How to fill missing documents with values 0 in mongoDB?

Question

I have a collection where I'm storing water dispensed for a particular day. Now for some days when the device isn't operated the data isn't stored in the database and I won't be getting the data in the collection. For example, I am querying water dispensed for the last 7 days where the device only operated for two day gives me something like this:

[{ 
    "uID" : "12345678", 
    "midNightTimeStamp" : NumberInt(1645381800), 
    "waterDispensed" : NumberInt(53)
},
{ 
    "uID" : "12345678", 
    "midNightTimeStamp" : NumberInt(1645641000), 
    "waterDispensed" : NumberInt(30)
}]

Converting the above two timestamps gives me data for Monday 21st February and Thursday 24th February. Now if I run the query for 21st Feb to 27th Feb something like this,

db.getCollection("analytics").find({ uID: "12345678", midNightTimeStamp: {"$in": [1645381800, 1645468200, 1645554600, 1645641000, 1645727400, 1645813800, 1645900200]}})

This returns me above two documents only, how to fill missing values for midNightTimeStamp supplied to get the document list like this which doesn't exists:

[{ 
    "uID" : "12345678", 
    "midNightTimeStamp" : 1645381800, 
    "waterDispensed" : 53
},
{ 
    "uID" : "12345678", 
    "midNightTimeStamp" : 1645468200, 
    "waterDispensed" : 0
},
{ 
    "uID" : "12345678", 
    "midNightTimeStamp" : 1645554600, 
    "waterDispensed" : 0
},
{ 
    "uID" : "12345678", 
    "midNightTimeStamp" : 1645641000, 
    "waterDispensed" : 30
},
{ 
    "uID" : "12345678", 
    "midNightTimeStamp" : 1645727400, 
    "waterDispensed" : 0
},
{ 
    "uID" : "12345678", 
    "midNightTimeStamp" : 1645813800, 
    "waterDispensed" : 0
},
{
    "uID" : "12345678", 
    "midNightTimeStamp" : 1645900200, 
    "waterDispensed" : 0
}

Answer 1

Maybe something like this:

db.collection.aggregate([
{
 $group: {
   _id: null,
   ar: {
    $push: "$$ROOT"
   },
   mind: {
    "$min": "$midNightTimeStamp"
   },
   maxd: {
    "$max": "$midNightTimeStamp"
   }
  }
 },
 {
  $project: {
  ar: {
    $map: {
      input: {
        $range: [
          "$mind",
          {
            "$sum": [
              "$maxd",
              86400
            ]
          },
          86400
        ]
      },
      as: "dateInRange",
      in: {
        $let: {
          vars: {
            dateIndex: {
              "$indexOfArray": [
                "$ar.midNightTimeStamp",
                "$$dateInRange"
              ]
            }
          },
          in: {
            $cond: {
              if: {
                $ne: [
                  "$$dateIndex",
                  -1
                ]
              },
              then: {
                $arrayElemAt: [
                  "$ar",
                  "$$dateIndex"
                ]
              },
              else: {
                midNightTimeStamp: "$$dateInRange",
                "waterDispensed": NumberInt(0)
              }
            }
          }
        }
       }
      }
     }
    }
  },
  {
   $unwind: "$ar"
  },
  {
   $project: {
    _id: 0,
    "waterDispensed": "$ar.waterDispensed",
    midNightTimeStamp: "$ar.midNightTimeStamp",
    "Date": {
      $toDate: {
         "$multiply": [
         "$ar.midNightTimeStamp",
         1000
       ]
      }
    }
   }
  }
])

Explained:

1. $group the documents to find max & min for the timestamps and $push all elements in temporary array named "ar"
2. $project the array $mapping with a $range of generated dated between max & min with 1x day step ( 86400 ) , fill the empty elements with waterDispanced:0
3. $unwind the array $ar
4. $project only the fields we need in the final output.

playground

Answer 2

As of MongoDB 5.1 you can use the $densify aggregation operator to fill in missing time series data with an average or default value.

https://www.mongodb.com/docs/rapid/reference/operator/aggregation/densify/

In your case, you may need to convert your timestamp field to a date while aggregating so that you can use $densify.

You can also watch a quick explanation of $densify in this presentation from MongoDB World 2022.

Answer 3

This is just a little different than the other answer, and it takes care to just grab the "uID" desired. Comments in the MQL explain the process.

db.collection.aggregate([
  { // The uID we want
    "$match": { "uID": "12345678" }
  },
  { // grab all the uID docs as "water"
    // keep uID
    "$group": {
      "_id": null,
      "water": { "$push": "$$CURRENT" },
      "uID": { "$first": "$uID" }
    }
  },
  { // create outArray
    "$set": {
      "outArray": {
        // by mapping time vals
        "$map": {
          "input": {
            "$range": [ NumberInt(1645381800), NumberInt(1645900200), 86400 ]
          },
          "in": {
            "$cond": [
              { // already have doc?
                "$in": [ "$$this", "$water.midNightTimeStamp" ]
              },
              { // yes!  Get it!
                "$arrayElemAt": [
                  "$water",
                  { "$indexOfArray": [ "$water.midNightTimeStamp", "$$this" ] }
                ]
              },
              { // no, create it
                "uID": "$uID",
                "midNightTimeStamp": "$$this",
                "waterDispensed": 0
              }
            ]
          }
        }
      }
    }
  },
  { // only need outArray now
    "$project": {
      "_id": 0,
      "outArray": 1
    }
  },
  { // create docs
    "$unwind": "$outArray"
  },
  { // hoist them
    "$replaceWith": "$outArray"
  },
  { // don't need _id
    "$unset": "_id"
  }
])

Try it on mongoplayground.net.