Here's an example of what I would like to do based on this example in Algolia docs: https://www.algolia.com/doc/api-reference/api-methods/multiple-queries/
var algolia = algoliasearch(app_id, search_only_key);
var regionIndex = algolia.initIndex("Global");
var algoliaPlaces = algoliasearch.initPlaces(app_id, search_only_key)
algolia.search([
{
index: algoliaPlaces,
query: "211 Solti St"
}, {
index: regionIndex,
query: "211 Solti St"
}
])
You cannot use multiple-queries to query Places since it is a service API and not a simple index.
You can query both separately and combine results, or take a look at the following example that does what you want!
https://community.algolia.com/places/examples.html#autocompletejs
Related
With some complex queries and aggregation, I got the list of object ids as below:
var objectIdsCollection = Array of ObjectIds
I have another collection, it's say Collection1 and It has OtherCollectionObjectId. Now, I need to filter this Collection1 based on object ids I got in an array.
Collection1 {
_id: ObjectId('xyz'),
name: ..
someOtherAttributes: ...
OtherCollectionObjectId: ObjectId('abc')
}
Below is the query which I am trying. I need to use await because, the result of this query is dependent on another query.
let queryData = await Document1.aggregate([
{
$match: {
OtherCollectionObjectId: {
$in: objectIdsCollection,
},
Deleted: false,
},
},
]);
But, this query is performing way slow. Sometimes it takes around 1 minute to fetch the results.
I tried couple of other suggestions from internet but nothing seems to work for this kind of scenario.
Please let me know anything which can improve the performance of this query.
Thanks
We are using MongoDB Atlas Search Indexes to query and filter the documents list. consider below document.
{_id:5sfgdfgf2c46e0fb00019bdecc,
user_id:4996,
bom_number:"112",
name:"test"}
Created default Index:
{
"mappings": {
"dynamic": false,
"fields": {
"user_id": {
"type": "string"
}
}
}
}
Query:
{
text: {
query: ["4996","3888"],
path: 'user_id'
}
}
It is not returning any documents. Can anyone please guide. I know we actually stored user_id as numeric form and I tried indexing and querying the field as String. Please help me out and suggest correct way of querying mongo atlas numeric field with multiple values.
$search is what you need to use to query using the index that you have created and you also need to mention the name of the index in the query.
The below draft might help you:
$search:{
{
index: "index_name_created_from_atlas_search",
text: {
query: "<actual data you need to search>",
path: "<field_name>"
}
}
}
And based on your example, if you want to have multiple conditions with the search, you can refer to official documentation here of all sorts of multiple conditions you can integrate with the $search aggregation using the compound operator.
I am working on a collection called Publications. Each publication has an array of objectives which are ids. I have also a custom array of objectives hand written. Now, I want to select all the publications that contains at least one element of the custom objectives array in their objectives. How can I do that ?
I've been trying to make this works with '$setIntersection' then '$count' and verify that the count is greater than 0 but I don't know how to implement this.
Example :
publication_1: {
'_id': ObjectId("sdfsdf46543")
'objectives': [ObjectId("1654351456341"), ObjectId("123456789")]
}
publication_2: {
'_id': ObjectId("sdfs216546543")
'objectives': [ObjectId("1654351456341"), ObjectId("46531132")]
}
custom_array = [ObjectId("123456789"), ObjectId("2416315463")]
The mongo query should return publication_1.
You can do like the following:
db.publications.find({
"objectives": {
"$in": [
ObjectId("123456789"),
ObjectId("2416315463")
]
}
})
Notice: "123456789" is not a valid ObjectId so the query itself may not work. Here is the working example
Mongodb playground link: https://mongoplayground.net/p/MbZK99Pd5YR
objectives is an array of objects, I guess you can just query that field directly:
let custom_array = [ObjectId("123456789"), ObjectId("2416315463")];
// You can search the array with $in property.
let result = await Model.find({ objectives: {$in : custom_array} })
I've got a question on the design of documents in order to be able to efficiently perform aggregation. I will take a dummy example of document :
{
product: "Name of the product",
description: "A new product",
comments: [ObjectId(xxxxx), ObjectId(yyyy),....]
}
As you could see, I have a simple document which describes a product and wraps some comments on it. Imagine this product is very popular so that it contains millions of comments. A comment is a simple document with a date, a text and eventually some other features. The probleme is that such a product can easily be larger than 16MB so I need not to embed comments in the product but in a separate collection.
What I would like to do now, is to perform aggregation on the product collection, a first step could be for example to select various products and sort the comments by date. It is a quite easy operation with embedded documents, but how could I do with such a design ? I only have the ObjectId of the comments and not their content. Of course, I'd like to perform this aggregation in a single operation, i.e. I don't want to have to perform the first part of the aggregation, then query the results and perform another aggregation.
I dont' know if that's clear enough ? ^^
I would go about it this way: create a temp collection that is the exact copy of the product collection with the only exception being the change in the schema on the comments array, which would be modified to include a comment object instead of the object id. The comment object will only have the _id and the date field. The above can be done in one step:
var comments = [];
db.product.find().forEach( function (doc){
doc.comments.forEach( function(x) {
var obj = {"_id": x };
var comment = db.comment.findOne(obj);
obj["date"] = comment.date;
comments.push(obj);
});
doc.comments = comments;
db.temp.insert(doc);
});
You can then run your aggregation query against the temp collection:
db.temp.aggregate([
{
$match: {
// your match query
}
},
{
$unwind: "$comments"
},
{
$sort: { "comments.date": 1 } // sort the pipeline by comments date
}
]);
I'm using Mongoose.js to perform an $in query, like so:
userModel.find({
'twitter_username': {
$in: friends
}
})
friends is just an array of strings. However, I'm having some case issues, and wondering if I can use Mongo's $regex functionality to make this $in query case-insensitive?
From the docs:
To include a regular expression in an $in query expression, you can
only use JavaScript regular expression objects (i.e. /pattern/ ). For
example:
{ name: { $in: [ /^acme/i, /^ack/ ] } }
One way is to create regular Expression for each Match and form the friends array.
var friends = [/^name1$/i,/^name2$/i];
or,
var friends = [/^(name1|name2)$/i]
userModel.find({"twitter_username":{$in:friends }})
Its a little tricky to do something like that
at first you should convert friends to new regex array list with:
var insesitiveFriends = [];
friends.forEach(function(item)
{
var re = new RegExp(item, "i");
insesitiveFriends.push(re);
})
then run the query
db.test.find(
{
'twitter_username':
{
$in: insesitiveFriends
}
})
I have the sample documents in test collection
/* 0 */
{
"_id" : ObjectId("5485e2111bb8a63952bc933d"),
"twitter_username" : "David"
}
/* 1 */
{
"_id" : ObjectId("5485e2111bb8a63952bc933e"),
"twitter_username" : "david"
}
and with var friends = ['DAvid','bob']; I got both documents
Sadly, mongodb tends to be pretty case-sensitive at the core. You have a couple of options:
1) Create a separate field that is a lowercase'd version of the twitter_username, and index that one instead. Your object would have twitter_username and twitter_username_lc. The non-lowerecase one you can use for display etc, but the lowercase one you index and use in your where clause etc.
This is the route I chose to go for my application.
2) Create a really ugly regex from your string of usernames in a loop prior to your find, then pass it in:
db.users.find({handle:{$regex: /^benhowdle89|^will shaver|^superman/i } })
Note that using the 'starts with' ^ carrot performs better if the field is indexed.