How to create a document in FaunaDB with a given _id using GraphQL instead of accepting the auto-generated one - graphql

It is possible to do it using FQL, but I can't find any example of a GraphQL mutation that creates a new document in FaunaDB where the _id is defined by the application and not by FaunaDB itself.
Of course I can add my application-generated ID (an uuidv4 for instance) as an additional attribute in the document and create an index for it, but it doesn't seem right considering the document will have another primary key anyway.

You can use resolver directive, associate with a user defined function (UDF) to accept _id as a parameter and then use Create.
Here is an example,
Schema file
type Order {
customerName: String!
price: Float!
}
input OrderInput {
orderID: Int!
customerName: String!
price: Float!
}
type Query {
CreateOrder(data: OrderInput!): Order! #resolver
}
UDF (CreateOrder)
Update(
Function("CreateOrder"),
{
body: Query(Lambda(["orderdata"],
Create(Ref(Collection("Order"), Select(["orderID"],Var("orderdata"))),
{
data: {
customerName: Select(["customerName"], Var("orderdata")),
price: Select(["price"], Var("orderdata"))
}
}
)))})
GraphQL Query

Related

GraphQL query with multiple nested resolvers and mapping fields to arguments

From GraphQL Client's perspective, how do I perform a query with multiple nested resolvers where the fields from the parent are passed as arguments to the child resolver?
Here is a minimal example:
GraphQL Schema:
type Author {
id: ID!
name: String!
}
type Book {
id: ID!
title: String!
releaseDate: String!
}
type Query {
// Returns a list of Authors ordered by name, 'first' indicates how many entries to return
getAllAuthors(first: Int!): [Author]!
// Returns a list of Books ordered by releaseDate, 'first' indicates how many entries to return
getBooksByAuthorId(first: Int! authorId: ID!): [Book]!
}
Is it possible to write a query to get all authors and their last released book? Something around the lines:
query GetAuthorsWithLastBook($first: Int!) {
getAllAuthors(first: $first) {
authorId: id
name
lastBook: getBooksByAuthor(1, authorId) {
title
}
}
}
In the example above, I attempted to alias getAllAuthors.id as authorId and pass the alias down as argument to getBooksByAuthor(...) but that didn't work.
The key aspect of the problem is that I don't know the authorIds beforehand. I could fetch the authors first and build a query to fetch their last book but that will result in multiple queries and that is something I would like to avoid.
Update
A Java Kickstarter example is available here: https://www.graphql-java-kickstart.com/tools/schema-definition/
yes, on the graphql definition, you need to add lastBook in the Author
type Author {
id: ID!
name: String!
lastBook: [Book]
}
Next up u need to write the resolver for the lastBook
const resolvers = {
Query: {
Author {
lastBook: (parent, args) {
const userId = parent.id;
return getBooksByAuthor(userId, 1);
},
}
}
};

Sorting results in AWS Amplify GraphQL without filtering

Provided a very simple model in graphql.schema, how would I perform a simple sort query?
type Todo #model
id: ID!
text: String!
}
Which generates the following in queries.js.
export const listTodos = /* GraphQL */ `
query ListTodos(
$filter: ModelTodoFilterInput
$limit: Int
$nextToken: String
) {
listTodos(filter: $filter, limit: $limit, nextToken: $nextToken) {
items {
id
text
}
nextToken
}
}
`;
I have found multiple sources pointing me in the direction of the #key directive. This similar question addresses that approach (GraphQL with AWS Amplify - how to enable sorting on query).
While that may seem promising and successfully generates new queries I can use, all the approaches I have tried require that I filter the data before sorting it. All I want to do is sort my todo results on a given column name, with a given sort direction (ASC/DESC).
This is how I would perform a simple (unsorted) query:
const todos = await API.graphql(graphqlOperation(listTodos));
I would be looking to do something along the lines of:
const todos = await API.graphql(graphqlOperation(listTodos, {sortField: "text", sortDirection: "ASC"} )).
Decorate your model with the #searchable directive, like so:
type Todo #model #searchable
{
id: ID!
text: String!
}
After that, you can query your data with sorting capabilities like below:
import { searchToDos } from '../graphql/queries';
import { API, graphqlOperation } from 'aws-amplify';
const toDoData = await API.graphql(graphqlOperation(searchToDos, {
sort: {
direction: 'asc',
field: 'text'
}
}));
console.log(toDoData.data.searchToDos.items);
For more information, see
https://github.com/aws-amplify/amplify-cli/issues/1851#issuecomment-545245633
https://docs.amplify.aws/cli/graphql-transformer/directives#searchable
Declaring #searchable incurs pointless extra server cost if all you need is straight forward sorting. It spins up an EBS and an OpenSearch that will be about $20 a month minumum.
Instead you need to use the #index directive.
As per the documentation here: https://docs.amplify.aws/guides/api-graphql/query-with-sorting/q/platform/js/
In your model, add the #index directive to one of the fields with a few parameters:
type Todo #model {
id: ID!
title: String!
type: String! #index(name: "todosByDate", queryField: "todosByDate", sortKeyFields: ["createdAt"])
createdAt: String!
}
By declaring the queryField and the sortKeyField you will now have a new query available to once you push your amplify config:
query todosByDate {
todosByDate(
type: "Todo"
sortDirection: ASC
) {
items {
id
title
createdAt
}
}
}
The field you declare this directive on can not be empty (notice the ! after the field name)
This is a much better way of doing it as opposed to #searchable, which is massively overkill.
I've accepted MTran's answer because it feels to me it is the nearest thing to an actual solution, but I've also decided to actually opt for a workaround. This way, I avoid adding a dependency to ElasticSearch.
I ended up adding a field to my schema and every single entry has the same value for that field. That way, I can filter by that value and still have the entire table of values, that I can then sort against.

Using nested arguments in GraphQL operations

I have a schema like so:
scalar Date
schema {
query: Query
}
type Query {
user(id: ID!): User
messages(userId: ID!): [ChatMessage!]!
}
type User {
id: ID!
username: String!
email: String!
}
type ChatMessage {
id: ID!
content: String!
time: Date!
user: User!
}
And I want to make an operation where you can get all messages for a user, but since User and ChatMessage are in separate database tables I would need to perform two queries (one to get the ChatMessages and one to get the User), so I thought I should model it like so:
query findMessagesForUser($userId: ID!) {
messages(userId: $userId) {
id
content
user(id: $userId) {
username
email
}
}
}
This returns a parse error on the schema:
GraphQLDocumentError: Unknown argument "id" on field "ChatMessage.user".
So, how do I get the $userId argument passed to the resolver for ChatMessage.user?
In your schema, you’ve defined an id input on your Query.user method. In your query, you are trying to supply an id to the Message.user property, however you haven't defined this input in your schema.
If you wanted to accept an id on ChatMessage.user, you'd need to define it as:
type ChatMessage {
id: ID!
content: String!
time: Date!
user(id: ID!): User
}
However, it wouldn't really make sense (at least to me) to construct a schema this way, I assume there's only one user (author) per message.
As indicated by #xadm, the object you resolved at the ChatMessage level will be passed into the user resolver as the first argument.
Even if you're not exposing ChatMessage.userId in the schema (that's fine), you'd still probably load this up in your back- end (the foreign key value in the ChatMessage table) and set this on the object used to resolve ChatMessage.
This way, you'll (lazy) load user IF that's included in the query, using the userId property of the parent ChatMessage object argument (remember you don't need to expose ChatMessage.userId via the schema, it's just on the object you use to resolve ChatMessage).
I'd consider modelling more like this (filter input used as an additional contrived example):
type Query {
user(id: ID!): User
messages(filter: MessageFilter): [ChatMessage!]!
}
type MessageFilter {
search: String
paging: PagingFilter
}
type PagingFilter {
after: ID!
pageSize: Int!
}
type User {
id: ID!
username: String!
email: String!
messages(filter: MessageFilter): [ChatMessage!]!
}
In your resolver map, you can wire up the same function to resolve messages at the User level and at the Query level. The only difference is you wouldn't have a userId at the Query level.
If consumers want to view/search messages from all users, they use the top level Query messages method.
{
messages({search: 'graphql'}) {
id,
content,
time
}
}
If the consumer wants to view/search one user's messages, go through the top level Query users method into messages.
{
user(id: 3) {
messages({search: 'graphql'}) {
id,
content,
time
}
}
}
The filter example is contrived, but could provide basic paging for loading of messages.
apollographql.com/docs/graphql-tools/resolvers

FaunaDB - How to bulk update list of entries within single graphQL mutation?

I want to bulk update list of entries with graphQL mutation in faunaDB.
The input data is list of coronavirus cases from external source. It will be updated frequently. The mutation should update existing entries if the entry name is present in collectio and create new ones if not present.
Current GRAPHQL MUTATION
mutation UpdateList($data: ListInput!) {
updateList(id: "260351229231628818", data: $data) {
title
cities {
data {
name
infected
}
}
}
}
GRAPHQL VARIABLES
{
"data": {
"title": "COVID-19",
"cities": {
"create": [
{
"id": 22,
"name": "Warsaw",
"location": {
"create": {
"lat": 52.229832,
"lng": 21.011689
}
},
"deaths": 0,
"cured": 0,
"infected": 37,
"type": "ACTIVE",
"created_timestamp": 1583671445,
"last_modified_timestamp": 1584389018
}
]
}
}
}
SCHEMA
type cityEntry {
id: Int!
name: String!
deaths: Int!
cured: Int!
infected: Int!
type: String!
created_timestamp: Int!
last_modified_timestamp: Int!
location: LatLng!
list: List
}
type LatLng {
lat: Float!
lng: Float!
}
type List {
title: String!
cities: [cityEntry] #relation
}
type Query {
items: [cityEntry!]
allCities: [cityEntry!]
cityEntriesByDeathFlag(deaths: Int!): [cityEntry!]
cityEntriesByCuredFlag(cured: Int!): [cityEntry!]
allLists: [List!]
}
Everytime the mutation runs it creates new duplicates.
What is the best way to update the list within single mutation?
my apologies for the delay, I wasn't sure exactly what the missing information was hence why I commented first :).
The Schema
An example of a part of a schema that has arguments:
type Mutation {
register(email: String!, password: String!): Account! #resolver
login(email: String!, password: String!): String! #resolver
}
When such a schema is imported in FaunaDB there will be placeholder functions provided.
The UDF parameters
As you can see all the function does is Abort with the message that the function still has to be implemented. The implementation starts with a Lambda that takes arguments and those arguments have to match what you defined in the resolver.
Query(Lambda(['email', 'password'],
... function body ...
))
Using the arguments is done with Var, that means Var('email') or Var('password') in this case. For example, in my specific case we would use the email that was passed in to get an account by email and use the password to pass on to the Login function which will return a secret (the reason I do the select here is that the return value for a GraphQL resolver has to be a valid GraphQL result (e.g. plain JSON
Query(Lambda(['email', 'password'],
Select(
['secret'],
Login(Match(Index('accountsByEmail'), Var('email')), {
password: Var('password')
})
)
))
Calling the UDF resolver via GraphQL
Finally, how to pass parameters when calling it? That should be clear from the GraphQL playground as it will provide you with the docs and autocompletion. For example, this is what the auto-generated GraphQL docs tell me after my schema import:
Which means we can call it as follows:
mutation CallLogin {
login (
email: "<some email>"
password: "<some pword>"
)
}
Bulk updates
For bulk updates, you can also pass a list of values to the User Defined Function (UDF). Let's say we would want to group a number of accounts together in a specific team via the UI and therefore want to update multiple accounts at the same time.
The mutation in our Schema could look as follows (ID's in GraphQL are similar to Strings)
type Mutation { updateAccounts(accountRefs: [ID]): [ID]! #resolver }
We could then call the mutation by providing in the id's that we receive from FaunaDB (the string, not the Ref in case you are mixing FQL and GraphQL, if you only use GraphQL, don't worry about it).
mutation {
updateAccounts(accountRefs: ["265317328423485952", "265317336075993600"] )
}
Just like before, we will have to fill in the User Defined Function that was generated by FaunaDB. A skeleton function that just takes in the array and returns it would look like:
Query(Lambda(['arr'],
Var('arr')
))
Some people might have seen an easier syntax and would be tempted to use this:
Query(Lambda(arr => arr))
However, this currently does not work with GraphQL when passing in arrays, it's a known issue that will be fixed.
The next step is to actually loop over the array. FQL is not declarative and draws inspiration from functional languages which means you would do that just by using a 'map' or a 'foreach'
Query(Lambda(["accountArray"],
Map(Var("accountArray"),
Lambda("account", Var("account")))
))
We now loop over the list but don't do anything with it yet since we just return the account in the map's body. We will now update the account and just set a value 'teamName' on there. For that we need the Update function which takes a FaunaDB Reference. GraphQL sends us strings and not references so we need to transform these ID strings to a reference with Ref as follows:
Ref(Collection('Account'), Var("account"))
If we put it all together we can add an extra attribute to a list of accounts ids as follows:
Query(Lambda(["accountArray"],
Map(Var("accountArray"),
Lambda("account",
Do(
Update(
Ref(Collection('Account'), Var("account")),
{ data: { teamName: "Awesome live-coders" } }
),
Var("account")
)
)
)
))
At the end of the Map, we just return the ID of the account again with Var("account") in order to return something that is just plain JSON, else we would be returning FaunaDB Refs which are more than just JSON and will not be accepted by the GraphQL call.
Passing in more complex types.
Sometimes you want to pass in more complex types. Let's say we have a simple todo schema.
type Todo {
title: String!
completed: Boolean!
}
And we want to set the completed value of a list of todos with specific titles to true. We can see in the extended schema generated by FaunaDB that there is a TodoInput.
If you see that extended schema you might think, "Hey that's exactly what I need!" but you can't access it when you write your mutations since you do not have that part of the schema at creation time and therefore can't just write:
type Mutation { updateTodos(todos: [TodoInput]): Boolean! #resolver }
As it will return the following error.
However, we can just add it to the schema ourselves. Fauna will just accept that you already wrote it and not override it (make sure that you keep the required fields, else your generated 'createTodo' mutation won't work anymore).
type Todo {
title: String!
completed: Boolean!
}
input TodoInput {
title: String!
completed: Boolean!
}
type Mutation { updateTodos(todos: [TodoInput]): Boolean! #resolver }
Which means that I can now write:
mutation {
updateTodos(todos: [{title: "test", completed: true}])
}
and dive into the FQL function to do things with this input.
Or if you want to include the ID along with data you can define a new type.
input TodoUpdateInput {
id: ID!
title: String!
completed: Boolean!
}
type Mutation { updateTodos(todos: [TodoUpdateInput]): Boolean! #resolver }
Once you get the hang of it and want to learn more about FQL (that's a whole different topic) we are currently writing a series of articles along with code for which the first one appeared here: https://css-tricks.com/rethinking-twitter-as-a-serverless-app/ which is probably a good gentle introduction.

How to combine multiple field in GraphQL Object

I am trying my first Graphql Schema design. Is it possible that single field inside object type refer to a complex object?
enum KeyPrefix {
WS
WK
SI
ENT
}
input generalKey {
keyPrefix:KeyPrefix!
key:Int!
}
type Item
{
pk: generalKey!
data: String!
name: String!
}
It gives me error as below.
The type of Item.pk must be Output Type but got: generalKey!
input is a keyword reserved for describing input to a GraphQL query. Your schema should look like this:
enum KeyPrefix {
(your values)
}
type PrimaryKey {
prefix: KeyPrefix!
key: Int!
}
type Item {
pk: PrimaryKey!
data: String!
name: String!
}
When you define a Query in your GraphQL schema, you will want to use an input, like so:
input PrimaryKeyInput {
prefix: KeyPrefix!
key: Int!
}
type Query {
getItemByPrimaryKey(input: PrimaryKeyInput!): Item
}
This will allow a client to ask for an Item using the same fields you have on PrimaryKey.

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