I am really struggling with this concept. I hope someone can help me understand it better.
The documentations uses a simple example and it's not 100% clear to me how it works.
I have tried using keyArgs, but they didn't work, so I adopted to use the args parameter in the read and merge functions. First, let me explain my scenario.
I have a couple of search endpoints that use the same parameters:
{
search:
{
searchTerm: "*",
includePartialMatch: true,
page: 1,
itemsToShow: 2,
filters: {},
facets: [],
orderBy: {}
}
}
So I have setup my type policies like this:
const cache = new InMemoryCache({
typePolicies: {
Query: {
fields: {
searchCategories: typePolicy,
searchBrands: typePolicy,
searchPages: typePolicy,
searchProducts: typePolicy,
},
},
},
});
And I was using a generic typePolicy for them all.
At first, I tried this:
const typePolicy = {
keyArgs: [
"search",
[
"identifier",
"searchTerm",
"includePartialMatches",
"filters",
"orderBy",
"facets",
],
],
// Concatenate the incoming list items with
// the existing list items.
merge(existing: any, incoming: any) {
console.log("existing", existing);
console.log("incoming", incoming);
if (!existing?.items) console.log("--------------");
if (!existing?.items) return { ...incoming }; // First request
const items = existing.items.concat(incoming.items);
const item = { ...existing, ...incoming };
item.items = items;
console.log("merged", item);
console.log("--------------");
return item;
},
};
But this does not do what I want.
What I would like, is for apollo to work as it does normally, but when the "page" changes for any field, it appends it instead of caching a new request.
Does anyone know what I am doing wrong or can provide me with a better example that what is on the documentation?
Related
I get data as ordered by some criteria.
export default {
Query: {
seeAllFeedOrder: protectedResolver(() => {
return client.user.findMany({
orderBy: {
feeds: {
_count: "desc",
},
},
and this data is ordered as below.
as you can see it descends by number.
But when I get data from front-end by using useQuery.
(I search and fetchPolicy can remain the order, so I put, but it doesn't work either.)
const { data: allFeedData, loading: allFeedLoading } = useQuery(
SEE_ALL_FEED_ORDER,
{
fetchPolicy: "cache-and-network",
}
);
result order is broken. (1->2->1)
Then it's meaningless to use order in backend.
Object {
"seeAllLikeOrder": Array [
Object {
"directFeedNumber": 1,
},
Object {
"directFeedNumber": 2,
},
Object {
"directFeedNumber": 1,
},
],
}
Should I order the fetched data again in frontend...?
After having implemented dataloader in the respective resolvers to solve the N+1 problem, I also need to be able to solve the N+N problem.
I need a decently efficient data loading mechanism to get a relation like this:
{
persons (active: true) {
id,
given_name,
projects (active: true) {
id,
title,
}
}
}
I've created a naive implementation for this, returning
{
persons: [
{
id: 1,
given_name: 'Mike'
projects: [
{
id: 1,
title: 'API'
},
{
id: 2,
title: 'Frontend'
}
]
}
{
id: 2,
given_name: 'Eddie'
projects: [
{
id: 2,
title: 'Frontend'
},
{
id: 3,
title: 'Testing'
}
]
}
]
}
In SQL the underlying structure would be represented by a many many to many relationship.
Is there a similiar tool like dataloader for solving this or can this maybe even be solved with dataloader itself?
The expectation with GraphQL is that the trip to the database is generally the fastest thing you can do, so you just add a resolver to Person.projects that makes a call to the database. You can still use dataLoaders for that.
const resolvers = {
Query: {
persons(parent, args, context) {
// 1st call to database
return someUsersService.list()
},
},
Person: {
projects(parent, args, context) {
// this should be a dataLoader behind the scenes.
// Makes second call to database
return projectsService.loadByUserId(parent.id)
}
}
}
Just remember that now your dataLoader is expecting to return an Array of objects in each slot instead of a single object.
I am currently using Gatsby's collection routes API to create pages for a simple blog with data coming from Contentful.
For example, creating a page for each blogpost category :
-- src/pages/categories/{contentfulBlogPost.category}.js
export const query = graphql`
query categoriesQuery($category: String = "") {
allContentfulBlogPost(filter: { category: { eq: $category } }) {
edges {
node {
title
category
description {
description
}
...
}
}
}
}
...
[React component mapping all blogposts from each category in a list]
...
This is working fine.
But now I would like to have multiple categories per blogpost, so I switched to Contentful's references, many content-type, which allows to have multiple entries for a field :
Now the result of my graphQL query on field category2 is an array of different categories for each blogpost :
Query :
query categoriesQuery {
allContentfulBlogPost {
edges {
node {
category2 {
id
name
slug
}
}
}
}
}
Output :
{
"data": {
"allContentfulBlogPost": {
"edges": [
{
"node": {
"category2": [
{
"id": "75b89e48-a8c9-54fd-9742-cdf70c416b0e",
"name": "Test",
"slug": "test"
},
{
"id": "568r9e48-t1i8-sx4t8-9742-cdf70c4ed789vtu",
"name": "Test2",
"slug": "test-2"
}
]
}
},
{
"node": {
"category2": [
{
"id": "75b89e48-a8c9-54fd-9742-cdf70c416b0e",
"name": "Test",
"slug": "test"
}
]
}
},
...
Now that categories are inside an array, I don't know how to :
write a query variable to filter categories names ;
use the slug field as a route to dynamically create the page.
For blogposts authors I was doing :
query authorsQuery($author__slug: String = "") {
allContentfulBlogPost(filter: { author: { slug: { eq: $author__slug } } }) {
edges {
node {
id
author {
slug
name
}
...
}
...
}
And creating pages with src/pages/authors/{contentfulBlogPost.author__slug}.js
I guess I'll have to use the createPages API instead.
You can achieve the result using the Filesystem API, something like this may work:
src/pages/category/{contentfulBlogPost.category2__name}.js
In this case, it seems that this approach may lead to some caveats, since you may potentially create duplicated pages with the same URL (slug) because the posts can contain multiple and repeated categories.
However, I think it's more succinct to use the createPages API as you said, keeping in mind that you will need to treat the categories to avoid duplicities because they are in a one-to-many relationship.
exports.createPages = async ({ graphql, actions }) => {
const { createPage } = actions
const result = await graphql(`
query {
allContentfulBlogPost {
edges {
node {
category2 {
id
name
slug
}
}
}
}
}
`)
let categories= { slugs: [], names: [] };
result.data.allContentfulBlogPost.edges.map(({node}))=> {
let { name, slug } = node.category2;
// make some checks if needed here
categories.slugs.push(slug);
categories.names.push(name);
return new Set(categories.slugs) && new Set(categories.names);
});
categories.slugs.forEach((category, index) => {
let name = categories.names[index];
createPage({
path: `category/${category}`,
component: path.resolve(`./src/templates/your-category-template.js`),
context: {
name
}
});
});
}
The code's quite self-explanatory. Basically you are defining an empty object (categories) that contains two arrays, slugs and names:
let categories= { slugs: [], names: [] };
After that, you only need to loop through the result of the query (result) and push the field values (name, slug, and others if needed) to the previous array, making the needed checks if you want (to avoid pushing empty values, or that matches some regular expression, etc) and return a new Set to remove the duplicates.
Then, you only need to loop through the slugs to create pages using createPage API and pass the needed data via context:
context: {
name
}
Because of redundancy, this is the same than doing:
context: {
name: name
}
So, in your template, you will get the name in pageContext props. Replace it with the slug if needed, depending on your situation and your use case, the approach is exactly the same.
I've got a very simple Nuxt app with Strapi GraphQL backend that I'm trying to use and learn more about GraphQL in the process.
One of my last features is to implement a search feature where a user enters a search query, and Strapi/GraphQL performs that search based on attributes such as image name and tag names that are associated with that image. I've been reading the Strapi documentation and there's a segment about performing a search.
So in my schema.graphql, I've added this line:
type Query {
...other generated queries
searchImages(searchQuery: String): [Image
}
Then in the /api/image/config/schema.graphql.js file, I've added this:
module.exports = {
query: `
searchImages(searchQuery: String): [Image]
`,
resolver: {
Query: {
searchImages: {
resolverOf: 'Image.find',
async resolver(_, { searchQuery }) {
if (searchQuery) {
const params = {
name_contains: searchQuery,
// tags_contains: searchQuery,
// location_contains: searchQuery,
}
const searchResults = await strapi.services.image.search(params);
console.log('searchResults: ', searchResults);
return searchResults;
}
}
}
},
},
};
At this point I'm just trying to return results in the GraphQL playground, however when I run something simple in the Playground like:
query($searchQuery: String!) {
searchImages(searchQuery:$searchQuery) {
id
name
}
}
I get the error: "TypeError: Cannot read property 'split' of undefined".
Any ideas what might be going on here?
UPDATE:
For now, I'm using deep filtering instead of the search like so:
query($searchQuery: String) {
images(
where: {
tags: { title_contains: $searchQuery }
name_contains: $searchQuery
}
) {
id
name
slug
src {
url
formats
}
}
}
This is not ideal because it's not an OR/WHERE operator, meaning it's not searching by tag title or image name. It seems to only hit the first where. Ideally I would like to use Strapi's search service.
I actually ran into this problem not to recently and took a different solution.
the where condition can be combined with using either _and or _or. as seen below.
_or
articles(where: {
_or: [
{ content_contains: $dataContains },
{ description_contains: $dataContains }
]})
_and
(where: {
_and: [
{slug_contains: $categoriesContains}
]})
Additionally, these operators can be combined given that where in this instance is an object.
For your solution I would presume you want an or condition in your where filter predicate like below
images(where: {
_or: [
{ title_contains: $searchQuery },
{ name_contains: $searchQuery }
]})
Lastly, you can perform a query that filters by a predicate by creating an event schema and adding the #search directive as seen here
I'm attempting to use graphql to tie together a number of rest endpoints, and I'm stuck on how to filter, sort and page the resulting data. Specifically, I need to filter and/or sort by nested values.
I cannot do the filtering on the rest endpoints in all cases because they are separate microservices with separate databases. (i.e. I could filter on title in the rest endpoint for articles, but not on author.name). Likewise with sorting. And without filtering and sorting, pagination cannot be done on the rest endpoints either.
To illustrate the problem, and as an attempt at a solution, I've come up with the following using formatResponse in apollo-server, but am wondering if there is a better way.
I've boiled down the solution to the most minimal set of files that i could think of:
data.js represents what would be returned by 2 fictional rest endpoints:
export const Authors = [{ id: 1, name: 'Sam' }, { id: 2, name: 'Pat' }];
export const Articles = [
{ id: 1, title: 'Aardvarks', author: 1 },
{ id: 2, title: 'Emus', author: 2 },
{ id: 3, title: 'Tapir', author: 1 },
]
the schema is defined as:
import _ from 'lodash';
import {
GraphQLSchema,
GraphQLObjectType,
GraphQLList,
GraphQLString,
GraphQLInt,
} from 'graphql';
import {
Articles,
Authors,
} from './data';
const AuthorType = new GraphQLObjectType({
name: 'Author',
fields: {
id: {
type: GraphQLInt,
},
name: {
type: GraphQLString,
}
}
});
const ArticleType = new GraphQLObjectType({
name: 'Article',
fields: {
id: {
type: GraphQLInt,
},
title: {
type: GraphQLString,
},
author: {
type: AuthorType,
resolve(article) {
return _.find(Authors, { id: article.author })
},
}
}
});
const RootType = new GraphQLObjectType({
name: 'Root',
fields: {
articles: {
type: new GraphQLList(ArticleType),
resolve() {
return Articles;
},
}
}
});
export default new GraphQLSchema({
query: RootType,
});
And the main index.js is:
import express from 'express';
import { apolloExpress, graphiqlExpress } from 'apollo-server';
var bodyParser = require('body-parser');
import _ from 'lodash';
import rql from 'rql/query';
import rqlJS from 'rql/js-array';
import schema from './schema';
const PORT = 8888;
var app = express();
function formatResponse(response, { variables }) {
let data = response.data.articles;
// Filter
if ({}.hasOwnProperty.call(variables, 'q')) {
// As an example, use a resource query lib like https://github.com/persvr/rql to do easy filtering
// in production this would have to be tightened up alot
data = rqlJS.query(rql.Query(variables.q), {}, data);
}
// Sort
if ({}.hasOwnProperty.call(variables, 'sort')) {
const sortKey = _.trimStart(variables.sort, '-');
data = _.sortBy(data, (element) => _.at(element, sortKey));
if (variables.sort.charAt(0) === '-') _.reverse(data);
}
// Pagination
if ({}.hasOwnProperty.call(variables, 'offset') && variables.offset > 0) {
data = _.slice(data, variables.offset);
}
if ({}.hasOwnProperty.call(variables, 'limit') && variables.limit > 0) {
data = _.slice(data, 0, variables.limit);
}
return _.assign({}, response, { data: { articles: data }});
}
app.use('/graphql', bodyParser.json(), apolloExpress((req) => {
return {
schema,
formatResponse,
};
}));
app.use('/graphiql', graphiqlExpress({
endpointURL: '/graphql',
}));
app.listen(
PORT,
() => console.log(`GraphQL Server running at http://localhost:${PORT}`)
);
For ease of reference, these files are available at this gist.
With this setup, I can send this query:
{
articles {
id
title
author {
id
name
}
}
}
Along with these variables (It seems like this is not the intended use for the variables, but it was the only way I could get the post processing parameters into the formatResponse function.):
{ "q": "author/name=Sam", "sort": "-id", "offset": 1, "limit": 1 }
and get this response, filtered to where Sam is the author, sorted by id descending, and getting getting the second page where the page size is 1.
{
"data": {
"articles": [
{
"id": 1,
"title": "Aardvarks",
"author": {
"id": 1,
"name": "Sam"
}
}
]
}
}
Or these variables:
{ "sort": "-author.name", "offset": 1 }
For this response, sorted by author name descending and getting all articles except the first.
{
"data": {
"articles": [
{
"id": 1,
"title": "Aardvarks",
"author": {
"id": 1,
"name": "Sam"
}
},
{
"id": 2,
"title": "Emus",
"author": {
"id": 2,
"name": "Pat"
}
}
]
}
}
So, as you can see, I am using the formatResponse function for post processing to do the filtering/paging/sorting. .
So, my questions are:
Is this a valid use case?
Is there a more canonical way to do filtering on deeply nested properties, along with sorting and paging?
Is this a valid use case? Is there a more canonical way to do filtering on deeply nested properties, along with sorting and paging?
Major part of original questing lies on segregating collections on different databases on separate microservices. In fact, it's nessasary to perform collection joining and subsequent filtering on some key, but it's directly impossible since there is no field in original collection to filter, sort or paginate.
Strightforward solution is perform full or filtered queries to original collections, and then perform joining and filtering result dataset on application server, e.g. by lodash, such at your solution. In is possible for small collections, but in general case causes large data transfer and unefficent sorting since there is no index structure - real RB-tree or SkipList, so with quadratic complexity it's not very good.
Dependent on resource volume on application server, special cache and index tables can be build there. If collection structure is fixed, some relations between collection entries and their fields can be reflected in special search table and update respectively on demain. It's like find & search index creation, but not it database, but on application server. Of cource, it will consume resources, but will be more fast than direct lodash-like sorting.
Also task can be solved from another side, if there is access to structure of original databases. Key is denormalization. In counter for classical relation approach, collections can have dublicate information for avioding further join operation. E.g., Articles collection can have some information from Authors collection, which is nessasary to perform filtering, sorting and pagination in further operations.