I want to convert the following SQL query to MongoDB query:
SELECT count(invoiceNo), year, month, manager
FROM battle
WHERE year=2021 AND month='Dec' OR year=2022 AND month='Jan' AND manager = 'name#test.com'
GROUP BY year,month;
I've tried to do so, but it seems to be incorrect:
const getNoOfOrders = await BattlefieldInfo.aggregate([
{
$match: {
$and: [
{
year: periodDate[0]['year']
},
{ month: periodDate[0]['month'] }
],
$or: [
{
$and: [
{
year: prevYear
},
{ month: prevMonth }
]
}
],
$and: [{ manager: email }]
}
},
{
$group: {
_id: '$month'
}
},
{
$project: {
// noOfOrders: { $count: '$invoiceNo' },
month: 1,
year: 1,
manager: 1
}
}
]);
Because I am getting an empty array. But it should be something like this:
| count(invoiceNo) | manager | year | month |
+------------------+---------------+------+-------+
2 name#test.com 2021 Dec
3 name#test.com 2022 Jan
From my point of view, I think parenthesis (bracket) is important to group the conditions together such as month and year.
SELECT count(invoiceNo), `year`, month, manager
FROM battle
WHERE (`year` = 2021 AND month = 'Dec')
OR (`year` = 2022 AND month = 'Jan')
AND manager = 'abc#email.com'
GROUP BY month, `year`
Sample DBFiddle
Same goes for your MongoDB query. While to search with month and year, you can do without $and as below:
{
year: 2021,
month: "Dec"
}
Instead of:
$and: [
{
year: 2021
},
{
month: "Dec"
}
]
And make sure that $group stage need an accumulator operator:
noOfOrders: {
$count: {}
}
Or
noOfOrders: {
$sum: 1
}
Complete MongoDB query
db.collection.aggregate([
{
$match: {
$or: [
{
year: 2021,
month: "Dec"
},
{
year: 2022,
month: "Jan"
}
],
manager: "abc#email.com"
}
},
{
$group: {
_id: {
month: "$month",
year: "$year"
},
noOfOrders: {
$count: {}
},
manager: {
$first: "$manager"
}
}
},
{
$project: {
_id: 0,
noOfOrders: 1,
month: "$_id.month",
year: "$_id.year",
manager: "$manager"
}
}
])
Sample Mongo Playground
Note:
Would be great for both queries to add manager as one of the group keys. Since you are filtering for the specific (only one) manager's record(s), it's fine. But without filtering for specific manager, your query will result in the wrong output.
Related
I have a question about "INTERSECT" query in the MongoDB query.
I want to query like the following SQL query in MongoDB.
(select course_id from section where semester = 'fall' and year = '2009')
intersect
(select course_id from section where semester = 'spring' and year = '2010');
In my MongoDB, Section collection data structure is as follows.
{
"_id" : {
"course_id" : "486",
"sec_id" : "1",
"semester" : "Fall",
"year" : 2009.0
},
"course_id" : "486",
"sec_id" : "1",
"semester" : "Fall",
"year" : 2009.0,
"building" : "Whitman",
"room_number" : "134",
"time_slot_id" : "K"
}
How to query to get the same result as SQL language?
It's not exactly sexy but you can do something like this:
db.collection.aggregate([
{
$match: {
$or: [
{
$and: [
{
year: 2009
},
{
semester: "fall"
}
]
},
{
$and: [
{
year: 2010
},
{
semester: "spring"
}
]
}
]
}
},
{
$group: {
_id: "$course_id",
years_x_semester: {$addToSet: {year: "$year", semester: "$semester"}},
}
},
{
$match: {
"years_x_semester.1": {$exists: true}
}
}
])
I'm a newbie on MongoDB. And I need help. I have a small project with SQLite (7 tables and 1 view). And I need to make this project on MongoDB, I'm using Studio 3T, I'm already migrate SQLite tables to MongoDB collections, but now I need to make (VIEW/TEST) for test this project. Please help how to write this SQL script with MongoDB.
SQLITE:
MongoDB:
SQLIte script I want to make with MongoDB:
CREATE VIEW rezultatas AS
SELECT p.pavadinimas AS detales_pavadinimas,
SUM(d.pagamintas_kiekis) AS pagamintas_kiekis,
SUM(z.gamybos_islaidos) AS vidutine_kaina,
STRFTIME('%m', d.pagaminimo_data) AS menuo,
STRFTIME('%Y', d.pagaminimo_data) AS metai
FROM detales d,
zinynas z,
produktas p
WHERE (z.detale_id = p._id_) AND
(d.detale_id = z.detale_id) AND
(d.pagaminimo_data >= z.data_nuo) AND
NOT EXISTS (
SELECT *
FROM zinynas
WHERE (d.detale_id = detale_id) AND
(d.pagaminimo_data >= data_nuo) AND
(z.data_nuo < data_nuo)
)
GROUP BY p.pavadinimas,
STRFTIME('%m', d.pagaminimo_data),
STRFTIME('%Y', d.pagaminimo_data)
I had to guess some things due to the lack of schemes but the basic layout should work.
We're going to use $createView with these parameters as input:
db.createView('rezultatas', 'produktas', pipeline)
Meaning our pipeline creating the view starts with the produktas collection.
The pipeline to use:
[
{ // match the documents from the zinyas collection.
$lookup:
{
from: "zinynas",
let: { produktas_id: "$_id" }, // i'm guessing its _id
pipeline: [
{ $match:
{ $expr: { $eq: [ "$detale_id", "$$produktas_id" ] }}
},
],
as: "z"
}
},
{
$unwind: "$z"
},
{ // match the documents from the detales collection. only keep the one with maximum data_nuo value.
$lookup:
{
from: "detales",
let: { z_detale_id: "$z.detale_id", z_data_nuo: "$z.data_nuo" },
pipeline: [
{ $match:
{
$and: [
{ $expr: { $eq: [ "$detale_id", "$$z_detale_id" ] }},
{ $expr: { $gte: [ "$pagaminimo_data", "$$z_data_nuo"]}}
]
}
},
{
$sort: {
data_nuo: -1
}
},
{
$limit: 1
}
],
as: "d"
}
},
{
$unwind: "$d"
},
{ // end up saving the fields we want.
$group: {
_id: { pavadinimas : "$pavadinimas", month: {$month: "$d.pagaminimo_data"}, year: {$year: "$d.pagaminimo_data"}},
pagamintas_kiekis: {$sum: "$d.pagamintas_kiekis"},
vidutine_kaina: {$sum: "$z.gamybos_islaidos"},
month: {$first: {$month: "$d.pagaminimo_data"}},
year: {$first: {$year: "$d.pagaminimo_data"}},
detales_pavadinimas: {$first: "$pavadinimas"}
}
}
]
Is there a way to group a collection which looks like
[
{_id: "5bd258a7877e74059b6b65b2", year: 2017, title: "One"},
{_id: "5bd258a7877e74059b6b65b3", year: 2017, title: "Two"},
{_id: "5bd258a7877e74059b6b65b4", year: 2018, title: "Three"},
{_id: "5bd258a7877e74059b6b65b5", year: 2018, title: "Four"}
]
and output the result as
{
2017: [
0: {_id: "5bd258a7877e74059b6b65b2", title: "One", …}
1: {_id: "5bd258a7877e74059b6b65b3", title: "Two", …}
],
2018: [
0: {_id: "5bd258a7877e74059b6b65b4", title: "Three", …}
1: {_id: "5bd258a7877e74059b6b65b5", title: "Four", …}
]
}
using mongodb aggregations? Similar to how lodash groupBy works
You can do that with the following mongoDB aggregation:
db.collection.aggregate([{
$group: {
_id: "$year",
docs: {
$addToSet: "$$CURRENT"
}
}
},
{
"$group": {
"_id": null,
"data": {
"$push": {
"k": {
$toString: "$_id"
},
"v": "$docs"
}
}
}
},
{
"$replaceRoot": {
"newRoot": {
"$arrayToObject": "$data"
}
}
}
])
You can see the result here
The idea is to group the data in a way where we can utilize $arrayToObject. First group gives you the grouped by year where the second is just prep for $arrayToObject which requires key, value object. Last thing is the $replaceRoot.
This requires MongoDB 3.6 and up due to $arrayToObject being introduced in that version. Before that you had to use $push etc.
Realise this topic has been asked many times - but the advice hasn't helped me solve this problem.
The following query is trying to determine the presence of sales on a given weekday using ISODay. Because the query will be run at the start of the month, I need to know how many occurrences of the specific ISOday occur in the month.
var query = { eventType: 'Sale', site : 4, tank: 1, txnDate : { "$gt" : new Date('2018-08-01T00:00:00') } };
db.tankevent.aggregate([
{ $match: query },
{ $project : {
isoDay: { $isoDayOfWeek: "$txnDate" },
dayDate: { $dateToString: { format: "%d", date:"$txnDate" } }
}
},
{ $group:
{ _id : { isoday: "$isoDay", dday: "$dayDate" }, count: { "$sum" : 1 } }
},
{ $sort: { "_id.isoday": 1, "_id.dday": 1 } }
])
provides the following output
/* 1 */
{
"_id" : {
"isoday" : 1,
"dday" : "06"
},
"count" : 62.0
}
/* 2 */
{
"_id" : {
"isoday" : 1,
"dday" : "13"
},
"count" : 69.0
}
/* 3 */
{
"_id" : {
"isoday" : 1,
"dday" : "20"
},
"count" : 72.0
}
/* 4 */
{
"_id" : {
"isoday" : 2,
"dday" : "07"
},
"count" : 75.0
}
I am trying to have "count" represent the number of unique "dday" records - so using the output above, I want count to be "3" for isoDay = 1. At the moment count is reporting number of sales events that occurred for the group combination
All you need to do is have the grouping twice.
db.tankevent.aggregate([
{ $match: query },
{ $project : {
isoDay: { $isoDayOfWeek: "$txnDate" },
dayDate: { $dateToString: { format: "%d", date:"$txnDate" } }
}
},
{ $group:
{ _id : { isoday: "$isoDay", dday: "$dayDate" }, count: { "$sum" : 1 } }
},
{ $project : {
isoDay_Final: "$_id.isoday"
}
},
{ $group:
{ _id : "$isoDay_Final", count: { "$sum" : 1 } }
},
{ $sort: { "_id": 1 } }
])
I have a collection as below
{"country":"US","city":"NY"}
{"country":"US","city":"AL"}
{"country":"US","city":"MA"}
{"country":"US","city":"NY"}
{"country":"US","city":"MA"}
{"country":"IN","city":"DL"}
{"country":"IN","city":"KA"}
{"country":"IN","city":"DL"}
{"country":"IN","city":"DL"}
{"country":"IN","city":"KA"}
and expecting an output
{ "data": { "US": {"NY": 2,"AL": 1,"MA": 2 },
"IN": {"DL": 3,"KA": 2 }}
}
Below is the mongodb query I tried, i was able to get to get the count at country level, but not at the state level. please help me in correcting the below query to get data at state level.
db.country_dash.aggregate([
{"$group": {
"_id":"$country",
"state": {"$addToSet": "$state"}
}},
{"$project": {
"_id":0,
"country":"$_id",
"state": {"$size": "$state"}
} }
])
db.country_dash.aggregate(
// Pipeline
[
// Stage 1
{
$group: {
_id: {
city: '$city'
},
total: {
$sum: 1
},
country: {
$addToSet: '$country'
}
}
},
// Stage 2
{
$project: {
total: 1,
country: {
$arrayElemAt: ['$country', 0]
},
city: '$_id.city',
_id: 0
}
},
// Stage 3
{
$group: {
_id: '$country',
data: {
$addToSet: {
city: '$city',
total: '$total'
}
}
}
},
]
);