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Version: current

Caching

Falcon-Server provides several ways of working with cache.

It provides cache component through GQL context available for all GraphQL Query and Mutation resolver methods.

It also exposes @cache directive through the Base GraphQL Schema to the rest of the extensions to define their own caching options. Such cache will be handled by @cache directive itself, so the Extension does not have to do anything by itself in terms of cache checks, cache-key generations, etc.

Cache adapters

By default, Falcon-Server uses InMemoryLRUCache as a cache backend.

There's an option to configure Redis or Memcached as a cache backend via Falcon-Server config:

{
"cache": {
"type": "redis",
"options": {
"host": "redis-server"
}
}
}
{
"cache": {
"type": "memcached",
"options": ["memcached-server-1", "memcached-server-2"]
}
}

Cache Component

Falcon-Server provides Cache wrapper-component with additional features described below.

As it was mentioned above, this component is accessible via context argument in all GraphQL resolvers:

async mySampleResolver(parent, args, context, info) {
// example of getting value for `cache-key` key
const value = await context.cache.get('cache-key');
}

get cache

async get(key: string, setOptions?: GetCacheOptions): Promise<CacheResult> method accepts the following arguments:

  • key: string - cache key
  • setOptions?: GetCacheOptions - optional object with the following sub-keys:
    • fetchData: () => Promise<GetCacheFetchResult> - this is an optional async fetch-callback, which should return a value if the cached value is missing. The fetched data will be then cached for a later use.
    • options: SetCacheOptions - options object to be passed to set method

Example of using keyOrOptions as an object with fetchData callback. Here's a piece of code that shows how you would normally work with the cache:

async mySampleResolver(parent, args, context, info) {
let value = await context.cache.get('cache-key');
if (typeof value === 'undefined') {
value = await fetchRemoteData('my-data');
await context.cache.set('cache-key', value, { ttl: 60 });
}
return value;
}

By passing fetchData callback as a part of keyOrOptions argument - you can combine this check within a single call:

async mySampleResolver(parent, args, context, info) {
return context.cache.get('cache-key', {
fetchData: async () => fetchRemoteData('my-data'),
options: {
ttl: 60
}
});
}

In this case fetchRemoteData('my-data') will be called only when the cache data was not found, and its result will be stored with cache-key key and { ttl: 60 } cache options.

Optionally, if fetchData callback returns data with value and options keys - Cache Component will merge the received options value with the options object passed to the method arguments. This way you can define cache options dynamically, for example:

async getToken(parent, args, context, info) {
return context.cache.get('token', {
fetchData: async () => {
const tokenData = await fetchToken();
return {
value: tokenData.token,
options: {
ttl: convertToSeconds(tokenData.lifetime)
}
};
}
});
}

set cache

async set(key, value, options): Promise<void> method accepts the following arguments:

  • key: string - cache key
  • value: any - cache value that needs to be stored under key cache key
  • options: SetCacheOptions - represents an optional config object with the following keys:
    • ttl: number (seconds) - for how long you want to store the data in cache
    • tags: string[] - a list of tags that should be associated with this cache key (if one of the tags is invalid - the value considered as expired)

Tags validation is being handled by the Cache component itself

delete cache

async delete(key): Promise<boolean | void> method accepts the following argument:

  • key: string|string[] - a key or a list of keys to be removed from the cache

Schema Caching

To use cache within your Extension - you need to put @cache directive next to the field you want to cache in the Extension's GraphQL Schema:

type Query {
myData: Data @cache
myOtherData: Data @cache(ttl: 20)
}

In this example - myData Query will be cached by Falcon-Server with a default cache TTL, and myOtherData Query will be cached with a cache TTL of 20 (20 minutes).

Default cache TTL equals 10 (10 minutes)

Sub-caching

It is also possible to cache nested data of your Extension (which for example may require some heavy requests or calculations):

type Query {
data(id: String): Data @cache
}
type Data {
nestedData: [String] @cache
}

In order to ensure the uniqueness of the cache key - @cache directive takes into account the name of the cached field, cache context of your dataSources, all input arguments for the current resolver and also checks its "parent" value:

  • in case of data - it will check id input value
  • in case of nestedData - it will check parent data value

Cache settings

As it was previously mentioned, caching mechanism may be configured to use different TTL values depending on your needs.

There's a default cache TTL value, defined by @cache directive itself, which is being used when @cache directive is being used without any extra arguments. If you want to change this value - you could easily do it via your Falcon-Server config:

{
"cache": {
"resolvers": {
"enabled": true,
"default": {
"ttl": 60
}
}
}
}

You could use special values for your production environment via config/production.json config file. You could even disable the cache while working with the app locally by setting cache.resolvers.enabled config flag to false.

Every author of the Extension can "mark" the provided Queries as "cacheable" by putting the @cache directive next to the corresponding queries in his Extension's GQL Schema. In some cases - you may disagree with these decisions and you may want to use higher values for TTL. It is possible to alter those values without touching the Extension's code by changing your Falcon-Server config:

{
"cache": {
"resolvers": {
"default": {
"ttl": 10
},
"query.menu": {
"ttl": 30
}
}
}
}

In this case, query.menu represents a "path" of your GraphQL Query like this:

query Menu {
menu {
id
name
urlPath
}
}

query - is a name of the GQL operation and menu is a name of the Query field. So in this case, instead of using a predefined TTL, Falcon-Server will cache the response of query.menu resolver for 30 minutes (from the config above).

@cache directive works on a Schema level only, meaning that you cannot mark existing Queries as cacheable by yourself via config to avoid introducing unintended behavior of the Extension.

Overriding cache options

Cache options are being checked with this order (from highest to lowest priority):

  • "named" GQL path in app config
  • @cache directive arguments in GQL Schema
  • global cache options in app config
  • default cache options defined by Base GraphQL Schema

Caching by tags

Full @cache GraphQL directive definition looks like this:

directive @cache(ttl: Int, idPath: [String]) on FIELD_DEFINITION

When you mark your GraphQL Type with a @cache directive, this directive will try to find ID field type inside of your specified type, for example:

type Query {
item(id: ID!): Item @cache
items: [Item] @cache
}
# Type name is going to be used as a tag prefix
type Item {
# @cache will check this field to generate a proper tag `Item:id`
id: ID!
name: String
}

Thus if you run query { item(id: 1) { id name } } GQL query, @cache will generate Item and Item:1 tags automatically for you, and will put the resolved value into the cache with the generated tags for further validation. The same works with a simple list, when you run query { items { id name } } - the directive will detect [Item] list and will extract ID values from each entry and will generate the following tags - Item, Item:1, Item:2 and so on.

This works great with "plain" values. But when you're dealing with nested listings - you need to help @cache directive by pointing out where to look for ID values. Let's assume you have the following GQL schema:

type Query {
items(page: Int): ItemList @cache(idPath: ["children"])
}
type ItemList {
children: [Item]
total: Int
}
type Item {
id: ID!
name: String
}

Such @cache(idPath: ["children"]) statement will tell to the @cache directive to look in children property for the required values to generate a tag list from. This way, the whole Query.items resolver value will be cached with the generated tags from ItemList.children values.

If you need to use a deep nesting key - you could simply pass @cache(idPath: ["children.entries"]) statement in the schema

There are cases when you need to switch the direction of how tags are being generated, for example when you would like to cache a nested value with its own resolver (as it would normally be with GraphQL) within your main type like the following example schema:

type Query {
post(id: Int): Post @cache
}
type Post {
id: ID!
comments: [Comment] @cache(idPath: ["$parent"])
}
type Comment {
id: ID!
text: String
}

In the example above we have 2 caching points:

  • Caching the main Post type (the directive will check its ID value to generate a tag)
  • Caching a nested Post.comments value with a (idPath: ["$parent"]) cache option.

$parent keyword is a special keyword which refers to a parent object (it's the first argument passed to the GraphQL resolver method), so in order to generate a list of tags - @cache directive will check a parent value for comments (which is a Post value and this directive is able to extract the ID from Post). Thus, if you run query { post(id: 1) { id comments { id text } } } - comments value will be cached with the following tags: Post:1, Comment, Comment:1, Comment:2 etc.

Cache invalidation

Falcon-Server provides two options to invalidate the cache:

  • via @cacheInvalidator GraphQL directive
  • via a custom REST endpoint (defined by a user)

@cacheInvalidator directive

Falcon-Server allows you to mark your Queries and Mutations with a @cacheInvalidator GraphQL directive to invalidate the cache when requested/submitted.

This directive accepts a list of entries for idPath argument with the following keys:

  • path - a required value to get value(s) from (just like idPath argument for @cache directive)
  • type - an optional value to force entity type (when it's needed)

Full GraphQL definition looks like this:

directive @cacheInvalidator(idPath: [IdPathEntryInput]) on FIELD_DEFINITION
input IdPathEntryInput {
type: String
path: String!
}

Be careful when using this directive, since it allows you to control your cache on a GraphQL-level per user. You have to use it responsibly and do not allow to invalidate the cache using simple queries.

To invalidate the cache, you have to specify the path to your data like:

type Query {
lastOrder: OrderDetails @cacheInvalidator(idPath: [{ path: "items" }])
}

In this case, @cacheInvalidator will check items key for the lastOrder Query result and it will try to extract value(s) with ID field type (it acts in the similar way like it does for @cache GQL directive).

There might be a case, when you would need to force a specific entity type to be returned by this directive. For example, for OrderDetails type, which will return a list of OrderItem for items key - you need to force Product type. To do that - you simply specify type key:

type Query {
lastOrder: Order @cacheInvalidator(idPath: [{ path: "items", type: "Product" }])
}

@cacheInvalidator directive will generate a list of cache tags by using items value and use Product type instead of OrderItem.

REST endpoint

Falcon-Server uses cache.url config value (by default: /cache) to define a route path which will be responsible for processing web-hooks to invalidate the cache by tags.

For security reasons - please make sure you're using a unique and complex value for this route on production to avoid exposing a vulnerable route.

This endpoint expects you to send a list of entries with the following keys:

  • type - entity type to be used for cache invalidation (required key)
  • id - entity ID (optional key). If not passed, Falcon-Server will use type as a cache key
curl -X POST http://localhost:4000/cache -H 'Content-Type: application/json' -d \
'[{"id": 1, "type": "Product"}, {"type": "Category"}]'

The example above will flush the cache for the following keys:

  • Product:1 - cache key for the specific product
  • Category - general Category cache key

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