Consider that you have a collection called population which has fields state and city. Which of the following query will calculate the population grouped by state and city?

Question

Options

• Adb.population.aggregate( [{ $group: { _id: { state: "$state", city: "$city" },pop: { $pop: 1 } } }] )
• Bdb.population.aggregate( [{ $group: { _id: { city: "$city" },pop: { $sum: "$pop" } } }] )Multi
• Cdb.population.aggregate( [{ $group: { _id: { state: Estate", city: "$city" },pop: { $sum: "$pop" } } }] )
• Ddb.population.aggregate( [{ $group: { _id: { state: Estate", city: "$city" },pop: { $sum: 1 > > >] )

• A
  3% (1)
• B
  3% (1)
• C
  80% (24)
• D
  13% (4)

Explanation

Option C is correct because it properly groups documents by both state and city using a compound _id object, and uses the $sum accumulator to total the pop field across each group - the only combination that satisfies what the question asks for.

• A is wrong because $pop is an array update operator, not a valid aggregation accumulator. The correct accumulator to sum a numeric field is $sum.
• B is wrong because it only groups by city, omitting state - so totals would collapse across states, giving you incorrect cross-state city aggregations.
• D is wrong due to a syntax error: $sum: 1 > > >] is malformed. $sum: 1 counts documents rather than summing the pop field, and the broken brackets make it invalid regardless.

Memory tip: When grouping by multiple fields in MongoDB $group, think of _id as your "group key" - pass it an object with each field you want to group by (e.g., { state: "$state", city: "$city" }), and always use $sum: "$fieldName" (with the $ prefix) to total an existing numeric field rather than just counting.

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