Redis Cluster

How to install

1. Clone the repository
2. Run docker compose up -d
3. Run docker inspect -f '{{range .NetworkSettings.Networks}}{{.IPAddress}}{{end}}' redis-node-1 to get the IP address of the first node
4. Repeat the previous step for the other nodes

Run docker exec -it redis-node-1 redis-cli --cluster create <ip1>:6379 <ip2>:6379 <ip3>:6379 <ip4>:6379 <ip5>:6379 <ip6>:6379 --cluster-replicas 1

Testing the cluster

1. Run docker exec -it redis-node-1 redis-cli -c to connect to the first node
2. Run cluster info to get information about the cluster
3. Run cluster nodes to get information about the nodes

Trying redis

1. Run set key value to set a key
2. Run get key to get the value of the key
3. Run keys * to get all the keys
4. Run del key to delete a key
5. Run flushall to delete all keys
6. Run exit to exit the redis-cli

Create a key in one node and try to get it from another node. You will see that the key is available in all nodes.

Hashes

• Run hset user:1 name "John Doe" to set a hash
• Run hget user:1 name to get the value of the hash
• Run hgetall user:1 to get all the values of the hash
• Run hmset user:1 name "John Doe" age 30 to set multiple values in a hash
• Run hmget user:1 name age to get multiple values of the hash
• Run hdel user:1 age to delete a value of the hash

Lists

• Run lpush list 1 2 3 4 5 to create a list
• Run lrange list 0 -1 to get all the values of the list
• Run lpop list to remove the first element of the list
• Run rpop list to remove the last element of the list
• Run ltrim list 0 2 to remove all elements of the list except the first three

Sets

• Run sadd set 1 2 3 4 5 to create a set
• Run smembers set to get all the values of the set
• Run srem set 1 to remove a value of the set

Sorted Sets

• Run zadd sorted-set 1 one 2 two 3 three 4 four 5 five to create a sorted set
• Run zrange sorted-set 0 -1 to get all the values of the sorted set
• Run zrange sorted-set 0 -1 withscores to get all the values of the sorted set with the scores
• Run zrem sorted-set one to remove a value of the sorted set

Expiring keys

• Run set key value to set a key
• Run expire key 10 to set the key to expire in 10 seconds
• Run ttl key to get the time to live of the key Wait 10 seconds and run get key to see that the key is no longer available
• Run setex key 10 value to set a key with an expiration time

Using Redis in a project

In this repository, you have a index.py file that shows how to connect to the Redis cluster using the redis library. Run docker compose --profile testing up -d to start the testing environment, it will add a new container that will run the index.py file. See the logs of the container to see the output of the script using docker logs -f python-project.

An existing project

I have this project https://github.com/Ayfri/UF_Project_B3 which is my end of year project for my third year at Ynov. We have to make BigQuery requests to get data of GDELT project and then use this data to make predictions. But each request takes a lot of time, around 30 seconds, so I thought about using Redis to cache the results of the requests.

So in this commit : 3c8aa9 I added a Redis instance in a Docker container and I used it to cache the results of the requests.

I used the redis library to connect to the Redis instance and I used the set and get methods to cache the results, also using JSON serialization to store complex data.

Redis integration introspection

Redis is great for caching and simple key-value storage thanks to its speed, scalability, and ease of use.

Pros

• Blazingly fast thanks to in-memory data storage and efficient data structures.
• Highly scalable with sharding and replication strategies.
• Simple data model and minimalistic commands make it easy to learn and integrate.
• Excellent for caching to improve application performance.
• Rich set of data structures like strings, hashes, lists, sets, etc.

Cons

• Data persistence requires configuration and can be challenging for high-write scenarios.
• Limited query capabilities compared to traditional databases or data warehouses.
• Memory usage can grow quickly with large datasets or memory-intensive data structures.
• Not well-suited for complex relational data or join operations.
• Limited transaction support may not meet strong consistency requirements.

I actually use Redis Stack Server in a private project for storing a large amount of complex data, and it works perfectly. It also gives us RedisSearch and RedisTimeSeries modules that we use for more advanced data management and querying. Before that, we were using local files, and that was a mess to manage and query. Redis was much faster.

One good tool present in the Redis environment is Redis Insight, a graphical user interface that gives Redis users a powerful way to visualize and interact with their data. Redis Insight allows viewing databases, querying keys and values, and executing common Redis commands through an intuitive interface. It also integrates tightly with Redis, enabling real-time monitoring and command inspection capabilities.

While Redis has limitations, it shines for use cases like caching, session management, real-time messaging, and scenarios needing high-performance data access with simple data structures. For more complex requirements, it's often combined with other solutions or Redis Stack Server for enhanced data management and querying capabilities.