Simon Willison’s Weblog

Blogmarks tagged redis

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huey. Charles Leifer’s “little task queue for Python”. Similar to Celery, but it’s designed to work with Redis, SQLite or in the parent process using background greenlets. Worth checking out for the really neat design. The project is new to me, but it’s been under active development since 2011 and has a very healthy looking rate of releases. # 25th February 2019, 7:49 pm

Introduction to Redis Streams. Redis 5.0 is out, introducing the first new Redis data type in several years: streams, a Kafka-like mechanism for implementing a replayable event stream that can be read by many different subscribers. # 18th October 2018, 8:35 am

Scaling a High-traffic Rate Limiting Stack With Redis Cluster. Brandur Leach describes the simple, elegant and performant design of Redis Cluster, and talks about how Stripe used it to scaled their rate-limiting from one to ten nodes. # 26th April 2018, 6:34 pm

Redis Streams and the Unified Log. In which Brandur Leach explores the new Kafka-style streams functionality coming to Redis 4.0, and shows an example of a robust at-least once processing architecture built on a combination of Redis streams and PostgreSQL transactions. I really like the pattern of writing log records to a staging table in PostgreSQL first in order to bundle them up in the same transaction as the originating state change, then have a separate process read them from that table and publish them to Redis. # 8th November 2017, 4:37 pm

Secondary indexing with Redis. I haven’t seen this section of the official Redis documentation before, and it’s absolutely fantastic—well worth reading the whole thing. It talks through various ways in which you can set up indexes in Redis, mainly by leaning on sorted sets—which it turns out will binary lexicographically sort items with the same score. This makes it easy to implement autocomplete with Redis—but if you use them creatively you can implement subject/predicate/object graph searches or even N-dimensional range queries as well. # 7th November 2017, 2 am

walrus. Fascinating collection of Python utilities for working with Redis, by Charles Leifer. There are a ton of interesting ideas in here. It starts with Python object wrappers for Redis so you can interact with lists, sets, sorted sets and Redis hashes using Python-like objects. Then it gets really interesting: walrus ships with implementations of autocomplete, rate limiting, a graph engine (using a sorted set hexastore) and an ORM-style models mechanism which manages secondary indexes and even implements basic full-text search. # 6th November 2017, 1:14 am

Scaling the GitLab database. Lots of interesting details on how GitLab have worked to scale their PostgreSQL setup. They’ve avoided sharding so far, instead opting for database pooling with pgbouncer and read-only replicas using hot standbys. I like the way they deal with replica lag—they store the current WAL position in a redis key for the user every time there’s a write, then use pg_last_xlog_replay_location() on the various replicas to check and see if they have caught up next time the user makes a request that needs to read some data. # 30th October 2017, 8:53 pm

Streams: a new general purpose data structure in Redis. Exciting new Redis feature inspired by Kafka: redis streams, which allow you to construct an efficient, in-memory list of messages (similar to a Kafka log) which clients can read sections of or block against and await real-time delivery of new messages. As expected from Salvatore the API design is clean, obvious and covers a wide range of exciting use-cases. Planned for release with Redis 4 by the end of the year! # 3rd October 2017, 3:25 pm

How we use Redis at Bump. A couple of neat tricks I hadn’t seen before: using Redis to aggregate log files from multiple servers (they all push in to a Redis queue, then one process pulls from the queue and writes to disk), and using Redis blocking queues for RPC by specifying a different temporary queue to return the result. # 16th July 2011, 4:37 pm

HotQueue. A super-simple Python work queue using Redis. The API is neat, and makes clever use of generators for blocking consumption of queue items. # 22nd December 2010, 11:51 am

How we deploy new features. GitHub are experimenting with using Redis for configuration management. I’ve been thinking about this recently too—managing feature flags feels like an ideal use-case for Redis, since it lets you read multiple values on every page access without adding a bunch of extra read traffic on your regular database. # 8th July 2010, 10:04 am

Zero-downtime Redis upgrade discussion. GitHub have a short window of scheduled downtime in order to upgrade their Redis server. I asked in their comments if they’d considered trying to run the upgrade with no downtime at all using Redis replication, and Ryan Tomayko has posted some interesting replies. # 28th May 2010, 2:50 pm

A fast, fuzzy, full-text index using Redis. Interesting twist on building a reverse-index using Redis sets: this one indexes only the metaphones of the words, resulting in a phonetic fuzzy search. # 5th May 2010, 5:51 pm

tempalias.com development diary (via) tempalias.com is a e-mail forwarding service that lets you create an address that will only work for a few days (or a limited number of messages) and will forward messages on to your real account. It’s implemented using Node.js and Redis and the code is released under an MIT license. Philip Hofstetter, the developer, maintained a detailed development diary throughout which is worth reading if you’re interested in Node.js. # 23rd April 2010, 7:36 pm

Redis weekly update #3—Pub/Sub and more. Redis is now a publish/subscribe server—and it ended up only taking 150 lines of C code since Redis internals were already based on that paradigm. # 30th March 2010, 3:15 pm

VMware: the new Redis home. Redis creator Salvatore Sanfilippo is joining VMWare to work on Redis full time. Sounds like a good match. # 16th March 2010, 11:26 am

Redis weekly update #1—Hashes and... many more! Hashes were the big missing data type in Redis—support is only partial at the moment (no ability to list all keys in a hash or delete a specific key) but at the rate Redis is developed I expect that to be fixed within a week or two. # 13th March 2010, 12:06 am

Cache Machine: Automatic caching for your Django models. This is the third new ORM caching layer for Django I’ve seen in the past month! Cache Machine was developed for zamboni, the port of addons.mozilla.org to Django. Caching is enabled using a model mixin class (to hook up some post_delete hooks) and a custom caching manager. Invalidation works by maintaining a “flush list” of dependent cache entries for each object—this is currently stored in memcached and hence has potential race conditions, but a comment in the source code suggests that this could be solved by moving to redis. # 11th March 2010, 7:35 pm

Node.js, redis, and resque (via) Paul Gross has been experimenting with Node.js proxies for allowing web applications to be upgraded without missing any requests. Here he places all incoming HTTP requests in a redis queue, then has his backend Rails servers consume requests from the queue and push the responses back on to a queue for Node to deliver. When the backend application is upgraded, requests remain in the queue and users see a few seconds of delay before their request is handled. It’s not production ready yet (POST requests aren’t handled, for example) but it’s a very interesting approach. # 28th February 2010, 11:02 pm

A Collection Of Redis Use Cases. Lots of interesting case studies here, collated by Mathias Meyer. Redis clearly shines for anything involving statistics or high volumes of small writes. # 16th February 2010, 3:04 pm

Redis in Practice: Who’s Online? Using Redis to implement a “which of your friends are online now” feature, by maintaining a set of active user IDs for every minute, then intersecting the past five minutes of user IDs with a set containing the IDs of your friends. # 14th February 2010, 5:17 pm

Redis Virtual Memory: the story and the code. Fascinating overview of the virtual memory feature coming to Redis 2.0, which will remove the requirement that all Redis data fit in RAM. Keys still stay in RAM, but rarely accessed values will be swapped to disk. 16 GB of RAM will be enough to hold 100 million keys, each with a value as large as you like. # 9th February 2010, 3:59 pm

Distributed lock on top of memcached. A simple Python context manager (taking advantage of the with statement) that implements a distributed lock using memcached to store lock state: “memcached_lock can be used to ensure that some global data is only updated by one server”. Redis would work well for this kind of thing as well. # 1st February 2010, 10:15 am

Help pick the best photos, but watch out, it’s addictive! My favourite WildlifeNearYou feature yet—our new tool asks you to pick the best from two photos, then uses the results to rank all of the photos for each species. It’s surprisingly addictive—we had over 5,000 votes in the first two hours, peaking at 4 or 5 votes a second. The feature seems to be staying nice and speedy thanks to Redis under the hood. Photos in the top three for any given species display a medal on their photo page. # 25th January 2010, 12:36 am

BLPOP and BRPOP in Redis. Added over Christmas—Redis now has blocking list pop operations. This means you can use Redis to drive a queue server without the need for polling—simply BLPOP against a key and, if it’s empty, your client will block until another client pushes an item on to the list. Multiple clients can block against the same key and only the first client will return when an item becomes available. # 7th January 2010, 10:50 pm

New Redis ZINCRBY command (via) Just added to Redis, a command which increments the “score” for an item in a sorted set and reorders the set to reflect the new scores. Looks ideally suited to real time stats, and I’m sure there are plenty of other exciting uses for it. # 22nd December 2009, 8:38 pm

Introducing Resque. A new background worker management queue developed at GitHub, using Redis for the persistence layer. The blog post explains both the design and the shortcomings of previous solutions at length. Within 24 hours of the release code an external developer, Adam Cooke, has completely reskinned the UI. # 4th November 2009, 8:20 pm

How We Made GitHub Fast. Detailed overview of the new GitHub architecture. It’s a lot more complicated than I would have expected—lots of moving parts are involved in ensuring they can scale horizontally when they need to. Interesting components include nginx, Unicorn, Rails, DRBD, HAProxy, Redis, Erlang, memcached, SSH, git and a bunch of interesting new open source projects produced by the GitHub team such as BERT/Ernie and ProxyMachine. # 21st October 2009, 9:14 pm

TwitterAlikeExample—redis. Excellent example of how you design a moderately complex system against a scalable key-value store (in this case redis). Most “how to build Twitter” code examples fail to address the hard problem of scaling user inboxes, but this one tackles it head on. # 21st May 2009, 11:14 pm

redis (via) An in-memory scalable key/value store but with an important difference: this one lets you perform list and set operations against keys, opening up a whole new set of possibilities for application development. It’s very young but already supports persistence to disk and master-slave replication. # 15th March 2009, 1:32 pm