Presented by Tom Schreiber, Senior Consulting Engineer, MongoDB Experience level: Beginner MongoDB supports a wide range of indexing options to enable fast querying of your data, but what are the right strategies for your application? In this talk we’ll cover how indexing works, the various indexing options, and cover use cases where each might be useful. We'll dive into common pitfalls using real-world examples to ensure that you're ready for scale. We'll show you the tools and techniques for diagnosing and tuning the performance of your MongoDB deployment. Whether you're running into problems or just want to optimize your performance, these skills will be useful.

1. Indexing and
Performance Tuning
Tom Schreiber
Senior Consulting Engineer, MongoDB

2. MongoDB's unique architecture

3. MongoDB's unique architecture

5. Indexes are the single biggest tunable
performance factor in MongoDB

6. Indexes are the single biggest tunable
performance factor in MongoDB
Mail from a German customer after a MongoDB Performance Tuning Consulting:

7. MongoDB's unique architecture

8. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}

9. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
db.test.find({a:5})

10. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
db.test.find({a:5})
Full collection scan

11. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
# documents scanned:
1
db.test.find({a:5})
Full collection scan
!

12. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
!
db.test.find({a:5}) # documents scanned:
2
Full collection scan

13. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
!
db.test.find({a:5}) # documents scanned:
3
Full collection scan

14. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
!
db.test.find({a:5}) # documents scanned:
4
Full collection scan

15. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
!
db.test.find({a:5}) # documents scanned:
5
Full collection scan

16. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
!
db.test.find({a:5}) # documents scanned:
6
Full collection scan

17. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
!
db.test.find({a:5}) # documents scanned:
7
Full collection scan

18. db.test.find({a:5}) # documents scanned:
8
Full collection scan
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
!

19. db.test.find({a:5}) # documents scanned:
8
Full collection scan
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
!

20. Time Complexity for searching in a list with n entries: O(n)
db.test.find({a:5}) # documents scanned:
8
Full collection scan
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
!

21. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
1 5 17
7
113
Index on 'a'
db.test.find({a:5})
Index scan
9

22. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
1 5 17
7
113
Index on 'a'
db.test.find({a:5})
Index scan
9
!
db.test.find({a:5})
# index entries scanned: 1
Index scan

23. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
1 5 17
7
113
Index on 'a'
db.test.find({a:5})
Index scan
9!
db.test.find({a:5})
# index entries scanned: 2
Index scan

24. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
1 5 17
7
113
Index on 'a'
db.test.find({a:5})
Index scan
9
!
db.test.find({a:5})
# index entries scanned: 3
Index scan

25. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
1 5 17
7
113
Index on 'a'
db.test.find({a:5})
Index scan
9
# index entries scanned: 3
!

26. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
1 5 17
7
113
Index on 'a'
db.test.find({a:5})
Index scan
9
# documents scanned: 1
# index entries scanned: 3
!

27. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
1 5 17
7
113
Index on 'a'
db.test.find({a:5})
Index scan
9
# documents scanned: 1
# index entries scanned: 3
Time Complexity for
searching in a binary
search tree with n nodes:
O(log2 n)
log2 10.000 = 13
log2 100.000 = 16
log2 1.000.000 = 19
!

28. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
Index on 'a'
1 7
3 51 17119
MongoDB Index Data Structure: B-Tree
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}

29. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
Index on 'a'
1 7
3 51 17119
MongoDB Index Data Structure: B-Tree
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
db.test.createIndex({a:1})

30. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
Index on 'a'
1 7
3 51 17119
MongoDB Index Data Structure: B-Tree
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
db.test.find({a:{$gte:9, $lte:17}})

31. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
Index on 'a'
1 7
3 51 17119
MongoDB Index Data Structure: B-Tree
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
db.test.find().sort({a:1})

32. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
Index on 'a'
1 7
3 51 17119
MongoDB Index Data Structure: B-Tree
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
db.test.find().sort({a:-1})

33. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
Index on 'a'
1 7
3 51 17119
MongoDB Index Data Structure: B-Tree
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
db.test.createIndex({a:1})

34. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
Index on 'a'
MongoDB Index Data Structure: B-Tree
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
db.test.createIndex({a:-1})
7 1
17 11 9 35 1

35. https://github.com/mongodb/mongo/tree/v3.0/src/mongo/db/storage/mmap_v1/btree

36. https://github.com/mongodb/mongo/tree/v3.0/src/third_party/wiredtiger/src/btree

37. WiredTiger Index- and Data Structures
{'a': 3,
'b': 20}
1
{'b': 30,
'a': 9 }
2
{'c': 40,
'a': 1 }
3
{'c': 9,
'b': 4,
'a': 7}
4
{'a': 1,
'c': 20}
5
{'a': 11}
6
{'a': 17}
7
{'a': 5,
'b': 80}
8
1 3 5 7
1 5
7
4
11
6
17
7
1 3 7 11
1 7
5
8
3
1
1
5
1
3
Collection B+-Tree
Index B+-Tree
Index on 'a'
https://github.com/mongodb/mongo/tree/v3.0/src/third_party/wiredtiger/src/btree
9
2

38. {...} {...} {...} {...}{...} {...} {...}{...}
MMAPv1
Flat Files for Collections
{...} {...}{...} {...}{...} {...}{...}
B-Trees for Indexes
B-Trees for Collections
WiredTiger
Index (and Collection-) Data Structures
are Storage Engine specific
B-Tree Indexes
LSM-Tree Indexes
https://github.com/mongodb/mongo/tree/
v3.0/src/mongo/db/storage/mmap_v1
https://github.com/mongodb/mongo/tree/
v3.0/src/third_party/wiredtiger
Pluggable Storage Engine API
MongoDB Database Engine

39. {...} {...} {...} {...}{...} {...} {...} {...}
MMAPv1
Flat Files for Collections
{...} {...} {...} {...}{...} {...} {...}
B-Trees for Indexes
B-Trees for Collections
WiredTiger
. . .
Index (and Collection-) Data Structures
are Storage Engine specific
B-Tree Indexes
LSM-Tree Indexes
https://github.com/mongodb/mongo/tree/
v3.0/src/mongo/db/storage/mmap_v1
https://github.com/mongodb/mongo/tree/
v3.0/src/third_party/wiredtiger
Fractal-Tree
Indexes
TokuMXse
LSM-Tree
Indexes
RocksDB
Pluggable Storage Engine API
MongoDB Database Engine

40. Balancing Speed of Reads and WritesPerformance
Fast reads Fast writesBoth
Easy:
• Add indexes
Easy:
• No indexes
Hard:
• Smart schema design
(hire a consultant)
• LSM index structures
B-Tree Indexes LSM-Tree Indexes

41. WiredTiger
B-Tree Index
WiredTiger
LSM-Index
WiredTiger
LSM-Index
WiredTiger
You can choose…
Single Thread
Update-heavy
"
Multi Thread
Update-heavy
"
Write-heavy
"
Analytics
"
Special
"
3rd party
In-Memory
In-Memory
In-Memory
Encrypted
MMAPv1

42. …even in the same replica set
Write-heavy
"
Analytics
"
Special
"
Secondary
Primary
Secondary
In-Memory
Encrypted
WiredTiger
LSM-Index

43. Query Execution Monitoring

44. tresult
The Query Optimizer
Chooses the most efficient query plan.
Information on query plans
and their execution statistics:
db.col.query.explain()
full collection scan
index on x
index on y
t0
Choose and Remenber
Terminate
db.col.query(...)

45. stage
plan root
stage stage
stage
stage stage
db.col.query.explain()
{...} {...} {...} {...} {...} {...} {...} {...} {...}

46. db.test.find({a:5}).explain()
{
"queryPlanner" : {
[...],
"winningPlan" : {
"stage" : "FETCH",
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"a" : 5
},
"indexName" : "a_1",
"isMultiKey" : false,
"direction" : "forward",
"indexBounds" : {
"a" : [
"[5.0, 5.0]"
]
}
}
}
},
[...]
}

47. db.test.find({a:5}).explain()
plan root
stage
FETCH
stage
IXSCAN
{
"queryPlanner" : {
[...],
"winningPlan" : {
"stage" : "FETCH",
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"a" : 5
},
"indexName" : "a_1",
"isMultiKey" : false,
"direction" : "forward",
"indexBounds" : {
"a" : [
"[5.0, 5.0]"
]
}
}
}
},
[...]
}

48. {'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
Index on 'a'
1 7
3 51 17119
MongoDB Index Data Structure: B-Tree
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
db.test.createIndex({a:1})
db.test.find({a:5}).explain()
{
"queryPlanner" : {
[...],
"winningPlan" : {
"stage" : "FETCH",
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"a" : 5
},
"indexName" : "a_1",
"isMultiKey" : false,
"direction" : "forward",
"indexBounds" : {
"a" : [
"[5.0, 5.0]"
]
}
}
}
},
[...]
}
stage
FETCH
plan root
stage
IXSCAN

49. Explain Levels
queryPlanner
"Which plan will MongoDB choose to run my query?"
executionStats
"How is my query performing?"
allPlansExecution
"I want as much information as possible to diagnose a slow query."

50. {
[...],
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 1,
"executionTimeMillis" : 0,
"totalKeysExamined" : 1,
"totalDocsExamined" : 1,
"executionStages" : {
"stage" : "FETCH",
"nReturned" : 1,
"executionTime
MillisEstimate" : 0,
"works" : 2,
"advanced" : 1,
"needTime" : 0,
"needFetch" : 0,
"saveState" : 0,
"restoreState" : 0,
"isEOF" : 1,
"invalidates" : 0,
"docsExamined" : 1,
"alreadyHasObj" : 0,
"inputStage" : {
"stage" : "IXSCAN",
db.test.find({a:5}).explain("executionStats")db.test.find({a:5}).explain()
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
Index on 'a'
1 7
3 51 17119
MongoDB Index Data Structure: B-Tree
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
db.test.createIndex({a:1})
stage
IXSCAN
stage
FETCH
plan root

51. "invalidates" : 0,
"docsExamined" : 1,
"alreadyHasObj" : 0,
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 1,
"executionTime
MillisEstimate" : 0,
"works" : 1,
"advanced" : 1,
"needTime" : 0,
"needFetch" : 0,
"saveState" : 0,
"restoreState" : 0,
"isEOF" : 1,
"invalidates" : 0,
"keyPattern" : {
"a" : 5
},
"indexName" : "a_1",
"isMultiKey" : false,
"direction" : "forward",
"indexBounds" : {
"a" : [
"[5.0, 5.0]"
]
},
"keysExamined" : 1,
"dupsTested" : 0,
"dupsDropped" : 0,
"seenInvalidated" : 0,
"matchTested" : 0
db.test.find({a:5}).explain("executionStats")db.test.find({a:5}).explain()
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
Index on 'a'
1 7
3 51 17119
MongoDB Index Data Structure: B-Tree
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
db.test.createIndex({a:1})
stage
IXSCAN
stage
FETCH
plan root
1
1
Loc1 Loc6Loc3 Loc4 Loc5Loc2 Loc7 Loc8Loc8
!!

52. "invalidates" : 0,
"docsExamined" : 1,
"alreadyHasObj" : 0,
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 1,
"executionTime
MillisEstimate" : 0,
"works" : 1,
"advanced" : 1,
"needTime" : 0,
"needFetch" : 0,
"saveState" : 0,
"restoreState" : 0,
"isEOF" : 1,
"invalidates" : 0,
"keyPattern" : {
"a" : 5
},
"indexName" : "a_1",
"isMultiKey" : false,
"direction" : "forward",
"indexBounds" : {
"a" : [
"[5.0, 5.0]"
]
},
"keysExamined" : 1,
"dupsTested" : 0,
"dupsDropped" : 0,
"seenInvalidated" : 0,
"matchTested" : 0
db.test.find({a:5}).explain("executionStats")db.test.find({a:5}).explain()
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
Index on 'a'
1 7
3 51 17119
MongoDB Index Data Structure: B-Tree
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
db.test.createIndex({a:1})
stage
IXSCAN
stage
FETCH
plan root
1
1
Loc8
Loc1 Loc6Loc3 Loc4 Loc5Loc2 Loc7 Loc8

53. "invalidates" : 0,
"docsExamined" : 1,
"alreadyHasObj" : 0,
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 1,
"executionTime
MillisEstimate" : 0,
"works" : 1,
"advanced" : 1,
"needTime" : 0,
"needFetch" : 0,
"saveState" : 0,
"restoreState" : 0,
"isEOF" : 1,
"invalidates" : 0,
"keyPattern" : {
"a" : 5
},
"indexName" : "a_1",
"isMultiKey" : false,
"direction" : "forward",
"indexBounds" : {
"a" : [
"[5.0, 5.0]"
]
},
"keysExamined" : 1,
"dupsTested" : 0,
"dupsDropped" : 0,
"seenInvalidated" : 0,
"matchTested" : 0
db.test.find({a:5}).explain("executionStats")db.test.find({a:5}).explain()
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
Index on 'a'
1 7
3 51 17119
MongoDB Index Data Structure: B-Tree
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
db.test.createIndex({a:1})
stage
IXSCAN
stage
FETCH
plan root
1
1
Loc8
Loc1 Loc6Loc3 Loc4 Loc5Loc2 Loc7 Loc8

54. "executionTimeMillis" : 0,
"totalKeysExamined" : 1,
"totalDocsExamined" : 1,
"executionStages" : {
"stage" : "FETCH",
"nReturned" : 1,
"executionTime
MillisEstimate" : 0,
"works" : 2,
"advanced" : 1,
"needTime" : 0,
"needFetch" : 0,
"saveState" : 0,
"restoreState" : 0,
"isEOF" : 1,
"invalidates" : 0,
"docsExamined" : 1,
"alreadyHasObj" : 0,
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 1,
"executionTime
MillisEstimate" : 0,
"works" : 1,
"advanced" : 1,
"needTime" : 0,
"needFetch" : 0,
"saveState" : 0,
"restoreState" : 0,
"isEOF" : 1,
db.test.find({a:5}).explain("executionStats")db.test.find({a:5}).explain()
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
Index on 'a'
1 7
3 51 17119
MongoDB Index Data Structure: B-Tree
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
db.test.createIndex({a:1})
stage
IXSCAN
stage
FETCH
plan root
1
1
1
1
Loc8
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
!
db.test.find({a:5}) # documents scanned:
2
Full collection scan
Loc1 Loc6Loc3 Loc4 Loc5Loc2 Loc7 Loc8

55. "executionTimeMillis" : 0,
"totalKeysExamined" : 1,
"totalDocsExamined" : 1,
"executionStages" : {
"stage" : "FETCH",
"nReturned" : 1,
"executionTime
MillisEstimate" : 0,
"works" : 2,
"advanced" : 1,
"needTime" : 0,
"needFetch" : 0,
"saveState" : 0,
"restoreState" : 0,
"isEOF" : 1,
"invalidates" : 0,
"docsExamined" : 1,
"alreadyHasObj" : 0,
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 1,
"executionTime
MillisEstimate" : 0,
"works" : 1,
"advanced" : 1,
"needTime" : 0,
"needFetch" : 0,
"saveState" : 0,
"restoreState" : 0,
"isEOF" : 1,
db.test.find({a:5}).explain("executionStats")db.test.find({a:5}).explain()
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
Index on 'a'
1 7
3 51 17119
MongoDB Index Data Structure: B-Tree
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
db.test.createIndex({a:1})
stage
IXSCAN
stage
FETCH
plan root
1
1
1
1
Loc8
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
!
db.test.find({a:5}) # documents scanned:
2
Full collection scan
Loc1 Loc6Loc3 Loc4 Loc5Loc2 Loc7 Loc8

56. "docsExamined" : 1,
"alreadyHasObj" : 0,
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 1,
"executionTime
MillisEstimate" : 0,
"works" : 1,
"advanced" : 1,
"needTime" : 0,
"needFetch" : 0,
"saveState" : 0,
"restoreState" : 0,
"isEOF" : 1,
"invalidates" : 0,
"keyPattern" : {
"a" : 5
},
"indexName" : "a_1",
"isMultiKey" : false,
"direction" : "forward",
"indexBounds" : {
"a" : [
"[5.0, 5.0]"
]
},
"keysExamined" : 1,
"dupsTested" : 0,
"dupsDropped" : 0,
"seenInvalidated" : 0,
"matchTested" : 0
}
Explain() method key metrics
# documents returned
How long did the query take
# index entries scanned
# documents scanned
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
Index on 'a'
1 7
3 51 17119
MongoDB Index Data Structure: B-Tree
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
db.test.createIndex({a:1})

57. Index used? Which one?
"docsExamined" : 1,
"alreadyHasObj" : 0,
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 1,
"executionTime
MillisEstimate" : 0,
"works" : 1,
"advanced" : 1,
"needTime" : 0,
"needFetch" : 0,
"saveState" : 0,
"restoreState" : 0,
"isEOF" : 1,
"invalidates" : 0,
"keyPattern" : {
"a" : 5
},
"indexName" : "a_1",
"isMultiKey" : false,
"direction" : "forward",
"indexBounds" : {
"a" : [
"[5.0, 5.0]"
]
},
"keysExamined" : 1,
"dupsTested" : 0,
"dupsDropped" : 0,
"seenInvalidated" : 0,
"matchTested" : 0
}
Explain() method key metrics
"IXSCAN"
"indexName" : "a_1"
# documents returned
How long did the query take
# index entries scanned
# documents scanned
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
Index on 'a'
1 7
3 51 17119
MongoDB Index Data Structure: B-Tree
{'a': 3,
'b': 20}
{'b': 30,
'a': 9 }
{'c': 40,
'a': 1 }
{'c': 9,
'b': 4,
'a': 7}
{'a': 1,
'c': 20}
{'a': 11} {'a': 17}
{'a': 5,
'b': 80}
db.test.createIndex({a:1})

58. Performance Tuning with
Query Execution Monitoring

59. United States Postal Service ZIP-Codes
db.zips.find() 29353 documents
media.mongodb.org/zips.json
{ "zip" : "01001", "city" : "AGAWAM", "loc" : [ -72.622739, 42.070206 ], "pop" : 15338, "state" : "MA" }
{ "zip" : "01002", "city" : "CUSHMAN", "loc" : [ -72.51564999999999, 42.377017 ], "pop" : 36963, "state" : "MA" }
{ "zip" : "01005", "city" : "BARRE", "loc" : [ -72.10835400000001, 42.409698 ], "pop" : 4546, "state" : "MA" }
{ "zip" : "01007", "city" : "BELCHERTOWN", "loc" : [ -72.41095300000001, 42.275103 ], "pop" : 10579, "state" : "MA" }
{ "zip" : "01008", "city" : "BLANDFORD", "loc" : [ -72.936114, 42.182949 ], "pop" : 1240, "state" : "MA" }
{ "zip" : "01010", "city" : "BRIMFIELD", "loc" : [ -72.188455, 42.116543 ], "pop" : 3706, "state" : "MA" }
{ "zip" : "01011", "city" : "CHESTER", "loc" : [ -72.988761, 42.279421 ], "pop" : 1688, "state" : "MA" }
{ "zip" : "01012", "city" : "CHESTERFIELD", "loc" : [ -72.833309, 42.38167 ], "pop" : 177, "state" : "MA" }
{ "zip" : "01013", "city" : "CHICOPEE", "loc" : [ -72.607962, 42.162046 ], "pop" : 23396, "state" : "MA" }
{ "zip" : "01020", "city" : "CHICOPEE", "loc" : [ -72.576142, 42.176443 ], "pop" : 31495, "state" : "MA" }
{ "zip" : "01022", "city" : "WESTOVER AFB", "loc" : [ -72.558657, 42.196672 ], "pop" : 1764, "state" : "MA" }
{ "zip" : "01026", "city" : "CUMMINGTON", "loc" : [ -72.905767, 42.435296 ], "pop" : 1484, "state" : "MA" }
{ "zip" : "01027", "city" : "MOUNT TOM", "loc" : [ -72.67992099999999, 42.264319 ], "pop" : 16864, "state" : "MA" }
{ "zip" : "01028", "city" : "EAST LONGMEADOW", "loc" : [ -72.505565, 42.067203 ], "pop" : 13367, "state" : "MA" }
{ "zip" : "01030", "city" : "FEEDING HILLS", "loc" : [ -72.675077, 42.07182 ], "pop" : 11985, "state" : "MA" }
{ "zip" : "01031", "city" : "GILBERTVILLE", "loc" : [ -72.19858499999999, 42.332194 ], "pop" : 2385, "state" : "MA" }
{ "zip" : "01032", "city" : "GOSHEN", "loc" : [ -72.844092, 42.466234 ], "pop" : 122, "state" : "MA" }
{ "zip" : "01033", "city" : "GRANBY", "loc" : [ -72.52000099999999, 42.255704 ], "pop" : 5526, "state" : "MA" }
{ "zip" : "01034", "city" : "TOLLAND", "loc" : [ -72.908793, 42.070234 ], "pop" : 1652, "state" : "MA" }
{ "zip" : "01035", "city" : "HADLEY", "loc" : [ -72.571499, 42.36062 ], "pop" : 4231, "state" : "MA" }

60. Question
Zip codes in New York City with population more than
100,000 ordered by population in descending order
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1})
{"zip" : "10021", "city" : "NEW YORK", "pop" : 106564, "state" : "NY" }
{"zip" : "10025", "city" : "NEW YORK", "pop" : 100027, "state" : "NY" }
{ "zip" : "99921", "city" : "CRAIG", "loc" : [ -133.117081, 55.47317 ], "pop" : 1398, "state" : "AK" }
{ "zip" : "99922", "city" : "HYDABURG", "loc" : [ -132.633175, 55.137406 ], "pop" : 891, "state" : "AK" }
{ "zip" : "99923", "city" : "HYDER", "loc" : [ -130.124915, 55.925867 ], "pop" : 116, "state" : "AK" }
{ "zip" : "99925", "city" : "KLAWOCK", "loc" : [ -133.055503, 55.552611 ], "pop" : 851, "state" : "AK" }
{ "zip" : "99926", "city" : "METLAKATLA", "loc" : [ -131.579001, 55.121491 ], "pop" : 1469, "state" : "AK" }
{ "zip" : "99927", "city" : "POINT BAKER", "loc" : [ -133.376372, 56.307858 ], "pop" : 426, "state" : "AK" }
{ "zip" : "99929", "city" : "WRANGELL", "loc" : [ -132.352918, 56.433524 ], "pop" : 2573, "state" : "AK" }
{ "zip" : "99950", "city" : "KETCHIKAN", "loc" : [ -133.18479, 55.942471 ], "pop" : 422, "state" : "AK" }

61. db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1})
No Index

62. db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
No Index

63. db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
{
"queryPlanner" : {
"winningPlan" : {
"stage" : "SORT",
"sortPattern" : {
"pop" : -1
},
"inputStage" : {
"stage" : "COLLSCAN",
"filter" : {
"$and" : [
{
"city" : {
"$eq" : "NEW YORK"
}
},
{
"state" : {
"$eq" : "NY"
}
No Index

64. db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
plan root
{
"queryPlanner" : {
"winningPlan" : {
"stage" : "SORT",
"sortPattern" : {
"pop" : -1
},
"inputStage" : {
"stage" : "COLLSCAN",
"filter" : {
"$and" : [
{
"city" : {
"$eq" : "NEW YORK"
}
},
{
"state" : {
"$eq" : "NY"
}
No Index

65. db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
plan root
SORT
{
"queryPlanner" : {
"winningPlan" : {
"stage" : "SORT",
"sortPattern" : {
"pop" : -1
},
"inputStage" : {
"stage" : "COLLSCAN",
"filter" : {
"$and" : [
{
"city" : {
"$eq" : "NEW YORK"
}
},
{
"state" : {
"$eq" : "NY"
}
No Index

66. {
"queryPlanner" : {
"winningPlan" : {
"stage" : "SORT",
"sortPattern" : {
"pop" : -1
},
"inputStage" : {
"stage" : "COLLSCAN",
"filter" : {
"$and" : [
{
"city" : {
"$eq" : "NEW YORK"
}
},
{
"state" : {
"$eq" : "NY"
}
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
plan root
SORT
COLLSCAN {...} {...} {...} {...} {...} {...} {...} {...} {...}
Collection Scan!
No Index

67. }
},
{
"pop" : {
"$gt" : 100000
}
}
]
},
"direction" : "forward"
}
},
"rejectedPlans" : [ ]
},
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 2,
"executionTimeMillis" : 15,
"totalKeysExamined" : 0,
"totalDocsExamined" : 29353,
"executionStages" : {
"stage" : "SORT",
"nReturned" : 2,
"executionTimeMillisEstimate" : 0,
"works" : 29359,
"advanced" : 2,
"needTime" : 29355,
"needFetch" : 0,
"saveState" : 229,
"restoreState" : 229,
"isEOF" : 1,
"invalidates" : 0,
"sortPattern" : {
"pop" : -1
.explain("executionStats")
{...} {...} {...} {...} {...} {...} {...} {...} {...}
plan root
SORT
COLLSCAN
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
Collection Scan!
No Index

68. }
},
{
"pop" : {
"$gt" : 100000
}
}
]
},
"direction" : "forward"
}
},
"rejectedPlans" : [ ]
},
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 2,
"executionTimeMillis" : 15,
"totalKeysExamined" : 0,
"totalDocsExamined" : 29353,
"executionStages" : {
"stage" : "SORT",
"nReturned" : 2,
"executionTimeMillisEstimate" : 0,
"works" : 29359,
"advanced" : 2,
"needTime" : 29355,
"needFetch" : 0,
"saveState" : 229,
"restoreState" : 229,
"isEOF" : 1,
"invalidates" : 0,
"sortPattern" : {
"pop" : -1
.explain("executionStats")
{...} {...} {...} {...} {...} {...} {...} {...} {...}
2 documents returnedplan root
SORT
COLLSCAN
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
Collection Scan!
No Index

69. }
},
{
"pop" : {
"$gt" : 100000
}
}
]
},
"direction" : "forward"
}
},
"rejectedPlans" : [ ]
},
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 2,
"executionTimeMillis" : 15,
"totalKeysExamined" : 0,
"totalDocsExamined" : 29353,
"executionStages" : {
"stage" : "SORT",
"nReturned" : 2,
"executionTimeMillisEstimate" : 0,
"works" : 29359,
"advanced" : 2,
"needTime" : 29355,
"needFetch" : 0,
"saveState" : 229,
"restoreState" : 229,
"isEOF" : 1,
"invalidates" : 0,
"sortPattern" : {
"pop" : -1
.explain("executionStats")
{...} {...} {...} {...} {...} {...} {...} {...} {...}
2 documents returned
29353 documents scanned
plan root
SORT
COLLSCAN
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
Collection Scan!
No Index

70. }
},
{
"pop" : {
"$gt" : 100000
}
}
]
},
"direction" : "forward"
}
},
"rejectedPlans" : [ ]
},
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 2,
"executionTimeMillis" : 15,
"totalKeysExamined" : 0,
"totalDocsExamined" : 29353,
"executionStages" : {
"stage" : "SORT",
"nReturned" : 2,
"executionTimeMillisEstimate" : 0,
"works" : 29359,
"advanced" : 2,
"needTime" : 29355,
"needFetch" : 0,
"saveState" : 229,
"restoreState" : 229,
"isEOF" : 1,
"invalidates" : 0,
"sortPattern" : {
"pop" : -1
.explain("executionStats")
{...} {...} {...} {...} {...} {...} {...} {...} {...}
2 documents returned
29353 documents scanned
plan root
SORT
COLLSCAN
In-Memory Sort!
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
Collection Scan!
No Index

71. db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
Single Field Index
db.zips.createIndex({state:1})

72. db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
Single Field Index
db.zips.createIndex({state:1})
{
"queryPlanner": {
"winningPlan": {
"stage": "SORT",
"sortPattern": {
"pop": -1
},
"inputStage": {
"stage": "FETCH",
"filter": {
"$and": [
{
"city": {
"$eq": "NEW YORK"
}
},
{
"pop": {
"$gt": 100000
}
plan root

73. db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
Single Field Index
db.zips.createIndex({state:1})
{
"queryPlanner": {
"winningPlan": {
"stage": "SORT",
"sortPattern": {
"pop": -1
},
"inputStage": {
"stage": "FETCH",
"filter": {
"$and": [
{
"city": {
"$eq": "NEW YORK"
}
},
{
"pop": {
"$gt": 100000
}
plan root
SORT

74. {
"queryPlanner": {
"winningPlan": {
"stage": "SORT",
"sortPattern": {
"pop": -1
},
"inputStage": {
"stage": "FETCH",
"filter": {
"$and": [
{
"city": {
"$eq": "NEW YORK"
}
},
{
"pop": {
"$gt": 100000
}
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
Single Field Index
db.zips.createIndex({state:1})
plan root
SORT
FETCH

75. "pop": -1
},
"inputStage": {
"stage": "FETCH",
"filter": {
"$and": [
{
"city": {
"$eq": "NEW YORK"
}
},
{
"pop": {
"$gt": 100000
}
}
]
},
"inputStage": {
"stage": "IXSCAN",
"keyPattern": {
"state": 1
},
"indexName": "state_1",
"isMultiKey": false,
"direction": "forward",
"indexBounds": {
"state": [
"["NY", "NY"]"
]
}
}
}
},
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
Single Field Index
db.zips.createIndex({state:1})
plan root
SORT
FETCH

76. "pop": -1
},
"inputStage": {
"stage": "FETCH",
"filter": {
"$and": [
{
"city": {
"$eq": "NEW YORK"
}
},
{
"pop": {
"$gt": 100000
}
}
]
},
"inputStage": {
"stage": "IXSCAN",
"keyPattern": {
"state": 1
},
"indexName": "state_1",
"isMultiKey": false,
"direction": "forward",
"indexBounds": {
"state": [
"["NY", "NY"]"
]
}
}
}
},
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
Single Field Index
db.zips.createIndex({state:1})
plan root
SORT
FETCH
IXSCAN
{...} {...} {...} {...} {...} {...} {...} {...} {...}

77. },
"indexName": "state_1",
"isMultiKey": false,
"direction": "forward",
"indexBounds": {
"state": [
"["NY", "NY"]"
]
}
}
}
},
"rejectedPlans": []
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 6,
"totalKeysExamined": 1595,
"totalDocsExamined": 1595,
"executionStages": {
"stage": "SORT",
"nReturned": 2,
"executionTimeMillisEstimate": 0,
"works": 1600,
"advanced": 2,
"needTime": 1596,
"needFetch": 0,
"saveState": 12,
"restoreState": 12,
"isEOF": 1,
"invalidates": 0,
"sortPattern": {
"pop": -1
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
Single Field Index
db.zips.createIndex({state:1})
plan root
SORT
FETCH
IXSCAN
{...} {...} {...} {...} {...} {...} {...} {...} {...}

78. },
"indexName": "state_1",
"isMultiKey": false,
"direction": "forward",
"indexBounds": {
"state": [
"["NY", "NY"]"
]
}
}
}
},
"rejectedPlans": []
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 6,
"totalKeysExamined": 1595,
"totalDocsExamined": 1595,
"executionStages": {
"stage": "SORT",
"nReturned": 2,
"executionTimeMillisEstimate": 0,
"works": 1600,
"advanced": 2,
"needTime": 1596,
"needFetch": 0,
"saveState": 12,
"restoreState": 12,
"isEOF": 1,
"invalidates": 0,
"sortPattern": {
"pop": -1
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
Single Field Index
db.zips.createIndex({state:1})
plan root
SORT
FETCH
IXSCAN
2 documents returned
{...} {...} {...} {...} {...} {...} {...} {...} {...}

79. },
"indexName": "state_1",
"isMultiKey": false,
"direction": "forward",
"indexBounds": {
"state": [
"["NY", "NY"]"
]
}
}
}
},
"rejectedPlans": []
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 6,
"totalKeysExamined": 1595,
"totalDocsExamined": 1595,
"executionStages": {
"stage": "SORT",
"nReturned": 2,
"executionTimeMillisEstimate": 0,
"works": 1600,
"advanced": 2,
"needTime": 1596,
"needFetch": 0,
"saveState": 12,
"restoreState": 12,
"isEOF": 1,
"invalidates": 0,
"sortPattern": {
"pop": -1
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
Single Field Index
db.zips.createIndex({state:1})
plan root
SORT
FETCH
IXSCAN
2 documents returned
1595 index entries scanned
{...} {...} {...} {...} {...} {...} {...} {...} {...}

80. },
"indexName": "state_1",
"isMultiKey": false,
"direction": "forward",
"indexBounds": {
"state": [
"["NY", "NY"]"
]
}
}
}
},
"rejectedPlans": []
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 6,
"totalKeysExamined": 1595,
"totalDocsExamined": 1595,
"executionStages": {
"stage": "SORT",
"nReturned": 2,
"executionTimeMillisEstimate": 0,
"works": 1600,
"advanced": 2,
"needTime": 1596,
"needFetch": 0,
"saveState": 12,
"restoreState": 12,
"isEOF": 1,
"invalidates": 0,
"sortPattern": {
"pop": -1
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
Single Field Index
db.zips.createIndex({state:1})
plan root
SORT
FETCH
IXSCAN
2 documents returned
1595 documents scanned
1595 index entries scanned
{...} {...} {...} {...} {...} {...} {...} {...} {...}

81. },
"indexName": "state_1",
"isMultiKey": false,
"direction": "forward",
"indexBounds": {
"state": [
"["NY", "NY"]"
]
}
}
}
},
"rejectedPlans": []
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 6,
"totalKeysExamined": 1595,
"totalDocsExamined": 1595,
"executionStages": {
"stage": "SORT",
"nReturned": 2,
"executionTimeMillisEstimate": 0,
"works": 1600,
"advanced": 2,
"needTime": 1596,
"needFetch": 0,
"saveState": 12,
"restoreState": 12,
"isEOF": 1,
"invalidates": 0,
"sortPattern": {
"pop": -1
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
Single Field Index
db.zips.createIndex({state:1})
plan root
SORT
FETCH
IXSCAN
2 documents returned
1595 documents scanned
1595 index entries scanned
In-Memory Sort!
{...} {...} {...} {...} {...} {...} {...} {...} {...}

82. db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1})
db.zips.createIndex({state:1})
NY NY NY NY NY NY NY NY NY NY NY NY NY NY NY OH OH OH OH OH OH OH OH OH O
NY TX
NY
NY OH OK OR
{ "state" : "NY", "city" : "NEW YORK", "pop" : 106564, "zip" : "10021", "loc" : [ -73.958805, 40.768476 ] }
{ "state" : "NY", "city" : "NORTH TARRYTOWN", "pop" : 20080, "zip" : "10591", "loc" : [ -73.859335, 41.078108 ] }
{ "state" : "NY", "city" : "YONKERS", "pop" : 19958, "zip" : "10703", "loc" : [ -73.885163, 40.951763 ] }
{ "state" : "NY", "city" : "NEW YORK", "pop" : 18913, "zip" : "10001", "loc" : [ -73.996705, 40.74838 ] }
{ "state" : "NY", "city" : "WHITE PLAINS", "pop" : 17843, "zip" : "10605", "loc" : [ -73.755247, 41.014053 ] }
{ "state" : "NY", "city" : "NEW YORK", "pop" : 84143, "zip" : "10002", "loc" : [ -73.987681, 40.715231 ] }
{ "state" : "NY", "city" : "WHITE PLAINS", "pop" : 13436, "zip" : "10606", "loc" : [ -73.778097, 41.024714 ] }
{ "state" : "NY", "city" : "NEW YORK", "pop" : 12465, "zip" : "10017", "loc" : [ -73.970661, 40.75172 ] }
{ "state" : "NY", "city" : "NEW YORK", "pop" : 100027, "zip" : "10025", "loc" : [ -73.968312, 40.797466 ] }
{ "state" : "NY", "city" : "EAST WHITE PLAIN", "pop" : 8899, "zip" : "10604", "loc" : [ -73.750727, 41.043295 ] }
{ "state" : "NY", "city" : "HASTINGS ON HUDS", "pop" : 8546, "zip" : "10706", "loc" : [ -73.875912, 40.99071 ] }
{ "state" : "NY", "city" : "WHITE PLAINS", "pop" : 8397, "zip" : "10601", "loc" : [ -73.765231, 41.032955 ] }
{ "state" : "NY", "city" : "PUTNAM VALLEY", "pop" : 7453, "zip" : "10579", "loc" : [ -73.85024, 41.372815 ] }

83. db.zips.createIndex({state:1, city:1})
Compound Index on two fields
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")

84. {
"queryPlanner": {
"winningPlan": {
"stage": "SORT",
"sortPattern": {
"pop": -1
},
"inputStage": {
"stage": "FETCH",
"filter": {
"pop": {
"$gt": 100000
}
},
"inputStage": {
"stage": "IXSCAN",
"keyPattern": {
"state": 1,
"city": 1
},
db.zips.createIndex({state:1, city:1})
Compound Index on two fields
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")

85. {
"queryPlanner": {
"winningPlan": {
"stage": "SORT",
"sortPattern": {
"pop": -1
},
"inputStage": {
"stage": "FETCH",
"filter": {
"pop": {
"$gt": 100000
}
},
"inputStage": {
"stage": "IXSCAN",
"keyPattern": {
"state": 1,
"city": 1
},
db.zips.createIndex({state:1, city:1})
Compound Index on two fields
plan root
SORT
FETCH
IXSCAN
{...} {...} {...} {...} {...} {...} {...} {...} {...}
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")

86. {
"queryPlanner": {
"winningPlan": {
"stage": "SORT",
"sortPattern": {
"pop": -1
},
"inputStage": {
"stage": "FETCH",
"filter": {
"pop": {
"$gt": 100000
}
},
"inputStage": {
"stage": "IXSCAN",
"keyPattern": {
"state": 1,
"city": 1
},
"indexName": "state_1_city_1",
"isMultiKey": false,
"direction": "forward",
"indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK
"]"
]
}
}
}
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
db.zips.createIndex({state:1, city:1})
Compound Index on two fields
plan root
SORT
FETCH
IXSCAN
{...} {...} {...} {...} {...} {...} {...} {...} {...}

87. {
"queryPlanner": {
"winningPlan": {
"stage": "SORT",
"sortPattern": {
"pop": -1
},
"inputStage": {
"stage": "FETCH",
"filter": {
"pop": {
"$gt": 100000
}
},
"inputStage": {
"stage": "IXSCAN",
"keyPattern": {
"state": 1,
"city": 1
},
"indexName": "state_1_city_1",
"isMultiKey": false,
"direction": "forward",
"indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK
"]"
]
}
}
}
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
db.zips.createIndex({state:1, city:1})
Compound Index on two fields
plan root
SORT
FETCH
IXSCAN
{...} {...} {...} {...} {...} {...} {...} {...} {...}

88. {
"queryPlanner": {
"winningPlan": {
"stage": "SORT",
"sortPattern": {
"pop": -1
},
"inputStage": {
"stage": "FETCH",
"filter": {
"pop": {
"$gt": 100000
}
},
"inputStage": {
"stage": "IXSCAN",
"keyPattern": {
"state": 1,
"city": 1
},
"indexName": "state_1_city_1",
"isMultiKey": false,
"direction": "forward",
"indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK
"]"
]
}
}
}
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
db.zips.createIndex({state:1, city:1})
Compound Index on two fields
plan root
SORT
FETCH
IXSCAN
{...} {...} {...} {...} {...} {...} {...} {...} {...}

89. "direction": "forward",
"indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK
"]"
]
}
}
}
}
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 4,
"totalKeysExamined": 40,
"totalDocsExamined": 40,
"executionStages": {
"stage": "SORT",
"nReturned": 2,
"executionTimeMillisEstimate": 4,
"works": 45,
"advanced": 2,
"needTime": 41,
"needFetch": 0,
"saveState": 0,
"restoreState": 0,
"isEOF": 1,
"invalidates": 0,
"sortPattern": {
"pop": -1
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
db.zips.createIndex({state:1, city:1})
Compound Index on two fields
plan root
SORT
FETCH
IXSCAN
{...} {...} {...} {...} {...} {...} {...} {...} {...}

90. "direction": "forward",
"indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK
"]"
]
}
}
}
}
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 4,
"totalKeysExamined": 40,
"totalDocsExamined": 40,
"executionStages": {
"stage": "SORT",
"nReturned": 2,
"executionTimeMillisEstimate": 4,
"works": 45,
"advanced": 2,
"needTime": 41,
"needFetch": 0,
"saveState": 0,
"restoreState": 0,
"isEOF": 1,
"invalidates": 0,
"sortPattern": {
"pop": -1
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
db.zips.createIndex({state:1, city:1})
Compound Index on two fields
plan root
SORT
FETCH
IXSCAN
{...} {...} {...} {...} {...} {...} {...} {...} {...}
2 documents returned

91. "direction": "forward",
"indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK
"]"
]
}
}
}
}
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 4,
"totalKeysExamined": 40,
"totalDocsExamined": 40,
"executionStages": {
"stage": "SORT",
"nReturned": 2,
"executionTimeMillisEstimate": 4,
"works": 45,
"advanced": 2,
"needTime": 41,
"needFetch": 0,
"saveState": 0,
"restoreState": 0,
"isEOF": 1,
"invalidates": 0,
"sortPattern": {
"pop": -1
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
db.zips.createIndex({state:1, city:1})
Compound Index on two fields
plan root
SORT
FETCH
IXSCAN
{...} {...} {...} {...} {...} {...} {...} {...} {...}
2 documents returned
40 index entries scanned

92. "direction": "forward",
"indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK
"]"
]
}
}
}
}
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 4,
"totalKeysExamined": 40,
"totalDocsExamined": 40,
"executionStages": {
"stage": "SORT",
"nReturned": 2,
"executionTimeMillisEstimate": 4,
"works": 45,
"advanced": 2,
"needTime": 41,
"needFetch": 0,
"saveState": 0,
"restoreState": 0,
"isEOF": 1,
"invalidates": 0,
"sortPattern": {
"pop": -1
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
db.zips.createIndex({state:1, city:1})
Compound Index on two fields
plan root
SORT
FETCH
IXSCAN
{...} {...} {...} {...} {...} {...} {...} {...} {...}
2 documents returned
40 documents scanned
40 index entries scanned

93. "direction": "forward",
"indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK
"]"
]
}
}
}
}
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 4,
"totalKeysExamined": 40,
"totalDocsExamined": 40,
"executionStages": {
"stage": "SORT",
"nReturned": 2,
"executionTimeMillisEstimate": 4,
"works": 45,
"advanced": 2,
"needTime": 41,
"needFetch": 0,
"saveState": 0,
"restoreState": 0,
"isEOF": 1,
"invalidates": 0,
"sortPattern": {
"pop": -1
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
db.zips.createIndex({state:1, city:1})
Compound Index on two fields
plan root
SORT
FETCH
IXSCAN
{...} {...} {...} {...} {...} {...} {...} {...} {...}
2 documents returned
40 documents scanned
40 index entries scanned
In-Memory Sort!

94. { "state" : "NY", "city" : "NEW YORK", "pop" : 57385, "zip" : "10023", "loc" : [ -73.982652, 40.77638 ] }
{ "state" : "NY", "city" : "NEW YORK", "pop" : 51224, "zip" : "10003", "loc" : [ -73.989223, 40.731253 ] }
{ "state" : "NY", "city" : "NEW YORK", "pop" : 46560, "zip" : "10011", "loc" : [ -73.99963, 40.740225 ] }
{ "state" : "NY", "city" : "NEW YORK", "pop" : 36602, "zip" : "10019", "loc" : [ -73.985834, 40.765069 ] }
{ "state" : "NY", "city" : "NEW YORK", "pop" : 28453, "zip" : "10026", "loc" : [ -73.953069, 40.801942 ] }
{ "state" : "NY", "city" : "NEW YORK", "pop" : 26365, "zip" : "10012", "loc" : [ -73.998284, 40.72553 ] }
{ "state" : "NY", "city" : "NEW YORK", "pop" : 106564, "zip" : "10021", "loc" : [ -73.958805, 40.768476 ] }
{ "state" : "NY", "city" : "NEW YORK", "pop" : 18913, "zip" : "10001", "loc" : [ -73.996705, 40.74838 ] }
{ "state" : "NY", "city" : "NEW YORK", "pop" : 84143, "zip" : "10002", "loc" : [ -73.987681, 40.715231 ] }
{ "state" : "NY", "city" : "NEW YORK", "pop" : 12465, "zip" : "10017", "loc" : [ -73.970661, 40.75172 ] }
{ "state" : "NY", "city" : "NEW YORK", "pop" : 100027, "zip" : "10025", "loc" : [ -73.968312, 40.797466 ] }
{ "state" : "NY", "city" : "NEW YORK", "pop" : 4834, "zip" : "10018", "loc" : [ -73.992503, 40.754713 ] }
{ "state" : "NY", "city" : "NEW YORK", "pop" : 393, "zip" : "10020", "loc" : [ -73.982347, 40.759729 ] }
ABERDEENOH
NEW YORKNYNEW YORKNYW YORK NEW YORKNY NEWARKNY
NEW YORKNY NEWARKNY
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1})
db.zips.createIndex({state:1, city:1})

95. db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
db.zips.createIndex({state:1,city:1,pop:1})
Compound Index on three fields

96. {
"queryPlanner": {
"winningPlan": {
"stage": "FETCH",
"inputStage": {
"stage": "IXSCAN",
"keyPattern": {
"state": 1,
"city": 1,
"pop": 1
},
"indexName": "state_1_city_1_pop_1",
"isMultiKey": false,
"direction": "backward",
"indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK"]"
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
db.zips.createIndex({state:1,city:1,pop:1})
Compound Index on three fields

97. {
"queryPlanner": {
"winningPlan": {
"stage": "FETCH",
"inputStage": {
"stage": "IXSCAN",
"keyPattern": {
"state": 1,
"city": 1,
"pop": 1
},
"indexName": "state_1_city_1_pop_1",
"isMultiKey": false,
"direction": "backward",
"indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK"]"
IXSCAN
FETCH
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
db.zips.createIndex({state:1,city:1,pop:1})
Compound Index on three fields
plan root
{...} {...} {...} {...} {...} {...} {...} {...} {...}

98. {
"queryPlanner": {
"winningPlan": {
"stage": "FETCH",
"inputStage": {
"stage": "IXSCAN",
"keyPattern": {
"state": 1,
"city": 1,
"pop": 1
},
"indexName": "state_1_city_1_pop_1",
"isMultiKey": false,
"direction": "backward",
"indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK"]"
],
"pop": [
"[inf.0, 100000.0)"
]
}
IXSCAN
FETCH
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
db.zips.createIndex({state:1,city:1,pop:1})
Compound Index on three fields
plan root
{...} {...} {...} {...} {...} {...} {...} {...} {...}

99. {
"queryPlanner": {
"winningPlan": {
"stage": "FETCH",
"inputStage": {
"stage": "IXSCAN",
"keyPattern": {
"state": 1,
"city": 1,
"pop": 1
},
"indexName": "state_1_city_1_pop_1",
"isMultiKey": false,
"direction": "backward",
"indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK"]"
],
"pop": [
"[inf.0, 100000.0)"
]
}
IXSCAN
FETCH
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
db.zips.createIndex({state:1,city:1,pop:1})
Compound Index on three fields
plan root
{...} {...} {...} {...} {...} {...} {...} {...} {...}?

100. {
"queryPlanner": {
"winningPlan": {
"stage": "FETCH",
"inputStage": {
"stage": "IXSCAN",
"keyPattern": {
"state": 1,
"city": 1,
"pop": 1
},
"indexName": "state_1_city_1_pop_1",
"isMultiKey": false,
"direction": "backward",
"indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK"]"
],
"pop": [
"[inf.0, 100000.0)"
]
}
IXSCAN
FETCH
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
db.zips.createIndex({state:1,city:1,pop:1})
Compound Index on three fields
plan root
{...} {...} {...} {...} {...} {...} {...} {...} {...}?

101. "indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK"]"
],
"pop": [
"[inf.0, 100000.0)"
]
}
}
}
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 2,
"totalKeysExamined": 2,
"totalDocsExamined": 2,
"executionStages": {
"stage": "FETCH",
"nReturned": 2,
"executionTimeMillisEstimate": 1,
"works": 3,
"advanced": 2,
"needTime": 0,
"needFetch": 0,
"saveState": 0,
"restoreState": 0,
"isEOF": 1,
"invalidates": 0,
"docsExamined": 2,
"alreadyHasObj": 0,
IXSCAN
FETCH
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
db.zips.createIndex({state:1,city:1,pop:1})
Compound Index on three fields
plan root
{...} {...} {...} {...} {...} {...} {...} {...} {...}

102. "indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK"]"
],
"pop": [
"[inf.0, 100000.0)"
]
}
}
}
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 2,
"totalKeysExamined": 2,
"totalDocsExamined": 2,
"executionStages": {
"stage": "FETCH",
"nReturned": 2,
"executionTimeMillisEstimate": 1,
"works": 3,
"advanced": 2,
"needTime": 0,
"needFetch": 0,
"saveState": 0,
"restoreState": 0,
"isEOF": 1,
"invalidates": 0,
"docsExamined": 2,
"alreadyHasObj": 0,
IXSCAN
FETCH
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
db.zips.createIndex({state:1,city:1,pop:1})
Compound Index on three fields
plan root
{...} {...} {...} {...} {...} {...} {...} {...} {...}
2 documents returned

103. "indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK"]"
],
"pop": [
"[inf.0, 100000.0)"
]
}
}
}
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 2,
"totalKeysExamined": 2,
"totalDocsExamined": 2,
"executionStages": {
"stage": "FETCH",
"nReturned": 2,
"executionTimeMillisEstimate": 1,
"works": 3,
"advanced": 2,
"needTime": 0,
"needFetch": 0,
"saveState": 0,
"restoreState": 0,
"isEOF": 1,
"invalidates": 0,
"docsExamined": 2,
"alreadyHasObj": 0,
IXSCAN
FETCH
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
db.zips.createIndex({state:1,city:1,pop:1})
Compound Index on three fields
plan root
{...} {...} {...} {...} {...} {...} {...} {...} {...}
2 documents returned
2 index entries scanned

104. "indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK"]"
],
"pop": [
"[inf.0, 100000.0)"
]
}
}
}
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 2,
"totalKeysExamined": 2,
"totalDocsExamined": 2,
"executionStages": {
"stage": "FETCH",
"nReturned": 2,
"executionTimeMillisEstimate": 1,
"works": 3,
"advanced": 2,
"needTime": 0,
"needFetch": 0,
"saveState": 0,
"restoreState": 0,
"isEOF": 1,
"invalidates": 0,
"docsExamined": 2,
"alreadyHasObj": 0,
IXSCAN
FETCH
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
db.zips.createIndex({state:1,city:1,pop:1})
Compound Index on three fields
plan root
{...} {...} {...} {...} {...} {...} {...} {...} {...}
2 documents returned
2 documents scanned
2 index entries scanned

105. "indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK"]"
],
"pop": [
"[inf.0, 100000.0)"
]
}
}
}
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 2,
"totalKeysExamined": 2,
"totalDocsExamined": 2,
"executionStages": {
"stage": "FETCH",
"nReturned": 2,
"executionTimeMillisEstimate": 1,
"works": 3,
"advanced": 2,
"needTime": 0,
"needFetch": 0,
"saveState": 0,
"restoreState": 0,
"isEOF": 1,
"invalidates": 0,
"docsExamined": 2,
"alreadyHasObj": 0,
IXSCAN
FETCH
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1}).explain("executionStats")
db.zips.createIndex({state:1,city:1,pop:1})
Compound Index on three fields
plan root
{...} {...} {...} {...} {...} {...} {...} {...} {...}
2 documents returned
2 documents scanned
2 index entries scanned
Index used for Sorting!

106. NEW YORKNY 106564NEW YORKNY 100027NEW YORKNY 8414374643
NEW YORKNY 51224 NEWARKNY
ADENAOH
{ "state" : "NY", "city" : "NEW YORK", "pop" : 106564, "zip" : "10021", "loc" : [ -73.958805, 40.768476 ] }
{ "state" : "NY", "city" : "NEW YORK", "pop" : 100027, "zip" : "10025", "loc" : [ -73.968312, 40.797466 ] }
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1})
db.zips.createIndex({state:1,city:1,pop:1})
"direction": "backward",
"indexBounds": {
“state": "["NY", "NY"]",
"city":"["NEW YORK", "NEW YORK"]",
"pop":"[inf.0, 100000.0)"

107. NEW YORKNY 106564NEW YORKNY 100027NEW YORKNY 8414374643
NEW YORKNY 51224 NEWARKNY
ADENAOH
{ "state" : "NY", "city" : "NEW YORK", "pop" : 106564, "zip" : "10021", "loc" : [ -73.958805, 40.768476 ] }
{ "state" : "NY", "city" : "NEW YORK", "pop" : 100027, "zip" : "10025", "loc" : [ -73.968312, 40.797466 ] }
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1})
db.zips.createIndex({state:1,city:1,pop:1})
"direction": "backward",
"indexBounds": {
“state": "["NY", "NY"]",
"city":"["NEW YORK", "NEW YORK"]",
"pop":"[inf.0, 100000.0)"

108. db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}})
.sort({pop:-1})
Projection on Index-only Data
db.zips.createIndex({state:1,city:1,pop:1})
{"zip" : "10021", "city" : "NEW YORK", "pop" : 106564, "state" : "NY" }
{"zip" : "10025", "city" : "NEW YORK", "pop" : 100027, "state" : "NY" }

109. db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}},
{state:1, city:1, pop:1})
.sort({pop:-1})
Projection on Index-only Data
db.zips.createIndex({state:1,city:1,pop:1})
{"state" : "NY", "city" : "NEW YORK", "pop" : 106564 }
{"state" : "NY", "city" : "NEW YORK", "pop" : 100027 }

110. db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}},
{state:1, city:1, pop:1})
.sort({pop:-1}).explain("executionStats")
Projection on Index-only Data
db.zips.createIndex({state:1,city:1,pop:1})

111. {
"queryPlanner": {
"winningPlan": {
"stage": "PROJECTION",
"transformBy": {
"state": 1,
"city": 1,
"pop": 1,
"zip": 0
},
"inputStage": {
"stage": "IXSCAN",
"keyPattern": {
"state": 1,
"city": 1,
"pop": 1
},
"indexName": "state_1_city_1_pop_1",
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}},
{state:1, city:1, pop:1})
.sort({pop:-1}).explain("executionStats")
Projection on Index-only Data
db.zips.createIndex({state:1,city:1,pop:1})

112. {
"queryPlanner": {
"winningPlan": {
"stage": "PROJECTION",
"transformBy": {
"state": 1,
"city": 1,
"pop": 1,
"zip": 0
},
"inputStage": {
"stage": "IXSCAN",
"keyPattern": {
"state": 1,
"city": 1,
"pop": 1
},
"indexName": "state_1_city_1_pop_1",
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}},
{state:1, city:1, pop:1})
.sort({pop:-1}).explain("executionStats")
Projection on Index-only Data
db.zips.createIndex({state:1,city:1,pop:1})
IXSCAN
PROJECTION
plan root

113. "isMultiKey": false,
"direction": "backward",
"indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK"]"
],
"pop": [
"[inf.0, 100000.0)"
]
}
}
}
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 0,
"totalKeysExamined": 2,
"totalDocsExamined": 0,
"executionStages": {
"stage": "PROJECTION",
"nReturned": 2,
"executionTimeMillisEstimate": 0,
"works": 3,
"advanced": 2,
"needTime": 0,
"needFetch": 0,
"saveState": 0,
"restoreState": 0,
"isEOF": 1,
"invalidates": 0,
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}},
{state:1, city:1, pop:1})
.sort({pop:-1}).explain("executionStats")
Projection on Index-only Data
db.zips.createIndex({state:1,city:1,pop:1})
IXSCAN
PROJECTION
plan root

114. "isMultiKey": false,
"direction": "backward",
"indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK"]"
],
"pop": [
"[inf.0, 100000.0)"
]
}
}
}
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 0,
"totalKeysExamined": 2,
"totalDocsExamined": 0,
"executionStages": {
"stage": "PROJECTION",
"nReturned": 2,
"executionTimeMillisEstimate": 0,
"works": 3,
"advanced": 2,
"needTime": 0,
"needFetch": 0,
"saveState": 0,
"restoreState": 0,
"isEOF": 1,
"invalidates": 0,
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}},
{state:1, city:1, pop:1})
.sort({pop:-1}).explain("executionStats")
Projection on Index-only Data
db.zips.createIndex({state:1,city:1,pop:1})
IXSCAN
PROJECTION
plan root 2 documents returned

115. "isMultiKey": false,
"direction": "backward",
"indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK"]"
],
"pop": [
"[inf.0, 100000.0)"
]
}
}
}
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 0,
"totalKeysExamined": 2,
"totalDocsExamined": 0,
"executionStages": {
"stage": "PROJECTION",
"nReturned": 2,
"executionTimeMillisEstimate": 0,
"works": 3,
"advanced": 2,
"needTime": 0,
"needFetch": 0,
"saveState": 0,
"restoreState": 0,
"isEOF": 1,
"invalidates": 0,
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}},
{state:1, city:1, pop:1})
.sort({pop:-1}).explain("executionStats")
Projection on Index-only Data
db.zips.createIndex({state:1,city:1,pop:1})
IXSCAN
PROJECTION
plan root 2 documents returned
2 index entries scanned

116. "isMultiKey": false,
"direction": "backward",
"indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK"]"
],
"pop": [
"[inf.0, 100000.0)"
]
}
}
}
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 0,
"totalKeysExamined": 2,
"totalDocsExamined": 0,
"executionStages": {
"stage": "PROJECTION",
"nReturned": 2,
"executionTimeMillisEstimate": 0,
"works": 3,
"advanced": 2,
"needTime": 0,
"needFetch": 0,
"saveState": 0,
"restoreState": 0,
"isEOF": 1,
"invalidates": 0,
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}},
{state:1, city:1, pop:1})
.sort({pop:-1}).explain("executionStats")
Projection on Index-only Data
db.zips.createIndex({state:1,city:1,pop:1})
IXSCAN
PROJECTION
plan root 2 documents returned
0 documents scanned
2 index entries scanned

117. "isMultiKey": false,
"direction": "backward",
"indexBounds": {
"state": [
"["NY", "NY"]"
],
"city": [
"["NEW YORK", "NEW YORK"]"
],
"pop": [
"[inf.0, 100000.0)"
]
}
}
}
},
"executionStats": {
"executionSuccess": true,
"nReturned": 2,
"executionTimeMillis": 0,
"totalKeysExamined": 2,
"totalDocsExamined": 0,
"executionStages": {
"stage": "PROJECTION",
"nReturned": 2,
"executionTimeMillisEstimate": 0,
"works": 3,
"advanced": 2,
"needTime": 0,
"needFetch": 0,
"saveState": 0,
"restoreState": 0,
"isEOF": 1,
"invalidates": 0,
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}},
{state:1, city:1, pop:1})
.sort({pop:-1}).explain("executionStats")
Projection on Index-only Data
db.zips.createIndex({state:1,city:1,pop:1})
IXSCAN
PROJECTION
plan root 2 documents returned
0 documents scanned
2 index entries scanned
"Covered Query "

118. NEW YORKNY 106564NEW YORKNY 100027NEW YORKNY 8414374643
NEW YORKNY 51224 NEWARKNY
ADENAOH
{ "state" : "NY", "city" : "NEW YORK", "pop" : 106564}
{ "state" : "NY", "city" : "NEW YORK", "pop" : 100027}
db.zips.createIndex({state:1,city:1,pop:1})
db.zips.find({state:'NY',city:'NEW YORK',pop:{'$gt':100000}},
{state:1, city:1, pop:1})
.sort({pop:-1})

119. Runtime (ms) Speedup
No Index 80.155 Baseline
Compound Index 126 400
Covered Query 40 2.000
Benchmark Results
Standalone MongoDB v3.2.0-rc1, WiredTiger (12 GB Cache Size and snappy block compressor)
Collection Storage-size: 3 GB
Collection Data-size: 6 GB
Compound-Index-Size: 1 GB
Total-Index-Size: 2 GB
2,2 GHz Intel Core i7, 16 GB 1600 MHz DDR3, SSD-Storage, OS X 10.11.1 (15B42)
100.000.000 ZIP-Code documents - via Datagenerator

120. Indexes are the single biggest tunable
performance factor in MongoDB
Runtime (ms) Speedup
No Index 80.155 Baseline
Compound Index 126 400
Covered Query 40 2.000
Benchmark Results
Standalone MongoDB v3.2.0-rc1, WiredTiger (12 GB Cache Size and snappy block compressor)
Collection Storage-size: 3 GB
Collection Data-size: 6 GB
Compound-Index-Size: 1 GB
Total-Index-Size: 2 GB
2,2 GHz Intel Core i7, 16 GB 1600 MHz DDR3, SSD-Storage, OS X 10.11.1 (15B42)
100.000.000 ZIP-Code documents - via Datagenerator

121. Indexes are the single biggest tunable
performance factor in MongoDB
Runtime (ms) Speedup
No Index 80.155 Baseline
Compound Index 126 400
Covered Query 40 2.000
Benchmark Results
Collection Storage-size: 3 GB
Collection Data-size: 6 GB
Compound-Index-Size: 1 GB
Total-Index-Size: 2 GB
But Memory Contention
can be a Showstopper…
Standalone MongoDB v3.2.0-rc1, WiredTiger (12 GB Cache Size and snappy block compressor)
2,2 GHz Intel Core i7, 16 GB 1600 MHz DDR3, SSD-Storage, OS X 10.11.1 (15B42)
100.000.000 ZIP-Code documents - via Datagenerator

122. Performance Tuning via
Memory Contention Reduction