Redis Configuration

GraphQL::Enterprise::ObjectCache requires a Redis connection to store cached responses. Unlike OperationStore or rate limiters, this Redis instance should be configured to evict keys as needed.

Data Structure

Under the hood, ObjectCache stores a mapping of queries and objects. Additionally, there are back-references from objects to queries that reference them. In general, like this:

"query1:result" => '{"data":{...}}'
"query1:objects" => ["obj1:v1", "obj2:v2"]

"query2:result" => '{"data":{...}}'
"query2:objects" => ["obj2:v2", "obj3:v1"]

"obj1:v1" => { "fingerprint" => "...", "id" => "...", "type_name" => "..." }
"obj2:v2" => { "fingerprint" => "...", "id" => "...", "type_name" => "..." }
"obj3:v1" => { "fingerprint" => "...", "id" => "...", "type_name" => "..." }

"obj1:v1:queries" => ["query1"]
"obj2:v2:queries" => ["query1", "query2"]
"obj3:v1:queries" => ["query2"]

These mappings enable proper clean-up when queries or objects are expired from the cache. Additionally, whenever ObjectCache finds incomplete data in storage (for example, a necessary key was evicted), then it invalidates the whole query and re-runs it.

Memory Management

Memory consumption is hard to estimate since it depends on how many queries the cache receives, how many objects those queries reference, how big the response is for those queries, and how long the fingerprints are for each object and query. To manage memory, configure the Redis instance with a maxmemory and maxmemory-policy directive, for example:

maxmemory 1gb
maxmemory-policy allkeys-lfu

Additionally, consider conditionally skipping the cache to prioritize your most critical GraphQL traffic.

Redis Cluster

ObjectCache also supports Redis Cluster. To use, pass redis_cluster::

use GraphQL::Enterprise::ObjectCache, redis_cluster: Redis::Cluster.new(...)

Under the hood, it uses query fingerprints as hash tags and each cached result has its own set of object metadata.