Dataloader is a generic utility to be used as part of your application's data fetching layer to provide a simplified and consistent API to perform batching and caching within a request. It is heavily inspired by Facebook's dataloader.
First, install Dataloader using bundler:
To get started, instantiate Dataloader. Each Dataloader instance represents a unique cache. Typically instances are created per request when used within a web-server. To see how to use with GraphQL server, see section below.
Dataloader is dependent on promise.rb (Promise class) which you can use freely for batch-ready code (e.g. loader can return Promise that returns a Promise that returns a Promise). Dataloader will try to batch most of them.
# It will be called only once with ids = [0, 1, 2] loader = Dataloader.new do |ids| User.find(*ids) end # Schedule data to load promise_one = loader.load(0) promise_two = loader.load_many([1, 2]) # Get promises results user0 = promise_one.sync user1, user2 = promise_two.sync
You can pass loaders passed inside context.
UserType = GraphQL::ObjectType.define do
field :name, types.String
end
QueryType = GraphQL::ObjectType.define do
name "Query"
description "The query root of this schema"
field :user do
type UserType
argument :id, !types.ID
resolve ->(obj, args, ctx) {
ctx[:user_loader].load(args["id"])
}
end
end
Schema = GraphQL::Schema.define do
lazy_resolve(Promise, :sync)
query QueryType
end
context = {
user_loader: Dataloader.new do |ids|
User.find(*ids)
end
}
Schema.execute("{ user(id: 12) { name } }", context: context)
You can create loaders by providing a batch loading function.
user_loader = Dataloader.new { |ids| User.find(*ids) }
A batch loading block accepts an Array of keys, and returns a Promise which resolves to an Array or Hash of values.
Dataloader will coalesce all individual loads which occur until first .sync is called on any promise returned by #load or #load_many, and then call your batch function with all requested keys.
user_loader.load(1)
.then { |user| user_loader.load(user.invited_by_id)) }
.then { |invited_by| "User 1 was invited by ${invited_by[:name]}" }
# Elsewhere in your backend
user_loader.load(2)
.then { |user| user_loader.load(user.invited_by_id)) }
.then { |invited_by| "User 2 was invited by ${invited_by[:name]}" }
A naive solution is to issue four SQL queries to get required information, but with Dataloader this application will make at most two queries (one to load users, and second one to load invites).
Dataloader allows you to decouple unrelated parts of your application without sacrificing the performance of batch data-loading. While the loader presents an API that loads individual values, all concurrent requests will be coalesced and presented to your batch loading function. This allows your application to safely distribute data fetching requirements throughout your application and maintain minimal outgoing data requests.
A batch loading function accepts an Array of keys, and returns Array of values or Hash that maps from keys to values (or a Promise that returns such Array or Hash). There are a few constraints that must be upheld:
For example, if your batch function was provided the Array of keys: [ 2, 9, 6 ], you could return one of following:
[
{ id: 2, name: "foo" },
{ id: 9, name: "bar" },
{ id: 6, name: "baz" }
]
{
2 => { id: 2, name: "foo" },
9 => { id: 9, name: "bar" },
6 => { id: 6, name: "baz" }
}
Dataloader provides a memoization cache for all loads which occur withing single instance of it. After #load is called once with a given key, the resulting Promise is cached to eliminate redundant loads.
In addition to relieving pressure on your data storage, caching results per-request also creates fewer objects which may relieve memory pressure on your application:
promise1 = user_loader.load(1)
promise2 = user_loader.load(1)
promise1 == promise2 # => true
Dataloader caching does not replace Redis, Memcache, or any other shared application-level cache. DataLoader is first and foremost a data loading mechanism, and its cache only serves the purpose of not repeatedly loading the same data in the context of a single request to your Application. To do this, it maintains a simple in-memory memoization cache (more accurately: #load is a memoized function).
Avoid multiple requests from different users using the same Dataloader instance, which could result in cached data incorrectly appearing in each request. Typically, Dataloader instances are created when a request begins, and are not used once the request ends.
See Using with GraphQL section to see how you can pass dataloader instances using context.
If a batch load fails (that is, a batch function throws or returns a rejected Promise), then the requested values will not be cached. However if a batch function returns an Error instance for an individual value, that Error will be cached to avoid frequently loading the same Error.
In some circumstances you may wish to clear the cache for these individual Errors:
user_loader.load(1).rescue do |error| user_loader.cache.delete(1) raise error end
In certain uncommon cases, a Dataloader which does not cache may be desirable. Calling Dataloader.new({ cache: nil }) { ... } will ensure that every call to #load will produce a new Promise, and requested keys will not be saved in memory.
However, when the memoization cache is disabled, your batch function will receive an array of keys which may contain duplicates! Each key will be associated with each call to #load. Your batch loader should provide a value for each instance of the requested key.
loader = Dataloader.new({ cache: nil }) do |keys|
puts keys
some_loading_function(keys)
end
loader.load('A')
loader.load('B')
loader.load('A')
// > [ 'A', 'B', 'A' ]
Dataloader is a class for fetching data given unique keys such as the id column (or any other key).
Each Dataloader instance contains a unique memoized cache. Because of it, it is recommended to use one Datalaoder instance per web request. You can use more long-lived instances, but then you need to take care of manually cleaning the cache.
You shouldn't share the same dataloader instance across different threads. This behavior is currently undefined.
Dataloader.new(options = {}, &batch_load)
Create a new Dataloader given a batch loading function and options.
batch_load: A block which accepts an Array of keys, and returns Array of values or Hash that maps from keys to values (or a Promise that returns such value).options: An optional hash of options:
:key A function to produce a cache key for a given load key. Defaults to function { |key| key }. Useful to provide when objects are keys and two similarly shaped objects should be considered equivalent.:cache An instance of cache used for caching of promies. Defaults to Concurrent::Map.new.
#compute_if_absent(key)).nil if you want to disable the cache.:max_batch_size Limits the number of items that get passed in to the batchLoadFn. Defaults to INFINITY. You can pass 1 to disable batching.key [Object] a key to load using batch_load
Returns a Promise of computed value.
You can resolve this promise when you actually need the value with promise.sync.
All calls to #load are batched until the first #sync is encountered. Then is starts batching again, et cetera.
keys [Array] list of keys to load using batch_load
Returns a Promise of array of computed values.
To give an example, to multiple keys:
promise = loader.load_many(['a', 'b']) object_a, object_b = promise.sync
This is equivalent to the more verbose:
promise = Promise.all([loader.load('a'), loader.load('b')])
object_a, object_b = promise.sync
Returns the internal cache that can be overridden with :cache option (see constructor)
This field is writable, so you can reset the cache with something like:
loader.cache = Concurrent::Map.new
Triggers all batched loaders until there are no keys to resolve.
This method is invoked automatically when the value of any promise is requested with #sync.
Here is the implementation that Dataloader sets as a default for Promise:
class Promise
def wait
Dataloader.wait
end
end
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