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The data in mongodb is like this

{
    "_id": "1",
    "a": 1,
    "b": 2,
    "c": 3
    "d": 4
}

I can update the document using a single "$set" operator.

db.collection.update({"_id": "1"}, {
        "$set": {
            "a": 100,
            "b": 200,
            "c": 300,
            "d": 400
        }
    })

I can also update the document using multiple "$set" (each field has a "$set").

db.collection.update({"_id": "1"}, [
        {
            "$set": { "a": 100 }
        },
        {
            "$set": { "b": 200 }
        },
        {
            "$set": { "c": 300 }
        },
        {
            "$set": { "d": 400 }
        }
    ])

I would like to know if there are any performance concerns on the mongodb end by using the "multi-set" version. Is it Ok to use the "multi-set" version if, for some cases, I need to.

2

Answers


  1. For your case, I think there will be a trivial performance difference, if not none. The explain plans for them are nearly identical.

    explain output for single $set:

    {
      "$clusterTime": {
        "clusterTime": Timestamp(1734276869, 3),
        "signature": {
          "hash": BinData(0, "tRv1PQVgmouDxOtttOdSk2z0O1U="),
          "keyId": NumberLong(7394893876424605697)
        }
      },
      "command": {
        "$db": "75f38391413d12711811639fd9b97e4f",
        "filter": {},
        "find": "collection",
        "maxTimeMS": NumberLong(20000)
      },
      "executionStats": {
        "allPlansExecution": [],
        "executionStages": {
          "advanced": 1,
          "direction": "forward",
          "docsExamined": 1,
          "executionTimeMillisEstimate": 0,
          "isEOF": 1,
          "nReturned": 1,
          "needTime": 0,
          "needYield": 0,
          "restoreState": 0,
          "saveState": 0,
          "stage": "COLLSCAN",
          "works": 2
        },
        "executionSuccess": true,
        "executionTimeMillis": 0,
        "nReturned": 1,
        "totalDocsExamined": 1,
        "totalKeysExamined": 0
      },
      "explainVersion": "1",
      "operationTime": Timestamp(1734276869, 3),
      "queryPlanner": {
        "indexFilterSet": false,
        "maxIndexedAndSolutionsReached": false,
        "maxIndexedOrSolutionsReached": false,
        "maxScansToExplodeReached": false,
        "namespace": "75f38391413d12711811639fd9b97e4f.collection",
        "parsedQuery": {},
        "planCacheKey": "5F5FC979",
        "queryHash": "5F5FC979",
        "rejectedPlans": [],
        "winningPlan": {
          "direction": "forward",
          "stage": "COLLSCAN"
        }
      },
      "serverParameters": {
        "internalDocumentSourceGroupMaxMemoryBytes": 104857600,
        "internalDocumentSourceSetWindowFieldsMaxMemoryBytes": 104857600,
        "internalLookupStageIntermediateDocumentMaxSizeBytes": 104857600,
        "internalQueryFacetBufferSizeBytes": 104857600,
        "internalQueryFacetMaxOutputDocSizeBytes": 104857600,
        "internalQueryMaxAddToSetBytes": 104857600,
        "internalQueryMaxBlockingSortMemoryUsageBytes": 104857600,
        "internalQueryProhibitBlockingMergeOnMongoS": 0
      }
    }
    

    Mongo Playground

    explain output for multiple $set:

    {
      "$clusterTime": {
        "clusterTime": Timestamp(1734276224, 3),
        "signature": {
          "hash": BinData(0, "QUsSlU1zBAvtbFAgbv3/fA7RENU="),
          "keyId": NumberLong(7394893876424605697)
        }
      },
      "command": {
        "$db": "3d58f286ab6b7455181163098d794665",
        "filter": {},
        "find": "collection",
        "maxTimeMS": NumberLong(20000)
      },
      "executionStats": {
        "allPlansExecution": [],
        "executionStages": {
          "advanced": 1,
          "direction": "forward",
          "docsExamined": 1,
          "executionTimeMillisEstimate": 0,
          "isEOF": 1,
          "nReturned": 1,
          "needTime": 0,
          "needYield": 0,
          "restoreState": 0,
          "saveState": 0,
          "stage": "COLLSCAN",
          "works": 2
        },
        "executionSuccess": true,
        "executionTimeMillis": 0,
        "nReturned": 1,
        "totalDocsExamined": 1,
        "totalKeysExamined": 0
      },
      "explainVersion": "1",
      "operationTime": Timestamp(1734276224, 3),
      "queryPlanner": {
        "indexFilterSet": false,
        "maxIndexedAndSolutionsReached": false,
        "maxIndexedOrSolutionsReached": false,
        "maxScansToExplodeReached": false,
        "namespace": "3d58f286ab6b7455181163098d794665.collection",
        "parsedQuery": {},
        "planCacheKey": "5F5FC979",
        "queryHash": "5F5FC979",
        "rejectedPlans": [],
        "winningPlan": {
          "direction": "forward",
          "stage": "COLLSCAN"
        }
      },
      "serverParameters": {
        "internalDocumentSourceGroupMaxMemoryBytes": 104857600,
        "internalDocumentSourceSetWindowFieldsMaxMemoryBytes": 104857600,
        "internalLookupStageIntermediateDocumentMaxSizeBytes": 104857600,
        "internalQueryFacetBufferSizeBytes": 104857600,
        "internalQueryFacetMaxOutputDocSizeBytes": 104857600,
        "internalQueryMaxAddToSetBytes": 104857600,
        "internalQueryMaxBlockingSortMemoryUsageBytes": 104857600,
        "internalQueryProhibitBlockingMergeOnMongoS": 0
      }
    }
    

    Mongo Playground

    Given your query pattern in the example on updating on only 1 document and you are fetching by _id, I don’t think there will be any observable performance difference.

    There are 2 caveats outside of performance though:

    1. If in your real use case, you have a dependency on the $set operations, you need to break them into different stages

    e.g. you $set a to be c * d = 12, and b to be a + 1 = 12 + 1 = 13. You will need to do:

    db.collection.update({
      "_id": "1"
    },
    [
      {
        "$set": {
          "a": {
            "$multiply": [
              "$c",
              "$d"
            ]
          }
        }
      },
      {
        "$set": {
          "b": {
            "$add": [
              "$a",
              1
            ]
          }
        }
      }
    ])
    

    Mongo Playground

    A single $set won’t give you expected result of b = 13, but 2 because a is yet to be evaluated as 12(keeping 1 as value)

    db.collection.update({
      "_id": "1"
    },
    [
      {
        "$set": {
          "a": {
            "$multiply": [
              "$c",
              "$d"
            ]
          },
          "b": {
            "$add": [
              "$a",
              1
            ]
          }
        }
      }
    ])
    

    Mongo Playground

    1. readablility: In real-life and more complex pipelines, you may find breaking up $set statement more readable or manageable. But I will admit this is quite subjective and you may consider the other way round.
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  2. Why do you think, someone "needs to do so"? The operators are JSON objects, you can create an update for example like this:

    let values = { a: 100 };
    values.b = 200;
    values["c"] = 300;
    values = Object.assign(values, { d: 400 });
    
    db.collection.update({"_id": "1"}, { $set: values })
    
    //or 
    const operation = { $set: values };
    db.collection.update({"_id": "1"}, operation)
    
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