I uploaded some json to my graphql using gatsby-transformer-json and gatsby-source-filesystem.
I would like to request an object of that data, which contains subfields.
When I try to make this request, I receive the error
Field \"sections\" of type \"DataJsonSections\" must have a selection of subfields. Did you mean \"sections { ... }\"?
Below is my json file. I am trying to request the section called "Sections". I would really like to find a way, so that I don't have to specify spiel and abbr for every section.
My json file
{
"slogan": "some slogan",
"drawIn": "Something to draw people in",
"fullName": "My full title",
"shortName": "My title",
"metadata": {
"desc": "...........",
"title": "............"
},
"sections": {
"about": {
"spiel": "..........."
},
"web-design": {
"abbr": "Websites",
"spiel": ".............."
},
"app-design": {
"abbr": "Apps",
"spiel": "..........."
},
"seo": {
"spiel": ".........."
},
"contact": {
"title": "Contact",
"subtitle": "Contact subtitle",
}
}
}
This is the request I would like to make, but I receive the error above when I do
query MyQuery {
allDataJson {
edges {
node {
sections
}
}
}
}
Extra
Within my gatsby-config.js(This is how I'm using gatsby-transformer-json and gatsby-source-filesystem)
`gatsby-transformer-json`,
{
resolve: `gatsby-source-filesystem`,
options: {
name: `data`,
path: `${__dirname}/src/data`
}
},
Field "sections" of type "DataJsonSections" must have a selection of subfields
Related
I have 2 JSON Data 1. Payers 2. Rules. I need to filter Payers JSON data based on PayerId from Rules JSON data.
{
"Payers": [
{
"payerId": "12345",
"name": "Test Payer1"
},
{
"payerId": "23456",
"name": "Test Payer2",
},
{
"payerId": "34567",
"name": "Test Payer3"
}}
Rules JSON file
{
"Rules": [
{
"actions": {
"canCopyRule": true
},
"RuleId": 123,
"description": "Test Rule",
"isDisabled": false,
"Criteria": [
{
"autoSecondaryCriteriaId": 8888,
"criteriaType": { "code": "primaryPayer", "value": "Primary Payer" },
"payerId": ["12345", "34567"]
}
]
}
}]}
I need to filter Payers JSON data based on Rules JSON data if PayerID matches
I need output like below
{
"Payers": [
{
"payerId": "12345",
"name": "Test Payer1"
},
{
"payerId": "34567",
"name": "Test Payer3"
}
}
How to filter?
You can use Array.filter like that (based on your data structure):
const filteredPayers = payersObj.Payers.filter((p) => rulesObj.Rules[0].Criteria[0].payerId.includes(p.payerId));
I can't figure out why your Rules json looks like this, I guess you have multiple rules. If so, you will need to iterate over each rule and invoke includes. Same for Criteria.
Code will check each rule and each critirias
and will return payers if payerId found in any of the given rules of any criteria
const payers = {
"Payers": [
{
"payerId": "12345",
"name": "Test Payer1"
},
{
"payerId": "23456",
"name": "Test Payer2",
},
{
"payerId": "34567",
"name": "Test Payer3"
}]}
const rules = {
"Rules": [
{
"actions": {
"canCopyRule": true
},
"RuleId": 123,
"description": "Test Rule",
"isDisabled": false,
"Criteria": [
{
"autoSecondaryCriteriaId": 8888,
"criteriaType": { "code": "primaryPayer", "value": "Primary Payer" },
"payerId": ["12345", "34567"]
}
]
}
]
}
const data = payers.Payers.filter(payer => rules.Rules.findIndex(rule => rule.Criteria.findIndex(criteria => criteria.payerId.includes(payer.payerId)) != -1) !== -1)
console.log(data)
I need to create a JSON schema for data that comes as an array directly within the root object, unnamed. An MWE for this kind of JSON would be:
{
[
{
"veggieName": "potato",
"veggieLike": true
},
{
"veggieName": "broccoli",
"veggieLike": false
}
]
}
I have seen examples for schemas which validate such an array which is not nested in an object. I have also seen examples which work when the array is named, for example
{
vegetables : [
{
"veggieName": "potato",
"veggieLike": true
},
{
"veggieName": "broccoli",
"veggieLike": false
}
]
}
This second example can be validated by the schema
{
"$id": "https://example.com/arrays.schema.json",
"$schema": "http://json-schema.org/draft-07/schema#",
"description": "A representation of a person, company, organization, or place",
"type": "object",
"properties": {
"vegetables": {
"type": "array",
"items": { "$ref": "#/definitions/veggie" }
}
},
"definitions": {
"veggie": {
"type": "object",
"required": [ "veggieName", "veggieLike" ],
"properties": {
"veggieName": {
"type": "string",
"description": "The name of the vegetable."
},
"veggieLike": {
"type": "boolean",
"description": "Do I like this vegetable?"
}
}
}
}
}
But the problem is, as soon as the name "vegetables" is removed, I was not able to find a way to define a valid schema. How do I properly represent my data structure in a schema?
(MWEs derived from http://json-schema.org/learn/miscellaneous-examples.html).
The schema you are looking for is the following:
{
"$id":"https://example.com/arrays.schema.json",
"$schema":"http://json-schema.org/draft-07/schema#",
"description":"A representation of a person, company, organization, or place",
"type":"array",
"items":{
"type":"object",
"required":[
"veggieName",
"veggieLike"
],
"properties":{
"veggieName":{
"type":"string",
"description":"The name of the vegetable."
},
"veggieLike":{
"type":"boolean",
"description":"Do I like this vegetable?"
}
}
}
}
You also need to modify your base array instance, your original one (the "unnamed" array) was not valid JSON:
[
{
"veggieName":"potato",
"veggieLike":true
},
{
"veggieName":"broccoli",
"veggieLike":false
}
]
Unlike XML, where you are allowed a single root node per document only, in JSON you can have either a type or an array as a root type.
I am trying to use graphQL in a GatsbyJS project, and am unsure how I can pull a specific 'URL' object, from a list of three, within a 'recipeImages' object. Right now, I can only pull the recipeImages object, like this:
<img src={node.recipeImages}/>
but I want to be able to get to the three individual URL objects seen in this query:
{
"data": {
"allContentfulBlogPost": {
"edges": [
{
"node": {
"id": "c1Qz3hWuPuQEIIUkSos0MEO",
"postTitle": "Schwarzwälder Kirschtorte",
"postDate": "2018-01-30T00:00+01:00",
"slug": "schwarzwälder-kirschtorte",
"methodText": {
"childMarkdownRemark": {
"html": "<p>This is the method text</p>"
}
},
"recipeImages": [
{
"title": "imageOne",
"file": {
"url": "//images.contentful.com/62o0h4ehxjxr/kkc57vWLPaEakYueyYqC6/c61b4641797a2fcaf3476ef9a3a24db6/image.jpg"
}
},
{
"title": "imageTwo",
"file": {
"url": "//images.contentful.com/62o0h4ehxjxr/2ifxQEvnYwkaAe6e2YKISa/de2b6f62c4cac3b501fe76146b745790/image1.jpg"
}
},
{
"title": "imageThree",
"file": {
"url": "//images.contentful.com/62o0h4ehxjxr/17g7ZHqrEWIgcyuye08myG/6b55386a31db2dd319148795953da7a4/image2.jpg"
}
}
]
}
}
]
}
}
}
i got it:
<img src={recipeImages[0].responsiveResolution.src}/>
I'm using document references to import parent fields into a child document. While searches against the parent fields work, the parent fields themselves do not seem to be included in the search results, only child fields.
To use the example in the documentation, salesperson_name does not appear in the fields entry for id:test:ad::1 when using query=John, or indeed when retrieving id:test:ad::1 via GET directly.
Here's a simplified configuration for my document model:
search definitions
person.sd - the parent
search person {
document person {
field name type string {
indexing: summary | attribute
}
}
fieldset default {
fields: name
}
}
event.sd - the child
search event {
document event {
field code type string {
indexing: summary | attribute
}
field speaker type reference<person> {
indexing: summary | attribute
}
}
import field speaker.name as name {}
fieldset default {
fields: code
}
}
documents
p1 - person
{
"fields": {
"name": "p1"
}
}
e1 - event
{
"fields": {
"code": "e1",
"speaker": "id:n1:person::1"
}
}
query result
curl -s "http://localhost:8080/search/?yql=select%20*%20from%20sources%20*where%20name%20contains%20%22p1%22%3B" | python -m json.tool
This returns both e1 and p1, as you would expect, given that name is present in both. But the fields of e1 do not include the name.
{
"root": {
"children": [
{
"fields": {
"documentid": "id:n1:person::1",
"name": "p1",
"sddocname": "person"
},
"id": "id:n1:person::1",
"relevance": 0.0017429193899782135,
"source": "music"
},
{
"fields": {
"code": "e1",
"documentid": "id:n1:event::1",
"sddocname": "event",
"speaker": "id:n1:person::1"
},
"id": "id:n1:event::1",
"relevance": 0.0017429193899782135,
"source": "music"
}
],
...
"fields": {
"totalCount": 2
},
}
}
Currently you'll need to add the imported 'name' into the default summary by
import field speaker.name as name {}
document-summary default {
summary name type string{}
}
More about explicit document summaries in http://docs.vespa.ai/documentation/document-summaries.html
The result of your query will then return
"children": [
{
"fields": {
"documentid": "id:n1:person::1",
"name": "p1",
"sddocname": "person"
},
"id": "id:n1:person::1",
"relevance": 0.0017429193899782135,
"source": "stuff"
},
{
"fields": {
"code": "e1",
"documentid": "id:n1:event::1",
"name": "p1",
"sddocname": "event",
"speaker": "id:n1:person::1"
},
"id": "id:n1:event::1",
"relevance": 0.0017429193899782135,
"source": "stuff"
}
],
We'll improve the documentation on this. Thanks for the very detailed write-up.
Add "summary" to the indexing statement of the imported field in the parent document type.
E.g in the documentation example change the "name" field in the "salesperson" document type to say "indexing: attribute | summary".
Currently I have a hundreds of thousands of files like so:
{
"_id": "1234567890",
"type": "file",
"name": "Demo File",
"file_type": "application/pdf",
"size": "1400",
"timestamp": "1491421149",
"folder_id": "root"
}
Currently, I index all the names, and a client can search for files based on the name of the file. These files also have tags that need to be associated with the file but they also have specific labels.
An example would be:
{
"tags": [
{ "client": "john doe" },
{ "office": "virginia" },
{ "ssn": "1234" }
]
}
Is adding the tags array to my above file object the ideal solution if I want to be able to search thousands of files with a client of John Doe?
The only other solution I can think of is having something an object per tag and having an array of file ID's associated with each tag like so:
{
"_id": "11111111",
"type": "tag",
"label": "client",
"items": [
"1234567890",
"1222222222",
"1333333333"
]
}
With this being a LOT of objects I need to add tags to, I'd rather do it the most efficient way possible FIRST so I don't have to backtrack in the near future when I start running into issues.
Any guidance would be greatly appreciated.
Your original design, with a tags array, works well with Cloudant Search: https://console.ng.bluemix.net/docs/services/Cloudant/api/search.html#search.
With this approach you would define a single design document that will index any tag in the tags array. You do not have to create different views for different tags and you can use the Lucene syntax for queries: http://lucene.apache.org/core/4_3_0/queryparser/org/apache/lucene/queryparser/classic/package-summary.html#Overview.
So, using your example, if you have a document that looks like this with tags:
{
"_id": "1234567890",
"type": "file",
"name": "Demo File",
"file_type": "application/pdf",
"size": "1400",
"timestamp": "1491421149",
"folder_id": "root",
"tags": [
{ "client": "john doe" },
{ "office": "virginia" },
{ "ssn": "1234" }
]
}
You can create a design document that indexes each tag like so:
{
"_id": "_design/searchFiles",
"views": {},
"language": "javascript",
"indexes": {
"byTag": {
"analyzer": "standard",
"index": "function (doc) {\n if (doc.type === \"file\" && doc.tags) {\n for (var i=0; i<doc.tags.length; i++) {\n for (var name in doc.tags[i]) {\n index(name, doc.tags[i][name]);\n }\n }\n }\n}"
}
}
}
The function looks like this:
function (doc) {
if (doc.type === "file" && doc.tags) {
for (var i=0; i<doc.tags.length; i++) {
for (var name in doc.tags[i]) {
index(name, doc.tags[i][name]);
}
}
}
}
Then you would search like this:
https://your_cloudant_account.cloudant.com/your_db/_design/searchFiles/_search/byTag
?q=client:jack+OR+office:virginia
&include_docs=true
The solution, that comes into my mind would be using map reduce functions.
To do that, you would add the tags to your original document:
{
"_id": "1234567890",
"type": "file",
"name": "Demo File",
"file_type": "application/pdf",
"size": "1400",
"timestamp": "1491421149",
"folder_id": "root",
"client": "john",
...
}
Afterwards, you can create a design document, that looks like this:
{
"_id": "_design/query",
"views": {
"byClient": {
"map": "function(doc) { if(doc.client) { emit(doc.client, doc._id) }}"
}
}
}
After the view is processed, you can open it with
GET /YOURDB/_design/query/_view/byClient?key="john"
By adding the query parameter include_docs=true, the whole document will be returned, instead of the id.
You can also write your tags into an tags attribute, but you have to update the map function to match the new design.
More information about views can be found here:
http://docs.couchdb.org/en/2.0.0/api/ddoc/views.html