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$first (array operator)

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$first

New in version 4.4.

Returns the first element in an array.

Note

Disambiguation

This page describes the $first array operator. For the $first aggregation accumulator, see $first (aggregation accumulator).

Tip

See also:

$first has the following syntax:

{ $first: <expression> }

The <expression> can be any valid expression as long as it resolves to an array, null or missing. For more information on expressions, see Expressions.

The $first operator is an alias for the following $arrayElemAt expression:

{ $arrayElemAt: [ <array expression>, 0 ] }

Valid operand for $first must resolve to an array, null, or missing

  • If the operand resolves to a non-empty array, $first returns the first element in the array:

  • If the operand resolves to an empty array [], $first does not return a value.

  • If the operand is null or missing, $first returns null.

For example, create a test collection example1 with the following documents:

db.example1.insertMany([
{ "_id" : 1, "x" : [ 1, 2, 3 ] }, // Non-empty array
{ "_id" : 2, "x" : [ [ ] ] }, // Non-empty array
{ "_id" : 3, "x" : [ null ] }, // Non-empty array
{ "_id" : 4, "x" : [ ] }, // Empty array
{ "_id" : 5, "x" : null }, // Is null
{ "_id" : 6 } // Is Missing
])

Then, the following adds a new field firstElem whose value is derived from applying the $first operator to the x field:

db.example1.aggregate([
{ $addFields: { firstElem: { $first: "$x" } } }
])

The operator returns the following documents:

{ "_id" : 1, "x" : [ 1, 2, 3 ], "firstElem" : 1 }
{ "_id" : 2, "x" : [ [ ] ], "firstElem" : [ ] }
{ "_id" : 3, "x" : [ null ], "firstElem" : null }
{ "_id" : 4, "x" : [ ] } // No output
{ "_id" : 5, "x" : null, "firstElem" : null }
{ "_id" : 6, "firstElem" : null }

If the operand does not resolve to an array, null, or missing, the aggregation operation as a whole errors.

For example, create a test collection example2 with the following documents:

db.example2.insertMany([
{ "_id" : 1, "x" : [ 1, 2, 3 ] },
{ "_id" : 2, "x" : 2 }, // x is not an array/null or missing
])

Then, the following aggregation operation returns an error because of the { "_id" : 2, "x" : 2 } document:

db.example2.aggregate( { $addFields: { firstElem: { $first: "$x" } } } )

That is, the operation returns the following:

2020-01-20T18:31:13.431-05:00 E QUERY [js] uncaught exception: Error: command failed: {
"ok" : 0,
"errmsg" : "$first's argument must be an array, but is double",
"code" : 28689,
"codeName" : "Location28689"
} : aggregate failed :

Create a sample collection runninglog with the following documents:

db.runninglog.insertMany([
{ "_id" : 1, "team" : "Anteater", log: [ { run: 1, distance: 8 }, { run2: 2, distance: 7.5 }, { run: 3, distance: 9.2 } ] },
{ "_id" : 2, "team" : "Bears", log: [ { run: 1, distance: 18 }, { run2: 2, distance: 17 }, { run: 3, distance: 16 } ] },
{ "_id" : 3, "team" : "Cobras", log: [ { run: 1, distance: 2 } ] }
])

The following aggregation uses the $first and $last operator on the log array to retrieve the information for the first run and the last run:

db.runninglog.aggregate([
{ $addFields: { firstrun: { $first: "$log" }, lastrun: { $last: "$log" } } }
])

The operation returns the following results:

{ "_id" : 1, "team" : "Anteater", "log" : [ { "run" : 1, "distance" : 8 }, { "run2" : 2, "distance" : 7.5 }, { "run" : 3, "distance" : 9.2 } ],
"firstrun" : { "run" : 1, "distance" : 8 }, "lastrun" : { "run" : 3, "distance" : 9.2 } }
{ "_id" : 2, "team" : "Bears", "log" : [ { "run" : 1, "distance" : 18 }, { "run2" : 2, "distance" : 17 }, { "run" : 3, "distance" : 16 } ],
"firstrun" : { "run" : 1, "distance" : 18 }, "lastrun" : { "run" : 3, "distance" : 16 } }
{ "_id" : 3, "team" : "Cobras", "log" : [ { "run" : 1, "distance" : 2 } ],
"firstrun" : { "run" : 1, "distance" : 2 }, "lastrun" : { "run" : 1, "distance" : 2 } }

To calculate the change between the first and the last distances, the following operation uses $cond and $size operators to calculate the difference (i.e. $subtract) the two distances if there are two or more elements in the log array:

db.runninglog.aggregate([
{ $addFields: { firstrun: { $first: "$log" }, lastrun: { $last: "$log" } } },
{ $project: { team: 1, progress:
{
$cond: {
if: { $gt: [ { $size:"$log" }, 1 ] } ,
then: { $subtract: [ "$lastrun.distance", "$firstrun.distance"] },
else: "Not enough data." }
}
}}
])

The operation returns the following documents:

{ "_id" : 1, "team" : "Anteater", "progress" : 1.1999999999999993 }
{ "_id" : 2, "team" : "Bears", "progress" : -2 }
{ "_id" : 3, "team" : "Cobras", "progress" : "Not enough data." }

By default, mongosh uses the 64-bit floating-point double for numbers. To improve precision, you can use Decimal128 instead.

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