Multiple condition on same column mongodb - mongodb

Question

{
"_id" : ObjectId("5ccfe06e2434de5c345d058e"),
"user_id" : 1,
"event" : "eventA",
"channel_id" : "1098",
"channel_node_id" : "2177",
"channel_name" : "New work",
"created_at" : NumberLong("1557127278000"),
"updated_at" : NumberLong("1557127278000"),
"user_raw_data" : {
"Name" : "akhilesh",
"Mobile" : "1234567890",
"Email" : "akhilesh#test.com"
},
{
"_id" : ObjectId("5ccfe06e2434de5c345d058e"),
"user_id" : 1
"event" : "eventB,
"channel_id" : "1098",
"channel_node_id" : "2177",
"channel_name" : "New work",
"created_at" : NumberLong("1557127278000"),
"updated_at" : NumberLong("1557127278000"),
"user_raw_data" : {
"Name" : "akhilesh",
"Mobile" : "1234567890",
"Email" : "akhilesh#test.com"
},
{
"_id" : ObjectId("5ccfe06e2434de5c345d058e"),
"user_id" : 1
"event" : "eventC,
"channel_id" : "1098",
"channel_node_id" : "2178",
"channel_name" : "New work",
"created_at" : NumberLong("1557127278000"),
"updated_at" : NumberLong("1557127278000"),
"user_raw_data" : {
"Name" : "akhilesh",
"Mobile" : "1234567890",
"Email" : "akhilesh#test.com"
}
,
{
"_id" : ObjectId("5ccfe06e2434de5c345d058e"),
"user_id" : 2
"event" : "eventA,
"channel_id" : "1098",
"channel_node_id" : "2178",
"channel_name" : "New work",
"created_at" : NumberLong("1557127278000"),
"updated_at" : NumberLong("1557127278000"),
"user_raw_data" : {
"Name" : "akhilesh",
"Mobile" : "1234567890",
"Email" : "akhilesh#test.com"
}
Now I want to get the count of events performed by the user so far. For eventA count will be 2, for eventB 1, and for eventC is 1. But this query will have multiple conditions so my condition is getting the count only if the user has performed (eventA or eventB) and eventC. So in that case from above doc user id 2 event will not be considered because they have not performed (eventA or eventB)
Also along with event match with mutiple and or condition I also want to apply filter on user_raw_data so my query should be like this
db.web_channel_events.aggregate([
{
$match: {
"channel_id": "1098",
"channel_node_id": "2177"
}
},
{
$group: {
"_id": {
"user_id": "$user_id",
"event": "$event"
},
"count": {
$sum: 1
}
}
},
{
$group: {
"_id": "$_id.user_id",
"event_details": {
$push: {
"k": "$_id.event",
"v": "$count"
}
}
}
},
{
$match: {
$and: [
{
$or: [
{
"event_details.k": "eventA",
"event_details.v": {
"$gte": 1
}
},
{
"event_details.k": "eventB",
"event_details.v": {
"$gte": 1
}
}
]
},
{
"event_details.k": "eventC",
"event_details.v": {
"$gte": 1
}
},
{
"user_raw_data.Name": "akhilesh"
}
]
}
},
{
"$unwind": "$event_details"
},
{
$group: {
"_id": "$event_details.k",
"count": {
$sum: "$event_details.v"
}
}
}
]).pretty();

Answer 1

The following query can get us the expected output:
db.collection.aggregate([
{
$group:{
"_id":{
"user_id":"$user_id",
"event":"$event"
},
"user_id":{
$first:"$user_id"
},
"event":{
$first:"$event"
},
"count":{
$sum:1
}
}
},
{
$group:{
"_id":"$user_id",
"user_id":{
$first:"$user_id"
},
"event_details":{
$push:{
"k":"$event",
"v":"$count"
}
}
}
},
{
$addFields:{
"event_details":{
$arrayToObject:"$event_details"
}
}
},
{
$match:{
$and:[
{
$or:[
{
"event_details.eventA":{
$gt:0
}
},
{
"event_details.eventB":{
$gt:0
}
}
]
},
{
"event_details.eventC":{
$gt:0
}
}
]
}
},
{
$group:{
"_id":null,
"eventA":{
$sum:"$event_details.eventA"
},
"eventB":{
$sum:"$event_details.eventB"
},
"eventC":{
$sum:"$event_details.eventC"
}
}
},
{
$project:{
"_id":0,
"event_details.eventA":"$eventA",
"event_details.eventB":"$eventB",
"event_details.eventC":"$eventC"
}
}
]).pretty()
Data set:
{
"_id" : ObjectId("5ccfe06e2434de5c345d0588"),
"event" : "eventA",
"user_id" : 1,
"created_at" : NumberLong("1557127278000"),
"updated_at" : NumberLong("1557127278000")
}
{
"_id" : ObjectId("5d8b132388edcf85b0aaa609"),
"event" : "eventA",
"user_id" : 1,
"created_at" : NumberLong("1557127278000"),
"updated_at" : NumberLong("1557127278000")
}
{
"_id" : ObjectId("5d8b132388edcf85b0aaa60a"),
"event" : "eventB",
"user_id" : 1,
"created_at" : NumberLong("1557127278000"),
"updated_at" : NumberLong("1557127278000")
}
{
"_id" : ObjectId("5d8b132388edcf85b0aaa60b"),
"event" : "eventC",
"user_id" : 1,
"created_at" : NumberLong("1557127278000"),
"updated_at" : NumberLong("1557127278000")
}
{
"_id" : ObjectId("5d8b132388edcf85b0aaa60c"),
"event" : "eventC",
"user_id" : 1,
"created_at" : NumberLong("1557127278000"),
"updated_at" : NumberLong("1557127278000")
}
{
"_id" : ObjectId("5d8b132388edcf85b0aaa60d"),
"event" : "eventC",
"user_id" : 2,
"created_at" : NumberLong("1557127278000"),
"updated_at" : NumberLong("1557127278000")
}
Output:
{ "event_details" : { "eventA" : 2, "eventB" : 1, "eventC" : 2 } }
Query analysis:
Grouping the data on the basis of user_id and event and calculating the count of that specific incident
Grouping only on the basis of user_id and pushing event and its
count into an array event_details as key-value pairs
Converting the event_details into an object
Applying the condition that the event count for ( A or B ) and C
should be greater than 0
Sum up individual event counts