Most efficient way to make a database query on GraphQL - performance

I have the following type definition for the type Post
type Post {
id: ID!
title: String!
body: String!
user:User!
indexRef: Int!
createdAt: String!
daysFromCreation: Int!
comments: [Comment]!
}
I'd like to get the fields of the types that are asked on the query, and the do the select with the asked fields. I already got this by using the graphql-fields package. So the resolver ended up like this
const posts = async (parent, args, {dataSources}, info) => {
const askedFields = Object.keys(graphqlFields(info))
const posts = await dataSources.postsApi.getPosts(askedFields.join(','))
return posts
}
Doing the following query
query getPosts{
posts{
title,
body
}
}
}
It'll end up doing a select title, posts from posts_table, but the problem is if I ask for the comment field for example, that's a "complex field" which has its own field resolver. If I ask for the comment field
query getPosts{
posts{
title,
body,
comments {
comment
}
}
}
}
The SQL command will be select title,body,comments from posts_table and that'll throw an exception, because comments of posts are in another table. So, any suggestion about how could I improve the database querying part? I don't like the idea of doing select *.
I thought about checking if the field that's about to be included in the query, is part of the type that the resolver returns... If it's, then include it in the query, if not, let it pass because it'll be resolved in the correspondent field resolver. Is it possible?

Related

GraphQL query error -- variable is never used in operation

I am performing a request for an individual post from Apollo Server / Express backend.
In the Apollo GraphQL sandbox, the query works and retrieves the correct post, however, the query has a red squiggle identifying an error which reads -
Variable "$getPostId" is never used in operation "Query".
The query is as follows -
query Query($getPostId: ID!) {
getPost(id:"20c9b3ac-afe6-4faa-a3f9-e00ef1b38ccf") {
title
author
id
}
}
The schema is as follows -
module.exports = gql`
type Post {
id: ID!
title: String!
author: String!
}
type Query {
getPosts: [Post]!
getPost(id: ID!): Post
}
...
`
The closest post which seems to address a similar problem I could find is here. However, I can't translate the resolution to my problem.
Why is the error showing (particularly when the query runs successfully)? What needs to be done to stop the error from showing?
Many thanks!
It sounds like
query Query($getPostId: ID!) {
getPost(id:"20c9b3ac-afe6-4faa-a3f9-e00ef1b38ccf") {
title
author
id
}
}
is supposed to be
query Query($getPostId: ID!) {
getPost(id: $getPostId) {
title
author
id
}
}
Or if your query is actually meant to hard-code the ID, then you want
query Query {
getPost(id:"20c9b3ac-afe6-4faa-a3f9-e00ef1b38ccf") {
title
author
id
}
}

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);
},
}
}
};

Query Appsync graphql with 3 different combinations

I am using appsync with amplify and trying to figure out how to query based on two different selectors. Basically I need to either query all if neither county or facility are supplied, query with county while facility is empty, or query with facility while county is empty. I thought I could wrap this into 1 query but it doesn't seem like I can. My appsync schemas look like this.
type Client
#model
#key(name: "clientByCountyOrFacility", fields: ["county", "facility"], queryField: "getClientsByCountyOrFacility")
#searchable {
id: ID!
facility: String!
county: String!
products: [Product] #connection(name: "ClientProducts")
}
type Product
#model
#searchable {
id: ID!
client: Client #connection(name: "ClientProducts")
}
I can get this to work by using (below query) but I am worried this will run into the 100 scan limit because it uses the listClients query underneath. Possibly if there was an easy way to change that could be a solution but it seems the files in amplify are autogenerated.
query getClientsByCountyOrFacility($county: String = "", $facility: String = "") {
listClients(filter: {
county: {
contains: $county
}
facility: {
contains: $facility
}
}) {
items {
id
products {
items {
id
}
}
}
}
}
I added the #key to see if I could create an index but it doesn't like that and I'm at a lose for how to acquire the data. How do I go about building this schema and query to get the data back?

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.

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.

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