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Tobi Autor Dezember at Sibylle Federer Januar at Snorri 5. Tobi Autor 5. Timmeiy März at Manos Since it is just a game and not a serious business application we do not require any specific delivery guarantees or consistency model for our distributed game state.
If one in hundred games crashes due to an irrecoverable inconsistency in the game state we can live with that.
What we are concerned about is performance. Latency can significantly impact the gaming experience. That is why one important aspect was low latency.
The storage medium should also be able to horizontally scale out in the form of a cluster and it should support some kind of publish and subscribe mechanism which we can leverage to distribute events across the instances.
With those requirements the choice fell on redis since it is an in-memory key-value store which focuses on performance and it offers a publish and subscribe mechanism.
Redis also supports scaling out with Redis-Cluster. So we were settled on Redis. But there was another elephant in the room. In which way do we save the state on the redis?
The game loop emits events which are distributed using build-in redis and publish and subscribe mechanism, which we extended to also save all events in order in a redis sorted set.
So all the events of a game are saved in a sorted set per game. The maximum events per game can not get very large since there is a maximum amount of rounds which can be played.
So having the game state itself saved in the redis and editing it with every event within a lock seems very expensive compared to just accumulating it from the events in the sorted set, which can be retrieved without any lock in a read only operation, whenever it is needed.
That is why we settled on pure event sourcing for the game state. So for example whenever a player tries to submit a picture all the events of the game are retrieved from the sorted set and accumulated to the current game state using the state pattern.
If the current state is RoundStarted and the player submits for this specific round and the player has not submitted for this round yet the submission is accepted and the picture is rated which leads to the following ImageAddedEvent.
So the state is important for validating client events. Although event sourcing significantly reduced the amount of locks we need within the game logic there is still logic that can lead to race conditions and therefore the need of locks.
For example while players are submitting a picture we need a mechanism that protects against a player submitting a picture twice which could be possible within the time frame of the AWS API calls which are used for giving a score to the picture since the ImageAddedEvent is emitted after this process was successful.
This is a common race condition which can be prevented by putting a lock around the logic from retrieving the state to emitting the event.
For locking we use the popular Redlock algorithm, which has its problems though which can lead to inconsistencies according to an article by Martin Kleppmann:.
There is optimistic locking built into redis, but only on specific key value pairs using WATCH. This does not offer quite what we want and because as mentioned earlier unlikely inconsistencies are not the end of the world for our project we decided to stick with Redlock.
Redis does only offer very primitive basic data types in the form of byte arrays and strings. The higher data types like the redis sorted set are just containers for those primitive data types.
That means if you want to store objects in redis you need lots of serialization and deserialization which introduces new problems. One problem is that serialization, especially non-binary serialization, can be quite expensive.
We ignored the expense of non-binary serialization in our app for the time being. This results in no call-by-reference but only call-by-value, so if you introduce for example cyclic dependencies in your data objects you need some kind of special algorithm to deal with it.
We did not want to have constraints on the objects which are serialized nor annoying manual instantiation of an actual class instance from the object.
That is why we created a small library which introduces a TypeScript Class Decorator Serializable for the classes you want to serialize and a function which deserializes and instantiates to the actual class instance.
This helped to increase productivity while working with redis as an object store. Under the hood it makes use of TypeScript Decorators, ES6 Object functions and an algorithm for dealing with cyclic dependencies.
From the beginning it was clear that our application needed a websocket interface for bidirectional communication between client and server.
Since NestJS provides Websocket support out of the box with socket. The biggest benefit of using socket. In retrospect though I would choose a pure websocket API instead of socket.
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The goal of pictionary is simple! Every round, one person gets to choose a word and draw it to their best ability.
The rest of the players have to guess what they think the word is as fast as they can.