detail: if you have a sharded setup with two physical nodes only, if one dies, all your data is gone. This is because you don't have any redundancy below the sharding layer (the recommended way is that each shard is composed of a replica set).
What you said about the replica set however is true: you can run it on two shared-nothing nodes and have an additional arbiter. However, the recommended setup would be 3 nodes: one primary and two secondaries.
http://www.markus-gattol.name/ws/mongodb.html#do_i_need_an_arbiter
Related
Sharding with replication]1
I have a multi tenant database with 3 tables(store,products,purchases) in 5 server nodes .Suppose I've 3 stores in my store table and I am going to shard it with storeId .
I need all data for all shards(1,2,3) available in nodes 1 and 2. But node 3 would contain only shard for store #1 , node 4 would contain only shard for store #2 and node 5 for shard #3. It is like a sharding with 3 replicas.
Is this possible at all? What database engines can be used for this purpose(preferably sql dbs)? Did you have any experience?
Regards
I have a feeling you have not adequately explained why you are trying this strange topology.
Anyway, I will point out several things relating to MySQL/MariaDB.
A Galera cluster already embodies multiple nodes (minimum of 3), but does not directly support "sharding". You can have multiple Galera clusters, one per "shard".
As with my comment about Galera, other forms of MySQL/MariaDB can have replication between nodes of each shard.
If you are thinking of having a server with all data, but replicate only parts to readonly Replicas, there are settings for replicate_do/ignore_database. I emphasize "readonly" because changes to these pseudo-shards cannot easily be sent back to the Primary server. (However see "multi-source replication")
Sharding is used primarily when there is simply too much traffic to handle on a single server. Are you saying that the 3 tenants cannot coexist because of excessive writes? (Excessive reads can be handled by replication.)
A tentative solution:
Have all data on all servers. Use the same Galera cluster for all nodes.
Advantage: When "most" or all of the network is working all data is quickly replicated bidirectionally.
Potential disadvantage: If half or more of the nodes go down, you have to manually step in to get the cluster going again.
Likely solution for the 'disadvantage': "Weight" the nodes differently. Give a height weight to the 3 in HQ; give a much smaller (but non-zero) weight to each branch node. That way, most of the branches could go offline without losing the system as a whole.
But... I fear that an offline branch node will automatically become readonly.
Another plan:
Switch to NDB. The network is allowed to be fragile. Consistency is maintained by "eventual consistency" instead of the "[virtually] synchronous replication" of Galera+InnoDB.
NDB allows you to immediately write on any node. Then the write is sent to the other nodes. If there is a conflict one of the values is declared the "winner". You choose which algorithm for determining the winner. An easy-to-understand one is "whichever write was 'first'".
I know Mongodb suggest the replication set minimum is 3
Can I use two servers to install Mongodb with 4 replication sets in order to prevent Write failure when one node down?
My idea is to install two more instances on each server to fake/get rid of it:
Mongodb 1
Replcation set 1 (Master)
Replcation set 2 (Secondary)
Mongodb 2
Replcation set 3 (Secondary)
Replcation set 4 (Arbiter)
If one server down, it still has two replication sets for it.
Can anyone can comment my idea?
I would like to know is there any issue/risk needed to consider?
Thanks!
This is a bad idea. Your suggested configuration would be counter-productive for two main reasons:
Running two instances of MongoDB on the same hosts will lead to them both running slowly and awkwardly, competing for memory, cpu, disk i/o, etc.
If one of the hosts goes down, the two nodes on the other will not be able to continue the replica set because with only two nodes running out of four, you don't have the majority necessary to become primary.
MongoDB is intended to be run effectively on multiple hosts, so it is designed for that; even if you could find a way to shoe-horn a functioning replica set onto only two hosts, you would be working against MongoDB's design and struggling to make it work effectively.
Really, your best option is to run a single mongod instance on each of your two hosts, and to run an arbiter on a third (separate) host; that kind of normal 3-host configuration is an effective and straightforward way of achieving both data replication and high availability.
Please read https://docs.mongodb.com/manual/replication/
Even number of members in a set is not recommended. The only reason to add an Arbiter is to resolve this issue and increase number of members by 1 to make it odd. It makes no sense to add 2 Arbiters at all.
Similarly there is no point to put an Arbiter to the same server with any other member. It is quite lightweight, so you can co-locate it with an application server for example.
Having 2 db servers the best replica set configuration would be:
Mongodb 1
Master
Mongodb 2
Secondary
Any other server
Arbiter
Simple answer is, no you cannot do it..
Reason is "majority". If you loose one server of those two, you don't have majority of votes online.
This is reason, why 3 is minimum. It can be 3 data bearing nodes or 2 data bearing nodes and one arbiter. All of those have one vote and if you loose one of those, replica set still have 2/3 votes what is majority. Like 3/5 or 4/7.
Values 1/2 (or 2/4) are not majority.
If find the replica set requirement a bit confusing, and I'm probably missing something obvious (like under which condition there are elections).
I understand that in normal operations you need quorum, and a voting takes place and to get a majority you need and odd numbers of machines.
But since we use a replica set for failover, if the master dies, then we are left with an even number of voting members, which based on my limited experience lengthen the time to elect a primary.
Also according to the documentation, the addition of a voting member doesn't start an election, it would seem that starting (booting) you replica set with an even number of nodes would make more sense?
So if we start say with 4 machines in the replica set, and one machine dies, there is a re-election with 3 machines, fast quorum. We add a machine back to get back to our normal operation state, no re-election and we are back to our normal operation conditions.
Can someone shed a light on this?
TL;DR: With single master systems, even partitions make it impossible to determine which remainder still has a majority, taking both systems down.
Let N be a cluster of four machines:
One machine dies, the others resume operation. Good.
Two machines die, we're offline because we no longer get a majority. Bad.
Let M be a cluster of three machines:
One machine dies, the others resume operation. Good.
Two machines die, we're offline because we no longer get a majority. Bad.
=> Same result at 3/4 of the cost.
Now, let's add an assumption or two:
We're also going to operate some kind of server application that uses the database
The network can be partitioned
Let's say you have two datacenters, one with two database instances and the backend server machines. If the connection to the backup center (which has one MongoDB instance) fails, you're still online.
Now if you added a second MongoDB instance at the backup data center, a network partition would, despite seemingly higher redundancy, yield lower availability since we'd lose the majority in case of a network partition and can't continue to operate.
=> Less availability at higher cost. But that doesn't answer the question yet.
Let's say you're really worried about availability: You have two data centers, with backend servers in both datacenters, anycast IPs, the whole deal. Now the network between the two DCs is partitioned, but some clients connect to DC A while other reach DC B. How do you now determine which datacenter may accept writes? It's not possible - this is why the odd number is necessary.
You don't actually need Anycast IPs, BGP or any fancy stuff for the problem to become real, any writing application (like a worker, a stale request, anything) would require later merging different writes, which is a completely different concurrency scheme.
We're using amazon web service for a business application which is using node.js server and mongodb as database. Currently the node.js server is runing on a EC2 medium instance. And we're keeping our mongodb database in a separate micro instance. Now we want to deploy replica set in our mongodb database, so that if the mongodb gets locked or unavailble, we still can run our database and get data from it.
So we're trying to keep each member of the replica set in separate instances, so that we can get data from the database even if the instance of the primary memeber shuts down.
Now, I want to add load balancer in the database, so that the database works fine even in huge traffic load at a time. In that case I can read balance the database by adding slaveOK config in the replicaSet. But it'll not load balance the database if there is huge traffic load for write operation in the database.
To solve this problem I got two options till now.
Option 1: I've to shard the database and keep each shard in separate instance. And under each shard there will be a reaplica set in the same instance. But there is a problem, as the shard divides the database in multiple parts, so each shard will not keep same data within it. So if one instance shuts down, we'll not be able to access the data from the shard within that instance.
To solve this problem I'm trying to divide the database in shards and each shard will have a replicaSet in separate instances. So even if one instance shuts down, we'll not face any problem. But if we've 2 shards and each shard has 3 members in the replicaSet then I need 6 aws instances. So I think it's not the optimal solution.
Option 2: We can create a master-master configuration in the mongodb, that means all the database will be primary and all will have read/write access, but I would also like them to auto-sync with each other every so often, so they all end up being clones of each other. And all these primary databases will be in separate instance. But I don't know whether mongodb supports this structure or not.
I've not got any mongodb doc/ blog for this situation. So, please suggest me what should be the best solution for this problem.
This won't be a complete answer by far, there is too many details and I could write an entire essay about this question as could many others however, since I don't have that kind of time to spare, I will add some commentary about what I see.
Now, I want to add load balancer in the database, so that the database works fine even in huge traffic load at a time.
Replica sets are not designed to work like that. If you wish to load balance you might in fact be looking for sharding which will allow you to do this.
Replication is for automatic failover.
In that case I can read balance the database by adding slaveOK config in the replicaSet.
Since, to stay up to date, your members will be getting just as many ops as the primary it seems like this might not help too much.
In reality instead of having one server with many connections queued you have many connections on many servers queueing for stale data since member consistency is eventual, not immediate unlike ACID technologies, however, that being said they are only eventually consistent by 32-odd ms which means they are not lagging enough to give decent throughput if the primary is loaded.
Since reads ARE concurrent you will get the same speed whether you are reading from the primary or secondary. I suppose you could delay a slave to create a pause of OPs but that would bring back massively stale data in return.
Not to mention that MongoDB is not multi-master as such you can only write to one node a time makes slaveOK not the most useful setting in the world any more and I have seen numerous times where 10gen themselves recommend you use sharding over this setting.
Option 2: We can create a master-master configuration in the mongodb,
This would require you own coding. At which point you may want to consider actually using a database that supports http://en.wikipedia.org/wiki/Multi-master_replication
This is since the speed you are looking for is most likely in fact in writes not reads as I discussed above.
Option 1: I've to shard the database and keep each shard in separate instance.
This is the recommended way but you have found the caveat with it. This is unfortunately something that remains unsolved that multi-master replication is supposed to solve, however, multi-master replication does add its own ship of plague rats to Europe itself and I would strongly recommend you do some serious research before you think as to whether MongoDB cannot currently service your needs.
You might be worrying about nothing really since the fsync queue is designed to deal with the IO bottleneck slowing down your writes as it would in SQL and reads are concurrent so if you plan your schema and working set right you should be able to get a massive amount of OPs.
There is in fact a linked question around here from a 10gen employee that is very good to read: https://stackoverflow.com/a/17459488/383478 and it shows just how much throughput MongoDB can achieve under load.
It will grow soon with the new document level locking that is already in dev branch.
Option 1 is the recommended way as pointed out by #Sammaye but you would not need 6 instances and can manage it with 4 instances.
Assuming you need below configuration.
2 shards (S1, S2)
1 copy for each shard (Replica set secondary) (RS1, RS2)
1 Arbiter for each shard (RA1, RA2)
You could then divide your server configuration like below.
Instance 1 : Runs : S1 (Primary Node)
Instance 2 : Runs : S2 (Primary Node)
Instance 3 : Runs : RS1 (Secondary Node S1) and RA2 (Arbiter Node S2)
Instance 4 : Runs : RS2 (Secondary Node S2) and RA1 (Arbiter Node S1)
You could run arbiter nodes along with your secondary nodes which would help you in election during fail-overs.
I currently have 2 physical servers and one arbiter configured as a replica set. I would like to try sharing with this configuration. I know it is possible to run two mongod instances on the same server, one as master of replica 1, the other as slave of replica 2: can these two processes (master of replica 1 and slave of replica 2) point to the same database? Isn't there the danger of a sort of loop?
Hmm I am unsure if you know what replication really is.
All members in the replica set will share the same database(s), they will replicate the database(s) between them and maintain them.
Replicas are exactly that, they are copies of each other, including database.
I suggest you read: http://docs.mongodb.org/manual/replication/
Edit
There could be another meaning here as in to the same files since you mention running the master and slaves on the same node.
First off running two replicas on the same node is pointless. You will get no benefit and if anything you will get a performance problem since that IO is now taking double the strain it normally would.
So I would begin by saying that your idea would be really bad design even if it was feasible which it is not, the physical files cannot have multiple file locks on them.