I am using MongoDB Atlas Search to perform a search in Collection, for this I created a Atlas Search Index:
{
"mappings": {
"dynamic": false,
"fields": {
"caption": {
"type": "string"
}
}
}
}
Here is my aggregation:
[
{
"$search":{
"text":{
"path":"caption",
"query":"Ingocnitáá",
"fuzzy":{
}
},
"highlight":{
"path":"caption"
}
}
}
]
I have below document in my collection:
{caption:"Ct tyu test Ingocnitáá"}
Issue: When I searching Ingocnitaa agreegation returning 0 result.
Is there anything wrong with my Search Index? I want an directive insensitive Search with highlight.
There are two things missing:
Include index name (Recommend to not use a default index, create a new index)
Always pass fuzzy:{}
Here is a working query:
[
{
"$search":{
"index": 'messageText',
"text":{
"path":"caption",
"query":"Ingocnitaa",
"fuzzy":{
}
},
"highlight":{
"path":"caption"
}
}
}
]
Where messageText is search index name.
Search Index Formattion:
{
"mappings": {
"dynamic": false,
"fields": {
"caption": {
"type": "string"
}
}
}
}
Reference: CLick here
Related
I have a JSON object:
{
"ownershipSheetB": {
"lrUnitShares": [{
"description": "blabla1",
"lrOwners": [{
"lrOwnerId": 35780527,
"name": "somename1",
"address": "someadress1",
"taxNumber": "12345678910"
}
],
"lrUnitShareId": 29181970,
"subSharesAndEntries": [],
"orderNumber": "1"
}, {
"description": "blabla2",
"lrOwners": [{
"lrOwnerId": 35780528,
"name": "somename2",
"address": "someadress2",
"taxNumber": "12345678911"
}
],
"lrUnitShareId": 29181971,
"subSharesAndEntries": [],
"orderNumber": "2"
}
],
"lrEntries": []
}
}
I would like to query all documents that have taxNumber field equal to some string (say "12345678911" from the example above).
I have tried this query:
{"ownershipSheetB.lrUnitShares": { "lrOwners": {"taxNumber": "12345678910"}}}
but it returns no documents.
Solution 1: With dot notation
db.collection.find({
"ownershipSheetB.lrUnitShares.lrOwners.taxNumber": "12345678910"
})
Demo Solution 1 # Mongo Playground
Solution 2: With $elemMatch
db.collection.find({
"ownershipSheetB.lrUnitShares": {
$elemMatch: {
"lrOwners": {
$elemMatch: {
"taxNumber": "12345678910"
}
}
}
}
})
Demo Solution 2 # Mongo Playground
I am trying to create a search index on atlas for a field in an object in an array.
However, the index I created doesn't work.
Example of the data:
{
"_id": "zyicGj7d2R3ezKB6s",
"arrayData": [{
_id: 'roGxCLhJPhQ7NLNed',
name: 'test'
},
{
_id: 'ziPszDHvSYXroLuFm',
name: 'test2'
}
],
}
The index I have at the moment is
{
"mappings": {
"dynamic": false,
"fields": {
"arrayData.name": {
"tokenization": "nGram",
"type": "autocomplete"
}
}
}
}
For the search I need it to be type autocomplete and I want to search on the name in the object's
I have a big collection (over 22M records, approx. 25GB) on an M10 cluster with MongoDB version 4.4.10. I set up an Atlas search index on one field (address) and it works pretty fast when I request through the search tester. However, when I try to paginate it by specifying a facet, it gets extremely slow in comparison with the query without the facet. Is there a way to optimize the facet or somehow replace the facet with one that works faster ? Below are the plain query and another one with the facet:
db.getCollection("users").aggregate([{
$search: {
index: 'address',
text: {
query: '7148 BIG WOODS DR',
path: {
'wildcard': '*'
}
}
}
}]);
db.getCollection("users").aggregate([{
$search: {
index: 'address',
text: {
query: '7148 BIG WOODS DR',
path: {
'wildcard': '*'
}
}
}
}, {
$facet: {
paginatedResult: [
{
$limit: 50
},
{
$skip: 0
}
],
totalCount: [
{
$count: 'total'
}
]
}
}]);
The fast and recommend way is using facet with the $searchMeta stage to retrieve metadata results only for the query
"$searchMeta": {
"index":"search_index_with_facet_fields",
"facet":{
"operator":{
"compound":{
"must":[
{
"text":{
"query":"red shirt",
"path":{
"wildcard":"*"
}
}
},
{
"compound":{
"filter":[
{
"text":{
"query":["clothes"],
"path":"category"
}
},
{
"text":{
"query":[
"maroon",
"blackandred",
"blackred",
"crimson",
"burgandy",
"burgundy"
],
"path":"color"
}
}
]
}
}
]
}
},
"facets":{
"brand":{
"type":"string",
"path":"brand"
},
"size":{
"type":"string",
"path":"size"
},
"color":{
"type":"string",
"path":"color"
}
}
}
}
}
Here we are fetching 3 facets brand, size, and color, which we need to be defined in your search_index as Facet fields such as
{
"mappings": {
"dynamic": false,
"fields": {
"category": [
{
"type": "string"
}
],
"brand": [
{
"type": "string"
},
{
"type": "stringFacet"
}
],
"size": [
{
"type": "string"
},
{
"type": "stringFacet"
}
],
"color": [
{
"type": "string"
},
{
"type": "stringFacet"
}
]
}
}
}
category is defined only as string since we are not using it in facets but only as a filter field.
We can also replace filter op with must or should based on our requirement.
Finally, we will get as our result.
*p.s. I am also new to mongo and got to this solution after searching a lot, so please upvote if you find it useful, also let me know if there is any error/improvement you notice. Thanks *
I have a collection in a Mongo Atlas DB on which I have a search index including some specific string fields. What I want to do is include a Int32 field in this search index to be able to do a search on this number, along with the other fields. I tried to add the field (Number) as a new field in the search index, with the type number, but it doesn't work. I guess it's because it compares the query, a string, with an Int32, but is there a way to make it work ? Or do I have to copy the "Number" in another field "NumberString" to include in the search index ?
Here is an example of one of these documents :
{
“_id” : ObjectId(“010000000000000000000003”),
“Description” : {
“fr-CA” : “Un lot de test”,
“en-CA” : “A test item”
},
“Name” : {
“fr-CA” : “Lot de test”,
“en-CA” : “Test item”
},
“Number” : 345,
“Partners” : [],
[...]
}
The index :
{
“mappings”: {
“dynamic”: false,
“fields”: {
“Description”: {
“fields”: {
“en-CA”: {
“analyzer”: “lucene.english”,
“searchAnalyzer”: “lucene.english”,
“type”: “string”
},
“fr-CA”: {
“analyzer”: “lucene.french”,
“searchAnalyzer”: “lucene.french”,
“type”: “string”
}
},
“type”: “document”
},
“Name”: {
“fields”: {
“en-CA”: {
“analyzer”: “lucene.english”,
“searchAnalyzer”: “lucene.english”,
“type”: “string”
},
“fr-CA”: {
“analyzer”: “lucene.french”,
“searchAnalyzer”: “lucene.french”,
“type”: “string”
}
},
“type”: “document”
},
“Number”:
{
“representation”: “int64”,
“type”: “number”
},
“Partners”: {
“fields”: {
“Name”: {
“type”: “string”
}
},
“type”: “document”
}}}}
And finally the query I try to do.
db.[myDB].aggregate([{ $search: { "index": "default", "text": { "query": "345", "path": ["Number", "Name.fr-CA", "Description.fr-CA", "Partners.Name"]}}}])
For this example, I want the query to be applied on Number, Name, Description and Partners and to return everything that matches. I would expect to have the item #345, but also any items with 345 in the name or description. Is it possible ?
Thanks !
With your current datatype you, should be able to search for #345 in text. However, I would structure the query like so, to support the numeric field as well:
db.[myDB].aggregate([
{
$search: {
"index": "default",
"compound": {
"should":[
{
"text": {
"query": "345",
"path": ["Name.fr-CA", "Description.fr-CA", "Partners.Name"]
}
},
{
"near": {
"origin": 345,
"path": "Number",
"pivot": 2
}
}
]
}
}
}
])
I'm new to mongo and need help finding db entries created at requested time. In my example there are a lot of embedded fields, and I do not understand syntaxis for request:
{
"_id": "54e1a045e4b03f5930293da6",
"_version": 31867,
"_transId": "4ae4d0e6-d3df-4a24-9621-1cdb7f12362f-10489329",
"accountBalances": {
"BALANCE": {
"thresholds": {
},
"quotas": "ROLLOVER_QUOTA": {
"thresholds": {
},
"quotaCode": "ROLLOVER_QUOTA",
"credits": {
"_1HVa0dJoEeSUwbM1-xYKvg": {
"startDate": ISODate("2015-03-24T21:00:00Z"),
"creditAmount": "547194099151",
"endDate": ISODate("2020-03-24T21:00:00Z"),
"started": true,
"debits": {
"consolidated": {
"creationDate": ISODate("2015-04-17T18:00:01.469Z"),
"debitAmount": "547194090291",
"debitId": "consolidated"
}
},
"creditId": "_1HVa0dJoEeSUwbM1-xYKvg"
}
}
}
}
}
I need to search for entries which have debit creation date $gte:ISODate("2015-03-16T00:00:00.000Z"), $lte:ISODate("2015-03-16T04:00:00.000Z"
You can use the dot notation to access the fields of an embedded document:
db.collection.find(
{
"accountBalances.BALANCE.quotas.ROLLOVER_QUOTA.credits._1HVa0dJoEeSUwbM1-xYKvg.debits.creationDate": {
"$gte": ISODate("2015-03-16T00:00:00.000Z"),
"$lte": ISODate("2015-03-16T04:00:00.000Z")
}
}
);