Chapter 6. Scaling with Redis Cluster and Sentinel
This chapter first explores a crucial strategy of scaling large datasets with Redis by partitioning, or splitting up, the data across multiple Redis instances. By looking at various algorithms that different groups and projects have taken in sharding data, including one of the most successful efforts to do this with Redis, Twitter's Twemproxy project. This provides the background and history behind one of the biggest changes to Redis in the past few years; the inclusion of Redis cluster into the stable branch of Redis in version 3. We'll move from the Twemproxy approach to sharding Redis instances, to the strategy ultimately adopted and implemented in the Redis cluster. We will then experiment with using a Redis cluster with a couple of large datasets and see how client application code should be modified to be able to use the Redis cluster.
Regardless of the partitioning strategy taken to use Redis with large data, managing...
