We have a single Redis instance with a good amount of data (over 100GB). We also have an empty Redis Cluster with 6 nodes. What would be the best way to move all that data from the stand-alone instance to the Redis Cluster and make it distribute it evenly?
After some searching around, I came across a post detailing how to move data over to a cluster. It may take some time to move lots of data over but this is the best way I've seen so far.
You can read about it here: https://fnordig.de/2014/03/11/redis-cluster-with-pre-existing-data/
You could make it easier by using redis-rdb-tools and a cluster proxy programm like redis-cerberus after you dump data into an RDB file
rdb --command protocol RDB_FILE_PATH | nc PROXY_HOST PROXY_PORT
Piping an AOF file into a proxy maybe doesn't work somehow if the AOF file contains cross-slots commands like RPOPLPUSH (depending on the proxy's implementation). However if you are actually using this kind of commands, you are not supposed to use a cluster.
Related
We are using redis server in production with 6 GB data size, Initially
we thought redis can be used as memory cache only, If it restarts then we can repopulate from the persistants data store with minimal downtime.
Now we realized that re-population of data from persistence store is not a good idea at all, It is causing major service downtime.
We want to evaluate redis persistant option by using RDB and AOF combination.We tried taking RDB snapshot once in a hour and committing to the AOF file with one second interval in test environments. AOF file is growing too big in test environment only. We tried to analyze the AOF file content and noticed that lot of keys we don't want to persist to the disk, We need them only in redis memory.
Is there any way to stop logging certain type of keys (block list keys) while logging to the AOF file
Generally, Redis does not provide a way to exclude certain types of keys from persistency. If you need some keys to persist to disk and others not to, you should use two independent Redis instances - one for each type and configure their persistency settings approriately. Divide and conquer.
Note: it is possible, however, to control what gets persisted in AOF inside the context if a Lua script - see the "Selective replication of commands" section of EVAL's documentation. That said, besides the consistency risks, it would be too much of a hassle to use this approach for what you need imo.
I am using redis version 2.8.3. I want to build a redis cluster. But in this cluster there should be multiple master. This means I need multiple nodes that has write access and applying ability to all other nodes.
I could build a cluster with a master and multiple slaves. I just configured slaves redis.conf files and added that ;
slaveof myMasterIp myMasterPort
Thats all. Than I try to write something into db via master. It is replicated to all slaves and I really like it.
But when I try to write via a slave, it told me that slaves have no right to write. After that I just set read-only status of slave in redis.conf file to false. Hence, I could write something into db.
But I realize that, it is not replicated to my master replication so it is not replicated to all other slave neigther.
This means I could'not build an active-active cluster.
I tried to find something whether redis has active-active cluster capability. But I could not find exact answer about it.
Is it available to build active-active cluster with redis?
If it is, How can I do it ?
Thank you!
Redis v2.8.3 does not support multi-master setups. The real question, however, is why do you want to set one up? Put differently, what challenge/problem are you trying to solve?
It looks like the challenge you're trying to solve is how to reduce the network load (more on that below) by eliminating over-the-net reads. Since Redis isn't multi-master (yet), the only way to do it is by setting up each app server with a master and a slave (to the other master) - i.e. grand total of 4 Redis instances (and twice the RAM).
The simple scenario is when each app updates only a mutually-exclusive subset of the database's keys. In that scenario this kind of setup may actually be beneficial (at least in the short term). If, however, both apps can touch all keys or if even just one key is "shared" for writes between the apps, then you'll need to bake locking/conflict resolution/etc... logic into your apps to consolidate local master and slave differences (and that may be a bit of an overkill). In either case, however, you'll end up with too many (i.e. more than 1) Redises, which means more admin effort at the very least.
Also note that by colocating app and database on the same server you're setting yourself for near-certain scalability failure. What will happen when you need more compute resources for your apps or Redis? How will you add yet another app server to the mix?
Which brings me back to the actual problem you are trying to solve - network load. Why exactly is that an issue? Are your apps so throughput-heavy or is the network so thin that you are willing to go to such lengths? Or maybe latency is the issue that you want to resolve? Be the case as it may be, I recommended that you consider a time-proven design instead, namely separating Redis from the apps and putting it on its own resources. True, network will hit you in the face and you'll have to work around/with it (which is what everybody else does). On the other hand, you'll have more flexibility and control over your much simpler setup and that, in my book, is a huge gain.
Redis Enterprise has had this feature for quite a while, but if you are looking for an open source solution KeyDB is a fork with Active Active support (called Active Replica).
Setting it up is just a little more work than standard replication:
Both servers must have "active-replica yes" in their respective configuration files
On server B execute the command "replicaof [A address] [A port]"
Server B will drop its database and load server A's dataset
On server A execute the command "replicaof [B address] [B port]"
Server A will drop its database and load server B's dataset (including the data it just transferred in the prior step)
Both servers will now propagate writes to each other. You can test this by writing to a key on Server A and ensuring it is visible on B and vice versa.
https://github.com/JohnSully/KeyDB/wiki/KeyDB-(Redis-Fork):-Active-Replica-Support
I'm developing project with redis.My redis configuration is normal redis setup configuration.
I don't know how should I do redis configuration? Master-Slave? Cluster?
Do you have anything suggestion redis configuration for production?
Standard approach would be to have one master and at least one slave. Depending on your I/O requirements and number of ops/sec, you can always have multiple read-only slaves. Slaves can be read from but not written to. So you'll want to design your application to take advantage of doing round-robin requests to the slaves and writes only to the single master.
Depending on your data storage/backup requirement, you can set fsync for append-only mode to be every second. So while this means you can lose up to one second worth of data, it's really much less than that because your slaves serve as hot backups, and they will have the data within milliseconds.
You'll at least want to do a BGSAVE every hour to get a dump.rdp produced. You can then save this file live while the server is still running, and store it to some off-site backup facility.
But if you're just using Redis as a standard memcache replacement and don't care about data, then you can ignore all of this. Much of it will be changing in Redis Cluster in the 3.0 version.
It depends on what your Read/Writes requirements are. Could you give us more informations on that matter ?
I think 10,000 people use instant my application.I persist member login token on redis.It's important for me.If I don't write redis, member don't login on application.
Even a Redis single instance will be enough to process 10K users (start redis-bench to the throughput available), so just to be sure use a Master/Slave configuration with autopromotion of the slave if the master goes down.
Since you want persistence, use RDB (maybe along with AOF), see this topic on Redisio.
Since the redis cluster is still a work in progress, I want to build a simplied one by myselfin the current stage. The system should support data sharding,load balance and master-slave backup. A preliminary plan is as follows:
Master-slave: use multiple master-slave pairs in different locations to enhance the data security. Matsters are responsible for the write operation, while both masters and slaves can provide the read service. Datas are sent to all the masters during one write operation. Use Keepalived between the master and the slave to detect failures and switch master-slave automatically.
Data sharding: write a consistant hash on the client side to support data sharding during write/read in case the memory is not enougth in single machine.
Load balance: use LVS to redirect the read request to the corresponding server for the load balance.
My question is how to combine the LVS and the data sharding together?
For example, because of data sharding, all keys are splited and stored in server A,B and C without overlap. Considering the slave backup and other master-slave pairs, the system will contain 1(A,B,C), 2(A,B,C) , 3(A,B,C) and so on, where each one has three servers. How to configure the LVS to support the redirection in such a situation when a read request comes? Or is there other approachs in redis to achieve the same goal?
Thanks:)
You can get really close to what you need by using:
twemproxy shard data across multiple redis nodes (it also supports node ejection and connection pooling)
redis slave master/slave replication
redis sentinel to handle master failover
depending on your needs you probably need some script listening to fail overs (see sentinel docs) and clean things up when a master goes down
I have a redis as big as 4G on one 4G memory machine,I want to split it into two 2G redis instance so that I can run the two on two different machines.
how to do that?
thx
AFAIK there is no easy way to do it.
One way to do it is to use the redis-rdb-tools package from Sripathi Krishnan. The procedure is:
choose a strategy to shard your data (i.e a function which distributes the keys over the instances)
write a Python script to parse a Redis dump file, connect to several instances, and apply the commands to insert the data on the correct instances
dump the Redis instance
flush the instance
create and start the second instance
run the script on the dump of the first instance
See more information at https://github.com/sripathikrishnan/redis-rdb-tools
you can use redis cluster
Redis Cluster provides a way to run a Redis installation where data is
automatically sharded across multiple Redis nodes.
Every Redis Cluster node requires two TCP connections open.
http://redis.io/topics/cluster-tutorial