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How to match in double nested array fields using aggregate in mongodb?

Below is the code I am trying but unable to get the desired results. matching on jobid and email.
mongoConn.aggregate({
collectionName: Collection.jobactivity,
data: [
{ $unwind: '$jobs' },
{ $match: { '$and': [{ 'jobs.jobid': candidateJobHistoryObj.jobid}, {'jobs.activity.email': candidateJobHistoryObj.candidateemail }] }},
{ $project: ({ '_id': 0, 'jobs.activity.activityname': 1, 'jobs.activity.firstname': 1, 'jobs.activity.middlename': 1, 'jobs.activity.lastname': 1, 'jobs.activity.createddatetime': 1, 'jobs.activity.createdbyuserid': 1, 'jobs.activity.modifiedtime': 1, 'jobs.activity.modifiedbyuserid': 1 }) },
{ $sort: { 'jobs.activity.createddatetime': -1 } }
],
})
Json code present in mongodb:
{
"_id" : ObjectId("61c9d42fc87b10aab2e6732a"),
"accountid" : 122,
"jobs" : [
{
"jobid" : 12,
"activity" : [
{
"firstname" : "Vikas Yadav Bhai",
"middlename" : null,
"lastname" : "Yadav",
"email" : "candidate1#abc.com",
"activityname" : "inserted the data into candidate engagement workflow",
"modifiedbyuserid" : 151,
"modifiedtime" : ISODate("2015-12-01T05:30:00.000+05:30"),
"createdbyuserid" : 151,
"createddatetime" : ISODate("2015-08-12T00:00:00.000+05:30")
},
{
"firstname" : "Vikas Yadav Bhai",
"middlename" : null,
"lastname" : "Yadav",
"email" : "candidate2#abc.com",
"activityname" : "updated the job details",
"modifiedbyuserid" : 151,
"modifiedtime" : ISODate("2015-12-01T05:30:00.000+05:30"),
"createdbyuserid" : 151,
"createddatetime" : ISODate("2015-08-12T00:00:00.000+05:30")
}
]
}
]
}
I want to match the documents where email is => candidate1#abc.com and jobid = 12

Group documents with same value, and get document with max value for every group

I have a similar mongodb collection:
{ "_id" : 1, "item" : "item1", "quantity" : 2, "date" : ISODate("2014-01-01T08:00:00Z") }
{ "_id" : 2, "item" : "item2", "quantity" : 1, "date" : ISODate("2014-02-03T09:00:00Z") }
{ "_id" : 3, "item" : "item2", "quantity" : 5, "date" : ISODate("2014-02-03T09:05:00Z") }
{ "_id" : 4, "item" : "item1", "quantity" : 10, "date" : ISODate("2014-02-15T08:00:00Z") }
{ "_id" : 5, "item" : "item2", "quantity" : 10, "date" : ISODate("2014-02-15T09:05:00Z") }
I want to get the latest document (based on date value) for every item
Means I want a query/aggregation to give me:
{ "_id" : 4, "item" : "item1", "quantity" : 10, "date" : ISODate("2014-02-15T08:00:00Z") }
{ "_id" : 5, "item" : "item2", "quantity" : 10, "date" : ISODate("2014-02-15T09:05:00Z") }

$sort by date in descending order
$group by item and get the first root document
$replaceRoot to replace root document object to root
db.collection.aggregate([
{ $sort: { date: -1 } },
{
$group: {
_id: "$item",
root: { $first: "$$ROOT" }
}
},
{ $replaceRoot: { newRoot: "$root" } }
])
Playground

Elastic Search delete a single element inside a field on _source

i`m trying to delete a element inside a field of my elastic field, current, I have this struct of data:
I need in my NODE application to delete a single element from produto_tags getting the id_produto_cor,
for example:
{
"_index" : "relatorio_recebimento_produto_hml",
"_type" : "_doc",
"_id" : "54XZ9HAB4DHa2O1nQlpk",
"_score" : 1.0,
"_source" : {
"id_usuario" : 1408,
"data_criacao" : "2020-03-19T22:10:40.465Z",
"produto_tags" : [
{
"id_produto_cor" : "2489664268",
"tags" : [ ]
},
{
"id_produto_cor" : "1000045010",
"tags" : [ ]
},
{
"id_produto_cor" : "1004600287",
"tags" : [ ]
},
{
"id_produto_cor" : "1032013410",
"tags" : [ ]
},
{
"id_produto_cor" : "2468436987",
"tags" : [ ]
}
],
"referencia_tags" : [ ],
"nome_relatorio" : "teste"
}
}
XDELETE
{
query: {
match: {
produto_tags.id_produto_cor: 489664268
}
}
}
I would expect my data to be like:
"_index" : "relatorio_recebimento_produto_hml",
"_type" : "_doc",
"_id" : "xYVD5XAB4DHa2O1ndFo1",
"_score" : 1.0,
"_source" : {
"id_usuario" : 1376,
"data_criacao" : "2020-03-16T21:32:46.369Z",
"produto_tags" : [
{
"id_produto_cor" : "1000045010",
"tags" : [ ]
},
{
"id_produto_cor" : "1004600287",
"tags" : [ ]
},
{
"id_produto_cor" : "1032013410",
"tags" : [ ]
},
{
"id_produto_cor" : "2468436987",
"tags" : [ ]
}
],
"referencia_tags" : { },
"nome_relatorio" : "teste"
}
},
...
This is my final structure
zzzzzzzzzzzzzzzzzzzz
zzzzzzzzzzzzzzzzzzzz

You can use _update_by_query
POST /index102/_update_by_query
{
"script":{
"source":"ctx._source.produto_tags.remove('1029831004')"
},
"query":{
"match_all":{} --> modify query to target specific documents
--> match_all will execute script on all documents
}
}
Query for changed structure:
iterate through produto_tags, match with specific value and store the matched object in an array (list). Then iteratate through list and remove the object from produto_tags
POST /<index_name>/_update_by_query
{
"script":{
"source":"if(ctx._source.produto_tags.size()==0) {return;} def list=[]; for(product in ctx._source.produto_tags) { if (product['id_produto_cor'] ==params.product_id){list.add(product)}} if(list.size()==0) return; for(d in list){ctx._source.produto_tags.remove(ctx._source.produto_tags.indexOf(d))}",
"params" : {
"product_id" : "2468436987"
}
},
"query":{
"match_all":{} --> to select specific documents
}
}

Re-structure the data of the MongoDB $lookup Query.

I want this to be the result
help me, thank you
{
"_id" : ObjectId("5b74f57d3eb9591fcc069406"),
"received_by" : ObjectId("5b6bac617e9f754ff8aebd65"),
"received_date" : "2019",
"code" : "TRSV16081800007",
"items" : [
{
"m_souvenir_id" : ObjectId("5b70e98ccb72df3bec00c94a"),
"qty" : "10"
},
{
"m_souvenir_id" : ObjectId("5b70e98ccb72df3bec00c94a"),
"qty" : "10"
},
]
}
the result is like this
{
"_id" : ObjectId("5b74f57d3eb9591fcc069406"),
"received_by" : ObjectId("5b6bac617e9f754ff8aebd65"),
"received_date" : "2019",
"code" : "TRSV16081800007",
"items" : [
{
"m_souvenir_id" : ObjectId("5b70e98ccb72df3bec00c94a"),
"qty" : "10"
}
]
}
/* 2 */
{
"_id" : ObjectId("5b74f57d3eb9591fcc069406"),
"received_by" : ObjectId("5b6bac617e9f754ff8aebd65"),
"received_date" : "2019",
"code" : "TRSV16081800007",
"items" : [
{
"m_souvenir_id" : ObjectId("5b70e9d7cb72df3bec00c94b"),
"qty" : "20"
}
]
}
I have a project with nosql in mongodb
I have a problem with nosql in mongodb, I've tried searching in various sources, but the results are still not what I wantI have a project like this in mongodb,
db.t_souvenir.aggregate([
{ $lookup: { from: "t_souvenir_item", localField:"_id", foreignField:"t_souvenir_id", as: "Items"}},
{ $unwind : "$Items" },
{ $project : {
"code":1,
"received_by":1,
"received_date":1,
items : {
"m_souvenir_id":"$Items.m_souvenir_id",
"qty":"$Items.qty",
},
}};**strong text**
]);

$multiply only supports numeric types, not array

I am trying to use the $multiply operator in MongoDB.
STEP 1
db.message1064sd_00011_3744.aggregate([
{$project : {
"prices.00026" : 1,
priceReal : {
price : "$prices.00026",
}
}},
{ $match : { "priceReal.price" : {$gt : 30 } } },
{ $limit : 1 }
])
I am getting the results
{
"result" : [
{
"_id" : "54884_00011_001",
"prices" : {
"00026" : 34.43
},
"priceReal" : {
"price" : 34.43
}
}
],
"ok" : 1
}
STEP 2
But, when I use $multiply, I get
$multiply only supports numeric types, not array
db.message1064sd_00011_3744.aggregate([
{$project : {
"prices.00026" : 1,
priceReal : {
price : { $multiply : ["$prices.00026", 1 ] },
}
}},
{ $match : { "priceReal.price" : {$gt : 30 } } },
{ $limit : 1 }
])
Help me anybody
Example document which I can get from db.message1064sd_00011_3744.findOne()
{
"_id" : "25906_00011_001",
"Message_ID" : 25906,
"Subdivision_ID" : 3747,
"Sub_Class_ID" : 6300,
"Checked" : 1,
"Nomencl_ID" : "10000014597",
"manufacturer_ID" : "П1170",
"disableIfZero" : 0,
"Discontinued" : 0,
"New" : 0,
"Nomencl_Group_ID" : 28,
"Nalichie" : "Мало",
"sort" : 99,
"Warehouse_ID" : "00011",
"ParentWarehouse_ID" : "00011",
"Kachestvo" : "001",
"Svobod_Nalichie" : "10",
"Svobod_sort" : 10,
"character" : [],
"prices" : {
"00014" : 1.51,
"00015" : 1.45,
"00016" : 1.41,
"00017" : 1.38,
"00018" : 1.35,
"00019" : 1.33,
"00021" : 1.31,
"00022" : 1.29,
"00023" : 1.28,
"00024" : 1.27,
"00025" : 1.25,
"00026" : 1.24
},
"price" : {
"Curr_ID" : 840,
"ChangePriceTime" : "2017-01-22 19:18:21",
"PriceUpDown" : "up",
"callPrice" : 0,
"Price_Value_RODP" : 1.24,
"Price_Value_RUR" : 72.04000000000001
},
"sName" : "чип epson m2300{m2400{mx20 8k (elp, китай)",
"sNomencl_ID" : "10000014597",
"sNomencl_Articul_Proizvod" : "elp-ch-e2300-8k",
"sItemID" : "elp-ch-e2300-8k",
"EnglishName" : "cZ277",
"begin_vl" : 121,
"Hidden_URL" : "/netshop/cZ079/cZ270/cZ277/",
"Checked_Subdivision" : 1
}

In case you want to ensure that only data from a certain data type enters your result set, for example in an aggregate query, you can add the following filter to the match:
{$match: {
// ... your query
, "priceReal.price": { $type : "double" }
}