I have two resolver.
The one is Company resolve that return the company details like id, name and list of documents ids, like this example:
{
"data": {
"companyOne": {
"name": "twitter",
"documents": [
"5c6c0213f0fa854bd7d4a38c",
"5c6c02948e0001a16529a1a1",
"5c6c02ee7e76c12075850119",
"5c6ef2ddd16e19889ffaffd0",
"5c72fb723ebf7b2881679ced",
"5c753d1c2e080fa4a2f86c87",
...
]
}
}
}
And the another resolver gets me all the details of documents like this example:
{
"data": {
"documentsMany": [{
"name": "doc1",
"_id": 5c6c0213f0fa854bd7d4a38c,
}, {
"name": "doc2",
"_id": 5c6c02948e0001a16529a1a1,
},
...
]
}
}
How to match every data.companyOne.documents[id] to data.documentsMany[..]._id? in the query level? is it possible to do this graphql?
The expect results should be when I run the companyOne query (without change the code - just in the query level) it's should return with documents as object instead of array of string ids.
maybe something like?
query {
companyOne {
name,
documents on documentsMany where _id is ___???
}
}
Related
I have a Node.js GraphQL server. From the client, I am trying get all the user entries using a query like this:
{
user {
name
entries {
title
body
}
}
}
In the Node.js GraphQL server, however I want to return user entries that are currently valid based on publishDate and expiryDate in the entries object.
For example:
{
"user": "john",
"entries": [
{
"title": "entry1",
"body": "body1",
"publishDate": "2019-02-12",
"expiryDate": "2019-02-13"
},
{
"title": "entry2",
"body": "body2",
"publishDate": "2019-02-13",
"expiryDate": "2019-03-01"
},
{
"title": "entry3",
"body": "body3",
"publishDate": "2020-01-01",
"expiryDate": "2020-01-31"
}
]
}
should return this
{
"user": "john",
"entries": [
{
"title": "entry2",
"body": "body2",
"publishDate": "2019-02-13",
"expiryDate": "2019-03-01"
}
]
}
The entries is fetched via a delegateToSchema call (https://www.apollographql.com/docs/graphql-tools/schema-delegation.html#delegateToSchema) and I don't have an option to pass publishDate and expiryDate as query parameters. Essentially, I need to get the results and then filter them in memory.
The issue I face is that the original query doesn't have publishDate and expiryDate in it to support this. Is there a way to add these fields to delegateToSchema call and then remove them while sending them back to the client?
You are looking for transformResult
Implementation details are:
At delegateToSchema you need to define transforms array.
At Transform you need to define transformResult function for filtering results.
If you have ability to send arguments to remote GraphQL server, then you should use
transformRequest
I would like to create a map/reduce function that filters the documents based on a nested value from the child document. But retrieve the parent document.
I have following documents:
{
"_id": "1",
"_rev": "1-991baf1d86435a73a3460335cc19063c",
"configuration_id": "225f9d47-841c-43c2-90c2-e65bb49083d3",
"name": "test",
"image": "",
"type": "A",
"created": "",
"updated": 1,
"destroyed": ""
}
{
"_id": "225f9d47-841c-43c2-90c2-e65bb49083d3",
"_rev": "1-3e3a1c357c86cbd1cd42b5980b9655a4",
"configuration_packages_id": "cd19b0ba-157d-4dd4-adac-56fd470bfed4",
"configuration_distribution_id": "5b538411-ca99-46c7-ac3c-1f382e4577a9",
"type": "CONFIGURATION",
"configuration": {
"hostname": "example123",
"images": [
"image1",
"image2"
]
}
}
Now I would like to retrieve all the documents of type A and with hostname example123.
At the moment I retrieve all the document of type A like this:
function (doc) {
if (doc.type === "A") {
emit([doc.updated], doc);
}
}
But now I would also like to filter on the host name as well.
I'm not sure on how to achieve this with CouchDB.
TLDR;
You cannot do this
Details
Your "nested" document is only accessible through a join but you can't query it.
The correct way to do that kind of query natively would have been to have a real nested document inside the parent document. Separating those documents has a cost.
Join example
function (doc) {
if (doc.type === "A") {
emit([doc.updated,0]);
emit([doc.updated,1],["_id":doc.configuration_id]);
}
}
If you query the view with "include_docs=true", this will get you the configuration document linked as well as the parent document itself. Then you can query to get the updated docs, merge the nested(1) with the parents(0) and filter them.
Let's take this document for example:
{
"id":1
"planet":"earth-616"
"data":[
["wolverine","mutant"],
["Storm","mutant"],
["Mark Zuckerberg","human"]]
}
I created a search index to index the name and type, for example if searched for name:wolverine or type:mutant I'd get the document that has it. But as per my requirement I don't want the whole document, I only want ["wolverine","mutant"] I've created a view that outputs as:
{
"id":1,
"key":"earth-616",
"value":["earth-616","wolverine","mutant"]
}
Then I found out I can query only with keys. (Is it possible to create search indexes on views?, Couldn't find anything in the documentation)
Or should I create views along with the one above like this:
{
"id":1,
"key":"wolverine",
"value":["earth-616","wolverine","mutant"]
}
And
{
"id":,
"key":"mutant"
"value":["earth-616","wolverine","mutant"]
}
This way I can query with keys that I want but I can't seem to partial match keys(Am I missing something?)
If you need the output to be exactly as described then I believe you have to use views, and to support wildcard searches I believe you will have to index every substring of a key.
One alternative is to use Cloudant Query, although admittedly you cannot get the exact output you are looking for. If you issue a query like so:
{
"selector": {
"_id": {
"$gt": 0
},
"data": {
"$elemMatch": {
"$elemMatch": {
"$regex": "(?i)zuck"
}
}
}
},
"fields": [
"data"
]
}
The result will be the entire data array:
{
"data": [
["wolverine", "mutant"],
["Storm", "mutant"],
["Mark Zuckerberg", "human"]
]
}
I have a document stored in ElasticSearch as below.
_source:
{
"firstname": "John",
"lastname": "Smith",
"medals":[
{
"bucket": 100,
"count": 1
},
{
"bucket": 150,
"count": 2
}
]
}
I can access the string type value inside a document using doc.firstname for scripted metric aggregation http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/search-aggregations-metrics-scripted-metric-aggregation.html.
But I am not able to get the field value using doc.medals[0].bucket.
Can you please help me out and let me know how to access the values inside nested fields?
Use _source for nested properties.
Doc holds fields that are loaded in memory. Nested documents may not be loaded and should be accessed with _source.
For instance:
GET index/type
{
"aggs": {
"NAME": {
"scripted_metric": {
"init_script": "_agg['collection']=[]",
"map_script": "_agg['tr'].add(_source.propertry1.prop);",
"combine_script": "return _agg",
"reduce_script": "return _aggs"
}
}
},
"size": 0
}
How do I search for all unique values of a given field with Elasticsearch?
I have such a kind of query like select full_name from authors, so I can display the list to the users on a form.
You could make a terms facet on your 'full_name' field. But in order to do that properly you need to make sure you're not tokenizing it while indexing, otherwise every entry in the facet will be a different term that is part of the field content. You most likely need to configure it as 'not_analyzed' in your mapping. If you are also searching on it and you still want to tokenize it you can just index it in two different ways using multi field.
You also need to take into account that depending on the number of unique terms that are part of the full_name field, this operation can be expensive and require quite some memory.
For Elasticsearch 1.0 and later, you can leverage terms aggregation to do this,
query DSL:
{
"aggs": {
"NAME": {
"terms": {
"field": "",
"size": 10
}
}
}
}
A real example:
{
"aggs": {
"full_name": {
"terms": {
"field": "authors",
"size": 0
}
}
}
}
Then you can get all unique values of authors field.
size=0 means not limit the number of terms(this requires es to be 1.1.0 or later).
Response:
{
...
"aggregations" : {
"full_name" : {
"buckets" : [
{
"key" : "Ken",
"doc_count" : 10
},
{
"key" : "Jim Gray",
"doc_count" : 10
},
]
}
}
}
see Elasticsearch terms aggregations.
Intuition:
In SQL parlance:
Select distinct full_name from authors;
is equivalent to
Select full_name from authors group by full_name;
So, we can use the grouping/aggregate syntax in ElasticSearch to find distinct entries.
Assume the following is the structure stored in elastic search :
[{
"author": "Brian Kernighan"
},
{
"author": "Charles Dickens"
}]
What did not work: Plain aggregation
{
"aggs": {
"full_name": {
"terms": {
"field": "author"
}
}
}
}
I got the following error:
{
"error": {
"root_cause": [
{
"reason": "Fielddata is disabled on text fields by default...",
"type": "illegal_argument_exception"
}
]
}
}
What worked like a charm: Appending .keyword with the field
{
"aggs": {
"full_name": {
"terms": {
"field": "author.keyword"
}
}
}
}
And the sample output could be:
{
"aggregations": {
"full_name": {
"buckets": [
{
"doc_count": 372,
"key": "Charles Dickens"
},
{
"doc_count": 283,
"key": "Brian Kernighan"
}
],
"doc_count": 1000
}
}
}
Bonus tip:
Let us assume the field in question is nested as follows:
[{
"authors": [{
"details": [{
"name": "Brian Kernighan"
}]
}]
},
{
"authors": [{
"details": [{
"name": "Charles Dickens"
}]
}]
}
]
Now the correct query becomes:
{
"aggregations": {
"full_name": {
"aggregations": {
"author_details": {
"terms": {
"field": "authors.details.name"
}
}
},
"nested": {
"path": "authors.details"
}
}
},
"size": 0
}
Working for Elasticsearch 5.2.2
curl -XGET http://localhost:9200/articles/_search?pretty -d '
{
"aggs" : {
"whatever" : {
"terms" : { "field" : "yourfield", "size":10000 }
}
},
"size" : 0
}'
The "size":10000 means get (at most) 10000 unique values. Without this, if you have more than 10 unique values, only 10 values are returned.
The "size":0 means that in result, "hits" will contain no documents. By default, 10 documents are returned, which we don't need.
Reference: bucket terms aggregation
Also note, according to this page, facets have been replaced by aggregations in Elasticsearch 1.0, which are a superset of facets.
The existing answers did not work for me in Elasticsearch 5.X, for the following reasons:
I needed to tokenize my input while indexing.
"size": 0 failed to parse because "[size] must be greater than 0."
"Fielddata is disabled on text fields by default." This means by default you cannot search on the full_name field. However, an unanalyzed keyword field can be used for aggregations.
Solution 1: use the Scroll API. It works by keeping a search context and making multiple requests, each time returning subsequent batches of results. If you are using Python, the elasticsearch module has the scan() helper function to handle scrolling for you and return all results.
Solution 2: use the Search After API. It is similar to Scroll, but provides a live cursor instead of keeping a search context. Thus it is more efficient for real-time requests.