Como manter várias versões de um registro no MongoDB (atualizações 2024)

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[ { $set : { a: 5 , previous_a: "$a" } }]

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{ 
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  a: 3
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}

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{
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  a: 5,
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  previous_a: 3
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}

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[ { $set : { a: 5 , b: 8  }  ,
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    $push : { history : { a:"$a",b:"$b"} } ]

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{"$set":{"history":
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       {"$concatArrays":[[{ _updateTime: "$$NOW", a:"$a",b:"$b"}}],
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                         {"$ifNull":["$history",[]]}]}}}

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{ 
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  a: 3,
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  b: 1
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}

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{
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  a: 5,
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  b: 8,
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  history: [
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             { 
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               _updateTime: Date(...),
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                         a: 3, 
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                         b: 1 
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             }
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      ]
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}

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// Configure the inspection depth for better readability in output
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config.set("inspectDepth", 8) // Set mongosh to print nicely
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// Connect to a specific database
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db = db.getSiblingDB("version_example")
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db.data.drop()
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const nFields = 5
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// Function to generate random field values based on a specified change percentage
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function randomFieldValues(percentageToChange) {
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 const fieldVals = new Object();
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 for (let fldNo = 1; fldNo < nFields; fldNo++) {
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   if (Math.random() < (percentageToChange / 100)) {
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     fieldVals[`field_${fldNo}`] = Math.floor(Math.random() * 100)
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   }
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 }
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 return fieldVals
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}
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// Loop to create and insert 10 records with random data into the 'data' collection
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for (let id = 0; id < 10; id++) {
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 const record = randomFieldValues(100)
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 record._id = id
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 record.dateUpdated = new Date()
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 db.data.insertOne(record)
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}
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// Log the message indicating the data that will be printed next
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console.log("ORIGINAL DATA")
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console.table(db.data.find().toArray())

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const oldTime = new Date()
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//We can make changes to these without history like so
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sleep(500);
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// Making the change and recording the OLD value
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for (let id = 0; id < 10; id++) {
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 const newValues = randomFieldValues(30)
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 //Check if any changes
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 if (Object.keys(newValues).length) {
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   newValues.dateUpdated = new Date()
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   const previousValues = new Object()
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   for (let fieldName in newValues) {
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     previousValues[fieldName] = `$${fieldName}`
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   }
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   const existingHistory = { $ifNull: ["$history", []] }
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   const history = { $concatArrays: [[previousValues], existingHistory] }
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   newValues.history = history
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   db.data.updateOne({ _id: id }, [{ $set: newValues }])
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 }
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}
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console.log("NEW DATA")
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db.data.find().toArray()

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{
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    _id: 6,
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    field_1: 85,
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    field_2: 3,
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    field_3: 71,
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    field_4: 71,
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    dateUpdated: ISODate('2024-04-15T13:34:31.915Z'),
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    history: [
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      {
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        field_2: 56,
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        field_3: 24,
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        field_4: 78,
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        dateUpdated: ISODate('2024-04-15T13:30:12.883Z')
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      }
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    ]
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  }

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//Get only history until point required
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const filterHistory = { $filter: { input: "$history", cond: { $lt: ["$$this.dateUpdated", oldTime] } } }
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//Merge them together and replace the top level document
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const applyChanges = { $replaceRoot: { newRoot: { $mergeObjects: { $concatArrays: [["$$ROOT"], { $ifNull: [filterHistory, []] }] } } } }
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// You can optionally add a $match here but you would normally be better to
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// $match on the history fields at the start of the pipeline
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const revertPipeline = [{ $set: { rewoundTO: oldTime } }, applyChanges]
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//Show results
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db.data.aggregate(revertPipeline).toArray()

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  {
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    _id: 6,
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    field_1: 85,
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    field_2: 56,
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    field_3: 24,
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    field_4: 78,
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    dateUpdated: ISODate('2024-04-15T13:30:12.883Z'),
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    history: [
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      {
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        field_2: 56,
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        field_3: 24,
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        field_4: 78,
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        dateUpdated: ISODate('2024-04-15T13:30:12.883Z')
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      }
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    ],
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    rewoundTO: ISODate('2024-04-15T13:34:31.262Z')
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  },