“Originally published in Mar 2015 at ObjectRocket.com/blog”
Redis® is an awesome tool, and the tech community loves it! It’s come a long way from being a small personal project from Antirez to being an industry-standard in-memory data storage. With that comes a set of best practices for using Redis properly. In this article, we explore ten quick tips on using Redis correctly.
1. Stop using keys
Okay, so maybe shouting at you isn’t a great way to start this article. But it’s quite possibly the most important point. Too often,
I look at a Redis instance, pull up a quick commandstats, and see a glaring KEYS staring right back at me. In all fairness,
coming from a programmatical standpoint, it would make sense to have pseudocode similar to this:
for key in 'keys *':
doAllTheThings()
But when you have, say, 13 million keys, things are going to slow down. Since KEYS is O(n) where n is the number of keys returned, your complexity is bound by the database size. Also, during this whole operation, you can’t run anything else against your instance.
As a substitute, check out SCAN, which allows you to scan through your database in increments instead. This operates on an iterator so you can stop and go as you see fit.
2. Find out what’s slowing down Redis
Because Redis doesn’t have the most verbose of logs, it’s often hard to trackdown what exactly is going on inside your instance.
Luckily Redis provides you with the commandstat utility to show you details similar to the following example:
127.0.0.1:6379> INFO commandstats
# Commandstats
cmdstat_get:calls=78,usec=608,usec_per_call=7.79
cmdstat_setex:calls=5,usec=71,usec_per_call=14.20
cmdstat_keys:calls=2,usec=42,usec_per_call=21.00
cmdstat_info:calls=10,usec=1931,usec_per_call=193.10
This gives you a breakdown of all the commands, how many times you’ve run them, and the number of microseconds it took to execute
(total and avg per call). To reset, run CONFIG RESETSTAT, and you’ve got a brand new slate.
3. Use Redis-Benchmark as a baseline, not the gospel truth
Salvatore, the creator of Redis, underlined that: “To test Redis doing GET/SET is like testing a Ferrari to see how good it
is at cleaning the mirror when it rains.” A lot of times, people come to me wondering why their Redis-Benchmark results are less
than optimal. But we have to take into account many different factors, such as:
- Client-side limitations
- Difference in versioning
- On-going tests
Redis-Benchmark provides an awesome baseline to ensure your redis-server is behaving normally, but it should never be considered
a true load test. Load tests need reflec how your application behaves in an environment as close to production as possible.
4. Hashes are your best friends
Invite hashes over for dinner. Wine and dine hashes. You’ll be amazed at what happiness they can bring if you just give them a chance. I’ve seen one too many key structures like the following before:
foo:first_name
foo:last_name
foo:address
In that example, foo might be a username for a user, and each one of those lines is a separate key. This adds room for errors and adds unnecessary keys to the fold. Instead, consider a hash. Suddenly you’ve only got one key:
127.0.0.1:6379> HSET foo first_name "Joe"
(integer) 1
127.0.0.1:6379> HSET foo last_name "Engel"
(integer) 1
127.0.0.1:6379> HSET foo address "1 Fanatical Pl"
(integer) 1
127.0.0.1:6379> HGETALL foo
1) "first_name"
2) "Joe"
3) "last_name"
4) "Engel"
5) "address"
6) "1 Fanatical Pl"
127.0.0.1:6379> HGET foo first_name
"Joe"
5. Set the TTL (Time To Live)!
Whenever possible, take advantage of expiring keys. A perfect example is storing something like temporary authentication keys. When you retrieve the auth key, using OAUTH as an example, you often get an expiration time. When you set the key, set it with the same expiration, and Redis cleans up for you! No more need for KEYS to iterate through all those keys.
6. Choosing the proper eviction policy
While we’re on the topic of cleaning up keys, let’s touch on eviction. When your Redis instance fills up, Redis tries to evict keys.
Depending on your use case, we highly recommend volatile-lru—assuming you have expiring keys. If you run something like a
cache and don’t have an expiry set, you could consider allkeys-lru. We recommend that you check out the available options
here.
7. If Your Data is important, put in a try/except
If it’s absolutely critical for data to make it to your Redis instance, I heavily recommend putting in a try/except. Because most
people configure Redis clients to fire-and-forget, you should always plan for when a key doesn’t actually make it to the database.
The complexity this adds to your Redis call is next to nothing in this case, and you can ensure your important data makes it to where
it should be.
8. Don’t flood one instance
Whenever possible, split up the workload between multiple Redis instances. Redis Cluster is available as of version 3.0.0. Redis Cluster enables you to break apart keys among sets of given primaries and secondaries based on key ranges. You can find a full breakdown of the magic behind Redis Cluster here. And if you’re looking for a tutorial, then look no further. You can find it here. If clustering is not an option, consider namespacing and distributing your keys among multiple instances. You can find an amazing write-up on partitioning your data on the redis.io website.
9. More cores = better performance, right?!
Wrong. Redis is a single-threaded process and will, at most, consume two cores if you have persistence enabled. Unless you plan on running multiple instances on the same host—hopefully only for dev testing, in that case—you shouldn’t need more than two cores for a Redis instance.
10. HA all the things!
Redis Sentinel is now very well tested, and many users have it running in production (Rackspace ObjectRocket included). If you rely heavily on Redis for your application, then you need to consider an high availability (HA) solution to keep you online. Of course, if you don’t want to manage all of that yourself, Rackspace ObjectRocket offers our HA platform with 24×7 support. Give it a shot.
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