we have many datacenters but datacenter1 is the main.
the master in datacenter1 is being monitored by sentinel so if the master goes down one the replicas will become master and also all data is being synced continuously.
we want to have one Redis replica in each datacenter, replicate all data from datacenter1 but without the ability to become master. (always get data from data center 1 and just replica 1 have the ability to become master but other replicas must not be able)
is there a Redis config for this or any idea?
Redis Multi Datacenter
Redis config [1] has a replica-priority parameter which should serve your purpose.
The replica priority is an integer number published by Redis in the INFO
output. It is used by Redis Sentinel in order to select a replica to promote
into a master if the master is no longer working correctly.
A replica with a low priority number is considered better for promotion, so
for instance if there are three replicas with priority 10, 100, 25 Sentinel
will pick the one with priority 10, that is the lowest.
However a special priority of 0 marks the replica as not able to perform the
role of master, so a replica with priority of 0 will never be selected by
Redis Sentinel for promotion.
By default the priority is 100.
The idea can be setting lower replica-priority value to replicas in datacenter1 and higher value to replicas in other datacenters.
[1] redis.conf file of Redis version 6.2.6: https://github.com/redis/redis/blob/6.2.6/redis.conf
Related
If this sound silly to you I apologise in advance, I am new to splunk and did udemy course but can't figure out this.
If I check my indexes.conf file in cluster master I get repFator=0
#
# By default none of the indexes are replicated.
#
repFactor = 0
but if I check https://:8089/services/cluster/config
I see replication factor :
replication_factor 2
So I am confused whether my data is getting replicated,
I have two indexes in a cluster
I believe replication_factor determines how many replicas to have amongst nodes in the cluster, and refFactor determines whether or not to replicate a particular index.
For repFactor, which is an index specific setting
The indexes.conf repFactor attribute
When you add a new index stanza, you must set the repFactor attribute to "auto". This causes the index's data to be replicated to other peers in the cluster.
Note: By default, repFactor is set to 0, which means that the index will not be replicated. For clustered indexes, you must set it to "auto".
The only valid values for repFactor are 0 and "auto".
For replication_factor, which is a cluster setting:
Replication factor and cluster resiliency
The cluster can tolerate a failure of (replication factor - 1) peer nodes. For example, to ensure that your system can tolerate a failure of two peers, you must configure a replication factor of 3, which means that the cluster stores three identical copies of each bucket on separate nodes. With a replication factor of 3, you can be certain that all your data will be available if no more than two peer nodes in the cluster fail. With two nodes down, you still have one complete copy of data available on the remaining peers.
By increasing the replication factor, you can tolerate more peer node failures. With a replication factor of 2, you can tolerate just one node failure; with a replication factor of 3, you can tolerate two concurrent failures; and so on.
The repFactor setting lets you choose which indexes are replicated. By default, none are. The replication_factor setting says how many copies of a replicated bucket to make. Both must be non-zero to replicate data.
The Cluster Manager should confirm that. Select Settings->Indexer Clustering to see which indexes are replicated and their state.
I'm trying to set up Redis Sentinel.
I know that when a master goes down the sentinel pick up one of its slaves and promote it as master.
I was wondering based on which attributes the new master is selected among the slaves and which slave got selected for being a new master?
After Sentinels election, the leader sentinel will do the following steps:
Remove slaves already in down status from slave list.
Remove slaves which disconnection time is more than ten times of down-after-milliseconds + master down time
Select slave(s) by replica-priority(configured in slave)
If multiple slaves are selected, sort them by sync offset, and select the most in-sync(maximum offset) slave.
If there are still multiple selection, sort with RunId and select the smaller one.
So you can see the process order of master selection can be following order:
Disconnection time
Priority
Replication offset
Run Id
I want to understand the behavior of aerospike in different consistancy mode.
Consider a aerospike cluster running with 3 nodes and replication factor 3.
AP modes is simple and it says
Aerospike will allow reads and writes in every sub-cluster.
And Maximum no. of node which can go down < 3 (replication factor)
For aerospike strong consistency it says
Note that the only successful writes are those made on replication-factor number of nodes. Every other write is unsuccessful
Does this really means the no writes are allowed if available nodes < replication factor.
And then same document says
All writes are committed to every replica before the system returns success to the client. In case one of the replica writes fails, the master will ensure that the write is completed to the appropriate number of replicas within the cluster (or sub cluster in case the system has been compromised.)
what does appropriate number of replica means ?
So if I lose one node from my 3 node cluster with strong consistency and replication factor 3 , I will not be able to wright data ?
For aerospike strong consistency it says
Note that the only successful writes are those made on
replication-factor number of nodes. Every other write is unsuccessful
Does this really means the no writes are allowed if available nodes <
replication factor.
Yes, if there are fewer than replication-factor nodes then it is impossible to meet the user specified replication-factor.
All writes are committed to every replica before the system returns
success to the client. In case one of the replica writes fails, the
master will ensure that the write is completed to the appropriate
number of replicas within the cluster (or sub cluster in case the
system has been compromised.)
what does appropriate number of replica means ?
It means replication-factor nodes must receive the write. When a node fails, a new node can be promoted to replica status until either the node returns or an operator registers a new roster (cluster membership list).
So if I lose one node from my 3 node cluster with strong consistency
and replication factor 3 , I will not be able to wright data ?
Yes, so having all nodes a replicas wouldn't be a very useful configuration. Replication-factor 3 allows up to 2 nodes to be down, but only if the remaining nodes are able to satisfy the replication-factor. So for replication-factor 3 you would probably want to run with a minimum of 5 nodes.
You are correct, with 3 nodes and RF 3, losing one node means the cluster will not be able to successfully take write transactions since it wouldn't be able to write the required number of copies (3 in this case).
Appropriate number of replicas means a number of replicas that would match the replication factor configured.
Been searching for a specific info but couldn't find; forgive me for being new at this.
I will try to replicate a Firebird DB using SymmetricsDS. This is an ERP database; which in my mind will have 1 master and 2 slaves. I will have 2 slave servers which will work locally and local machines will connect them as clients.
Say for example I am a client of local slave 1. I am creating a new customer which will automatically get a customer ID 100. At the same time a client of the local slave (server) 2 creates a new customer and it takes the same customer ID. Now when these two slaves sync to the master; there will be a conflict.
I know this sounds quite noob; you know you can't hide it.
What would be the best approach to prevent this; rather solving?
I don't think there is one "the best" approach. It depends on system specific details what works best... anyway, some options are:
UUID
Use UUID as customer ID. Since version 2.5 Firebird has some built in support for generating and converting UUIDs.
Segmented generators
On each local slave init the customer ID sequence so that IDs generated by it doesn't overlap with other slaves. Ie if you use 32 bit integers as PK and need max two slaves you dedicate top bit as "slave ID". That means that on first slave you start the sequence from zero while at the second you starti it from 2147483648 (bin 1000 0000 0000 0000 0000 0000 0000 0000). See the ALTER SEQUENCE statement for how to set the sequence's starting value.
ID server
You could have a service which generates IDs. Whenever slave needs ID for a customer it recuests it from a special service. To help with the perfomance it probably makes sense to request new IDs in patches and cache them for later use.
I suppose the system is legacy and you don't have the ability to change how it works. In a similar occasion I have solved this problem letting each slave generating sequences. I've added a write filter in symmetricDs on the master node that will intercept each push from a slave and add a unique prefix per slave. If data has to be synced back to the slaves after data is routed to each slave add a write filter to symmetric slave that will strip the added prefix.
For example maximum number of slaves is 99. Let's say slave 1 creates a sequence 198976, assuming the sequence length is 10, use slave's ID, pad left the sequence with zeros and add the slave id as prefix: (0)100198976. If slave 17 generated the same sequence, master node's filter would change it to 1700198976.
If the same data has is changed on the master and has to be sent back to the slave that generated it, write filter on the slave will strip the first two digits (after left padding with 0 in case of one digit slave IDs). Slave 1's sequence from master (0)100198976 will become again 198976; and slave 17's sequence from master 1700198976 will become 198976.
If the whole length of the ID column has been used on the slaves, alter the column on the master by widening the it to accommodate for the width of slave IDs
I am writing a script to monitor redis replication latency in a group of redis slaves managed using sentinel. I am looking at the results of the INFO replication command, which look like this:
# Replication
role:master
connected_slaves:5
slave0:ip=x.x.x.x,port=6379,state=online,offset=22246539656,lag=0
slave1:ip=y.y.y.y,port=6379,state=online,offset=22246538633,lag=1
slave2:ip=z.z.z.z,port=6379,state=online,offset=22247193804,lag=0
slave3:ip=n.n.n.n,port=6379,state=online,offset=22246538633,lag=1
slave4:ip=m.m.m.m,port=6379,state=online,offset=22244239193,lag=1
master_repl_offset:22246539199
repl_backlog_active:1
repl_backlog_size:536870912
repl_backlog_first_byte_offset:21709668288
repl_backlog_histlen:536870912
I had thought that the offset for each slave was a measure of how much data had been replicated so far, so I could look at the difference between the master_repl_offset and the offset values for the various slaves to determine the amount of data not yet replicated. However, in the above output, the offsets for slave0 and slave2 are both higher than for the master. Have I misunderstood what these numbers mean?