Speaker: Christopher Harris, Technical Services Engineer, MongoDB

1. Avoiding Query Pitfalls
Stop trying to do silly faster

2. Chris Harris
Technical Services Engineer
MongoDB

3. • Motivation
• Who am I?
Roadmap

4. • Motivation
• Who am I?
• Three Items to be aware of:
• Blocking Stages
• Using the $or operator
• Case-insensitivity
Roadmap

5. The Power of Query Optimization
Query tuning results in:
• Improved performance
• Reduced resource utilization
This may lead to:
• Improved stability and predictability
• A smaller hardware footprint
Not uncommon to observe efficiency improvements greater than 99%

6. • Technical Services Engineer (Support)
• 2.5 year tenure
• Member of the Technical Experts program
• Focus: Queries and Indexing
• Previously: Data Warehouse workload optimization
About Me

7. • Technical Services Engineer (Support)
• 2.5 year tenure
• Member of the Technical Experts program
• Focus: Queries and Indexing
• Previously: Data Warehouse workload optimization
About Me

8. Meet Asya
• DBA at Acme Game, Inc.
• MongoDB Champion
Meet Stakeholders
• Others at Acme, Inc.
• Developers
• Leadership
• RDBMS Historically

9. Acme Games Introduces...
ShortFite!
Brand new Battle Royale game
Launching July 1st

10. • Game nearly complete
• Developers have learned a lot from Asya
Stakeholder Concerns

11. • Game nearly complete
• Developers have learned a lot from Asya
Stakeholder Concerns
Indexes support the efficient
execution of queries in MongoDB

12. • Game nearly complete
• Developers have learned a lot from Asya
Stakeholder Concerns
Indexes support the efficient
execution of queries in MongoDB

13. • Game nearly complete
• Developers have learned a lot from Asya
Stakeholder Concerns
Ace Bob Sue
… …Indexes support the efficient
execution of queries in MongoDB

14. • Game nearly complete
• Developers have learned a lot from Asya
Stakeholder Concerns
• App being stress tested

15. • Game nearly complete
• Developers have learned a lot from Asya
Stakeholder Concerns
• App being stress tested
• Concerns over current performance

16. Stakeholder Concern #1
Developers created index
db.games.createIndex({ gamerTag: 1 })
This query takes several seconds to execute:
db.games.find( { gamerTag: "Ace" } ).sort({score:-1})
Adding the index on score does not help!
db.games.createIndex({ score: -1 })

17. Stakeholder Concern #1
Developers created index
{db.games.createIndex({ gamerTag: 1 })
This query takes several seconds to execute:
db.games.find( { gamerTag: "Ace" } ).sort({score:-1})
Adding the index on score does not help!
{db.games.createIndex({ score: 1 })
“Clearly MongoDB
is not webscale!”

18. Blocking Operations

19. Blocking Operation
● Formally:
■ “An operation which must process all input before it can begin to produce
any output.”
● Opposite of the often desirable “fully pipelined” plan which can stream results
back as soon as they are found.
● Commonly observed when a sort is added to a query

20. Sorting with blocking

21. Sorting with blocking

22. Sorting with blocking

23. Sorting with blocking

24. Sorting with blocking

25. Sorting with blocking

26. Sorting with blocking

27. Sorting with blocking

28. Sorting with blocking

29. Sorting with blocking

30. Sorting with blocking

31. Sorting with blocking

32. Sorting with blocking

33. Sorting with blocking

34. Sorting with blocking

35. Sorting with blocking

36. Sorting with blocking

37. Sorting with blocking

38. Sorting with blocking

39. Sorting with blocking

40. Sorting with blocking

41. Sorting with blocking

42. Sorting with blocking

43. Sorting with blocking

44. Sorting without blocking

45. Sorting without blocking

46. Sorting without blocking

47. Sorting without blocking

48. Blocking Stages
• $sort
• In aggregation and find
• $group
• $bucket
• $count
• $facet
Are there any other blocking
operations?

49. Working with blocking stages
For sorting:
Add a supporting index
Worth the overhead in almost all circumstances
For other stages:
Do you need the blocking stage?
Offload to secondary member

50. Stakeholder Concern #1
Performance of
db.games.find( { gamerTag: "Ace" } ).sort({score:-1})
“Clearly MongoDB is not webscale!”

51. Stakeholder Concern #1
Performance of
db.games.find( { gamerTag: "Ace" } ).sort({score:-1})
db.games.createIndex({ gamerTag: 1, score:-1 })

52. Stakeholder Concern #1
Performance of
db.games.find( { gamerTag: "Ace" } ).sort({score:-1})
db.games.createIndex({ gamerTag: 1, score:-1 })
"That’ll work great!”

53. Stakeholder Concern #2
The $and version of a query
returns quickly:
db.games.find({
$and : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
But the $or version is slow:
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

54. Stakeholder Concern #2
The $and version of a query
returns quickly:
db.games.find({
$and : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
But the $or version is slow:
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
We just created an index with both
those fields… Can it be used?

55. $or

56. $and example
Matching games:
{ gamerTag: "Ace", score: 9500 }
Non-matching games:
{ gamerTag: "Ace", score: 500 },
{ gamerTag: "Bob", score: 9500 },
{ gamerTag: "Bob", score: 500 }
Query on games:
db.games.find({
$and : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

57. Groups of documents
score: {$gt: 9000}gamerTag: "Ace"
{ gamerTag: "Ace",
score: 9500 }
{ gamerTag: "Ace",
score: 500 }
{ gamerTag: "Bob",
score: 9500 }
{ gamerTag: "Bob",
score: 500 }

58. $and Venn Diagram (logical)
score: {$gt: 9000}gamerTag: "Ace"
{ gamerTag: "Ace",
score: 9500 }
{ gamerTag: "Ace",
score: 500 }
{ gamerTag: "Bob",
score: 9500 }
{ gamerTag: "Bob",
score: 500 }
db.games.find({
$and : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

59. $and Venn Diagram (logical)
score: {$gt: 9000}gamerTag: "Ace"
{ gamerTag: "Ace",
score: 9500 }
{ gamerTag: "Ace",
score: 500 }
{ gamerTag: "Bob",
score: 9500 }
{ gamerTag: "Bob",
score: 500 }
db.games.find({
$and : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

60. $and Venn Diagram (logical)
score: {$gt: 9000}gamerTag: "Ace"
db.games.find({
$and : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

61. $and Venn Diagram (logical)
score: {$gt: 9000}gamerTag: "Ace"
db.games.find({
$and : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

62. $and Venn Diagram (logical)
score: {$gt: 9000}gamerTag: "Ace"
db.games.find({
$and : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

63. $and Venn Diagram (logical)
score: {$gt: 9000}gamerTag: "Ace"
db.games.find({
$and : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

64. $and Venn Diagram (logical)
score: {$gt: 9000}gamerTag: "Ace"
db.games.find({
$and : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

65. $and Venn Diagram (logical)
db.games.find({
$and : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
Ace Bob
{gamerTag:1
, score:-1}
500 9500
500 9500

66. $and Venn Diagram (logical)
db.games.find({
$and : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
Ace Bob
500 9500
500 9500
"indexBounds" : {
"gamerTag" : [
"["Ace", "Ace"]"
],
"score" : [
"[inf.0, 9000.0)"
]
}
{gamerTag:1
, score:-1}

67. $and Venn Diagram (logical)
db.games.find({
$and : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
Ace Bob
500 9500
500 9500
{gamerTag:1
, score:-1}
"indexBounds" : {
"gamerTag" : [
"["Ace", "Ace"]"
],
"score" : [
"[inf.0, 9000.0)"
]
}

68. $and Venn Diagram (logical)
db.games.find({
$and : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
Ace Bob
500 9500
500 9500
{gamerTag:1
, score:-1}
"indexBounds" : {
"gamerTag" : [
"["Ace", "Ace"]"
],
"score" : [
"[inf.0, 9000.0)"
]
}

69. $and Venn Diagram (logical)
db.games.find({
$and : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
Ace Bob
500 9500
500 9500
{gamerTag:1
, score:-1}
"indexBounds" : {
"gamerTag" : [
"["Ace", "Ace"]"
],
"score" : [
"[inf.0, 9000.0)"
]
}

70. Matching games:
{ gamerTag: "Ace", score: 9500 },
{ gamerTag: "Ace", score: 500 },
{ gamerTag: "Bob", score: 9500 }
Non-matching games:
{ gamerTag: "Bob", score: 500 }
Query on games:
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
$or example

71. $or Venn Diagram (logical)
score: {$gt: 9000}gamerTag: "Ace"
{ gamerTag: "Ace",
score: 9500 }
{ gamerTag: "Ace",
score: 500 }
{ gamerTag: "Bob",
score: 9500 }
{ gamerTag: "Bob",
score: 500 }
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

72. $or Venn Diagram (logical)
score: {$gt: 9000}gamerTag: "Ace"
{ gamerTag: "Ace",
score: 9500 }
{ gamerTag: "Ace",
score: 500 }
{ gamerTag: "Bob",
score: 9500 }
{ gamerTag: "Bob",
score: 500 }
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

73. $or Venn Diagram (logical)
score: {$gt: 9000}gamerTag: "Ace"
{ gamerTag: "Ace",
score: 9500 }
{ gamerTag: "Ace",
score: 500 }
{ gamerTag: "Bob",
score: 9500 }
{ gamerTag: "Bob",
score: 500 }
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

74. $or Venn Diagram (logical)
score: {$gt: 9000}gamerTag: "Ace"
{ gamerTag: "Ace",
score: 9500 }
{ gamerTag: "Ace",
score: 500 }
{ gamerTag: "Bob",
score: 9500 }
{ gamerTag: "Bob",
score: 500 }
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

75. $or Venn Diagram (logical)
score: {$gt: 9000}gamerTag: "Ace"
{ gamerTag: "Ace",
score: 9500 }
{ gamerTag: "Ace",
score: 500 }
{ gamerTag: "Bob",
score: 9500 }
{ gamerTag: "Bob",
score: 500 }
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

76. $or Venn Diagram (logical)
score: {$gt: 9000}gamerTag: "Ace"
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

77. $or Venn Diagram (logical)
score: {$gt: 9000}gamerTag: "Ace"
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

78. $or Venn Diagram (logical)
score: {$gt: 9000}gamerTag: "Ace"
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

79. $or Venn Diagram (logical)
score: {$gt: 9000}gamerTag: "Ace"
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

80. $or Venn Diagram (logical)
score: {$gt: 9000}gamerTag: "Ace"
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

81. $or (single) Index visualization
Ace Bob
{gamerTag:1
, score:-1}
500 9500
500 9500
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

82. $or (single) Index visualization
Ace Bob
{gamerTag:1
, score:-1}
500 9500
500 9500
Expected Index Bounds:
"indexBounds" : {
"gamerTag" : [
"["Ace", "Ace"]"
],
"score" : [
"[inf.0, 9000]"
]
}
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

83. $or (single) Index visualization
Ace Bob
500 9500
500 9500
{gamerTag:1
, score:-1}
Expected Index Bounds:
"indexBounds" : {
"gamerTag" : [
"["Ace", "Ace"]"
],
"score" : [
"[inf.0, 9000]"
]
}
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

84. $or (single) Index visualization
Ace Bob
500 9500
500 9500
{gamerTag:1
, score:-1}
Expected Index Bounds:
"indexBounds" : {
"gamerTag" : [
"["Ace", "Ace"]"
],
"score" : [
"[inf.0, 9000]"
]
}
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

85. $or (single) Index visualization
Ace Bob
500 9500
500 9500
{gamerTag:1
, score:-1}
Expected Index Bounds:
"indexBounds" : {
"gamerTag" : [
"["Ace", "Ace"]"
],
"score" : [
"[inf.0, 9000]"
]
}
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

86. $or (single) Index visualization
Ace Bob
500 9500
500 9500
{gamerTag:1
, score:-1}
Expected Index Bounds:
"indexBounds" : {
"gamerTag" : [
"["Ace", "Ace"]"
],
"score" : [
"[inf.0, 9000]"
]
}
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

87. $or (single) Index visualization
Ace Bob
500 9500
500 9500
{gamerTag:1
, score:-1}
Expected Index Bounds:
"indexBounds" : {
"gamerTag" : [
"["Ace", "Ace"]"
],
"score" : [
"[inf.0, 9000]"
]
}
Actual (Hinted) Index Bounds:
"indexBounds" : {
"gamerTag" : [
"[MinKey, MaxKey]"
],
"score" : [
"[MaxKey, MinKey]"
]
}
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

88. $or (single) Index visualization
Ace Bob
500 9500
500 9500
{gamerTag:1
, score:-1}
Expected Index Bounds:
"indexBounds" : {
"gamerTag" : [
"["Ace", "Ace"]"
],
"score" : [
"[inf.0, 9000]"
]
}
Actual (Hinted) Index Bounds:
"indexBounds" : {
"gamerTag" : [
"[MinKey, MaxKey]"
],
"score" : [
"[MaxKey, MinKey]"
]
}
So is there anything we can do to
improve the performance of this query?
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

89. Recommendations
Use multiple indexes!
db.data.createIndex({gamerTag: 1})
db.data.createIndex({score: 1})

90. $or (multiple) Index visualization
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
Ace Bob
{gamerTag:1
, score:-1}
500 9500
500 9500

91. $or (multiple) Index visualization
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})

92. $or (multiple) Index visualization
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
Ace

93. $or (multiple) Index visualization
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
Ace Bob

94. $or (multiple) Index visualization
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
Ace Bob
{gamerTag:1}

95. $or (multiple) Index visualization
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
Ace Bob
{gamerTag:1}
500

96. $or (multiple) Index visualization
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
Ace Bob
{gamerTag:1}
500 9500

97. $or (multiple) Index visualization
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
Ace Bob
{gamerTag:1}
500 9500
{score:1}

98. $or (multiple) Index visualization
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
Ace Bob
{gamerTag:1}
500 9500
{score:1}
"indexBounds" : {
"gamerTag" : [
"["Ace", "Ace"]"
]
}
"indexBounds" : {
"score" : [
"(9000.0, inf.0]"
]
}

99. $or (multiple) Index visualization
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
Ace Bob
{gamerTag:1}
500 9500
{score:1}
"indexBounds" : {
"gamerTag" : [
"["Ace", "Ace"]"
]
}
"indexBounds" : {
"score" : [
"(9000.0, inf.0]"
]
}

100. $or (multiple) Index visualization
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
Ace Bob
{gamerTag:1}
500 9500
{score:1}
"indexBounds" : {
"gamerTag" : [
"["Ace", "Ace"]"
]
}
"indexBounds" : {
"score" : [
"(9000.0, inf.0]"
]
}

101. $or (multiple) Index visualization
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
Ace Bob
{gamerTag:1}
500 9500
{score:1}
"indexBounds" : {
"gamerTag" : [
"["Ace", "Ace"]"
]
}
"indexBounds" : {
"score" : [
"(9000.0, inf.0]"
]
}

102. $or (multiple) Index visualization
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
Ace Bob
{gamerTag:1}
500 9500
{score:1}
"indexBounds" : {
"gamerTag" : [
"["Ace", "Ace"]"
]
}
"indexBounds" : {
"score" : [
"(9000.0, inf.0]"
]
}

103. $or (multiple) Index visualization
db.games.find({
$or : [
{ gamerTag: "Ace" },
{ score: {$gt: 9000} }
]
})
Ace Bob
{gamerTag:1}
500 9500
{score:1}
"indexBounds" : {
"gamerTag" : [
"["Ace", "Ace"]"
]
}
"indexBounds" : {
"score" : [
"(9000.0, inf.0]"
]
}

104. Recommendations
Use multiple indexes!
db.data.createIndex({gamerTag: 1})
db.data.createIndex({score: 1})

105. Recommendations
Use multiple indexes!
db.data.createIndex({gamerTag: 1})
db.data.createIndex({score: 1})
We already have the {gamerTag:1, score:-1}
index, do we need both of these new ones?

106. Recommendations
Use multiple indexes!
db.data.createIndex({gamerTag: 1})
db.data.createIndex({score: 1})
We already have the {gamerTag:1, score:-1}
index, do we need both of these new ones?

107. Recommendations
Use multiple indexes!
db.data.createIndex({gamerTag: 1})
db.data.createIndex({score: 1})
Works with sorting
Generate a SORT_MERGE plan

108. Stakeholder Concern #2
db.games.find({
$or : [ { gamerTag: "Ace" }, { score: {$gt: 9000} } ]
})
Having the right index is critical

109. Stakeholder Concern #2
db.games.find({
$or : [ { gamerTag: "Ace" }, { score: {$gt: 9000} } ]
})
Having the right index is critical

110. Stakeholder Concern #2
db.games.find({
$or : [ { gamerTag: "Ace" }, { score: {$gt: 9000} } ]
})
Having the right index is critical
"Super!!”

111. Stakeholder Concern #3
“Wait wait wait, we can’t even FIND the gamers!”
A basic search on gamerTag takes several seconds already:
db.games.find({gamerTag: /Ace/i})
“This query is SLOWER with the index than it is without it!”

112. Case Insensitive

113. Case Sensitive
db.games.find({
gamerTag: /^Ace$/
})
//equivalent to
db.games.find({
gamerTag: “Ace”
})
Matching games:
{ gamerTag: "Ace", score: 9500 },
Non-matching games:
{ gamerTag: "ACE", score: 500 },
{ gamerTag: "aCe", score: 9500 },
{ gamerTag: "ace", score: 0 },
{ gamerTag: "Bob", score: 500 },
{ gamerTag: "acxyz", score: 9500 },
{ gamerTag: "Ace mdb", score: 9500 }

114. Case Sensitive
Matching games:
{ gamerTag: "Ace", score: 9500 },
Non-matching games:
{ gamerTag: "ACE", score: 500 },
{ gamerTag: "aCe", score: 9500 },
{ gamerTag: "ace", score: 0 },
{ gamerTag: "Bob", score: 500 },
{ gamerTag: "acxyz", score: 9500 },
{ gamerTag: "Ace mdb", score: 9500 }
ace aCe acxyz Ace
Ace
mdb
ACE Bob
"indexBounds" : {
"gamerTag" : [
"["Ace", "Acf")",
"[/^Ace$/, /^Ace$/]"
]
}

115. Case insensitive
db.games.find({
gamerTag: /^Ace$/i
})
//equivalent to
db.games.find({
gamerTag: {
$regex: “^Ace$”,
$options: “i”
}
})
//equivalent to
db.games.find({ gamerTag: “Ace”})
.collation({locale:’en’, strength:2})
Matching games:
{ gamerTag: "Ace", score: 9500 },
{ gamerTag: "ACE", score: 500 },
{ gamerTag: "aCe", score: 9500 },
{ gamerTag: "ace", score: 0 }
Non-matching games:
{ gamerTag: "Bob", score: 500 },
{ gamerTag: "acxyz", score: 9500 },
{ gamerTag: "Ace mdb", score: 9500 }

116. Case insensitive
db.games.find({
gamerTag: /^Ace$/i
})
//equivalent to
db.games.find({
gamerTag: {
$regex: “^Ace$”,
$options: “i”
}
})
//equivalent to
db.games.find({ gamerTag: “Ace”})
.collation({locale:’en’, strength:2})
Matching games:
{ gamerTag: "Ace", score: 9500 },
{ gamerTag: "ACE", score: 500 },
{ gamerTag: "aCe", score: 9500 },
{ gamerTag: "ace", score: 0 }
Non-matching games:
{ gamerTag: "Bob", score: 500 },
{ gamerTag: "acxyz", score: 9500 },
{ gamerTag: "Ace mdb", score: 9500 }
Would a $text search be the same as
well?

117. Case INsensitive
Matching games:
{ gamerTag: "Ace", score: 9500 },
{ gamerTag: "ACE", score: 500 },
{ gamerTag: "aCe", score: 9500 },
{ gamerTag: "ace", score: 0 }
Non-matching games:
{ gamerTag: "Bob", score: 500 },
{ gamerTag: "acxyz", score: 9500 },
{ gamerTag: "Ace mdb", score: 9500 }
ace aCe acxyz Ace
Ace
mdb
ACE Bob
"indexBounds" : {
"gamerTag" : [
“["", {})",
"[/^Ace$/i, /^Ace$/i]"
]
}

118. Recommendations
Case insensitive index!
Collations available since 3.4

119. Recommendations
Case insensitive index!
Collations available since 3.4
db.games.createIndex( { gamerTag: 1},
{ collation: { locale: 'en', strength: 2 } } )

120. Recommendations
Case insensitive index!
Collations available since 3.4
db.games.createIndex( { gamerTag: 1},
{ collation: { locale: 'en', strength: 2 } } )
> db.games.find( { gamerTag: "Ace"}).collation( { locale: 'en', strength: 2 } )

121. Recommendations
Case insensitive index!
Collations available since 3.4
db.games.createIndex( { gamerTag: 1},
{ collation: { locale: 'en', strength: 2 } } )
> db.games.find( { gamerTag: "Ace"}).collation( { locale: 'en', strength: 2 } )
{ "_id" : ObjectId("5b29dbee6c7d4f531bf73b5d"), "gamerTag" : "Ace", "score" : 9500 }
{ "_id" : ObjectId("5b29dbee6c7d4f531bf73b5e"), "gamerTag" : "ACE", "score" : 500 }
{ "_id" : ObjectId("5b29dbee6c7d4f531bf73b5f"), "gamerTag" : "aCe", "score" : 9500 }
{ "_id" : ObjectId("5b29dbee6c7d4f531bf73b60"), "gamerTag" : "ace", "score" : 0 }

122. Recommendations
Case insensitive index!
Collations available since 3.4
db.games.createIndex( { gamerTag: 1},
{ collation: { locale: 'en', strength: 2 } } )
Store a transformed (eg toLower()) copy of the string

123. Stakeholder Concern #3
db.games.find({gamerTag: “Ace”})
.collation({locale:'en', strength:2})

124. Stakeholder Concern #3
db.games.find({gamerTag: “Ace”})
.collation({locale:'en', strength:2})

125. Stakeholder Concern #3
db.games.find({gamerTag: “Ace”})
.collation({locale:'en', strength:2})
“Wow, MongoDB can do anything!!!!1!”

126. Summary

127. Work Smarter Not Harder
• Understand the business logic
• Index appropriately
• Is it the right index to support the query?
• Be aware of:
• Blocking Stages
• Usage of $or
• Case sensitivity
• Leverage the Performance Advisor

128. Work Smarter Not Harder
• Understand the business logic
• Index appropriately
• Is it the right index to support the query?
• Be aware of:
• Blocking Stages
• Usage of $or
• Case sensitivity
• Leverage the Performance Advisor

129. Countdown to ShortFite
Powered by an optimized MongoDB
environment, ShortFite is sure to be a hit!

130. Queries?

131. Results

132. Before/After metrics comparison

133. Questions?