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Analyze Query Performance
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The explain plan results for queries are subject to change between MongoDB versions.
Evaluate the Performance of a Query
Consider a collection inventory with the following documents:
{ "_id" : 1, "item" : "f1", type: "food", quantity: 500 } { "_id" : 2, "item" : "f2", type: "food", quantity: 100 } { "_id" : 3, "item" : "p1", type: "paper", quantity: 200 } { "_id" : 4, "item" : "p2", type: "paper", quantity: 150 } { "_id" : 5, "item" : "f3", type: "food", quantity: 300 } { "_id" : 6, "item" : "t1", type: "toys", quantity: 500 } { "_id" : 7, "item" : "a1", type: "apparel", quantity: 250 } { "_id" : 8, "item" : "a2", type: "apparel", quantity: 400 } { "_id" : 9, "item" : "t2", type: "toys", quantity: 50 } { "_id" : 10, "item" : "f4", type: "food", quantity: 75 }
Query with No Index
The difference between the number of matching documents and the number of examined documents may suggest that, to improve efficiency, the query might benefit from the use of an index.
Query with Index
To support the query on the quantity field, add an index on the
quantity field:
Without the index, the query would scan the whole collection of 10
documents to return 3 matching documents. The query also had to
scan the entirety of each document, potentially pulling them into
memory. This results in an expensive and potentially slow query
operation.
When run with an index, the query scanned 3 index entries
and 3 documents to return 3 matching documents, resulting
in a very efficient query.