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 have multiple servers that all store set members in a shared Redis cache. When the cache fills up, I need to persist the data to disk to free up RAM. I then plan to parse the dumped data such that I will be able to combine all of the values that belong to a given key in MongoDB.
My first plan was to have each server process attempt an sadd operation. If the request fails because Redis has reached maxmemory, I planned to query for each of my set keys, and write each to disk.
However, I am wondering if there is a way to use one of the inbuilt persistence methods in Redis to write the Redis data to disk and delete the key/value pairs after writing. If this is possible I could just parse the rdb dump and work with the data in that fashion. I'd be grateful for any help others can offer on this question.
Redis' persistence is meant to be used for whatever's in the RAM. Put differently, you can't persist what ain't in RAM.
To answer your question: no, you can't use persistence to "offload" data from RAM.
Redis SAVE and BGSAVE commands dump the complete Redis data to a persistent file.
But is there a way to dump only one DB index?
I am using the same Redis server with multiple DB indices.
I use DB 0 as config which is edited manually and contains just a small number of keys. I wish to dump this to a file as a config snapshot (versioned) to keep track of manual changes in the prod environment.
The rest of the DBs have a large number of items, that will take too long to dump, and I don't need to back them up.
Redis' persistence scope is the entire instance, meaning all shared/numbered databases and all keys in them. Saving only a subset of these is not supported.
Instead, use two independent Redis instances and configure each to persist (or not) per your needs. The overhead of running an insurance is a few megabytes so it is practically negligible.
I understand that Redis serves all data from memory, but does it persist as well across server reboot so that when the server reboots it reads into memory all the data from disk. Or is it always a blank store which is only to store data while apps are running with no persistence?
I suggest you read about this on http://redis.io/topics/persistence . Basically you lose the guaranteed persistence when you increase performance by using only in-memory storing. Imagine a scenario where you INSERT into memory, but before it gets persisted to disk lose power. There will be data loss.
Redis supports so-called "snapshots". This means that it will do a complete copy of whats in memory at some points in time (e.g. every full hour). When you lose power between two snapshots, you will lose the data from the time between the last snapshot and the crash (doesn't have to be a power outage..). Redis trades data safety versus performance, like most NoSQL-DBs do.
Most NoSQL-databases follow a concept of replication among multiple nodes to minimize this risk. Redis is considered more a speedy cache instead of a database that guarantees data consistency. Therefore its use cases typically differ from those of real databases:
You can, for example, store sessions, performance counters or whatever in it with unmatched performance and no real loss in case of a crash. But processing orders/purchase histories and so on is considered a job for traditional databases.
Redis server saves all its data to HDD from time to time, thus providing some level of persistence.
It saves data in one of the following cases:
automatically from time to time
when you manually call BGSAVE command
when redis is shutting down
But data in redis is not really persistent, because:
crash of redis process means losing all changes since last save
BGSAVE operation can only be performed if you have enough free RAM (the amount of extra RAM is equal to the size of redis DB)
N.B.: BGSAVE RAM requirement is a real problem, because redis continues to work up until there is no more RAM to run in, but it stops saving data to HDD much earlier (at approx. 50% of RAM).
For more information see Redis Persistence.
It is a matter of configuration. You can have none, partial or full persistence of your data on Redis. The best decision will be driven by the project's technical and business needs.
According to the Redis documentation about persistence you can set up your instance to save data into disk from time to time or on each query, in a nutshell. They provide two strategies/methods AOF and RDB (read the documentation to see details about then), you can use each one alone or together.
If you want a "SQL like persistence", they have said:
The general indication is that you should use both persistence methods if you want a degree of data safety comparable to what PostgreSQL can provide you.
The answer is generally yes, however a fuller answer really depends on what type of data you're trying to store. In general, the more complete short answer is:
Redis isn't the best fit for persistent storage as it's mainly performance focused
Redis is really more suitable for reliable in-memory storage/cacheing of current state data, particularly for allowing scalability by providing a central source for data used across multiple clients/servers
Having said this, by default Redis will persist data snapshots at a periodic interval (apparently this is every 1 minute, but I haven't verified this - this is described by the article below, which is a good basic intro):
http://qnimate.com/redis-permanent-storage/
TL;DR
From the official docs:
RDB persistence [the default] performs point-in-time snapshots of your dataset at specified intervals.
AOF persistence [needs to be explicitly configured] logs every write operation received by the server, that will be played again at server startup, reconstructing the
original dataset.
Redis must be explicitly configured for AOF persistence, if this is required, and this will result in a performance penalty as well as growing logs. It may suffice for relatively reliable persistence of a limited amount of data flow.
You can choose no persistence at all.Better performance but all the data lose when Redis shutting down.
Redis has two persistence mechanisms: RDB and AOF.RDB uses a scheduler global snapshooting and AOF writes update to an apappend-only log file similar to MySql.
You can use one of them or both.When Redis reboots,it constructes data from reading the RDB file or AOF file.
All the answers in this thread are talking about the possibility of redis to persist the data: https://redis.io/topics/persistence (Using AOF + after every write (change)).
It's a great link to get you started, but it is defenently not showing you the full picture.
Can/Should You Really Persist Unrecoverable Data/State On Redis?
Redis docs does not talk about:
Which redis providers support this (AOF + after every write) option:
Almost none of them - redis labs on the cloud does NOT provide this option. You may need to buy the on-premise version of redis-labs to support it. As not all companies are willing to go on-premise, then they will have a problem.
Other Redis Providers does not specify if they support this option at all. AWS Cache, Aiven,...
AOF + after every write - This option is slow. you will have to test it your self on your production hardware to see if it fits your requirements.
Redis enterpice provide this option and from this link: https://redislabs.com/blog/your-cloud-cant-do-that-0-5m-ops-acid-1msec-latency/ let's see some banchmarks:
1x x1.16xlarge instance on AWS - They could not achieve less than 2ms latency:
where latency was measured from the time the first byte of the request arrived at the cluster until the first byte of the ‘write’ response was sent back to the client
They had additional banchmarking on a much better harddisk (Dell-EMC VMAX) which results < 1ms operation latency (!!) and from 70K ops/sec (write intensive test) to 660K ops/sec (read intensive test). Pretty impresive!!!
But it defenetly required a (very) skilled devops to help you create this infrastructure and maintain it over time.
One could (falsy) argue that if you have a cluster of redis nodes (with replicas), now you have full persistency. this is false claim:
All DBs (sql,non-sql,redis,...) have the same problem - For example, running set x 1 on node1, how much time it takes for this (or any) change to be made in all the other nodes. So additional reads will receive the same output. well, it depends on alot of fuctors and configurations.
It is a nightmare to deal with inconsistency of a value of a key in multiple nodes (any DB type). You can read more about it from Redis Author (antirez): http://antirez.com/news/66. Here is a short example of the actual ngihtmare of storing a state in redis (+ a solution - WAIT command to know how much other redis nodes received the latest change change):
def save_payment(payment_id)
redis.rpush(payment_id,”in progress”) # Return false on exception
if redis.wait(3,1000) >= 3 then
redis.rpush(payment_id,”confirmed”) # Return false on exception
if redis.wait(3,1000) >= 3 then
return true
else
redis.rpush(payment_id,”cancelled”)
return false
end
else
return false
end
The above example is not suffeint and has a real problem of knowing in advance how much nodes there actually are (and alive) at every moment.
Other DBs will have the same problem as well. Maybe they have better APIs but the problem still exists.
As far as I know, alot of applications are not even aware of this problem.
All in all, picking more dbs nodes is not a one click configuration. It involves alot more.
To conclude this research, what to do depends on:
How much devs your team has (so this task won't slow you down)?
Do you have a skilled devops?
What is the distributed-system skills in your team?
Money to buy hardware?
Time to invest in the solution?
And probably more...
Many Not well-informed and relatively new users think that Redis is a cache only and NOT an ideal choice for Reliable Persistence.
The reality is that the lines between DB, Cache (and many more types) are blurred nowadays.
It's all configurable and as users/engineers we have choices to configure it as a cache, as a DB (and even as a hybrid).
Each choice comes with benefits and costs. And this is NOT an exception for Redis but all well-known Distributed systems provide options to configure different aspects (Persistence, Availability, Consistency, etc). So, if you configure Redis in default mode hoping that it will magically give you highly reliable persistence then it's team/engineer fault (and NOT that of Redis).
I have discussed these aspects in more detail on my blog here.
Also, here is a link from Redis itself.
Is Redis memory only store like memcached or does it write the data to the disk? If it does write to the disk, how often is the disk written to?
Redis persistence is described in detail here:
http://redis.io/topics/persistence
By default, redis performs snapshotting:
By default Redis saves snapshots of the dataset on disk, in a binary file called dump.rdb. You can configure Redis to have it save the dataset every N seconds if there are at least M changes in the dataset, or you can manually call the SAVE or BGSAVE commands.
For example, this configuration will make Redis automatically dump the dataset to disk every 60 seconds if at least 1000 keys changed: save 60 1000
Another good reference is this link to the author's blog where he tries to explain how redis persistance works:
http://antirez.com/post/redis-persistence-demystified.html
Redis holds all data in memory. If the size of an application's data is too large for that, then Redis is not an appropriate solution.
However, Redis also offers two ways to make the data persistent:
1) Snapshots at predefined intervals, which may also depend on the number of changes. Any changes between these intervals will be lost at a power failure or crash.
2) Writing a kind of change log at every data change. You can fine-tune how often this is physically written to the disk, but if you chose to always write immediately (which will cost you some performance), then there will be no data loss caused by the in-memory nature of Redis.