SlideShare a Scribd company logo
@
#MDBlocal
Tips and Tricks for
Effective Indexing
Alex Bevilacqua
Technical Services Engineer
alexbevi
TORONTO
#MDBLocal
• Your data should be accessible … quickly
• When applied properly, indexes can
improve performance as if by …
WHY DOES THIS MATTER?
#MDBLocal
• Working hard can suck and we all want
to do less when possible
• This goes for our database as well
• The less index keys scanned
or documents fetched from disk or cache
… the better!
• Let’s learn how to improve our indexes,
TOGETHER!
WHY DOES THIS MATTER?
#MDBLocal
IT’S ME … MARIO! ALEX!
• Application Developer
• Development Lead
• System Architect
• Technical Services
Engineer
• Author
• MongoDB Fanboy
#MDBLocal
Alex Bevilacqua
Technical Services Engineer
Toronto
Hi Phil!
#MDBLocal
Alex Bevilacqua
Technical Services Engineer
Toronto
I think I found some slow
queries that may be missing
indexes. What should I
know?
Equality Sort Range "Rule"
#MDBLocal
Roadmap
E-S-R Overview
Guidelines:
• Eà R
• Eà S
• Sà R
E-S-R Considerations
Operator Type Checks
Consecutive Index Keys
Exceptions?
#MDBLocal
Roadmap
E-S-R Overview
Guidelines:
• Eà R
• Eà S
• Sà R
E-S-R Considerations
Operator Type Checks
Consecutive Index Keys
Exceptions?
#MDBLocal
E-S-R
The ordering of index keys in a compound index is critically important.
#MDBLocal
E-S-R
The ordering of index keys in a compound index is critically important.
WHY?
#MDBLocal
E-S-R
The ordering of index keys in a compound index is critically important.
E-S-R provides guidance that is useful in most cases:
• Equality first
• Sort next
• Range last
#MDBLocal
E-S-R
The ordering of index keys in a compound index is critically important.
E-S-R provides guidance that is useful in most cases:
• Equality first
• Sort next
• Range last
Nope, I don’t get it.
Equality? Range? ….. Explain!
#MDBLocal
Definitions
Equality Fields
An exact match on a single
value. For example:
• {x:123}
• {x:{$eq:123}}
• {"x.y":123}
Bounds:
"[123.0, 123.0]"
#MDBLocal
Definitions
Equality Fields Sort
The (entire) requested sort.
.sort({a:1, b:-1})
Bounds:
"[MinKey, MaxKey]",
"[MinKey, MaxKey]"
An exact match on a single
value. For example:
• {x:123}
• {x:{$eq:123}}
• {"x.y":123}
Bounds:
"[123.0, 123.0]"
#MDBLocal
Definitions
Equality Fields Sort Range Predicates
Any predicates that are not
exact matches. Some
operators include:
• {z:{$gt:9000}}
• {z:{$lte:1000}}
Bounds:
"[9000.0, inf.0]",
"[-inf.0, 1000.0]"
The (entire) requested sort.
.sort({a:1, b:-1})
Bounds:
"[MinKey, MaxKey]",
"[MinKey, MaxKey]"
An exact match on a single
value. For example:
• {x:123}
• {x:{$eq:123}}
• {"x.y":123}
Bounds:
"[123.0, 123.0]"
#MDBLocal
Roadmap
E-S-R Overview
Guidelines:
• Eà R
• Eà S
• Sà R
E-S-R Considerations
Operator Type Checks
Consecutive Index Keys
Exceptions?
#MDBLocal
Equality
Equality keys are placed first in any order
If present in the query shape,
equality fields should always form the prefix for the index.
#MDBLocal
Equality
Equality keys are placed first in any order
If present in the query shape,
equality fields should always form the prefix for the index.
WHY?
#MDBLocal
Equality
Equality keys are placed first in any order
If present in the query shape,
equality fields should always form the prefix for the index.
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
#MDBLocal
Equality
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
If present in the query shape,
equality fields should always form the prefix for the index.
Equality keys are placed first in any order
#MDBLocal
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
Equality
{gamertag: "Ace", score: 100}
{gamertag: "Ace", score: 99,999}
{gamertag: "Bob", score: 15,000}
{gamertag: "Bob", score: 50,000}
#MDBLocal
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
{} {}
{}{}
100 15,000 50,000 99,999
Ace Bob Bob Ace
{gamertag: "Ace", score: 100}
{gamertag: "Ace", score: 99,999}
{gamertag: "Bob", score: 15,000}
{gamertag: "Bob", score: 50,000}
Equality
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Bob Ace
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
{} {} {} {}
Equality
"indexBounds" : {
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"["Ace", "Ace"]"
]
}
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Bob Ace
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
{} {} {} {}
Equality
"indexBounds" : {
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"["Ace", "Ace"]"
]
}
gamertag
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Bob Ace
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
{} {} {} {}
Equality
"indexBounds" : {
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"["Ace", "Ace"]"
]
}
gamertag
score
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Bob Ace
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
{} {} {} {}
Equality
"indexBounds" : {
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"["Ace", "Ace"]"
]
}
gamertag
score
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Bob Ace
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
{} {} {} {}
Equality
"indexBounds" : {
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"["Ace", "Ace"]"
]
}
gamertag
score
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Bob Ace
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
{} {} {} {}
Equality
"indexBounds" : {
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"["Ace", "Ace"]"
]
}
gamertag
score
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Bob Ace
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
{} {} {} {}
Equality
"indexBounds" : {
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"["Ace", "Ace"]"
]
}
gamertag
score
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Bob Ace
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
{} {} {} {}
Equality
"indexBounds" : {
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"["Ace", "Ace"]"
]
}
gamertag
score
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Bob Ace
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
{} {} {} {}
Equality
"indexBounds" : {
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"["Ace", "Ace"]"
]
}
gamertag
score
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Bob Ace
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
{} {} {} {}
Equality
"indexBounds" : {
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"["Ace", "Ace"]"
]
}
gamertag
score
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Bob Ace
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
{} {} {} {}
Equality
#MDBLocal
Ace Bob Bob Ace
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
100 99,999 15,000 50,000
{} {} {} {}
Equality
#MDBLocal
100
Ace Bob
99,999 15,000 50,000
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
{} {} {} {}
Equality
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"(9000.0, inf.0]"
],
}
db.games.createIndex({gamertag:1, score:1})
#MDBLocal
100
Ace Bob
99,999 15,000 50,000
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
{} {} {} {}
Equality
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"(9000.0, inf.0]"
],
}
gamertag
db.games.createIndex({gamertag:1, score:1})
#MDBLocal
100
Ace Bob
99,999 15,000 50,000
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
{} {} {} {}
Equality
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"(9000.0, inf.0]"
],
}
gamertag
score
db.games.createIndex({gamertag:1, score:1})
#MDBLocal
100
Ace Bob
99,999 15,000 50,000
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
{} {} {} {}
Equality
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"(9000.0, inf.0]"
],
}
gamertag
score
db.games.createIndex({gamertag:1, score:1})
#MDBLocal
100
Ace Bob
99,999 15,000 50,000
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
{} {} {} {}
Equality
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"(9000.0, inf.0]"
],
}
gamertag
score
db.games.createIndex({gamertag:1, score:1})
#MDBLocal
100
Ace Bob
99,999 15,000 50,000
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
{} {} {} {}
Equality
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"(9000.0, inf.0]"
],
}
gamertag
score
db.games.createIndex({gamertag:1, score:1})
#MDBLocal
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
R
E R
E
Equality before Range
#MDBLocal
Roadmap
E-S-R Overview
Guidelines:
• Eà R
• Eà S
• Sà R
E-S-R Considerations
Operator Type Checks
Consecutive Index Keys
Exceptions?
#MDBLocal
Sort fields are placed next
Placing sort predicates after sequential equality keys allow for the index to:
Provide a non-blocking sort.
Minimize the amount of scanning required.
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
Sort
#MDBLocal
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
Sort
100 15,000 50,000 99,999
Ace Bob Bob Acegamertag
score
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
Sort
100 15,000 50,000 99,999
Ace Bob Bob Ace
{} {} {} {}
gamertag
score
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
Sort
100 15,000 50,000 99,999
Ace Bob Bob Ace
{} {} {} {}
gamertag
score
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
Sort
100 15,000 50,000 99,999
Ace Bob Bob Ace
{1} {} {} {2}
gamertag
score
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
Sort
100 15,000 50,000 99,999
Ace Bob Bob Ace
{1} {} {} {2}
gamertag
score
"indexBounds" : {
"score" : [
"[MinKey, MaxKey]"
],
"gamertag" : [
"["Ace", "Ace"]"
]
}
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
Sort
100 15,000 50,000 99,999
Ace Bob Bob Ace
{1} {} {} {2}
gamertag
score
"indexBounds" : {
"score" : [
"[MinKey, MaxKey]"
],
"gamertag" : [
"["Ace", "Ace"]"
]
}
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
Sort
100 15,000 50,000 99,999
Ace Bob Bob Ace
{1} {} {} {2}
gamertag
score
"indexBounds" : {
"score" : [
"[MinKey, MaxKey]"
],
"gamertag" : [
"["Ace", "Ace"]”
]
}
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
Sort
100 15,000 50,000 99,999
Ace Bob Bob Ace
{1} {} {} {2}
gamertag
score
"indexBounds" : {
"score" : [
"[MinKey, MaxKey]"
],
"gamertag" : [
"["Ace", "Ace"]”
]
}
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
Sort
100 15,000 50,000 99,999
Ace Bob Bob Ace
{1} {} {} {2}
gamertag
score
"indexBounds" : {
"score" : [
"[MinKey, MaxKey]"
],
"gamertag" : [
"["Ace", "Ace"]”
]
}
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
Sort
100 15,000 50,000 99,999
Ace Bob Bob Ace
{1} {} {} {2}
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
gamertag
score
"indexBounds" : {
"score" : [
"[MinKey, MaxKey]"
],
"gamertag" : [
"["Ace", "Ace"]”
]
}
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
Sort
100 15,000 50,000 99,999
Ace Bob Bob Ace
{1} {} {} {2}
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
gamertag
score
"indexBounds" : {
"score" : [
"[MinKey, MaxKey]"
],
"gamertag" : [
"["Ace", "Ace"]”
]
}
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
Sort
100 15,000 50,000 99,999
Ace Bob Bob Ace
{1} {} {} {2}
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
gamertag
score
"indexBounds" : {
"score" : [
"[MinKey, MaxKey]"
],
"gamertag" : [
"["Ace", "Ace"]”
]
}
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
Sort
100 15,000 50,000 99,999
Ace Bob Bob Ace
{1} {} {} {2}
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
gamertag
score
"indexBounds" : {
"score" : [
"[MinKey, MaxKey]"
],
"gamertag" : [
"["Ace", "Ace"]”
]
}
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
Sort
100 15,000 50,000 99,999
Ace Bob Bob Ace
{1} {} {} {2}
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
gamertag
score
"indexBounds" : {
"score" : [
"[MinKey, MaxKey]"
],
"gamertag" : [
"["Ace", "Ace"]”
]
}
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
Sort
100 15,000 50,000 99,999
Ace Bob Bob Ace
{1} {} {} {2}
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
gamertag
score
"indexBounds" : {
"score" : [
"[MinKey, MaxKey]"
],
"gamertag" : [
"["Ace", "Ace"]”
]
}
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
Sort
100 15,000 50,000 99,999
Ace Bob Bob Ace
{1} {} {} {2}
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
gamertag
score
"indexBounds" : {
"score" : [
"[MinKey, MaxKey]"
],
"gamertag" : [
"["Ace", "Ace"]”
]
}
db.games.createIndex({score:1, gamertag:1})
#MDBLocal
Sort
100 15,000 50,000 99,999
Ace Bob Bob Ace
{1} {} {} {2}
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
#MDBLocal
Sort
Ace Bob Bob Ace
100 99,999 15,000 50,000
{1} {2} {} {}
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
#MDBLocal
Sort
100
Ace Bob
99,999 15,000 50,000
{}{1} {2} {}
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
gamertag
score
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
”score" : [
"[MinKey, MaxKey]"
]
}
db.games.createIndex({gamertag:1, score:1})
#MDBLocal
Sort
100
Ace Bob
99,999 15,000 50,000
{}{1} {2} {}
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
gamertag
score
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
”score" : [
"[MinKey, MaxKey]"
]
}
db.games.createIndex({gamertag:1, score:1})
#MDBLocal
Sort
100
Ace Bob
99,999 15,000 50,000
{}{1} {2} {}
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
gamertag
score
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
”score" : [
"[MinKey, MaxKey]"
]
}
db.games.createIndex({gamertag:1, score:1})
#MDBLocal
Sort
100
Ace Bob
99,999 15,000 50,000
{}{1} {2} {}
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
gamertag
score
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
”score" : [
"[MinKey, MaxKey]"
]
}
db.games.createIndex({gamertag:1, score:1})
#MDBLocal
Sort
100
Ace Bob
99,999 15,000 50,000
{}{1} {2} {}
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
gamertag
score
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
”score" : [
"[MinKey, MaxKey]"
]
}
db.games.createIndex({gamertag:1, score:1})
#MDBLocal
Sort
100
Ace Bob
99,999 15,000 50,000
{}{1} {2} {}
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
gamertag
score
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
”score" : [
"[MinKey, MaxKey]"
]
}
db.games.createIndex({gamertag:1, score:1})
#MDBLocal
Sort
100
Ace Bob
99,999 15,000 50,000
{}{1} {2} {}
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
gamertag
score
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
”score" : [
"[MinKey, MaxKey]"
]
}
db.games.createIndex({gamertag:1, score:1})
#MDBLocal
Sort after Equality
S
E S
E
db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
Don’t do this, it may require a full index
scan
#MDBLocal
Roadmap
E-S-R Overview
Guidelines:
• Eà R
• Eà S
• Sà R
E-S-R Considerations
Operator Type Checks
Consecutive Index Keys
Exceptions?
#MDBLocal
Range fields are usually last
This allows them to:
Still participate in filtering the data
But does not force a blocking sort.
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
Range
#MDBLocal
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
R
E R
E
Range after Equality
#MDBLocal
db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
R
E R
E
Range after Equality
Should range come after sort too?
#MDBLocal
R
E R
E
Range after Equality
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Should range come after sort too?
#MDBLocal
R
E R
E
Range
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Bob Ace
*
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
gamertag
score
db.games.createIndex({ …, score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Bob Ace
*
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
gamertag
score
db.games.createIndex({ …, score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Cali Ace
*
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
gamertag
score
db.games.createIndex({ …, score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Cali Ace
*
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
{} {} {} {}{1}{2} {3}
gamertag
score
db.games.createIndex({ …, score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Cali Ace
*
{} {2} {3} {1}
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
gamertag
score
"indexBounds" : {
*,
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"[MinKey, MaxKey]"
]
}
db.games.createIndex({ …, score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Cali Ace
*
{} {2} {3} {1}
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
gamertag
score
"indexBounds" : {
*,
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"[MinKey, MaxKey]"
]
}
db.games.createIndex({ …, score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Cali Ace
*
{} {2} {3} {1}
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
gamertag
score
"indexBounds" : {
*,
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"[MinKey, MaxKey]"
]
}
db.games.createIndex({ …, score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Cali Ace
*
{} {2} {3} {1}
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
gamertag
score
"indexBounds" : {
*,
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"[MinKey, MaxKey]"
]
}
db.games.createIndex({ …, score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Cali Ace
*
{} {2} {3} {1}
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
gamertag
score
"indexBounds" : {
*,
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"[MinKey, MaxKey]"
]
}
db.games.createIndex({ …, score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Cali Ace
*
{} {2} {3} {1}
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
gamertag
score
"indexBounds" : {
*,
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"[MinKey, MaxKey]"
]
}
db.games.createIndex({ …, score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Cali Ace
*
{} {2} {3} {1}
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
gamertag
score
"indexBounds" : {
*,
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"[MinKey, MaxKey]"
]
}
db.games.createIndex({ …, score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Cali Ace
*
{} {2} {3} {1}
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
gamertag
score
"indexBounds" : {
*,
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"[MinKey, MaxKey]"
]
}
db.games.createIndex({ …, score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Cali Ace
*
{} {2} {3} {1}
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
gamertag
score
"indexBounds" : {
*,
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"[MinKey, MaxKey]"
]
}
db.games.createIndex({ …, score:1, gamertag:1})
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Cali Ace
*
{} {2} {3} {1}
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
gamertag
score
"indexBounds" : {
*,
"score" : [
"(9000.0, inf.0]"
],
"gamertag" : [
"[MinKey, MaxKey]"
]
}
db.games.createIndex({ …, score:1, gamertag:1})
#MDBLocal
{2} {3} {1}
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
Blocking SortBlocking
Sort
BS
#MDBLocal
{2}{3}{1}
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
BS
#MDBLocal
100 15,000 50,000 99,999
Ace Bob Cali Ace
*
{} {2} {3} {1}
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
#MDBLocal
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
*
Ace Bob Cali Ace
100 15,000 50,00099,999
{} {1} {2} {3}
#MDBLocal
*
100 15,000 50,00099,999
Ace Bob Cali
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
{} {1} {3}
score
gamertag
"indexBounds" : {
*,
"gamertag" : [
"[MinKey, MaxKey]"
]
"score" : [
"(9000.0, inf.0]"
]
}
db.games.createIndex({ …, gamertag:1, score:1})
{2}
#MDBLocal
*
100 15,000 50,00099,999
Ace Bob Cali
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
{} {1} {3}
score
gamertag
"indexBounds" : {
*,
"gamertag" : [
"[MinKey, MaxKey]"
]
"score" : [
"(9000.0, inf.0]"
]
}
db.games.createIndex({ …, gamertag:1, score:1})
{2}
#MDBLocal
*
100 15,000 50,00099,999
Ace Bob Cali
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
{} {1} {3}
score
gamertag
"indexBounds" : {
*,
"gamertag" : [
"[MinKey, MaxKey]"
]
"score" : [
"(9000.0, inf.0]"
]
}
db.games.createIndex({ …, gamertag:1, score:1})
{2}
#MDBLocal
*
100 15,000 50,00099,999
Ace Bob Cali
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
{} {1} {3}
score
gamertag
"indexBounds" : {
*,
"gamertag" : [
"[MinKey, MaxKey]"
]
"score" : [
"(9000.0, inf.0]"
]
}
db.games.createIndex({ …, gamertag:1, score:1})
{2}
#MDBLocal
*
100 15,000 50,00099,999
Ace Bob Cali
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
{} {1} {3}
score
gamertag
"indexBounds" : {
*,
"gamertag" : [
"[MinKey, MaxKey]"
]
"score" : [
"(9000.0, inf.0]"
]
}
db.games.createIndex({ …, gamertag:1, score:1})
{2}
#MDBLocal
*
100 15,000 50,00099,999
Ace Bob Cali
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
{} {1} {3}
score
gamertag
"indexBounds" : {
*,
"gamertag" : [
"[MinKey, MaxKey]"
]
"score" : [
"(9000.0, inf.0]"
]
}
db.games.createIndex({ …, gamertag:1, score:1})
{2}
#MDBLocal
*
100 15,000 50,00099,999
Ace Bob Cali
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
{} {1} {3}
score
gamertag
"indexBounds" : {
*,
"gamertag" : [
"[MinKey, MaxKey]"
]
"score" : [
"(9000.0, inf.0]"
]
}
db.games.createIndex({ …, gamertag:1, score:1})
{2}
#MDBLocal
*
100 15,000 50,00099,999
Ace Bob Cali
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
{} {1} {3}
score
gamertag
"indexBounds" : {
*,
"gamertag" : [
"[MinKey, MaxKey]"
]
"score" : [
"(9000.0, inf.0]"
]
}
db.games.createIndex({ …, gamertag:1, score:1})
{2}
#MDBLocal
*
100 15,000 50,00099,999
Ace Bob Cali
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
{} {1} {3}
score
gamertag
"indexBounds" : {
*,
"gamertag" : [
"[MinKey, MaxKey]"
]
"score" : [
"(9000.0, inf.0]"
]
}
db.games.createIndex({ …, gamertag:1, score:1})
{2}
#MDBLocal
*
100 15,000 50,00099,999
Ace Bob Cali
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
{} {1} {3}
score
gamertag
"indexBounds" : {
*,
"gamertag" : [
"[MinKey, MaxKey]"
]
"score" : [
"(9000.0, inf.0]"
]
}
db.games.createIndex({ …, gamertag:1, score:1})
{2}
#MDBLocal
*
100 15,000 50,00099,999
Ace Bob Cali
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range
{} {1} {3}
score
gamertag
"indexBounds" : {
*,
"gamertag" : [
"[MinKey, MaxKey]"
]
"score" : [
"(9000.0, inf.0]"
]
}
db.games.createIndex({ …, gamertag:1, score:1})
{2}
#MDBLocal
BS
R S
R
S
db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
Range after Sort
#MDBLocal
Roadmap
E-S-R Overview
Guidelines:
• Eà R
• Eà S
• Sà R
E-S-R Considerations
Operator Type Checks
Consecutive Index Keys
Exceptions?
#MDBLocal
Operator Type Check
Some operators are simple
$eq: Equality
$gte: Range
Others are trickier
#MDBLocal
Operator Type Check - Inequality
Inequality Operators: E, S, or R?
• $ne:123
• $nin:[1,2]
Range!
#MDBLocal
Operator Type Check - Inequality
Inequality Operators: E, S, or R?
• $ne:123
• $nin:[1,2]
Range!
But … how do you know?
#MDBLocal
Operator Type Check - Inequality
Inequality Operators: E, S, or R?
• $ne:123
• $nin:[1,2]
Range!
"indexBounds" : {
"x" : [
"[MinKey, 123.0)",
"(123.0, MaxKey]"
]
}
#MDBLocal
Operator Type Check - Inequality
Range!
"indexBounds" : {
"x" : [
"[MinKey, 123.0)",
"(123.0, MaxKey]"
]
}
50 123 999
#MDBLocal
Operator Type Check - Inequality
Range!
"indexBounds" : {
"x" : [
"[MinKey, 123.0)",
"(123.0, MaxKey]"
]
}
50 123 999
#MDBLocal
Operator Type Check - Inequality
Range!
"indexBounds" : {
"x" : [
"[MinKey, 123.0)",
"(123.0, MaxKey]"
]
}
50 123 999
#MDBLocal
Operator Type Check - Regex
Regex Operators: E, S, or R?
• {str:/car/}
• {str:/^car/i}
Range!
#MDBLocal
Operator Type Check - Regex
Regex Operators: E, S, or R?
• {str:/car/}
• {str:/^car/i}
Range!
#MDBLocal
Operator Type Check - Regex
Regex Operators: E, S, or R?
• {str:/car/}
• {str:/^car/i}
Range!
planecar racecar
#MDBLocal
Operator Type Check - Regex
Regex Operators: E, S, or R?
• {str:/car/}
• {str:/^car/i}
Range!
planecar racecar
#MDBLocal
Operator Type Check - Regex
Regex Operators: E, S, or R?
• {str:/car/}
• {str:/^car/i}
Range!
planecar racecar
#MDBLocal
Operator Type Check - Regex
Regex Operators: E, S, or R?
• {str:/car/}
• {str:/^car/i}
Range!
p???ecar racecar
#MDBLocal
Operator Type Check - Regex
Regex Operators: E, S, or R?
• {str:/car/}
• {str:/^car/i}
Range!
p???ecar racecar
#MDBLocal
Operator Type Check - Regex
Regex Operators: E, S, or R?
• {str:/car/}
• {str:/^car/i}
Range!
#MDBLocal
Operator Type Check - Regex
Regex Operators: E, S, or R?
• {str:/car/}
• {str:/^car/i}
Range!
raincarry
#MDBLocal
Operator Type Check - Regex
Regex Operators: E, S, or R?
• {str:/car/}
• {str:/^car/i}
Range!
raincarry
#MDBLocal
Operator Type Check - Regex
Regex Operators: E, S, or R?
• {str:/car/}
• {str:/^car/i}
Range!
raincarry Carpool
#MDBLocal
Operator Type Check - Regex
Regex Operators: E, S, or R?
• {str:/car/}
• {str:/^car/i}
Range!
raincarry Carpool
#MDBLocal
Operator Type Check - Regex
Regex Operators: E, S, or R?
• {str:/car/}
• {str:/^car/i}
Range!
raincarry Carpool
#MDBLocal
Operator Type Check - Regex
Regex Operators: E, S, or R?
• {str:/car/}
• {str:/^car/i}
Range!
raincarry
Carpoo
l
Woah Woah WOAH …. Since the regex is left
anchored, can’t we skip the middle tree?
#MDBLocal
Operator Type Check - Regex
Regex Operators: E, S, or R?
• {str:/car/}
• {str:/^car/i}
Range!
raincarry
Carpoo
l
Woah Woah WOAH …. Since the regex is left
anchored, can’t we skip the middle tree?
#MDBLocal
Operator Type Check - Regex
Regex Operators: E, S, or R?
• {str:/car/}
• {str:/^car/i}
Range!
cArrycarry
Carpoo
l
Woah Woah WOAH …. Since the regex is left
anchored, can’t we skip the middle tree?
#MDBLocal
Operator Type Check - Regex
Regex Operators: E, S, or R?
• {str:/car/}
• {str:/^car/i}
Range!
cArrycarry
Carpoo
l
Woah Woah WOAH …. Since the regex is left
anchored, can’t we skip the middle tree?
#MDBLocal
Operator Type Check - Regex
Regex Operators: E, S, or R?
• {str:/car/}
• {str:/^car/i}
Range!
cArrycarry
Carpoo
l
#MDBLocal
Operator Type Check - $in
$in filters: E, S, or R?
• {field:{$in:[1,3]}}
… it depends with respect to key
ordering
Alone: a series of Equality matches
Combined: possibly a Range
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
"[3.0, 3.0]"
]
}
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
"[3.0, 3.0]"
]
}
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
"[3.0, 3.0]"
]
}
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
"[3.0, 3.0]"
]
}
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
"[3.0, 3.0]"
]
}
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
"[3.0, 3.0]"
]
}
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}})
.sort({sortField:1})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
"[3.0, 3.0]"
]
}
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}})
.sort({sortField:1})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
"[3.0, 3.0]"
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}})
.sort({sortField:1})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
"[3.0, 3.0]"
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}})
.sort({sortField:1})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
"[3.0, 3.0]"
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}})
.sort({sortField:1})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
"[3.0, 3.0]"
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}})
.sort({sortField:1})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
"[3.0, 3.0]"
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
?
1 2 3
C G B F A D
BS
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}})
.sort({sortField:1})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
"[3.0, 3.0]"
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
?
1 2 3
C G B F A D
BS
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}})
.sort({sortField:1})
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}}).sort({sortField:1}) ?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}}).sort({sortField:1})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}}).sort({sortField:1})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}}).sort({sortField:1})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}}).sort({sortField:1})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}}).sort({sortField:1})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}}).sort({sortField:1})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
"indexBounds" : {
"field" : [
"[3.0, 3.0]",
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}}).sort({sortField:1})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
"indexBounds" : {
"field" : [
"[3.0, 3.0]",
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
?
1 2 3
C G B F A D
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}}).sort({sortField:1})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
"indexBounds" : {
"field" : [
"[3.0, 3.0]",
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
?
1 2 3
C G B F A D
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}}).sort({sortField:1})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
"indexBounds" : {
"field" : [
"[3.0, 3.0]",
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
?
1 2 3
C G B F A D
?
1 2 3
C G B F A D
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
Operator Type Check - $in
.find({field:{$in:[1,3]}}).sort({sortField:1})
"indexBounds" : {
"field" : [
"[1.0, 1.0]",
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
"indexBounds" : {
"field" : [
"[3.0, 3.0]",
],
"sortField" : [
"[MinKey, MaxKey]"
]
}
?
1 2 3
C G B F A D
?
1 2 3
C G B F A D
{2} {4} {1} {3}
Sort Merge
db.coll.createIndex({field:1, sortField:1})
#MDBLocal
BS
S M
Operator Type Check - $in
#MDBLocal
Roadmap
E-S-R Overview
Guidelines:
• Eà R
• Eà S
• Sà R
E-S-R Considerations
Operator Type Checks
Consecutive Index Keys
Exceptions?
#MDBLocal
Consecutive Index Keys
Given Indexes:
{gamertag:1, date:1, game:1}
{gamertag:1, game:1, date:1}
Which one is “better”?
It depends on the query shape(s)!
Consider the query:
.find({
gamertag:"Ace",
game: "Halo”
})
#MDBLocal
Consecutive Index Keys
.find({
gamertag:"Ace",
game: "Halo”
})
#MDBLocal
Consecutive Index Keys
Ace
Mario Halo
2016 2017
Mario Halo
2018 2019
.find({
gamertag:"Ace",
game: "Halo”
})
db.games.createIndex({gamertag:1, date:1, game:1})
#MDBLocal
Consecutive Index Keys
Ace
Mario Halo
2016 2017
Mario Halo
2018 2019
.find({
gamertag:"Ace",
game: "Halo”
})
{} {} {} {}
db.games.createIndex({gamertag:1, date:1, game:1})
#MDBLocal
Consecutive Index Keys
Ace
Mario Halo
2016 2017
Mario Halo
2018 2019
.find({
gamertag:"Ace",
game: "Halo”
})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"date" : [
"[MinKey, MaxKey]"
],
"game" : [
"["Halo", "Halo"]"
]
}
{} {} {} {}
db.games.createIndex({gamertag:1, date:1, game:1})
#MDBLocal
Consecutive Index Keys
Ace
Mario Halo
2016 2017
Mario Halo
2018 2019
.find({
gamertag:"Ace",
game: "Halo”
})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"date" : [
"[MinKey, MaxKey]"
],
"game" : [
"["Halo", "Halo"]"
]
}
{} {} {} {}
db.games.createIndex({gamertag:1, date:1, game:1})
#MDBLocal
Consecutive Index Keys
Ace
Mario Halo
2016 2017
Mario Halo
2018 2019
.find({
gamertag:"Ace",
game: "Halo”
})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"date" : [
"[MinKey, MaxKey]"
],
"game" : [
"["Halo", "Halo"]"
]
}
{} {} {} {}
db.games.createIndex({gamertag:1, date:1, game:1})
#MDBLocal
Consecutive Index Keys
Ace
Mario Halo
2016 2017
Mario Halo
2018 2019
.find({
gamertag:"Ace",
game: "Halo”
})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"date" : [
"[MinKey, MaxKey]"
],
"game" : [
"["Halo", "Halo"]"
]
}
{} {} {} {}
db.games.createIndex({gamertag:1, date:1, game:1})
#MDBLocal
Consecutive Index Keys
Ace
Mario Halo
2016 2017
Mario Halo
2018 2019
.find({
gamertag:"Ace",
game: "Halo”
})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"date" : [
"[MinKey, MaxKey]"
],
"game" : [
"["Halo", "Halo"]"
]
}
{} {} {} {}
db.games.createIndex({gamertag:1, date:1, game:1})
#MDBLocal
Consecutive Index Keys
Ace
Mario Halo
2016 2017
Mario Halo
2018 2019
.find({
gamertag:"Ace",
game: "Halo”
})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"date" : [
"[MinKey, MaxKey]"
],
"game" : [
"["Halo", "Halo"]"
]
}
{} {} {} {}
db.games.createIndex({gamertag:1, date:1, game:1})
#MDBLocal
Consecutive Index Keys
Ace
Mario Halo
2016 2017
Mario Halo
2018 2019
.find({
gamertag:"Ace",
game: "Halo”
})
{} {}
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"date" : [
"[MinKey, MaxKey]"
],
"game" : [
"["Halo", "Halo"]"
]
}
{} {}
db.games.createIndex({gamertag:1, date:1, game:1})
#MDBLocal
Consecutive Index Keys
Ace
Mario Halo
2016 2017
Mario Halo
2018 2019
.find({
gamertag:"Ace",
game: "Halo”
})
{} {}
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"date" : [
"[MinKey, MaxKey]"
],
"game" : [
"["Halo", "Halo"]"
]
}
{} {}
db.games.createIndex({gamertag:1, date:1, game:1})
#MDBLocal
Consecutive Index Keys
Ace
Mario Halo
2016 2017
Mario Halo
2018 2019
.find({
gamertag:"Ace",
game: "Halo”
})
{} {}
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"date" : [
"[MinKey, MaxKey]"
],
"game" : [
"["Halo", "Halo"]"
]
}
{} {}
db.games.createIndex({gamertag:1, date:1, game:1})
#MDBLocal
Consecutive Index Keys
Ace
Mario Halo
2016 2017
Mario Halo
2018 2019
.find({
gamertag:"Ace",
game: "Halo”
})
{} {}
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"date" : [
"[MinKey, MaxKey]"
],
"game" : [
"["Halo", "Halo"]"
]
}
{} {}
db.games.createIndex({gamertag:1, date:1, game:1})
#MDBLocal
Consecutive Index Keys
Ace
Mario Halo
2016 2017
Mario Halo
2018 2019
.find({
gamertag:"Ace",
game: "Halo”
})
{} {}
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"date" : [
"[MinKey, MaxKey]"
],
"game" : [
"["Halo", "Halo"]"
]
}
{} {}
db.games.createIndex({gamertag:1, date:1, game:1})
#MDBLocal
Consecutive Index Keys
.find({
gamertag:"Ace",
game: "Halo”
})
{} {} {} {}
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"date" : [
"[MinKey, MaxKey]"
],
"game" : [
"["Halo", "Halo"]"
]
}
Halo
Ace
Mario Halo
2016 2017
Mario
2018 2019
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"game" : [
"["Halo", "Halo"]"
]
}
db.games.createIndex({gamertag:1, game:1})
#MDBLocal
Ace
2016 2017Mario2018 2019Halo
Consecutive Index Keys
.find({
gamertag:"Ace",
game: "Halo”
})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"game" : [
"["Halo", "Halo"]"
]
}
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"game" : [
"["Halo", "Halo"]"
],
"date" : [
"[MinKey, MaxKey]"
]
}
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"game" : [
"["Halo", "Halo"]"
]
}
{}{} {}{}
db.games.createIndex({gamertag:1, game:1, date:1})
#MDBLocal
R
E
E E
E
E
E
Consecutive Index Keys
R
Look familiar? This is equality after range!
#MDBLocal
Roadmap
E-S-R Overview
Guidelines:
• Eà R
• Eà S
• Sà R
E-S-R Considerations
Operator Type Checks
Consecutive Index Keys
Exceptions?
#MDBLocal
Exceptions
Is the E-S-R “rule” always optimal?
Nope.
Consider the following query:
db.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
1 5,000 9,0012 9,000
… …
2001 2000 2015 2019 2019
gamertag
score
date
{} {} {} {1} {2}
db.games.createIndex({gamertag:1, score:1, date:1})
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
1 5,000 9,0012 9,000
… …
2001 2000 2015 2019 2019
gamertag
score
date
{} {} {}
db.games.createIndex({gamertag:1, score:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"[MinKey, MaxKey]"
],
"date" : [
"[2019.0, inf.0]"
]
}
{1} {2}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
1 5,000 9,0012 9,000
… …
2001 2000 2015 2019 2019
gamertag
score
date
{} {} {}
db.games.createIndex({gamertag:1, score:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"[MinKey, MaxKey]"
],
"date" : [
"[2019.0, inf.0]"
]
}
{1} {2}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
1 5,000 9,0012 9,000
… …
2001 2000 2015 2019 2019
gamertag
score
date
{} {} {}
db.games.createIndex({gamertag:1, score:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"[MinKey, MaxKey]"
],
"date" : [
"[2019.0, inf.0]"
]
}
{1} {2}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
1 5,000 9,0012 9,000
… …
2001 2000 2015 2019 2019
gamertag
score
date
{} {} {}
db.games.createIndex({gamertag:1, score:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"[MinKey, MaxKey]"
],
"date" : [
"[2019.0, inf.0]"
]
}
{1} {2}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
1 5,000 9,0012 9,000
… …
2001 2000 2015 2019 2019
gamertag
score
date
{} {} {}
db.games.createIndex({gamertag:1, score:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"[MinKey, MaxKey]"
],
"date" : [
"[2019.0, inf.0]"
]
}
{1} {2}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
1 5,000 9,0012 9,000
… …
2001 2000 2015 2019 2019
gamertag
score
date
{} {} {}
db.games.createIndex({gamertag:1, score:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"[MinKey, MaxKey]"
],
"date" : [
"[2019.0, inf.0]"
]
}
{1} {2}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
1 5,000 9,0012 9,000
… …
2001 2000 2015 2019 2019
gamertag
score
date
{} {} {}
db.games.createIndex({gamertag:1, score:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"[MinKey, MaxKey]"
],
"date" : [
"[2019.0, inf.0]"
]
}
{1} {2}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
1 5,000 9,0012 9,000
… …
2001 2000 2015 2019 2019
gamertag
score
date
{} {} {}
db.games.createIndex({gamertag:1, score:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"[MinKey, MaxKey]"
],
"date" : [
"[2019.0, inf.0]"
]
}
{1} {2}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
1 5,000 9,0012 9,000
… …
2001 2000 2015 2019 2019
gamertag
score
date
{} {} {}
db.games.createIndex({gamertag:1, score:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"[MinKey, MaxKey]"
],
"date" : [
"[2019.0, inf.0]"
]
}
{1} {2}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
1 5,000 9,0012 9,000
… …
2001 2000 2015 2019 2019
gamertag
score
date
{} {} {}
db.games.createIndex({gamertag:1, score:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"[MinKey, MaxKey]"
],
"date" : [
"[2019.0, inf.0]"
]
}
{1} {2}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
1 5,000 9,0012 9,000
… …
2001 2000 2015 2019 2019
gamertag
score
date
{} {} {}
db.games.createIndex({gamertag:1, score:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"[MinKey, MaxKey]"
],
"date" : [
"[2019.0, inf.0]"
]
}
{1} {2}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
1 5,000 9,0012 9,000
… …
2001 2000 2015 2019 2019
gamertag
score
date
{} {} {}
db.games.createIndex({gamertag:1, score:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"[MinKey, MaxKey]"
],
"date" : [
"[2019.0, inf.0]"
]
}
{1} {2}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
1 5,000 9,0012 9,000
… …
2001 2000 2015 2019 2019
gamertag
score
date
{} {} {}
db.games.createIndex({gamertag:1, score:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"[MinKey, MaxKey]"
],
"date" : [
"[2019.0, inf.0]"
]
}
{1} {2}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
1 5,000 9,0012 9,000
… …
2001 2000 2015 2019 2019
gamertag
score
date
{} {} {}
db.games.createIndex({gamertag:1, score:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"score" : [
"[MinKey, MaxKey]"
],
"date" : [
"[2019.0, inf.0]"
]
}
{1} {2}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
1 5,000 9,0012 9,000
… …
2001 2000 2015 2019 2019
gamertag
score
date
{} {} {}
"executionStats" : {
"nReturned" : 2,
"executionTimeMillis" : 23,
"totalKeysExamined" : 9001,
"totalDocsExamined" : 2,
db.games.createIndex({gamertag:1, score:1, date:1})
{1} {2}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
1 5,000 9,0012 9,000
… …
2001 2000 2015 2019 2019
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
2001 2000 2015 2019 2019
{score:2} {score:1} {score:5000} {score:9001} {score:9000}
… …
gamertag
date
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
… …
2000 2001 2015 2019 2019
{score:2} {score:1} {score:5000} {score:9001} {score:9000}
gamertag
date
db.games.createIndex({gamertag:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"date" : [
"[2019.0, inf.0]"
]
}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
… …
2000 2001 2015 2019 2019
{score:2} {score:1} {score:5000} {score:9001} {score:9000}
gamertag
date
db.games.createIndex({gamertag:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"date" : [
"[2019.0, inf.0]"
]
}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
… …
2000 2001 2015 2019 2019
{score:2} {score:1} {score:5000} {score:9001} {score:9000}
gamertag
date
db.games.createIndex({gamertag:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"date" : [
"[2019.0, inf.0]"
]
}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
… …
2000 2001 2015 2019 2019
{score:2} {score:1} {score:5000} {score:9001} {score:9000}
gamertag
date
db.games.createIndex({gamertag:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"date" : [
"[2019.0, inf.0]"
]
}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
… …
2000 2001 2015 2019 2019
{score:2} {score:1} {score:5000} {score:9001} {score:9000}
gamertag
date
db.games.createIndex({gamertag:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"date" : [
"[2019.0, inf.0]"
]
}
#MDBLocal
Exceptionsdb.games
.find({gamertag:"Ace", date:{$gte:2019}})
.sort({score:1})
Ace
… …
2000 2001 2015 2019 2019
{score:2} {score:1} {score:5000}
gamertag
date
{score:9001} {score:9000}
BS
"executionStats" : {
"nReturned" : 2,
"executionTimeMillis" : 0,
"totalKeysExamined" : 2,
"totalDocsExamined" : 2,
"executionStats" : {
"nReturned" : 2,
"executionTimeMillis" : 0,
"totalKeysExamined" : 2,
"totalDocsExamined" : 2,
"executionStages" : {
"stage" : "SORT",
"memUsage" : 154,
"memLimit" : 33554432,
db.games.createIndex({gamertag:1, date:1})
"indexBounds" : {
"gamertag" : [
"["Ace", "Ace"]"
],
"date" : [
"[2019.0, inf.0]"
]
}
#MDBLocal
Exceptions
……… …
BS
S
R
E
R
E
Summary
#MDBLocal
E-S-R Guidance
A good starting place applicable to
most use cases
Place keys in the following order:
Equality first
Sort next
Range last
Remember:
• Some operators may be range
instead of equality
• Having consecutive keys used in
the index is important
• Specifics about your data set may
need a different approach
Thank You!
MongoDB .local Toronto 2019: Tips and Tricks for Effective Indexing
MongoDB .local Toronto 2019: Tips and Tricks for Effective Indexing
Ad

More Related Content

What's hot (20)

MongoDB .local Toronto 2019: Aggregation Pipeline Power++: How MongoDB 4.2 Pi...
MongoDB .local Toronto 2019: Aggregation Pipeline Power++: How MongoDB 4.2 Pi...MongoDB .local Toronto 2019: Aggregation Pipeline Power++: How MongoDB 4.2 Pi...
MongoDB .local Toronto 2019: Aggregation Pipeline Power++: How MongoDB 4.2 Pi...
MongoDB
 
Indexing and Performance Tuning
Indexing and Performance TuningIndexing and Performance Tuning
Indexing and Performance Tuning
MongoDB
 
Fast querying indexing for performance (4)
Fast querying   indexing for performance (4)Fast querying   indexing for performance (4)
Fast querying indexing for performance (4)
MongoDB
 
Introduction to Mongodb execution plan and optimizer
Introduction to Mongodb execution plan and optimizerIntroduction to Mongodb execution plan and optimizer
Introduction to Mongodb execution plan and optimizer
Mydbops
 
MongoDB Performance Tuning
MongoDB Performance TuningMongoDB Performance Tuning
MongoDB Performance Tuning
Puneet Behl
 
MongoDB Aggregation Performance
MongoDB Aggregation PerformanceMongoDB Aggregation Performance
MongoDB Aggregation Performance
MongoDB
 
MongoDB Aggregation Framework
MongoDB Aggregation FrameworkMongoDB Aggregation Framework
MongoDB Aggregation Framework
Caserta
 
MongoDB and Indexes - MUG Denver - 20160329
MongoDB and Indexes - MUG Denver - 20160329MongoDB and Indexes - MUG Denver - 20160329
MongoDB and Indexes - MUG Denver - 20160329
Douglas Duncan
 
Indexing with MongoDB
Indexing with MongoDBIndexing with MongoDB
Indexing with MongoDB
MongoDB
 
Indexing
IndexingIndexing
Indexing
Mike Dirolf
 
MongoDB (Advanced)
MongoDB (Advanced)MongoDB (Advanced)
MongoDB (Advanced)
TO THE NEW | Technology
 
MongoDB Performance Tuning
MongoDB Performance TuningMongoDB Performance Tuning
MongoDB Performance Tuning
MongoDB
 
Naver속도의, 속도에 의한, 속도를 위한 몽고DB (네이버 컨텐츠검색과 몽고DB) [Naver]
Naver속도의, 속도에 의한, 속도를 위한 몽고DB (네이버 컨텐츠검색과 몽고DB) [Naver]Naver속도의, 속도에 의한, 속도를 위한 몽고DB (네이버 컨텐츠검색과 몽고DB) [Naver]
Naver속도의, 속도에 의한, 속도를 위한 몽고DB (네이버 컨텐츠검색과 몽고DB) [Naver]
MongoDB
 
Get to know PostgreSQL!
Get to know PostgreSQL!Get to know PostgreSQL!
Get to know PostgreSQL!
Oddbjørn Steffensen
 
MongodB Internals
MongodB InternalsMongodB Internals
MongodB Internals
Norberto Leite
 
Introduction to MongoDB
Introduction to MongoDBIntroduction to MongoDB
Introduction to MongoDB
Mike Dirolf
 
New Indexing and Aggregation Pipeline Capabilities in MongoDB 4.2
New Indexing and Aggregation Pipeline Capabilities in MongoDB 4.2New Indexing and Aggregation Pipeline Capabilities in MongoDB 4.2
New Indexing and Aggregation Pipeline Capabilities in MongoDB 4.2
Antonios Giannopoulos
 
How to Use JSON in MySQL Wrong
How to Use JSON in MySQL WrongHow to Use JSON in MySQL Wrong
How to Use JSON in MySQL Wrong
Karwin Software Solutions LLC
 
MongoDB vs Scylla: Production Experience from Both Dev & Ops Standpoint at Nu...
MongoDB vs Scylla: Production Experience from Both Dev & Ops Standpoint at Nu...MongoDB vs Scylla: Production Experience from Both Dev & Ops Standpoint at Nu...
MongoDB vs Scylla: Production Experience from Both Dev & Ops Standpoint at Nu...
ScyllaDB
 
Building Advanced XSS Vectors
Building Advanced XSS VectorsBuilding Advanced XSS Vectors
Building Advanced XSS Vectors
Rodolfo Assis (Brute)
 
MongoDB .local Toronto 2019: Aggregation Pipeline Power++: How MongoDB 4.2 Pi...
MongoDB .local Toronto 2019: Aggregation Pipeline Power++: How MongoDB 4.2 Pi...MongoDB .local Toronto 2019: Aggregation Pipeline Power++: How MongoDB 4.2 Pi...
MongoDB .local Toronto 2019: Aggregation Pipeline Power++: How MongoDB 4.2 Pi...
MongoDB
 
Indexing and Performance Tuning
Indexing and Performance TuningIndexing and Performance Tuning
Indexing and Performance Tuning
MongoDB
 
Fast querying indexing for performance (4)
Fast querying   indexing for performance (4)Fast querying   indexing for performance (4)
Fast querying indexing for performance (4)
MongoDB
 
Introduction to Mongodb execution plan and optimizer
Introduction to Mongodb execution plan and optimizerIntroduction to Mongodb execution plan and optimizer
Introduction to Mongodb execution plan and optimizer
Mydbops
 
MongoDB Performance Tuning
MongoDB Performance TuningMongoDB Performance Tuning
MongoDB Performance Tuning
Puneet Behl
 
MongoDB Aggregation Performance
MongoDB Aggregation PerformanceMongoDB Aggregation Performance
MongoDB Aggregation Performance
MongoDB
 
MongoDB Aggregation Framework
MongoDB Aggregation FrameworkMongoDB Aggregation Framework
MongoDB Aggregation Framework
Caserta
 
MongoDB and Indexes - MUG Denver - 20160329
MongoDB and Indexes - MUG Denver - 20160329MongoDB and Indexes - MUG Denver - 20160329
MongoDB and Indexes - MUG Denver - 20160329
Douglas Duncan
 
Indexing with MongoDB
Indexing with MongoDBIndexing with MongoDB
Indexing with MongoDB
MongoDB
 
MongoDB Performance Tuning
MongoDB Performance TuningMongoDB Performance Tuning
MongoDB Performance Tuning
MongoDB
 
Naver속도의, 속도에 의한, 속도를 위한 몽고DB (네이버 컨텐츠검색과 몽고DB) [Naver]
Naver속도의, 속도에 의한, 속도를 위한 몽고DB (네이버 컨텐츠검색과 몽고DB) [Naver]Naver속도의, 속도에 의한, 속도를 위한 몽고DB (네이버 컨텐츠검색과 몽고DB) [Naver]
Naver속도의, 속도에 의한, 속도를 위한 몽고DB (네이버 컨텐츠검색과 몽고DB) [Naver]
MongoDB
 
Introduction to MongoDB
Introduction to MongoDBIntroduction to MongoDB
Introduction to MongoDB
Mike Dirolf
 
New Indexing and Aggregation Pipeline Capabilities in MongoDB 4.2
New Indexing and Aggregation Pipeline Capabilities in MongoDB 4.2New Indexing and Aggregation Pipeline Capabilities in MongoDB 4.2
New Indexing and Aggregation Pipeline Capabilities in MongoDB 4.2
Antonios Giannopoulos
 
MongoDB vs Scylla: Production Experience from Both Dev & Ops Standpoint at Nu...
MongoDB vs Scylla: Production Experience from Both Dev & Ops Standpoint at Nu...MongoDB vs Scylla: Production Experience from Both Dev & Ops Standpoint at Nu...
MongoDB vs Scylla: Production Experience from Both Dev & Ops Standpoint at Nu...
ScyllaDB
 

Similar to MongoDB .local Toronto 2019: Tips and Tricks for Effective Indexing (20)

MongoDB .local Munich 2019: Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB .local Munich 2019: Tips and Tricks++ for Querying and Indexing MongoDBMongoDB .local Munich 2019: Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB .local Munich 2019: Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB
 
MongoDB .local London 2019: Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB .local London 2019: Tips and Tricks++ for Querying and Indexing MongoDBMongoDB .local London 2019: Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB .local London 2019: Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB
 
MongoDB .local London 2019: Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB .local London 2019: Tips and Tricks++ for Querying and Indexing MongoDBMongoDB .local London 2019: Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB .local London 2019: Tips and Tricks++ for Querying and Indexing MongoDB
Lisa Roth, PMP
 
MongoDB.local Austin 2018: Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB.local Austin 2018: Tips and Tricks for Avoiding Common Query PitfallsMongoDB.local Austin 2018: Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB.local Austin 2018: Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB
 
MongoDB .local Bengaluru 2019: Tips and Tricks++ for Querying and Indexing Mo...
MongoDB .local Bengaluru 2019: Tips and Tricks++ for Querying and Indexing Mo...MongoDB .local Bengaluru 2019: Tips and Tricks++ for Querying and Indexing Mo...
MongoDB .local Bengaluru 2019: Tips and Tricks++ for Querying and Indexing Mo...
MongoDB
 
MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...
MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...
MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...
MongoDB
 
Tips and Tricks for Avoiding Common Query Pitfalls
Tips and Tricks for Avoiding Common Query PitfallsTips and Tricks for Avoiding Common Query Pitfalls
Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB
 
MongoDB.local Sydney 2019: Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB.local Sydney 2019: Tips and Tricks for Avoiding Common Query PitfallsMongoDB.local Sydney 2019: Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB.local Sydney 2019: Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB
 
MongoDB.local Dallas 2019: Tips & Tricks for Avoiding Common Query Pitfalls
MongoDB.local Dallas 2019: Tips & Tricks for Avoiding Common Query PitfallsMongoDB.local Dallas 2019: Tips & Tricks for Avoiding Common Query Pitfalls
MongoDB.local Dallas 2019: Tips & Tricks for Avoiding Common Query Pitfalls
MongoDB
 
Avoid Query Pitfalls
Avoid Query PitfallsAvoid Query Pitfalls
Avoid Query Pitfalls
Norberto Leite
 
MongoDB World 2018: Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB World 2018: Tips and Tricks for Avoiding Common Query PitfallsMongoDB World 2018: Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB World 2018: Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB
 
Tips and Tricks for Avoiding Common Query Pitfalls
Tips and Tricks for Avoiding Common Query PitfallsTips and Tricks for Avoiding Common Query Pitfalls
Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB
 
Tips and Tricks for Avoiding Common Query Pitfalls Christian Kurze
Tips and Tricks for Avoiding Common Query Pitfalls Christian KurzeTips and Tricks for Avoiding Common Query Pitfalls Christian Kurze
Tips and Tricks for Avoiding Common Query Pitfalls Christian Kurze
MongoDB
 
MongoDB.local Seattle 2019: Tips & Tricks for Avoiding Common Query Pitfalls
MongoDB.local Seattle 2019: Tips & Tricks for Avoiding Common Query PitfallsMongoDB.local Seattle 2019: Tips & Tricks for Avoiding Common Query Pitfalls
MongoDB.local Seattle 2019: Tips & Tricks for Avoiding Common Query Pitfalls
MongoDB
 
MongoDB .local Houston 2019:Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB .local Houston 2019:Tips and Tricks++ for Querying and Indexing MongoDBMongoDB .local Houston 2019:Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB .local Houston 2019:Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB
 
Fazendo mágica com ElasticSearch
Fazendo mágica com ElasticSearchFazendo mágica com ElasticSearch
Fazendo mágica com ElasticSearch
Pedro Franceschi
 
MongoDB .local Paris 2020: Tout savoir sur le moteur de recherche Full Text S...
MongoDB .local Paris 2020: Tout savoir sur le moteur de recherche Full Text S...MongoDB .local Paris 2020: Tout savoir sur le moteur de recherche Full Text S...
MongoDB .local Paris 2020: Tout savoir sur le moteur de recherche Full Text S...
MongoDB
 
MongoDB .local Chicago 2019: Still Haven't Found What You Are Looking For? Us...
MongoDB .local Chicago 2019: Still Haven't Found What You Are Looking For? Us...MongoDB .local Chicago 2019: Still Haven't Found What You Are Looking For? Us...
MongoDB .local Chicago 2019: Still Haven't Found What You Are Looking For? Us...
MongoDB
 
Mongo db mug_2012-02-07
Mongo db mug_2012-02-07Mongo db mug_2012-02-07
Mongo db mug_2012-02-07
Will Button
 
CREATE INDEX … USING VODKA. VODKA CONNECTING INDEXES, Олег Бартунов, Александ...
CREATE INDEX … USING VODKA. VODKA CONNECTING INDEXES, Олег Бартунов, Александ...CREATE INDEX … USING VODKA. VODKA CONNECTING INDEXES, Олег Бартунов, Александ...
CREATE INDEX … USING VODKA. VODKA CONNECTING INDEXES, Олег Бартунов, Александ...
Ontico
 
MongoDB .local Munich 2019: Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB .local Munich 2019: Tips and Tricks++ for Querying and Indexing MongoDBMongoDB .local Munich 2019: Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB .local Munich 2019: Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB
 
MongoDB .local London 2019: Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB .local London 2019: Tips and Tricks++ for Querying and Indexing MongoDBMongoDB .local London 2019: Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB .local London 2019: Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB
 
MongoDB .local London 2019: Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB .local London 2019: Tips and Tricks++ for Querying and Indexing MongoDBMongoDB .local London 2019: Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB .local London 2019: Tips and Tricks++ for Querying and Indexing MongoDB
Lisa Roth, PMP
 
MongoDB.local Austin 2018: Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB.local Austin 2018: Tips and Tricks for Avoiding Common Query PitfallsMongoDB.local Austin 2018: Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB.local Austin 2018: Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB
 
MongoDB .local Bengaluru 2019: Tips and Tricks++ for Querying and Indexing Mo...
MongoDB .local Bengaluru 2019: Tips and Tricks++ for Querying and Indexing Mo...MongoDB .local Bengaluru 2019: Tips and Tricks++ for Querying and Indexing Mo...
MongoDB .local Bengaluru 2019: Tips and Tricks++ for Querying and Indexing Mo...
MongoDB
 
MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...
MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...
MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...
MongoDB
 
Tips and Tricks for Avoiding Common Query Pitfalls
Tips and Tricks for Avoiding Common Query PitfallsTips and Tricks for Avoiding Common Query Pitfalls
Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB
 
MongoDB.local Sydney 2019: Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB.local Sydney 2019: Tips and Tricks for Avoiding Common Query PitfallsMongoDB.local Sydney 2019: Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB.local Sydney 2019: Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB
 
MongoDB.local Dallas 2019: Tips & Tricks for Avoiding Common Query Pitfalls
MongoDB.local Dallas 2019: Tips & Tricks for Avoiding Common Query PitfallsMongoDB.local Dallas 2019: Tips & Tricks for Avoiding Common Query Pitfalls
MongoDB.local Dallas 2019: Tips & Tricks for Avoiding Common Query Pitfalls
MongoDB
 
MongoDB World 2018: Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB World 2018: Tips and Tricks for Avoiding Common Query PitfallsMongoDB World 2018: Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB World 2018: Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB
 
Tips and Tricks for Avoiding Common Query Pitfalls
Tips and Tricks for Avoiding Common Query PitfallsTips and Tricks for Avoiding Common Query Pitfalls
Tips and Tricks for Avoiding Common Query Pitfalls
MongoDB
 
Tips and Tricks for Avoiding Common Query Pitfalls Christian Kurze
Tips and Tricks for Avoiding Common Query Pitfalls Christian KurzeTips and Tricks for Avoiding Common Query Pitfalls Christian Kurze
Tips and Tricks for Avoiding Common Query Pitfalls Christian Kurze
MongoDB
 
MongoDB.local Seattle 2019: Tips & Tricks for Avoiding Common Query Pitfalls
MongoDB.local Seattle 2019: Tips & Tricks for Avoiding Common Query PitfallsMongoDB.local Seattle 2019: Tips & Tricks for Avoiding Common Query Pitfalls
MongoDB.local Seattle 2019: Tips & Tricks for Avoiding Common Query Pitfalls
MongoDB
 
MongoDB .local Houston 2019:Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB .local Houston 2019:Tips and Tricks++ for Querying and Indexing MongoDBMongoDB .local Houston 2019:Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB .local Houston 2019:Tips and Tricks++ for Querying and Indexing MongoDB
MongoDB
 
Fazendo mágica com ElasticSearch
Fazendo mágica com ElasticSearchFazendo mágica com ElasticSearch
Fazendo mágica com ElasticSearch
Pedro Franceschi
 
MongoDB .local Paris 2020: Tout savoir sur le moteur de recherche Full Text S...
MongoDB .local Paris 2020: Tout savoir sur le moteur de recherche Full Text S...MongoDB .local Paris 2020: Tout savoir sur le moteur de recherche Full Text S...
MongoDB .local Paris 2020: Tout savoir sur le moteur de recherche Full Text S...
MongoDB
 
MongoDB .local Chicago 2019: Still Haven't Found What You Are Looking For? Us...
MongoDB .local Chicago 2019: Still Haven't Found What You Are Looking For? Us...MongoDB .local Chicago 2019: Still Haven't Found What You Are Looking For? Us...
MongoDB .local Chicago 2019: Still Haven't Found What You Are Looking For? Us...
MongoDB
 
Mongo db mug_2012-02-07
Mongo db mug_2012-02-07Mongo db mug_2012-02-07
Mongo db mug_2012-02-07
Will Button
 
CREATE INDEX … USING VODKA. VODKA CONNECTING INDEXES, Олег Бартунов, Александ...
CREATE INDEX … USING VODKA. VODKA CONNECTING INDEXES, Олег Бартунов, Александ...CREATE INDEX … USING VODKA. VODKA CONNECTING INDEXES, Олег Бартунов, Александ...
CREATE INDEX … USING VODKA. VODKA CONNECTING INDEXES, Олег Бартунов, Александ...
Ontico
 
Ad

More from MongoDB (20)

MongoDB SoCal 2020: Migrate Anything* to MongoDB Atlas
MongoDB SoCal 2020: Migrate Anything* to MongoDB AtlasMongoDB SoCal 2020: Migrate Anything* to MongoDB Atlas
MongoDB SoCal 2020: Migrate Anything* to MongoDB Atlas
MongoDB
 
MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!
MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!
MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!
MongoDB
 
MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...
MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...
MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...
MongoDB
 
MongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDB
MongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDBMongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDB
MongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDB
MongoDB
 
MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...
MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...
MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...
MongoDB
 
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series Data
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series DataMongoDB SoCal 2020: Best Practices for Working with IoT and Time-series Data
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series Data
MongoDB
 
MongoDB SoCal 2020: MongoDB Atlas Jump Start
 MongoDB SoCal 2020: MongoDB Atlas Jump Start MongoDB SoCal 2020: MongoDB Atlas Jump Start
MongoDB SoCal 2020: MongoDB Atlas Jump Start
MongoDB
 
MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]
MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]
MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]
MongoDB
 
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2
MongoDB
 
MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...
MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...
MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...
MongoDB
 
MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!
MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!
MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!
MongoDB
 
MongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your Mindset
MongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your MindsetMongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your Mindset
MongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your Mindset
MongoDB
 
MongoDB .local San Francisco 2020: MongoDB Atlas Jumpstart
MongoDB .local San Francisco 2020: MongoDB Atlas JumpstartMongoDB .local San Francisco 2020: MongoDB Atlas Jumpstart
MongoDB .local San Francisco 2020: MongoDB Atlas Jumpstart
MongoDB
 
MongoDB .local San Francisco 2020: Aggregation Pipeline Power++
MongoDB .local San Francisco 2020: Aggregation Pipeline Power++MongoDB .local San Francisco 2020: Aggregation Pipeline Power++
MongoDB .local San Francisco 2020: Aggregation Pipeline Power++
MongoDB
 
MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...
MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...
MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...
MongoDB
 
MongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep Dive
MongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep DiveMongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep Dive
MongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep Dive
MongoDB
 
MongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & Golang
MongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & GolangMongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & Golang
MongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & Golang
MongoDB
 
MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...
MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...
MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...
MongoDB
 
MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...
MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...
MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...
MongoDB
 
MongoDB .local Paris 2020: Les bonnes pratiques pour sécuriser MongoDB
MongoDB .local Paris 2020: Les bonnes pratiques pour sécuriser MongoDBMongoDB .local Paris 2020: Les bonnes pratiques pour sécuriser MongoDB
MongoDB .local Paris 2020: Les bonnes pratiques pour sécuriser MongoDB
MongoDB
 
MongoDB SoCal 2020: Migrate Anything* to MongoDB Atlas
MongoDB SoCal 2020: Migrate Anything* to MongoDB AtlasMongoDB SoCal 2020: Migrate Anything* to MongoDB Atlas
MongoDB SoCal 2020: Migrate Anything* to MongoDB Atlas
MongoDB
 
MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!
MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!
MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!
MongoDB
 
MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...
MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...
MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...
MongoDB
 
MongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDB
MongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDBMongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDB
MongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDB
MongoDB
 
MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...
MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...
MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...
MongoDB
 
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series Data
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series DataMongoDB SoCal 2020: Best Practices for Working with IoT and Time-series Data
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series Data
MongoDB
 
MongoDB SoCal 2020: MongoDB Atlas Jump Start
 MongoDB SoCal 2020: MongoDB Atlas Jump Start MongoDB SoCal 2020: MongoDB Atlas Jump Start
MongoDB SoCal 2020: MongoDB Atlas Jump Start
MongoDB
 
MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]
MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]
MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]
MongoDB
 
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2
MongoDB
 
MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...
MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...
MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...
MongoDB
 
MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!
MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!
MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!
MongoDB
 
MongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your Mindset
MongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your MindsetMongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your Mindset
MongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your Mindset
MongoDB
 
MongoDB .local San Francisco 2020: MongoDB Atlas Jumpstart
MongoDB .local San Francisco 2020: MongoDB Atlas JumpstartMongoDB .local San Francisco 2020: MongoDB Atlas Jumpstart
MongoDB .local San Francisco 2020: MongoDB Atlas Jumpstart
MongoDB
 
MongoDB .local San Francisco 2020: Aggregation Pipeline Power++
MongoDB .local San Francisco 2020: Aggregation Pipeline Power++MongoDB .local San Francisco 2020: Aggregation Pipeline Power++
MongoDB .local San Francisco 2020: Aggregation Pipeline Power++
MongoDB
 
MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...
MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...
MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...
MongoDB
 
MongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep Dive
MongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep DiveMongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep Dive
MongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep Dive
MongoDB
 
MongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & Golang
MongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & GolangMongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & Golang
MongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & Golang
MongoDB
 
MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...
MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...
MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...
MongoDB
 
MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...
MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...
MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...
MongoDB
 
MongoDB .local Paris 2020: Les bonnes pratiques pour sécuriser MongoDB
MongoDB .local Paris 2020: Les bonnes pratiques pour sécuriser MongoDBMongoDB .local Paris 2020: Les bonnes pratiques pour sécuriser MongoDB
MongoDB .local Paris 2020: Les bonnes pratiques pour sécuriser MongoDB
MongoDB
 
Ad

Recently uploaded (20)

Limecraft Webinar - 2025.3 release, featuring Content Delivery, Graphic Conte...
Limecraft Webinar - 2025.3 release, featuring Content Delivery, Graphic Conte...Limecraft Webinar - 2025.3 release, featuring Content Delivery, Graphic Conte...
Limecraft Webinar - 2025.3 release, featuring Content Delivery, Graphic Conte...
Maarten Verwaest
 
Bepents tech services - a premier cybersecurity consulting firm
Bepents tech services - a premier cybersecurity consulting firmBepents tech services - a premier cybersecurity consulting firm
Bepents tech services - a premier cybersecurity consulting firm
Benard76
 
Kit-Works Team Study_팀스터디_김한솔_nuqs_20250509.pdf
Kit-Works Team Study_팀스터디_김한솔_nuqs_20250509.pdfKit-Works Team Study_팀스터디_김한솔_nuqs_20250509.pdf
Kit-Works Team Study_팀스터디_김한솔_nuqs_20250509.pdf
Wonjun Hwang
 
Top 5 Benefits of Using Molybdenum Rods in Industrial Applications.pptx
Top 5 Benefits of Using Molybdenum Rods in Industrial Applications.pptxTop 5 Benefits of Using Molybdenum Rods in Industrial Applications.pptx
Top 5 Benefits of Using Molybdenum Rods in Industrial Applications.pptx
mkubeusa
 
Reimagine How You and Your Team Work with Microsoft 365 Copilot.pptx
Reimagine How You and Your Team Work with Microsoft 365 Copilot.pptxReimagine How You and Your Team Work with Microsoft 365 Copilot.pptx
Reimagine How You and Your Team Work with Microsoft 365 Copilot.pptx
John Moore
 
Smart Investments Leveraging Agentic AI for Real Estate Success.pptx
Smart Investments Leveraging Agentic AI for Real Estate Success.pptxSmart Investments Leveraging Agentic AI for Real Estate Success.pptx
Smart Investments Leveraging Agentic AI for Real Estate Success.pptx
Seasia Infotech
 
How to Install & Activate ListGrabber - eGrabber
How to Install & Activate ListGrabber - eGrabberHow to Install & Activate ListGrabber - eGrabber
How to Install & Activate ListGrabber - eGrabber
eGrabber
 
Cybersecurity Threat Vectors and Mitigation
Cybersecurity Threat Vectors and MitigationCybersecurity Threat Vectors and Mitigation
Cybersecurity Threat Vectors and Mitigation
VICTOR MAESTRE RAMIREZ
 
Could Virtual Threads cast away the usage of Kotlin Coroutines - DevoxxUK2025
Could Virtual Threads cast away the usage of Kotlin Coroutines - DevoxxUK2025Could Virtual Threads cast away the usage of Kotlin Coroutines - DevoxxUK2025
Could Virtual Threads cast away the usage of Kotlin Coroutines - DevoxxUK2025
João Esperancinha
 
AI 3-in-1: Agents, RAG, and Local Models - Brent Laster
AI 3-in-1: Agents, RAG, and Local Models - Brent LasterAI 3-in-1: Agents, RAG, and Local Models - Brent Laster
AI 3-in-1: Agents, RAG, and Local Models - Brent Laster
All Things Open
 
AI x Accessibility UXPA by Stew Smith and Olivier Vroom
AI x Accessibility UXPA by Stew Smith and Olivier VroomAI x Accessibility UXPA by Stew Smith and Olivier Vroom
AI x Accessibility UXPA by Stew Smith and Olivier Vroom
UXPA Boston
 
May Patch Tuesday
May Patch TuesdayMay Patch Tuesday
May Patch Tuesday
Ivanti
 
Top-AI-Based-Tools-for-Game-Developers (1).pptx
Top-AI-Based-Tools-for-Game-Developers (1).pptxTop-AI-Based-Tools-for-Game-Developers (1).pptx
Top-AI-Based-Tools-for-Game-Developers (1).pptx
BR Softech
 
Artificial_Intelligence_in_Everyday_Life.pptx
Artificial_Intelligence_in_Everyday_Life.pptxArtificial_Intelligence_in_Everyday_Life.pptx
Artificial_Intelligence_in_Everyday_Life.pptx
03ANMOLCHAURASIYA
 
machines-for-woodworking-shops-en-compressed.pdf
machines-for-woodworking-shops-en-compressed.pdfmachines-for-woodworking-shops-en-compressed.pdf
machines-for-woodworking-shops-en-compressed.pdf
AmirStern2
 
IT488 Wireless Sensor Networks_Information Technology
IT488 Wireless Sensor Networks_Information TechnologyIT488 Wireless Sensor Networks_Information Technology
IT488 Wireless Sensor Networks_Information Technology
SHEHABALYAMANI
 
Integrating FME with Python: Tips, Demos, and Best Practices for Powerful Aut...
Integrating FME with Python: Tips, Demos, and Best Practices for Powerful Aut...Integrating FME with Python: Tips, Demos, and Best Practices for Powerful Aut...
Integrating FME with Python: Tips, Demos, and Best Practices for Powerful Aut...
Safe Software
 
Zilliz Cloud Monthly Technical Review: May 2025
Zilliz Cloud Monthly Technical Review: May 2025Zilliz Cloud Monthly Technical Review: May 2025
Zilliz Cloud Monthly Technical Review: May 2025
Zilliz
 
Dark Dynamism: drones, dark factories and deurbanization
Dark Dynamism: drones, dark factories and deurbanizationDark Dynamism: drones, dark factories and deurbanization
Dark Dynamism: drones, dark factories and deurbanization
Jakub Šimek
 
Developing System Infrastructure Design Plan.pptx
Developing System Infrastructure Design Plan.pptxDeveloping System Infrastructure Design Plan.pptx
Developing System Infrastructure Design Plan.pptx
wondimagegndesta
 
Limecraft Webinar - 2025.3 release, featuring Content Delivery, Graphic Conte...
Limecraft Webinar - 2025.3 release, featuring Content Delivery, Graphic Conte...Limecraft Webinar - 2025.3 release, featuring Content Delivery, Graphic Conte...
Limecraft Webinar - 2025.3 release, featuring Content Delivery, Graphic Conte...
Maarten Verwaest
 
Bepents tech services - a premier cybersecurity consulting firm
Bepents tech services - a premier cybersecurity consulting firmBepents tech services - a premier cybersecurity consulting firm
Bepents tech services - a premier cybersecurity consulting firm
Benard76
 
Kit-Works Team Study_팀스터디_김한솔_nuqs_20250509.pdf
Kit-Works Team Study_팀스터디_김한솔_nuqs_20250509.pdfKit-Works Team Study_팀스터디_김한솔_nuqs_20250509.pdf
Kit-Works Team Study_팀스터디_김한솔_nuqs_20250509.pdf
Wonjun Hwang
 
Top 5 Benefits of Using Molybdenum Rods in Industrial Applications.pptx
Top 5 Benefits of Using Molybdenum Rods in Industrial Applications.pptxTop 5 Benefits of Using Molybdenum Rods in Industrial Applications.pptx
Top 5 Benefits of Using Molybdenum Rods in Industrial Applications.pptx
mkubeusa
 
Reimagine How You and Your Team Work with Microsoft 365 Copilot.pptx
Reimagine How You and Your Team Work with Microsoft 365 Copilot.pptxReimagine How You and Your Team Work with Microsoft 365 Copilot.pptx
Reimagine How You and Your Team Work with Microsoft 365 Copilot.pptx
John Moore
 
Smart Investments Leveraging Agentic AI for Real Estate Success.pptx
Smart Investments Leveraging Agentic AI for Real Estate Success.pptxSmart Investments Leveraging Agentic AI for Real Estate Success.pptx
Smart Investments Leveraging Agentic AI for Real Estate Success.pptx
Seasia Infotech
 
How to Install & Activate ListGrabber - eGrabber
How to Install & Activate ListGrabber - eGrabberHow to Install & Activate ListGrabber - eGrabber
How to Install & Activate ListGrabber - eGrabber
eGrabber
 
Cybersecurity Threat Vectors and Mitigation
Cybersecurity Threat Vectors and MitigationCybersecurity Threat Vectors and Mitigation
Cybersecurity Threat Vectors and Mitigation
VICTOR MAESTRE RAMIREZ
 
Could Virtual Threads cast away the usage of Kotlin Coroutines - DevoxxUK2025
Could Virtual Threads cast away the usage of Kotlin Coroutines - DevoxxUK2025Could Virtual Threads cast away the usage of Kotlin Coroutines - DevoxxUK2025
Could Virtual Threads cast away the usage of Kotlin Coroutines - DevoxxUK2025
João Esperancinha
 
AI 3-in-1: Agents, RAG, and Local Models - Brent Laster
AI 3-in-1: Agents, RAG, and Local Models - Brent LasterAI 3-in-1: Agents, RAG, and Local Models - Brent Laster
AI 3-in-1: Agents, RAG, and Local Models - Brent Laster
All Things Open
 
AI x Accessibility UXPA by Stew Smith and Olivier Vroom
AI x Accessibility UXPA by Stew Smith and Olivier VroomAI x Accessibility UXPA by Stew Smith and Olivier Vroom
AI x Accessibility UXPA by Stew Smith and Olivier Vroom
UXPA Boston
 
May Patch Tuesday
May Patch TuesdayMay Patch Tuesday
May Patch Tuesday
Ivanti
 
Top-AI-Based-Tools-for-Game-Developers (1).pptx
Top-AI-Based-Tools-for-Game-Developers (1).pptxTop-AI-Based-Tools-for-Game-Developers (1).pptx
Top-AI-Based-Tools-for-Game-Developers (1).pptx
BR Softech
 
Artificial_Intelligence_in_Everyday_Life.pptx
Artificial_Intelligence_in_Everyday_Life.pptxArtificial_Intelligence_in_Everyday_Life.pptx
Artificial_Intelligence_in_Everyday_Life.pptx
03ANMOLCHAURASIYA
 
machines-for-woodworking-shops-en-compressed.pdf
machines-for-woodworking-shops-en-compressed.pdfmachines-for-woodworking-shops-en-compressed.pdf
machines-for-woodworking-shops-en-compressed.pdf
AmirStern2
 
IT488 Wireless Sensor Networks_Information Technology
IT488 Wireless Sensor Networks_Information TechnologyIT488 Wireless Sensor Networks_Information Technology
IT488 Wireless Sensor Networks_Information Technology
SHEHABALYAMANI
 
Integrating FME with Python: Tips, Demos, and Best Practices for Powerful Aut...
Integrating FME with Python: Tips, Demos, and Best Practices for Powerful Aut...Integrating FME with Python: Tips, Demos, and Best Practices for Powerful Aut...
Integrating FME with Python: Tips, Demos, and Best Practices for Powerful Aut...
Safe Software
 
Zilliz Cloud Monthly Technical Review: May 2025
Zilliz Cloud Monthly Technical Review: May 2025Zilliz Cloud Monthly Technical Review: May 2025
Zilliz Cloud Monthly Technical Review: May 2025
Zilliz
 
Dark Dynamism: drones, dark factories and deurbanization
Dark Dynamism: drones, dark factories and deurbanizationDark Dynamism: drones, dark factories and deurbanization
Dark Dynamism: drones, dark factories and deurbanization
Jakub Šimek
 
Developing System Infrastructure Design Plan.pptx
Developing System Infrastructure Design Plan.pptxDeveloping System Infrastructure Design Plan.pptx
Developing System Infrastructure Design Plan.pptx
wondimagegndesta
 

MongoDB .local Toronto 2019: Tips and Tricks for Effective Indexing

  • 1. @ #MDBlocal Tips and Tricks for Effective Indexing Alex Bevilacqua Technical Services Engineer alexbevi TORONTO
  • 2. #MDBLocal • Your data should be accessible … quickly • When applied properly, indexes can improve performance as if by … WHY DOES THIS MATTER?
  • 3. #MDBLocal • Working hard can suck and we all want to do less when possible • This goes for our database as well • The less index keys scanned or documents fetched from disk or cache … the better! • Let’s learn how to improve our indexes, TOGETHER! WHY DOES THIS MATTER?
  • 4. #MDBLocal IT’S ME … MARIO! ALEX! • Application Developer • Development Lead • System Architect • Technical Services Engineer • Author • MongoDB Fanboy
  • 6. #MDBLocal Alex Bevilacqua Technical Services Engineer Toronto I think I found some slow queries that may be missing indexes. What should I know?
  • 8. #MDBLocal Roadmap E-S-R Overview Guidelines: • Eà R • Eà S • Sà R E-S-R Considerations Operator Type Checks Consecutive Index Keys Exceptions?
  • 9. #MDBLocal Roadmap E-S-R Overview Guidelines: • Eà R • Eà S • Sà R E-S-R Considerations Operator Type Checks Consecutive Index Keys Exceptions?
  • 10. #MDBLocal E-S-R The ordering of index keys in a compound index is critically important.
  • 11. #MDBLocal E-S-R The ordering of index keys in a compound index is critically important. WHY?
  • 12. #MDBLocal E-S-R The ordering of index keys in a compound index is critically important. E-S-R provides guidance that is useful in most cases: • Equality first • Sort next • Range last
  • 13. #MDBLocal E-S-R The ordering of index keys in a compound index is critically important. E-S-R provides guidance that is useful in most cases: • Equality first • Sort next • Range last Nope, I don’t get it. Equality? Range? ….. Explain!
  • 14. #MDBLocal Definitions Equality Fields An exact match on a single value. For example: • {x:123} • {x:{$eq:123}} • {"x.y":123} Bounds: "[123.0, 123.0]"
  • 15. #MDBLocal Definitions Equality Fields Sort The (entire) requested sort. .sort({a:1, b:-1}) Bounds: "[MinKey, MaxKey]", "[MinKey, MaxKey]" An exact match on a single value. For example: • {x:123} • {x:{$eq:123}} • {"x.y":123} Bounds: "[123.0, 123.0]"
  • 16. #MDBLocal Definitions Equality Fields Sort Range Predicates Any predicates that are not exact matches. Some operators include: • {z:{$gt:9000}} • {z:{$lte:1000}} Bounds: "[9000.0, inf.0]", "[-inf.0, 1000.0]" The (entire) requested sort. .sort({a:1, b:-1}) Bounds: "[MinKey, MaxKey]", "[MinKey, MaxKey]" An exact match on a single value. For example: • {x:123} • {x:{$eq:123}} • {"x.y":123} Bounds: "[123.0, 123.0]"
  • 17. #MDBLocal Roadmap E-S-R Overview Guidelines: • Eà R • Eà S • Sà R E-S-R Considerations Operator Type Checks Consecutive Index Keys Exceptions?
  • 18. #MDBLocal Equality Equality keys are placed first in any order If present in the query shape, equality fields should always form the prefix for the index.
  • 19. #MDBLocal Equality Equality keys are placed first in any order If present in the query shape, equality fields should always form the prefix for the index. WHY?
  • 20. #MDBLocal Equality Equality keys are placed first in any order If present in the query shape, equality fields should always form the prefix for the index. db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )
  • 21. #MDBLocal Equality db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) If present in the query shape, equality fields should always form the prefix for the index. Equality keys are placed first in any order
  • 22. #MDBLocal db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) Equality {gamertag: "Ace", score: 100} {gamertag: "Ace", score: 99,999} {gamertag: "Bob", score: 15,000} {gamertag: "Bob", score: 50,000}
  • 23. #MDBLocal db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) {} {} {}{} 100 15,000 50,000 99,999 Ace Bob Bob Ace {gamertag: "Ace", score: 100} {gamertag: "Ace", score: 99,999} {gamertag: "Bob", score: 15,000} {gamertag: "Bob", score: 50,000} Equality
  • 24. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Bob Ace db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) {} {} {} {} Equality "indexBounds" : { "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "["Ace", "Ace"]" ] } db.games.createIndex({score:1, gamertag:1})
  • 25. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Bob Ace db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) {} {} {} {} Equality "indexBounds" : { "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "["Ace", "Ace"]" ] } gamertag db.games.createIndex({score:1, gamertag:1})
  • 26. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Bob Ace db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) {} {} {} {} Equality "indexBounds" : { "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "["Ace", "Ace"]" ] } gamertag score db.games.createIndex({score:1, gamertag:1})
  • 27. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Bob Ace db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) {} {} {} {} Equality "indexBounds" : { "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "["Ace", "Ace"]" ] } gamertag score db.games.createIndex({score:1, gamertag:1})
  • 28. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Bob Ace db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) {} {} {} {} Equality "indexBounds" : { "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "["Ace", "Ace"]" ] } gamertag score db.games.createIndex({score:1, gamertag:1})
  • 29. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Bob Ace db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) {} {} {} {} Equality "indexBounds" : { "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "["Ace", "Ace"]" ] } gamertag score db.games.createIndex({score:1, gamertag:1})
  • 30. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Bob Ace db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) {} {} {} {} Equality "indexBounds" : { "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "["Ace", "Ace"]" ] } gamertag score db.games.createIndex({score:1, gamertag:1})
  • 31. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Bob Ace db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) {} {} {} {} Equality "indexBounds" : { "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "["Ace", "Ace"]" ] } gamertag score db.games.createIndex({score:1, gamertag:1})
  • 32. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Bob Ace db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) {} {} {} {} Equality "indexBounds" : { "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "["Ace", "Ace"]" ] } gamertag score db.games.createIndex({score:1, gamertag:1})
  • 33. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Bob Ace db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) {} {} {} {} Equality "indexBounds" : { "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "["Ace", "Ace"]" ] } gamertag score db.games.createIndex({score:1, gamertag:1})
  • 34. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Bob Ace db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) {} {} {} {} Equality
  • 35. #MDBLocal Ace Bob Bob Ace db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) 100 99,999 15,000 50,000 {} {} {} {} Equality
  • 36. #MDBLocal 100 Ace Bob 99,999 15,000 50,000 db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) {} {} {} {} Equality "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "(9000.0, inf.0]" ], } db.games.createIndex({gamertag:1, score:1})
  • 37. #MDBLocal 100 Ace Bob 99,999 15,000 50,000 db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) {} {} {} {} Equality "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "(9000.0, inf.0]" ], } gamertag db.games.createIndex({gamertag:1, score:1})
  • 38. #MDBLocal 100 Ace Bob 99,999 15,000 50,000 db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) {} {} {} {} Equality "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "(9000.0, inf.0]" ], } gamertag score db.games.createIndex({gamertag:1, score:1})
  • 39. #MDBLocal 100 Ace Bob 99,999 15,000 50,000 db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) {} {} {} {} Equality "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "(9000.0, inf.0]" ], } gamertag score db.games.createIndex({gamertag:1, score:1})
  • 40. #MDBLocal 100 Ace Bob 99,999 15,000 50,000 db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) {} {} {} {} Equality "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "(9000.0, inf.0]" ], } gamertag score db.games.createIndex({gamertag:1, score:1})
  • 41. #MDBLocal 100 Ace Bob 99,999 15,000 50,000 db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) {} {} {} {} Equality "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "(9000.0, inf.0]" ], } gamertag score db.games.createIndex({gamertag:1, score:1})
  • 42. #MDBLocal db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) R E R E Equality before Range
  • 43. #MDBLocal Roadmap E-S-R Overview Guidelines: • Eà R • Eà S • Sà R E-S-R Considerations Operator Type Checks Consecutive Index Keys Exceptions?
  • 44. #MDBLocal Sort fields are placed next Placing sort predicates after sequential equality keys allow for the index to: Provide a non-blocking sort. Minimize the amount of scanning required. db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) Sort
  • 45. #MDBLocal db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) Sort 100 15,000 50,000 99,999 Ace Bob Bob Acegamertag score db.games.createIndex({score:1, gamertag:1})
  • 46. #MDBLocal db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) Sort 100 15,000 50,000 99,999 Ace Bob Bob Ace {} {} {} {} gamertag score db.games.createIndex({score:1, gamertag:1})
  • 47. #MDBLocal db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) Sort 100 15,000 50,000 99,999 Ace Bob Bob Ace {} {} {} {} gamertag score db.games.createIndex({score:1, gamertag:1})
  • 48. #MDBLocal db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) Sort 100 15,000 50,000 99,999 Ace Bob Bob Ace {1} {} {} {2} gamertag score db.games.createIndex({score:1, gamertag:1})
  • 49. #MDBLocal db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) Sort 100 15,000 50,000 99,999 Ace Bob Bob Ace {1} {} {} {2} gamertag score "indexBounds" : { "score" : [ "[MinKey, MaxKey]" ], "gamertag" : [ "["Ace", "Ace"]" ] } db.games.createIndex({score:1, gamertag:1})
  • 50. #MDBLocal db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) Sort 100 15,000 50,000 99,999 Ace Bob Bob Ace {1} {} {} {2} gamertag score "indexBounds" : { "score" : [ "[MinKey, MaxKey]" ], "gamertag" : [ "["Ace", "Ace"]" ] } db.games.createIndex({score:1, gamertag:1})
  • 51. #MDBLocal db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) Sort 100 15,000 50,000 99,999 Ace Bob Bob Ace {1} {} {} {2} gamertag score "indexBounds" : { "score" : [ "[MinKey, MaxKey]" ], "gamertag" : [ "["Ace", "Ace"]” ] } db.games.createIndex({score:1, gamertag:1})
  • 52. #MDBLocal db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) Sort 100 15,000 50,000 99,999 Ace Bob Bob Ace {1} {} {} {2} gamertag score "indexBounds" : { "score" : [ "[MinKey, MaxKey]" ], "gamertag" : [ "["Ace", "Ace"]” ] } db.games.createIndex({score:1, gamertag:1})
  • 53. #MDBLocal db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) Sort 100 15,000 50,000 99,999 Ace Bob Bob Ace {1} {} {} {2} gamertag score "indexBounds" : { "score" : [ "[MinKey, MaxKey]" ], "gamertag" : [ "["Ace", "Ace"]” ] } db.games.createIndex({score:1, gamertag:1})
  • 54. #MDBLocal Sort 100 15,000 50,000 99,999 Ace Bob Bob Ace {1} {} {} {2} db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) gamertag score "indexBounds" : { "score" : [ "[MinKey, MaxKey]" ], "gamertag" : [ "["Ace", "Ace"]” ] } db.games.createIndex({score:1, gamertag:1})
  • 55. #MDBLocal Sort 100 15,000 50,000 99,999 Ace Bob Bob Ace {1} {} {} {2} db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) gamertag score "indexBounds" : { "score" : [ "[MinKey, MaxKey]" ], "gamertag" : [ "["Ace", "Ace"]” ] } db.games.createIndex({score:1, gamertag:1})
  • 56. #MDBLocal Sort 100 15,000 50,000 99,999 Ace Bob Bob Ace {1} {} {} {2} db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) gamertag score "indexBounds" : { "score" : [ "[MinKey, MaxKey]" ], "gamertag" : [ "["Ace", "Ace"]” ] } db.games.createIndex({score:1, gamertag:1})
  • 57. #MDBLocal Sort 100 15,000 50,000 99,999 Ace Bob Bob Ace {1} {} {} {2} db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) gamertag score "indexBounds" : { "score" : [ "[MinKey, MaxKey]" ], "gamertag" : [ "["Ace", "Ace"]” ] } db.games.createIndex({score:1, gamertag:1})
  • 58. #MDBLocal Sort 100 15,000 50,000 99,999 Ace Bob Bob Ace {1} {} {} {2} db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) gamertag score "indexBounds" : { "score" : [ "[MinKey, MaxKey]" ], "gamertag" : [ "["Ace", "Ace"]” ] } db.games.createIndex({score:1, gamertag:1})
  • 59. #MDBLocal Sort 100 15,000 50,000 99,999 Ace Bob Bob Ace {1} {} {} {2} db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) gamertag score "indexBounds" : { "score" : [ "[MinKey, MaxKey]" ], "gamertag" : [ "["Ace", "Ace"]” ] } db.games.createIndex({score:1, gamertag:1})
  • 60. #MDBLocal Sort 100 15,000 50,000 99,999 Ace Bob Bob Ace {1} {} {} {2} db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) gamertag score "indexBounds" : { "score" : [ "[MinKey, MaxKey]" ], "gamertag" : [ "["Ace", "Ace"]” ] } db.games.createIndex({score:1, gamertag:1})
  • 61. #MDBLocal Sort 100 15,000 50,000 99,999 Ace Bob Bob Ace {1} {} {} {2} db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
  • 62. #MDBLocal Sort Ace Bob Bob Ace 100 99,999 15,000 50,000 {1} {2} {} {} db.games.find( {gamertag: "Ace"} ).sort( {score: 1} )
  • 63. #MDBLocal Sort 100 Ace Bob 99,999 15,000 50,000 {}{1} {2} {} db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) gamertag score "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], ”score" : [ "[MinKey, MaxKey]" ] } db.games.createIndex({gamertag:1, score:1})
  • 64. #MDBLocal Sort 100 Ace Bob 99,999 15,000 50,000 {}{1} {2} {} db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) gamertag score "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], ”score" : [ "[MinKey, MaxKey]" ] } db.games.createIndex({gamertag:1, score:1})
  • 65. #MDBLocal Sort 100 Ace Bob 99,999 15,000 50,000 {}{1} {2} {} db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) gamertag score "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], ”score" : [ "[MinKey, MaxKey]" ] } db.games.createIndex({gamertag:1, score:1})
  • 66. #MDBLocal Sort 100 Ace Bob 99,999 15,000 50,000 {}{1} {2} {} db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) gamertag score "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], ”score" : [ "[MinKey, MaxKey]" ] } db.games.createIndex({gamertag:1, score:1})
  • 67. #MDBLocal Sort 100 Ace Bob 99,999 15,000 50,000 {}{1} {2} {} db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) gamertag score "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], ”score" : [ "[MinKey, MaxKey]" ] } db.games.createIndex({gamertag:1, score:1})
  • 68. #MDBLocal Sort 100 Ace Bob 99,999 15,000 50,000 {}{1} {2} {} db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) gamertag score "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], ”score" : [ "[MinKey, MaxKey]" ] } db.games.createIndex({gamertag:1, score:1})
  • 69. #MDBLocal Sort 100 Ace Bob 99,999 15,000 50,000 {}{1} {2} {} db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) gamertag score "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], ”score" : [ "[MinKey, MaxKey]" ] } db.games.createIndex({gamertag:1, score:1})
  • 70. #MDBLocal Sort after Equality S E S E db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) Don’t do this, it may require a full index scan
  • 71. #MDBLocal Roadmap E-S-R Overview Guidelines: • Eà R • Eà S • Sà R E-S-R Considerations Operator Type Checks Consecutive Index Keys Exceptions?
  • 72. #MDBLocal Range fields are usually last This allows them to: Still participate in filtering the data But does not force a blocking sort. db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) Range
  • 73. #MDBLocal db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) R E R E Range after Equality
  • 74. #MDBLocal db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) R E R E Range after Equality Should range come after sort too?
  • 75. #MDBLocal R E R E Range after Equality db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Should range come after sort too?
  • 76. #MDBLocal R E R E Range db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})
  • 77. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Bob Ace * db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range gamertag score db.games.createIndex({ …, score:1, gamertag:1})
  • 78. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Bob Ace * db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range gamertag score db.games.createIndex({ …, score:1, gamertag:1})
  • 79. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Cali Ace * db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range gamertag score db.games.createIndex({ …, score:1, gamertag:1})
  • 80. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Cali Ace * db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range {} {} {} {}{1}{2} {3} gamertag score db.games.createIndex({ …, score:1, gamertag:1})
  • 81. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Cali Ace * {} {2} {3} {1} db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range gamertag score "indexBounds" : { *, "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "[MinKey, MaxKey]" ] } db.games.createIndex({ …, score:1, gamertag:1})
  • 82. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Cali Ace * {} {2} {3} {1} db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range gamertag score "indexBounds" : { *, "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "[MinKey, MaxKey]" ] } db.games.createIndex({ …, score:1, gamertag:1})
  • 83. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Cali Ace * {} {2} {3} {1} db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range gamertag score "indexBounds" : { *, "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "[MinKey, MaxKey]" ] } db.games.createIndex({ …, score:1, gamertag:1})
  • 84. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Cali Ace * {} {2} {3} {1} db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range gamertag score "indexBounds" : { *, "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "[MinKey, MaxKey]" ] } db.games.createIndex({ …, score:1, gamertag:1})
  • 85. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Cali Ace * {} {2} {3} {1} db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range gamertag score "indexBounds" : { *, "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "[MinKey, MaxKey]" ] } db.games.createIndex({ …, score:1, gamertag:1})
  • 86. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Cali Ace * {} {2} {3} {1} db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range gamertag score "indexBounds" : { *, "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "[MinKey, MaxKey]" ] } db.games.createIndex({ …, score:1, gamertag:1})
  • 87. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Cali Ace * {} {2} {3} {1} db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range gamertag score "indexBounds" : { *, "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "[MinKey, MaxKey]" ] } db.games.createIndex({ …, score:1, gamertag:1})
  • 88. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Cali Ace * {} {2} {3} {1} db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range gamertag score "indexBounds" : { *, "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "[MinKey, MaxKey]" ] } db.games.createIndex({ …, score:1, gamertag:1})
  • 89. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Cali Ace * {} {2} {3} {1} db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range gamertag score "indexBounds" : { *, "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "[MinKey, MaxKey]" ] } db.games.createIndex({ …, score:1, gamertag:1})
  • 90. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Cali Ace * {} {2} {3} {1} db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range gamertag score "indexBounds" : { *, "score" : [ "(9000.0, inf.0]" ], "gamertag" : [ "[MinKey, MaxKey]" ] } db.games.createIndex({ …, score:1, gamertag:1})
  • 91. #MDBLocal {2} {3} {1} db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range Blocking SortBlocking Sort BS
  • 92. #MDBLocal {2}{3}{1} db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range BS
  • 93. #MDBLocal 100 15,000 50,000 99,999 Ace Bob Cali Ace * {} {2} {3} {1} db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range
  • 94. #MDBLocal db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range * Ace Bob Cali Ace 100 15,000 50,00099,999 {} {1} {2} {3}
  • 95. #MDBLocal * 100 15,000 50,00099,999 Ace Bob Cali db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range {} {1} {3} score gamertag "indexBounds" : { *, "gamertag" : [ "[MinKey, MaxKey]" ] "score" : [ "(9000.0, inf.0]" ] } db.games.createIndex({ …, gamertag:1, score:1}) {2}
  • 96. #MDBLocal * 100 15,000 50,00099,999 Ace Bob Cali db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range {} {1} {3} score gamertag "indexBounds" : { *, "gamertag" : [ "[MinKey, MaxKey]" ] "score" : [ "(9000.0, inf.0]" ] } db.games.createIndex({ …, gamertag:1, score:1}) {2}
  • 97. #MDBLocal * 100 15,000 50,00099,999 Ace Bob Cali db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range {} {1} {3} score gamertag "indexBounds" : { *, "gamertag" : [ "[MinKey, MaxKey]" ] "score" : [ "(9000.0, inf.0]" ] } db.games.createIndex({ …, gamertag:1, score:1}) {2}
  • 98. #MDBLocal * 100 15,000 50,00099,999 Ace Bob Cali db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range {} {1} {3} score gamertag "indexBounds" : { *, "gamertag" : [ "[MinKey, MaxKey]" ] "score" : [ "(9000.0, inf.0]" ] } db.games.createIndex({ …, gamertag:1, score:1}) {2}
  • 99. #MDBLocal * 100 15,000 50,00099,999 Ace Bob Cali db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range {} {1} {3} score gamertag "indexBounds" : { *, "gamertag" : [ "[MinKey, MaxKey]" ] "score" : [ "(9000.0, inf.0]" ] } db.games.createIndex({ …, gamertag:1, score:1}) {2}
  • 100. #MDBLocal * 100 15,000 50,00099,999 Ace Bob Cali db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range {} {1} {3} score gamertag "indexBounds" : { *, "gamertag" : [ "[MinKey, MaxKey]" ] "score" : [ "(9000.0, inf.0]" ] } db.games.createIndex({ …, gamertag:1, score:1}) {2}
  • 101. #MDBLocal * 100 15,000 50,00099,999 Ace Bob Cali db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range {} {1} {3} score gamertag "indexBounds" : { *, "gamertag" : [ "[MinKey, MaxKey]" ] "score" : [ "(9000.0, inf.0]" ] } db.games.createIndex({ …, gamertag:1, score:1}) {2}
  • 102. #MDBLocal * 100 15,000 50,00099,999 Ace Bob Cali db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range {} {1} {3} score gamertag "indexBounds" : { *, "gamertag" : [ "[MinKey, MaxKey]" ] "score" : [ "(9000.0, inf.0]" ] } db.games.createIndex({ …, gamertag:1, score:1}) {2}
  • 103. #MDBLocal * 100 15,000 50,00099,999 Ace Bob Cali db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range {} {1} {3} score gamertag "indexBounds" : { *, "gamertag" : [ "[MinKey, MaxKey]" ] "score" : [ "(9000.0, inf.0]" ] } db.games.createIndex({ …, gamertag:1, score:1}) {2}
  • 104. #MDBLocal * 100 15,000 50,00099,999 Ace Bob Cali db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range {} {1} {3} score gamertag "indexBounds" : { *, "gamertag" : [ "[MinKey, MaxKey]" ] "score" : [ "(9000.0, inf.0]" ] } db.games.createIndex({ …, gamertag:1, score:1}) {2}
  • 105. #MDBLocal * 100 15,000 50,00099,999 Ace Bob Cali db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range {} {1} {3} score gamertag "indexBounds" : { *, "gamertag" : [ "[MinKey, MaxKey]" ] "score" : [ "(9000.0, inf.0]" ] } db.games.createIndex({ …, gamertag:1, score:1}) {2}
  • 106. #MDBLocal BS R S R S db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range after Sort
  • 107. #MDBLocal Roadmap E-S-R Overview Guidelines: • Eà R • Eà S • Sà R E-S-R Considerations Operator Type Checks Consecutive Index Keys Exceptions?
  • 108. #MDBLocal Operator Type Check Some operators are simple $eq: Equality $gte: Range Others are trickier
  • 109. #MDBLocal Operator Type Check - Inequality Inequality Operators: E, S, or R? • $ne:123 • $nin:[1,2] Range!
  • 110. #MDBLocal Operator Type Check - Inequality Inequality Operators: E, S, or R? • $ne:123 • $nin:[1,2] Range! But … how do you know?
  • 111. #MDBLocal Operator Type Check - Inequality Inequality Operators: E, S, or R? • $ne:123 • $nin:[1,2] Range! "indexBounds" : { "x" : [ "[MinKey, 123.0)", "(123.0, MaxKey]" ] }
  • 112. #MDBLocal Operator Type Check - Inequality Range! "indexBounds" : { "x" : [ "[MinKey, 123.0)", "(123.0, MaxKey]" ] } 50 123 999
  • 113. #MDBLocal Operator Type Check - Inequality Range! "indexBounds" : { "x" : [ "[MinKey, 123.0)", "(123.0, MaxKey]" ] } 50 123 999
  • 114. #MDBLocal Operator Type Check - Inequality Range! "indexBounds" : { "x" : [ "[MinKey, 123.0)", "(123.0, MaxKey]" ] } 50 123 999
  • 115. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range!
  • 116. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range!
  • 117. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range! planecar racecar
  • 118. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range! planecar racecar
  • 119. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range! planecar racecar
  • 120. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range! p???ecar racecar
  • 121. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range! p???ecar racecar
  • 122. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range!
  • 123. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range! raincarry
  • 124. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range! raincarry
  • 125. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range! raincarry Carpool
  • 126. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range! raincarry Carpool
  • 127. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range! raincarry Carpool
  • 128. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range! raincarry Carpoo l Woah Woah WOAH …. Since the regex is left anchored, can’t we skip the middle tree?
  • 129. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range! raincarry Carpoo l Woah Woah WOAH …. Since the regex is left anchored, can’t we skip the middle tree?
  • 130. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range! cArrycarry Carpoo l Woah Woah WOAH …. Since the regex is left anchored, can’t we skip the middle tree?
  • 131. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range! cArrycarry Carpoo l Woah Woah WOAH …. Since the regex is left anchored, can’t we skip the middle tree?
  • 132. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range! cArrycarry Carpoo l
  • 133. #MDBLocal Operator Type Check - $in $in filters: E, S, or R? • {field:{$in:[1,3]}} … it depends with respect to key ordering Alone: a series of Equality matches Combined: possibly a Range
  • 134. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}})
  • 135. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}) "indexBounds" : { "field" : [ "[1.0, 1.0]", "[3.0, 3.0]" ] } ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 136. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}) "indexBounds" : { "field" : [ "[1.0, 1.0]", "[3.0, 3.0]" ] } ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 137. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}) "indexBounds" : { "field" : [ "[1.0, 1.0]", "[3.0, 3.0]" ] } ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 138. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}) "indexBounds" : { "field" : [ "[1.0, 1.0]", "[3.0, 3.0]" ] } ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 139. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}) "indexBounds" : { "field" : [ "[1.0, 1.0]", "[3.0, 3.0]" ] } ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 140. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}) "indexBounds" : { "field" : [ "[1.0, 1.0]", "[3.0, 3.0]" ] } ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 141. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}) .sort({sortField:1}) "indexBounds" : { "field" : [ "[1.0, 1.0]", "[3.0, 3.0]" ] } ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 142. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}) .sort({sortField:1}) "indexBounds" : { "field" : [ "[1.0, 1.0]", "[3.0, 3.0]" ], "sortField" : [ "[MinKey, MaxKey]" ] } ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 143. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}) .sort({sortField:1}) "indexBounds" : { "field" : [ "[1.0, 1.0]", "[3.0, 3.0]" ], "sortField" : [ "[MinKey, MaxKey]" ] } ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 144. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}) .sort({sortField:1}) "indexBounds" : { "field" : [ "[1.0, 1.0]", "[3.0, 3.0]" ], "sortField" : [ "[MinKey, MaxKey]" ] } ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 145. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}) .sort({sortField:1}) "indexBounds" : { "field" : [ "[1.0, 1.0]", "[3.0, 3.0]" ], "sortField" : [ "[MinKey, MaxKey]" ] } ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 146. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}) .sort({sortField:1}) "indexBounds" : { "field" : [ "[1.0, 1.0]", "[3.0, 3.0]" ], "sortField" : [ "[MinKey, MaxKey]" ] } ? 1 2 3 C G B F A D BS db.coll.createIndex({field:1, sortField:1})
  • 147. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}) .sort({sortField:1}) "indexBounds" : { "field" : [ "[1.0, 1.0]", "[3.0, 3.0]" ], "sortField" : [ "[MinKey, MaxKey]" ] } ? 1 2 3 C G B F A D BS db.coll.createIndex({field:1, sortField:1})
  • 148. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}) .sort({sortField:1}) ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 149. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}).sort({sortField:1}) ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 150. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}).sort({sortField:1}) "indexBounds" : { "field" : [ "[1.0, 1.0]", ], "sortField" : [ "[MinKey, MaxKey]" ] } ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 151. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}).sort({sortField:1}) "indexBounds" : { "field" : [ "[1.0, 1.0]", ], "sortField" : [ "[MinKey, MaxKey]" ] } ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 152. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}).sort({sortField:1}) "indexBounds" : { "field" : [ "[1.0, 1.0]", ], "sortField" : [ "[MinKey, MaxKey]" ] } ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 153. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}).sort({sortField:1}) "indexBounds" : { "field" : [ "[1.0, 1.0]", ], "sortField" : [ "[MinKey, MaxKey]" ] } ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 154. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}).sort({sortField:1}) "indexBounds" : { "field" : [ "[1.0, 1.0]", ], "sortField" : [ "[MinKey, MaxKey]" ] } ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 155. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}).sort({sortField:1}) "indexBounds" : { "field" : [ "[1.0, 1.0]", ], "sortField" : [ "[MinKey, MaxKey]" ] } "indexBounds" : { "field" : [ "[3.0, 3.0]", ], "sortField" : [ "[MinKey, MaxKey]" ] } ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 156. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}).sort({sortField:1}) "indexBounds" : { "field" : [ "[1.0, 1.0]", ], "sortField" : [ "[MinKey, MaxKey]" ] } "indexBounds" : { "field" : [ "[3.0, 3.0]", ], "sortField" : [ "[MinKey, MaxKey]" ] } ? 1 2 3 C G B F A D ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 157. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}).sort({sortField:1}) "indexBounds" : { "field" : [ "[1.0, 1.0]", ], "sortField" : [ "[MinKey, MaxKey]" ] } "indexBounds" : { "field" : [ "[3.0, 3.0]", ], "sortField" : [ "[MinKey, MaxKey]" ] } ? 1 2 3 C G B F A D ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 158. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}).sort({sortField:1}) "indexBounds" : { "field" : [ "[1.0, 1.0]", ], "sortField" : [ "[MinKey, MaxKey]" ] } "indexBounds" : { "field" : [ "[3.0, 3.0]", ], "sortField" : [ "[MinKey, MaxKey]" ] } ? 1 2 3 C G B F A D ? 1 2 3 C G B F A D db.coll.createIndex({field:1, sortField:1})
  • 159. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}}).sort({sortField:1}) "indexBounds" : { "field" : [ "[1.0, 1.0]", ], "sortField" : [ "[MinKey, MaxKey]" ] } "indexBounds" : { "field" : [ "[3.0, 3.0]", ], "sortField" : [ "[MinKey, MaxKey]" ] } ? 1 2 3 C G B F A D ? 1 2 3 C G B F A D {2} {4} {1} {3} Sort Merge db.coll.createIndex({field:1, sortField:1})
  • 161. #MDBLocal Roadmap E-S-R Overview Guidelines: • Eà R • Eà S • Sà R E-S-R Considerations Operator Type Checks Consecutive Index Keys Exceptions?
  • 162. #MDBLocal Consecutive Index Keys Given Indexes: {gamertag:1, date:1, game:1} {gamertag:1, game:1, date:1} Which one is “better”? It depends on the query shape(s)! Consider the query: .find({ gamertag:"Ace", game: "Halo” })
  • 164. #MDBLocal Consecutive Index Keys Ace Mario Halo 2016 2017 Mario Halo 2018 2019 .find({ gamertag:"Ace", game: "Halo” }) db.games.createIndex({gamertag:1, date:1, game:1})
  • 165. #MDBLocal Consecutive Index Keys Ace Mario Halo 2016 2017 Mario Halo 2018 2019 .find({ gamertag:"Ace", game: "Halo” }) {} {} {} {} db.games.createIndex({gamertag:1, date:1, game:1})
  • 166. #MDBLocal Consecutive Index Keys Ace Mario Halo 2016 2017 Mario Halo 2018 2019 .find({ gamertag:"Ace", game: "Halo” }) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[MinKey, MaxKey]" ], "game" : [ "["Halo", "Halo"]" ] } {} {} {} {} db.games.createIndex({gamertag:1, date:1, game:1})
  • 167. #MDBLocal Consecutive Index Keys Ace Mario Halo 2016 2017 Mario Halo 2018 2019 .find({ gamertag:"Ace", game: "Halo” }) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[MinKey, MaxKey]" ], "game" : [ "["Halo", "Halo"]" ] } {} {} {} {} db.games.createIndex({gamertag:1, date:1, game:1})
  • 168. #MDBLocal Consecutive Index Keys Ace Mario Halo 2016 2017 Mario Halo 2018 2019 .find({ gamertag:"Ace", game: "Halo” }) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[MinKey, MaxKey]" ], "game" : [ "["Halo", "Halo"]" ] } {} {} {} {} db.games.createIndex({gamertag:1, date:1, game:1})
  • 169. #MDBLocal Consecutive Index Keys Ace Mario Halo 2016 2017 Mario Halo 2018 2019 .find({ gamertag:"Ace", game: "Halo” }) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[MinKey, MaxKey]" ], "game" : [ "["Halo", "Halo"]" ] } {} {} {} {} db.games.createIndex({gamertag:1, date:1, game:1})
  • 170. #MDBLocal Consecutive Index Keys Ace Mario Halo 2016 2017 Mario Halo 2018 2019 .find({ gamertag:"Ace", game: "Halo” }) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[MinKey, MaxKey]" ], "game" : [ "["Halo", "Halo"]" ] } {} {} {} {} db.games.createIndex({gamertag:1, date:1, game:1})
  • 171. #MDBLocal Consecutive Index Keys Ace Mario Halo 2016 2017 Mario Halo 2018 2019 .find({ gamertag:"Ace", game: "Halo” }) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[MinKey, MaxKey]" ], "game" : [ "["Halo", "Halo"]" ] } {} {} {} {} db.games.createIndex({gamertag:1, date:1, game:1})
  • 172. #MDBLocal Consecutive Index Keys Ace Mario Halo 2016 2017 Mario Halo 2018 2019 .find({ gamertag:"Ace", game: "Halo” }) {} {} "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[MinKey, MaxKey]" ], "game" : [ "["Halo", "Halo"]" ] } {} {} db.games.createIndex({gamertag:1, date:1, game:1})
  • 173. #MDBLocal Consecutive Index Keys Ace Mario Halo 2016 2017 Mario Halo 2018 2019 .find({ gamertag:"Ace", game: "Halo” }) {} {} "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[MinKey, MaxKey]" ], "game" : [ "["Halo", "Halo"]" ] } {} {} db.games.createIndex({gamertag:1, date:1, game:1})
  • 174. #MDBLocal Consecutive Index Keys Ace Mario Halo 2016 2017 Mario Halo 2018 2019 .find({ gamertag:"Ace", game: "Halo” }) {} {} "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[MinKey, MaxKey]" ], "game" : [ "["Halo", "Halo"]" ] } {} {} db.games.createIndex({gamertag:1, date:1, game:1})
  • 175. #MDBLocal Consecutive Index Keys Ace Mario Halo 2016 2017 Mario Halo 2018 2019 .find({ gamertag:"Ace", game: "Halo” }) {} {} "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[MinKey, MaxKey]" ], "game" : [ "["Halo", "Halo"]" ] } {} {} db.games.createIndex({gamertag:1, date:1, game:1})
  • 176. #MDBLocal Consecutive Index Keys Ace Mario Halo 2016 2017 Mario Halo 2018 2019 .find({ gamertag:"Ace", game: "Halo” }) {} {} "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[MinKey, MaxKey]" ], "game" : [ "["Halo", "Halo"]" ] } {} {} db.games.createIndex({gamertag:1, date:1, game:1})
  • 177. #MDBLocal Consecutive Index Keys .find({ gamertag:"Ace", game: "Halo” }) {} {} {} {} "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[MinKey, MaxKey]" ], "game" : [ "["Halo", "Halo"]" ] } Halo Ace Mario Halo 2016 2017 Mario 2018 2019 "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "game" : [ "["Halo", "Halo"]" ] } db.games.createIndex({gamertag:1, game:1})
  • 178. #MDBLocal Ace 2016 2017Mario2018 2019Halo Consecutive Index Keys .find({ gamertag:"Ace", game: "Halo” }) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "game" : [ "["Halo", "Halo"]" ] } "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "game" : [ "["Halo", "Halo"]" ], "date" : [ "[MinKey, MaxKey]" ] } "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "game" : [ "["Halo", "Halo"]" ] } {}{} {}{} db.games.createIndex({gamertag:1, game:1, date:1})
  • 179. #MDBLocal R E E E E E E Consecutive Index Keys R Look familiar? This is equality after range!
  • 180. #MDBLocal Roadmap E-S-R Overview Guidelines: • Eà R • Eà S • Sà R E-S-R Considerations Operator Type Checks Consecutive Index Keys Exceptions?
  • 181. #MDBLocal Exceptions Is the E-S-R “rule” always optimal? Nope. Consider the following query: db.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1})
  • 182. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace 1 5,000 9,0012 9,000 … … 2001 2000 2015 2019 2019 gamertag score date {} {} {} {1} {2} db.games.createIndex({gamertag:1, score:1, date:1})
  • 183. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace 1 5,000 9,0012 9,000 … … 2001 2000 2015 2019 2019 gamertag score date {} {} {} db.games.createIndex({gamertag:1, score:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "[MinKey, MaxKey]" ], "date" : [ "[2019.0, inf.0]" ] } {1} {2}
  • 184. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace 1 5,000 9,0012 9,000 … … 2001 2000 2015 2019 2019 gamertag score date {} {} {} db.games.createIndex({gamertag:1, score:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "[MinKey, MaxKey]" ], "date" : [ "[2019.0, inf.0]" ] } {1} {2}
  • 185. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace 1 5,000 9,0012 9,000 … … 2001 2000 2015 2019 2019 gamertag score date {} {} {} db.games.createIndex({gamertag:1, score:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "[MinKey, MaxKey]" ], "date" : [ "[2019.0, inf.0]" ] } {1} {2}
  • 186. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace 1 5,000 9,0012 9,000 … … 2001 2000 2015 2019 2019 gamertag score date {} {} {} db.games.createIndex({gamertag:1, score:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "[MinKey, MaxKey]" ], "date" : [ "[2019.0, inf.0]" ] } {1} {2}
  • 187. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace 1 5,000 9,0012 9,000 … … 2001 2000 2015 2019 2019 gamertag score date {} {} {} db.games.createIndex({gamertag:1, score:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "[MinKey, MaxKey]" ], "date" : [ "[2019.0, inf.0]" ] } {1} {2}
  • 188. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace 1 5,000 9,0012 9,000 … … 2001 2000 2015 2019 2019 gamertag score date {} {} {} db.games.createIndex({gamertag:1, score:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "[MinKey, MaxKey]" ], "date" : [ "[2019.0, inf.0]" ] } {1} {2}
  • 189. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace 1 5,000 9,0012 9,000 … … 2001 2000 2015 2019 2019 gamertag score date {} {} {} db.games.createIndex({gamertag:1, score:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "[MinKey, MaxKey]" ], "date" : [ "[2019.0, inf.0]" ] } {1} {2}
  • 190. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace 1 5,000 9,0012 9,000 … … 2001 2000 2015 2019 2019 gamertag score date {} {} {} db.games.createIndex({gamertag:1, score:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "[MinKey, MaxKey]" ], "date" : [ "[2019.0, inf.0]" ] } {1} {2}
  • 191. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace 1 5,000 9,0012 9,000 … … 2001 2000 2015 2019 2019 gamertag score date {} {} {} db.games.createIndex({gamertag:1, score:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "[MinKey, MaxKey]" ], "date" : [ "[2019.0, inf.0]" ] } {1} {2}
  • 192. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace 1 5,000 9,0012 9,000 … … 2001 2000 2015 2019 2019 gamertag score date {} {} {} db.games.createIndex({gamertag:1, score:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "[MinKey, MaxKey]" ], "date" : [ "[2019.0, inf.0]" ] } {1} {2}
  • 193. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace 1 5,000 9,0012 9,000 … … 2001 2000 2015 2019 2019 gamertag score date {} {} {} db.games.createIndex({gamertag:1, score:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "[MinKey, MaxKey]" ], "date" : [ "[2019.0, inf.0]" ] } {1} {2}
  • 194. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace 1 5,000 9,0012 9,000 … … 2001 2000 2015 2019 2019 gamertag score date {} {} {} db.games.createIndex({gamertag:1, score:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "[MinKey, MaxKey]" ], "date" : [ "[2019.0, inf.0]" ] } {1} {2}
  • 195. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace 1 5,000 9,0012 9,000 … … 2001 2000 2015 2019 2019 gamertag score date {} {} {} db.games.createIndex({gamertag:1, score:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "[MinKey, MaxKey]" ], "date" : [ "[2019.0, inf.0]" ] } {1} {2}
  • 196. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace 1 5,000 9,0012 9,000 … … 2001 2000 2015 2019 2019 gamertag score date {} {} {} db.games.createIndex({gamertag:1, score:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "[MinKey, MaxKey]" ], "date" : [ "[2019.0, inf.0]" ] } {1} {2}
  • 197. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace 1 5,000 9,0012 9,000 … … 2001 2000 2015 2019 2019 gamertag score date {} {} {} "executionStats" : { "nReturned" : 2, "executionTimeMillis" : 23, "totalKeysExamined" : 9001, "totalDocsExamined" : 2, db.games.createIndex({gamertag:1, score:1, date:1}) {1} {2}
  • 199. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace 2001 2000 2015 2019 2019 {score:2} {score:1} {score:5000} {score:9001} {score:9000} … … gamertag date
  • 200. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace … … 2000 2001 2015 2019 2019 {score:2} {score:1} {score:5000} {score:9001} {score:9000} gamertag date db.games.createIndex({gamertag:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[2019.0, inf.0]" ] }
  • 201. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace … … 2000 2001 2015 2019 2019 {score:2} {score:1} {score:5000} {score:9001} {score:9000} gamertag date db.games.createIndex({gamertag:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[2019.0, inf.0]" ] }
  • 202. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace … … 2000 2001 2015 2019 2019 {score:2} {score:1} {score:5000} {score:9001} {score:9000} gamertag date db.games.createIndex({gamertag:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[2019.0, inf.0]" ] }
  • 203. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace … … 2000 2001 2015 2019 2019 {score:2} {score:1} {score:5000} {score:9001} {score:9000} gamertag date db.games.createIndex({gamertag:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[2019.0, inf.0]" ] }
  • 204. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace … … 2000 2001 2015 2019 2019 {score:2} {score:1} {score:5000} {score:9001} {score:9000} gamertag date db.games.createIndex({gamertag:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[2019.0, inf.0]" ] }
  • 205. #MDBLocal Exceptionsdb.games .find({gamertag:"Ace", date:{$gte:2019}}) .sort({score:1}) Ace … … 2000 2001 2015 2019 2019 {score:2} {score:1} {score:5000} gamertag date {score:9001} {score:9000} BS "executionStats" : { "nReturned" : 2, "executionTimeMillis" : 0, "totalKeysExamined" : 2, "totalDocsExamined" : 2, "executionStats" : { "nReturned" : 2, "executionTimeMillis" : 0, "totalKeysExamined" : 2, "totalDocsExamined" : 2, "executionStages" : { "stage" : "SORT", "memUsage" : 154, "memLimit" : 33554432, db.games.createIndex({gamertag:1, date:1}) "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[2019.0, inf.0]" ] }
  • 208. #MDBLocal E-S-R Guidance A good starting place applicable to most use cases Place keys in the following order: Equality first Sort next Range last Remember: • Some operators may be range instead of equality • Having consecutive keys used in the index is important • Specifics about your data set may need a different approach
  翻译: