Good day!
Suppose we have a redis-master and several slaves. The master goal is to store all data while slaves are used for quering data for users. Hovewer quering is a bit complex and some temporary data needs to be stored. And also I want to cache the query result for a couple of minutes.
How should I configure replication to save temporary data and caches?
Redis slaves have optional support to accept writes, however you have to understand a few limitations of writable slaves before to use them, since they have non trivial issues.
Keys created on the slaves will not support expires. Actually in recent versions of Redis they appear to work but are actually leaked instead of expired, until the next time you resynchronize the slave with the master from scratch or issue FLUSHALL or alike. There are deep reasons for this issue... it is currently not clear if we'll deprecate writable slaves at all, find a solution, or deny expires for writable slaves.
You may want, anyway, to use a different Redis numerical DB (SELECT command) in order to store your intermediate data (you may use MULTI/.../MOVE/EXEC transaction in order to generate your intermediate results in the currently selected DB where data belongs, and MOVE the keys off to some other DB, so it will be clear if keys are accumulating and you can FLUSHDB from time to time).
The keys you create on your slave are volatile, they may go away in any moment when the master will resynchronize with the slave. Does not look like an issue for you since if they key is no longer there, you could recompute, but care should be take,
If you elect this slave into a master you have additional keys inside.
So there are definitely things to take in mind in this setup, however it is doable in some way. However you may want to consider alternative strategies.
Lua scripts on the slave side in order to filter your data inside Lua. Not as fast as Redis C commands often.
Precomputation of data directly in the actual data set in order to make your queries possible just using read only commands.
MIGRATE in order to migrate interesting keys from a slave to an instance (another master) designed specifically to perform post-computations.
Hard to tell what's the best strategy without in-depth analysis of the actual use case / problem, but I hope this general guidelines help.
Related
we have a small project, and we want to start using a non-clustered version of either keydb or redis. I've read a lot of reviews. I would like to hear more. Which system will be easier to turn into a cluster in the future, and maybe transfer to kubernetes?
Regarding scaling/simplicity, I would point out both Redis and KeyDB are able to turn into sharded clusters, or add replica nodes, KeyDB also offers active replication (some limits, but avoids sentinel). Both are also compatible with RESP protocol so can use any Redis client.
A few points relevant to both KeyDB and Redis when trying to simplify scaling in the future (ie. moving to a sharded data set):
Ensure you use a client that is compatible with cluster-mode enabled as not all are
Be careful of how you use transactions. If you rely heavily on transactions that hit multiple keys, you may need to rethink this when spreading data across multiple shards.
The point above also applies to certain commands that can hit multiple shards such as SCAN, KEYS, batch requests (ie. MGET), SUNION, etc. Planning how you structure your data may make this easier when you decide to scale up.
Could you please answer these 2 questions and correct me if wrong.
I assume Both Redis Database and Redis Cache are stored in Memory and not in Disk. Am I correct?
If Yes, What are the major difference between both. I am assuming both are stored in memory and it should not make much difference between them both. I mean the speed should be the same as they are in memory only. Do we still need Cache again?
Could you please tell me what are the differences and advantages between the both.
Second Question: Can the server restart remove all data in the Redis database? Cache must be deleted for sure I believe.
Thanks
Not sure what do you mean?
Redis is a product first of all - its an in-memory data structures store.
Depending on its configurations it can be targeted to different use cases:
Database
Cache
Even message broker
If you're coming from the cloud world, cloud providers can call this "Cache" and this means that they offer a redis that is pre-configured to be used as a cache (remove the oldest records when the memory becomes next to be fully utilized, etc).
But after you'll you will work with some kind of redis client that will interact with remote redis server.
Two issues
Do lua scripts really solve all cases for redis transactions?
What are best practices for asynchronous transactions from one client?
Let me explain, first issue
Redis transactions are limited, with an inability to unwatch specific keys, and all keys being unwatched upon exec; we are limited to a single ongoing transaction on a given client.
I've seen threads where many redis users claim that lua scripts are all they need. Even the redis official docs state they may remove transactions in favour of lua scripts. However, there are cases where this is insufficient, such as the most standard case: using redis as a cache.
Let's say we want to cache some data from a persistent data store, in redis. Here's a quick process:
Check cache -> miss
Load data from database
Store in redis
However, what if, between step 2 (loading data), and step 3 (storing in redis) the data is updated by another client?
The data stored in redis would be stale. So... we use a redis transaction right? We watch the key before loading from db, and if the key is updated somewhere else before storage, storage would fail. Great! However, within an atomic lua script, we cannot load data from an external database, so lua cannot be used here. Hopefully I'm simply missing something, or there is something wrong with our process.
Moving on to the 2nd issue (asynchronous transactions)
Let's say we have a socket.io cluster which processes various messages, and requests for a game, for high speed communication between server and client. This cluster is written in node.js with appropriate use of promises and asynchronous concepts.
Say two requests hit a server in our cluster, which require data to be loaded and cached in redis. Using our transaction from above, multiple keys could be watched, and multiple multi->exec transactions would run in overlapping order on one redis connection. Once the first exec is run, all watched keys will be unwatched, even if the other transaction is still running. This may allow the second transaction to succeed when it should have failed.
These overlaps could happen in totally separate requests happening on the same server, or even sometimes in the same request if multiple data types need to load at the same time.
What is best practice here? Do we need to create a separate redis connection for every individual transaction? Seems like we would lose a lot of speed, and we would see many connections created just from one server if this is case.
As an alternative we could use redlock / mutex locking instead of redis transactions, but this is slow by comparison.
Any help appreciated!
I have received the following, after my query was escalated to redis engineers:
Hi Jeremy,
Your method using multiple backend connections would be the expected way to handle the problem. We do not see anything wrong with multiple backend connections, each using an optimistic Redis transaction (WATCH/MULTI/EXEC) - there is no chance that the “second transaction will succeed where it should have failed”.
Using LUA is not a good fit for this problem.
Best Regards,
The Redis Labs Team
I'm a newbie to Redis and I was wondering if someone could help me to understand if it can be the right tool.
This is my scenario:
I have many different nodes, everyone behaving like a master and accepting clients connections to read and write a few geographical data data and the timestamp of the incoming record.
Each master node could be hosted onto a drone that only randomly get in touch and can comunicate with others, accordind to network conditions; when this happens they should synchronize their data according to their age (only the ones more recent than a specified time).
Is there any way to achieve this by Redis or do I have to implement this feature at application level?
I tried master/slaves configuration without success and I was wondering if Redis Cluster can somewhat meet my neeeds.
I googled around, but what I found had not an answer good for me
https://serverfault.com/questions/717406/redis-multi-master-replication
Using Redis Replication on different machines (multi master)
Teo, as a matter of fact, redis don't have a multi master replication.
And the cluster shard it's data through different instances. Say you have only two redis instances. Instance1 will accept store and retrieve instance1 and instance2 data. But he will ask for, and store in, instance2 every key that does not belong to his shard.
This is not, I think, really what you want. You could give a try to PostgreSQL+BDR as PostgreSQL supports nosql store and BDR provides a real master master replication (https://wiki.postgresql.org/wiki/BDR_Project) if that's really what you need.
I work with both today (and also MongoDB). Each one with a different goal. Redis would provide a smaller overhead and memory use, fast connection and fast replication. But it won't provide multi master (if you really need it).
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