I’ve got a question I can’t seemingly resolve on my own.
Together with basic Query, Mutation and so on types I’ve made the following type definition:
module Types
UserType = GraphQL::ObjectType.define do
name 'User'
description 'A user'
implements GraphQL::Relay::Node.interface
global_id_field :id
field :email, !types.String, 'Email address'
connection :docs, DocType.connection_type, 'Available docs'
end
end
And I then try to query it with:
query FileListQuery(
$after: String
$first: Int
) {
viewer {
currentUser {
docs(first: $first, after: $after) {
edges {
node {
id
name
__typename
}
cursor
}
pageInfo {
endCursor
hasNextPage
hasPreviousPage
startCursor
}
}
id
}
id
}
}
And I pass the following as query variables:
{
"first": 1,
"after": null
}
The problem is it bails out with the following:
{
"errors": [
{
"message": "Int isn't a defined input type (on $first)",
"locations": [
{
"line": 3,
"column": 3
}
],
"fields": [
"query FileListQuery"
]
}
]
}
I honestly have no clue why it complains about the Int type…
If I get rid of the problematic $first query variable in the request, it works fine.
This:
query FileListQuery(
$after: String
) {
viewer {
currentUser {
docs(first: 10, after: $after) {
edges {
node {
id
name
__typename
}
cursor
}
pageInfo {
endCursor
hasNextPage
hasPreviousPage
startCursor
}
}
id
}
id
}
}
Produces this:
{
"data": {
"viewer": {
"currentUser": {
"docs": {
"edges": [
{
"node": {
"id": "1",
"name": "First Doc",
"__typename": "Doc"
},
"cursor": "MQ=="
}
],
"pageInfo": {
"endCursor": "MQ==",
"hasNextPage": false,
"hasPreviousPage": false,
"startCursor": "MQ=="
}
},
"id": "1"
},
"id": "VIEWER"
}
}
}
Any hints, ideas on how to fix this? I use the graphql gem v1.6.3.
Currently, there seems to be a bug in graphql-ruby that prevents types not explicitly used in a schema from being propagated. Check out this issue on GitHub: https://github.com/rmosolgo/graphql-ruby/issues/788#issuecomment-308996229
To fix the error one has to include an Int field somewhere in the schema. Turns out I haven't had one. Yikes.
This fixed it for me:
# Make sure Int is included in the schema:
field :testInt, types.Int
Below is json I translated from ruby hash for ease of representation for this question using hash.to_json. Notice how the key range is being repeated since the values in the nested doc are different. How do I merge the ranges so that for the weight key both "gt": 2232, "lt": 4444 fall under the one hash key weight inside range. Is there some union or collapse method in ruby to sort of "compactify" hashes?
{
"must": [
{
"match": {
"status_type": "good"
}
},
{
"range": {
"created_date": {
"lte": 43252
}
}
},
{
"range": {
"created_date": {
"gt": "42323"
}
}
},
{
"range": {
"created_date": {
"gte": 523432
}
}
},
{
"range": {
"weight": {
"gt": 2232
}
}
},
{
"range": {
"weight": {
"lt": 4444
}
}
}
],
"should": [
{
"match": {
"product_age": "old"
}
}
]
}
Want to change the above to this:
{
"must": [
{
"range": {
"created_date": {
"gte": 523432,
"gt": "42323"
}
}
},
{
"range": {
"weight": {
"gt": 2232,
"lt": 4444
}
}
}
],
"should": [
{
"match": {
"product_age": "old"
}
}
]
}
I don't know of a built in way to handle something like this, but you could write a method that does something like this:
def collapse(array, key)
# Get only the hashes with :range
to_collapse = array.select { |elem| elem.has_key? key }
uncollapsed = array - to_collapse
# Get the hashes that :range points to
to_collapse = to_collapse.map { |elem| elem.values }.flatten
collapsed = {}
# Iterate through each range hash and their subsequent subhashes.
# Collapse the values into the collapsed hash as necessary
to_collapse.each do |elem|
elem.each do |k, v|
collapsed[k] = {} unless collapsed.has_key? k
v.each do |inner_key, inner_val|
collapsed[k][inner_key] = inner_val
end
end
end
[uncollapsed, collapsed].flatten
end
hash[:must] = collapse hash[:must], :range
Note that this is a specific solution that's mainly applicable to the presented problem. It only works for the hash/array depths specified here. You could probably write a recursive solution that could potentially work at any level of depth with a bit more work.
How do I construct the query JSON so that while filtering it checks for the presence of external params.
{"query": {
"filtered": {
"query": {
"match_all": {}
}}},
"filter": {
"and": {
"filters": [
{
"term": {
"locality_name": params[:locality_name] if params[:locality_name].present?
}
}
]
}
}}:
The if clause in the JSON is invalid syntax for query DSL.
I think you can combine existFilter and termFilter with and filter like this.
This will retrieve documents for which locality_name field exist and locality_name field value is equal to your specified value.
"filter" : {
"and" : [
{
"exists" : { "field" : "locality_name" }
},
{
"term" : { "locality_name" : "your_locality_name" }
}
]
}
http://www.elasticsearch.org/guide/reference/query-dsl/exists-filter/
http://www.elasticsearch.org/guide/reference/query-dsl/and-filter/
I am building my search query for some listing data. As part of the search people can ask for multiple rooms which sleeps a min amount of people, ie two rooms which sleep 2 and 3 people.
Im not sure how I can perform that with a filter.
Here is a shortened search query so far.
{
"query":{
"filtered":{
"query":{
"match_all":{}
}
}
},
"filter":{
"and":
[
{
"term":{
"status":"live"
}
},
{
"geo_bounding_box":{
"location":{
"top_left":"60.856553, -8.64935719999994",
"bottom_right":"49.8669688, 1.76270959999999"
}
}
}
,{
"range":{
"bedrooms":{
"gte":"2"
}
}
}
]
}
,
"size":10
}
Test Data
{
"took":1,
"timed_out":false,
"_shards":{
"total":5,
"successful":5,
"failed":0
},
"hits":{
"total":3,
"max_score":1.0,
"hits":[
{
"_index":"listings",
"_type":"listing",
"_id":"1",
"_score":1.0,
"_source":{
"name:":"Listing One",
"address1":"Some Street",
"bedrooms":2,
"city":"A City",
"id":1,
"refno":"FI451",
"user_id":1,
"rooms":[
{
"bathroom":"Shared bathroom with bath",
"double_standard":null,
"id":5,
"single":2,
"sleeps":2,
"title":"Twinny",
},
{
"bathroom":"Ensuite with bath",
"double_king_size":1,
"double_standard":1,
"id":1,
"single":null,
"sleeps":2,
"title":"Double Ensuite Room",
}
]
}
},
{
"_index":"listings",
"_type":"listing",
"_id":"2",
"_score":1.0,
"_source":{
"name":"Listing Two",
"address1":"Some Street",
"bedrooms":2,
"city":"A City",
"id":2,
"refno":"BL932",
"user_id":1,
"rooms":[
{
"bathroom":"Ensuite with bath",
"double_standard":1,
"id":4,
"single":1,
"sleeps":3,
"title":"Family Room",
},
{
"bathroom":"Ensuite with shower",
"double_standard":1,
"id":2,
"single":null,
"sleeps":2,
"title":"Single Room",
}
]
}
},
{
"_index":"listings",
"_type":"listing",
"_id":"3",
"_score":1.0,
"_source":{
"name":"Listing Three",
"address1":"Another Address",
"bedrooms":1,
"city":"Your City",
"id":3,
"refno":"TE2116",
"user_id":1,
"rooms":[
{
"bathroom":"Ensuite with shower",
"double_king_size":null,
"double_standard":1,
"id":3,
"single":1,
"sleeps":3,
"title":"Family Room",
}
]
}
}
]
}
}
If you look at my data I have 3 listings, two of them have multiple rooms (Listing One & Two) but only Listing Two would match my search, Reason it has one room with that sleeps two and the other sleeps three.
Is it possible to perform this query with elasticsearch?
If what you want is "Find all listings where a bedroom sleeps 2 AND another bedroom sleeps 3", this query will work. It makes one big assumptions: that you are using inner objects, and not the Nested data type.
This query is using the fact that inner objects are collapsed into a single field, causing "rooms.sleeps" to equal [2,3] for the desired field. Since the field is collapsed into a single array, a simple Terms query will match them. When you change the execution mode to And, it forces both 2 and 3 to be matched.
The caveat is that a room that has [2,3,4] will also be matched.
I've omitted the geo and status portion since that data wasn't provided in the source documents.
{
"query": {
"filtered": {
"query": {
"match_all": {}
}
}
},
"filter": {
"and": [
{
"range": {
"bedrooms": {
"gte": "2"
}
}
},
{
"terms": {
"rooms.sleeps": [2,3],
"execution": "and"
}
}
]
},
"size": 10
}
As far as I know the filter has to be a sibling of the query inside the filtered element. See: http://www.elasticsearch.org/guide/reference/query-dsl/filtered-query/
If you combine that with Zach's solution it should work.
{
"query":
{
"filtered":
{
"query":
{
"match_all":{}
},
"filter":
{
"put" : "your filter here"
}
}
}
}
When I am searching my ElasticSearch documents using a nested filter -> and -> geo_distance I retrieve documents which are too far away (and I don't want returned.) You can see the query and a screenshot below of the results (raw results on the left and manually filtered results on the right).
Here's another copy of the query:
{
"query":{
"match_all":{
}
},
"filter":{
"and":[
{
"term":{
"PropertySubType":"Single Family"
}
},
{
"term":{
"City":"Los Angeles"
}
},
{
"geo_distance":{
"distance":"2.25miles",
"Location":[
34.111583657,
-118.324646099
]
}
},
{
"range":{
"BedroomsTotal":{
"gte":3
}
}
},
{
"range":{
"BuildingSize":{
"gte":3000
}
}
},
{
"range":{
"YearBuilt":{
"lte":2000
}
}
},
{
"terms":{
"ListingStatus":[
"Active",
"Pending",
"Closed"
]
}
}
]
},
"size":100
}
Adding the option "distance_type" and setting it to "plane" fixed this issue. See "distance_type" here:
http://www.elasticsearch.org/guide/reference/query-dsl/geo-distance-filter.html