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Type:
Improvement
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Resolution: Unresolved
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Priority:
Major - P3
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Affects Version/s: None
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Component/s: None
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Query Optimization
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Given this scenerio,
db.c.drop()
db.c.insert({a: 1, b: 1})
db.c.createIndex({a: 1, b: 1})
db.c.createIndex({a: 1, c: 1})
db.c.find({$or: [{a: 1}, {a: {$gt: 2}}], b: 3})
We produce a candidate plan that looks like
{
isCached: false,
stage: 'FETCH',
inputStage: {
stage: 'OR',
inputStages: [
{
stage: 'IXSCAN',
keyPattern: { a: 1, b: 1 },
indexName: 'a_1_b_1',
isMultiKey: false,
multiKeyPaths: { a: [], b: [] },
isUnique: false,
isSparse: false,
isPartial: false,
indexVersion: 2,
direction: 'forward',
indexBounds: { a: [ '[1, 1]' ], b: [ '[3, 3]' ] }
},
{
stage: 'IXSCAN',
keyPattern: { a: 1, b: 1 },
indexName: 'a_1_b_1',
isMultiKey: false,
multiKeyPaths: { a: [], b: [] },
isUnique: false,
isSparse: false,
isPartial: false,
indexVersion: 2,
direction: 'forward',
indexBounds: { a: [ '(2, inf.0]' ], b: [ '[3, 3]' ] }
}
]
}
},
With an OR stage that contains two index scan stages on over the same index. A more efficient plan would be one with a single index scan since these bounds can be unioned.
indexBounds: { a: [ '[1, 1]', '(2, inf.0]' ], b: [ '[3, 3]' ] }
- is related to
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- Backlog
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