I have the following documents:
{
"_id": "doc1"
"binds": {
"subject": {
"Test1": ["something"]
},
"object": {
"Test2": ["something"]
}
},
},
{
"_id": "doc2"
"binds": {
"subject": {
"Test1": ["something"]
},
"object": {
"Test3": ["something"]
}
},
}
I need a Mango selector that retrieves documents where any field inside binds (subject, object etc) has an object with key equals to any values from an array passed as parameter. That is, if keys of binds contains any values of some array it should returns that document.
For instance, consider the array ["Test2"] my selector should retrieve doc1 since binds["subject"]["Test1"] exists; the array ["Test1"] should retrieve doc1 and doc2 and the array ["Test2", "Test3"] should also retrieve doc1 and doc2.
F.Y.I. I am using Node.js with nano lib to access CouchDB API.
I am providing this answer because the luxury of altering document "schema" is not always an option.
With the given document structure this cannot be done with Mango in any reasonable manner. Yes, it can be done, but only when employing very brittle and inefficient practices.
Mango does not provide an efficient means of querying documents for dynamic properties; it does support searching within property values e.g. arrays1.
Using worst practices, this selector will find docs with binds properties subject and object having properties named Test2 and Test3
{
"selector": {
"$or": [
{
"binds.subject.Test2": {
"$exists": true
}
},
{
"binds.object.Test2": {
"$exists": true
}
},
{
"binds.subject.Test3": {
"$exists": true
}
},
{
"binds.object.Test3": {
"$exists": true
}
}
]
}
}
Yuk.
The problems
The queried property names vary so a Mango index cannot be leveraged (Test37 anyone?)
Because of (1) a full index scan (_all_docs) occurs every query
Requires programmatic generation of the $or clause
Requires a knowledge of the set of property names to query (Test37 anyone?)
The given document structure is a show stopper for a Mango index and query.
This is where map/reduce shines
Consider a view with the map function
function (doc) {
for(var prop in doc.binds) {
if(doc.binds.hasOwnProperty(prop)) {
// prop = subject, object, foo, bar, etc
var obj = doc.binds[prop];
for(var objProp in obj) {
if(obj.hasOwnProperty(objProp)) {
// objProp = Test1, Test2, Test37, Fubar, etc
emit(objProp,prop)
}
}
}
}
}
So the map function creates a view for any docs with a binds property with two nested properties, e.g. binds.subject.Test1, binds.foo.bar.
Given the two documents in the question, this would be the basic view index
id
key
value
doc1
Test1
subject
doc2
Test1
subject
doc1
Test2
object
doc2
Test3
object
And since view queries provide the keys parameter, this query would provide your specific solution using JSON
{
include_docs: true,
reduce: false,
keys: ["Test2","Test3"]
}
Querying that index with cUrl
$ curl -G http://{view endpoint} -d 'include_docs=false' -d
'reduce=false' -d 'keys=["Test2","Test3"]'
would return
{
"total_rows": 4,
"offset": 2,
"rows": [
{
"id": "doc1",
"key": "Test2",
"value": "object"
},
{
"id": "doc2",
"key": "Test3",
"value": "object"
}
]
}
Of course there are options to expand the form and function of such a view by leveraging collation and complex keys, and there's the handy reduce feature.
I've seen commentary that Mango is great for those new to CouchDB due to it's "ease" in creating indexes and the query options, and that map/reduce if for the more seasoned. I believe such comments are well intentioned but misguided; Mango is alluring but has its pitfalls1. Views do require considerable thought, but hey, that's we're supposed to be doing anyway.
1) $elemMatch for example require in memory scanning which can be very costly.
Related
I have a Cosmos DB with documents that look like the following:
{
"name": {
"productName": "someProductName"
},
"identifiers": [
{
"identifierCode": "1234",
"identifierLabel": "someLabel1"
},
{
"identifierCode": "432",
"identifierLabel": "someLabel2"
}
]
}
I would like to write a sql query to obtain an entire document using "identifierLabel" as a filter when searching for the document.
I attempted to write a query based on an example I found from the following blog:
SELECT c,t AS identifiers
FROM c
JOIN t in c.identifiers
WHERE t.identifierLabel = "someLabel2"
However, when the result is returned, it appends the following to the end of the document:
{
"name": {
"productName": "someProductName"
},
"identifiers": [
{
"identifierCode": "1234",
"identifierLabel": "someLabel1"
},
{
"identifierCode": "432",
"identifierLabel": "someLabel2"
}
]
},
{
"identifierCode": "432",
"identifierLabel": "someLabel2"
}
How can I avoid this and get the result that I desire, i.e. the entire document with nothing appended to it?
Thanks in advance.
Using ARRAY_CONTAINS(), you should be able to do something like this to retrieve the entire document, without any need for a self-join:
SELECT *
FROM c
where ARRAY_CONTAINS(c.identifiers, {"identifierLabel":"someLabel2"}, true)
Note that ARRAY_CONTAINS() can search for either scalar values or objects. By specifying true as the third parameter, it signifies searching through objects. So, in the above query, it's searching all objects in the array where identifierLabel is set to "someLabel2" (and then it should be returning the original document, unchanged, avoiding the issue you ran into with the self-join).
I'm trying to efficiently query data via Mango (as that seems to be the only option given my requirements Searching for sub-objects with a date range containing the queried date value), but I can't even get a very simple index/query pair to work: although I specify my index manually for the query, I'm told that my index "was not used because it does not contain a valid index for this query. No matching index found, create an index to optimize query time."
(I'm doing all of this via Fauxton on CouchDB v. 3.0.0)
Let's say my documents look like this:
{
"tenant": "TNNT_a",
"$doctype": "JobOpening",
// a bunch of other fields
}
All documents with a $doctype of "JobOpening" are guaranteed to have a tenant property. The searches I wish to perform will only ever be for documents with $doctype of "JobOpening" and a tenant selector will always be provided when querying.
Here's the test index I've configured:
{
"index": {
"fields": [
"tenant",
"$doctype"
],
"partial_filter_selector": {
"\\$doctype": {
"$eq": "JobOpening"
}
}
},
"ddoc": "job-openings-doctype-index",
"type": "json"
}
And here's the query
{
"selector": {
"tenant": "TNNT_a",
"\\$doctype": "JobOpening"
},
"use_index": "job-openings-doctype-index"
}
Why isn't the index being used for the query?
I've tried not using a partial index, and I think the $doctype escaping is done properly in the requisite places, but nothing seems to keep CouchDB from performing a full scan.
The index isn't being used because the $doctype field is not being recognized by the query planner as expected.
Changing the fields declaration from $doctype to \\$doctype in the design document solves the issue.
{
"index": {
"fields": [
"tenant",
"\\$doctype"
],
"partial_filter_selector": {
"\\$doctype": {
"$eq": "JobOpening"
}
}
},
"ddoc": "job-openings-doctype-index",
"type": "json"
}
After that small refactor, the query
{
"selector": {
"tenant": "TNNT_a",
"\\$doctype": "JobOpening"
},
"use_index": "job-openings-doctype-index"
}
Returns the expected result, and produces an "explain" which confirms the job-openings-doctype-index was queried:
{
"dbname": "stack",
"index": {
"ddoc": "_design/job-openings-doctype-index",
"name": "7f5c5cea5acd90f11fffca3e3355b6a03677ad53",
"type": "json",
"def": {
"fields": [
{
"tenant": "asc"
},
{
"\\$doctype": "asc"
}
],
"partial_filter_selector": {
"\\$doctype": {
"$eq": "JobOpening"
}
}
}
},
// etc etc etc
Whether this change is intuitive or not is unclear, however it is consistent - and perhaps reveals leading field names with a "special" character may not be desirable.
Regarding the indexing of the filtered field, as per the documentation regarding partial_filter_selector
Technically, we don’t need to include the filter on the "status" [e.g.
$doctype here] field in the query selector ‐ the partial index
ensures this is always true - but including it makes the intent of the
selector clearer and will make it easier to take advantage of future
improvements to query planning (e.g. automatic selection of partial
indexes).
Despite that, I would not choose to index a field whose value is constant.
I am trying to create a CouchDB Mango Query with an index with the hope that the query runs faster. At the moment I have the following Mango Query which returns what I am looking for but it's slow. Therefore, I assume, I need to create an index to make it faster. I need help figuring out how to create that index.
selector: {
categoryIds: {
$in: categoryIds,
},
},
sort: [{ publicationDate: 'desc' }],
You can assume that my documents are let say news articles from different categories. Therefore in each document I have a field that contains one or more categories that the news article belongs to. For that I have an array of categoryIds for each document. My query needs to be optimized for queries like "Give me all news that have categoryId1 in their array of categoryIds sorted by publicationDate". What I don't know how to do is 1. How to define an index 2. What that index should be 3. How to use that index in "use_index" field of the Mango Query. Any help is appreciated.
Update after "Alexis Côté" answer:
If I define the index like this:
{
"_id": "_design/0f11ca4ef1ea06de05b31e6bd8265916c1bbe821",
"_rev": "6-adce50034e870aa02dc7e1e075c78361",
"language": "query",
"views": {
"categoryIds-json-index": {
"map": {
"fields": {
"categoryIds": "asc"
},
"partial_filter_selector": {}
},
"reduce": "_count",
"options": {
"def": {
"fields": [
"categoryIds"
]
}
}
}
}
}
And run the Mango Query like this:
{
"selector": {
"categoryIds": {
"$in": [
"e0bd5f97ac35bdf6893351337d269230"
]
}
},
"use_index": "categoryIds-json-index"
}
It still does return the results but they are not sorted in the order I want by publicationDate. So I am not clear what you are suggesting the solution is.
You can create an index as documented here
In your case, you will need an index on the "categoryIds" field.
You can specify the index using "use_index": "_design/<name>"
Note:The query planner should automatically pick this index if it's compatible.
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 ___???
}
}
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.