MongoDB .local Munich 2019: Tips and Tricks++ for Querying and Indexing MongoDB

1. WHEN WHERE Tips and Tricks++ for Querying and Indexing MongoDB Dr. Christian Kurze, Principal Solutions Architect 22 October 2019, 03:00 – 3:45PM Room 1

2. #MDBLocal

3. #MDBLocal Is there anything new about indexes in MongoDB 4.2 that I should be aware of?

4. #MDBLocal { "_id" : ObjectId("5c1d358bf383fbee028aea0b"), "product_name" : "Blaster Gauntlet", "product_attributes" : { "elements" : [ "Fire" , "Water" ], "price" : 250 ... } }, { "_id" : ObjectId("5c1d358bf383fbee028aea0c"), "product_name" : "Super Suit", "product_attributes" : { "superFlight" : true, "resistance" : [ "Bludgeoning", "Piercing", "Slashing" ] ... }, } Wildcard Indexes Allow more natural data modeling, avoids pre-defining indexes for every access pattern Polymorphic document structures: Product catalogs, CMS Ad-hoc queries & data exploration Define a filter that indexes all matching fields, sub-documents, and arrays Sparse index, omit specific fields Covered queries & collations Strongly consistent: updated atomically with base data Index all sub-documents & arrays under Product Attributes

5. #MDBLocal I identified slow queries. What index do I make?

6. #MDBLocal Roadmap E-S-R Overview Guidelines: • Eà R • Eà S • Sà R E-S-R Considerations Operator Type Checks Consecutive Index Keys Exceptions?

8. Equality Sort Range "Rule"

9. #MDBLocal E-S-R The ordering of index keys in a compound index is critically important.

10. #MDBLocal E-S-R The ordering of index keys in a compound index is critically important. Does it really matter?

11. #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

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 What is the difference between Equality and Range?

13. #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]"

14. #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]"

15. #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]", 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 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.

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. Why?

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. db.games.find( {gamertag: "Ace", score: {$gt: 9000}} )

20. #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

21. #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}

22. #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 db.games.createIndex({score:1, gamertag:1})

23. #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})

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"]" ] } gamertag 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 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

34. #MDBLocal Ace Bob Bob Ace db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) 100 99,999 15,000 50,000 {} {} {} {} Equality db.games.createIndex({gamertag:1, score:1})

35. #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})

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]" ], } gamertag 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 score db.games.createIndex({gamertag:1, score:1})

41. #MDBLocal db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) R E R E Equality before Range

43. #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

44. #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})

45. #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})

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 {1} {} {} {2} 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 "indexBounds" : { "score" : [ "[MinKey, MaxKey]" ], "gamertag" : [ "["Ace", "Ace"]" ] } 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})

53. #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} )

61. #MDBLocal Sort Ace Bob Bob Ace 100 99,999 15,000 50,000 {1} {2} {} {} db.games.find( {gamertag: "Ace"} ).sort( {score: 1} ) db.games.createIndex({gamertag:1, score:1})

62. #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 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 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

72. #MDBLocal db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) R E R E Range after Equality

73. #MDBLocal db.games.find( {gamertag: "Ace", score: {$gt: 9000}} ) R E R E Range after Equality Should range come after sort too?

74. #MDBLocal R E R E Range after Equality Should range come after sort too? db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})

75. #MDBLocal R E R E Range db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1})

76. #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})

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 Cali 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 {} {} {} {}{1}{2} {3} gamertag score db.games.createIndex({ …, score:1, gamertag:1})

80. #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 {2} {3} {1} db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range Blocking SortBlocking Sort BS

91. #MDBLocal {2}{3}{1} db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range BS

92. #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

93. #MDBLocal db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range * Ace Bob Cali Ace 100 15,000 50,00099,999 {} {1} {2} {3} db.games.createIndex({ …, gamertag:1, score:1})

94. #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 BS R S R S db.games.find({*, score: {$gt: 9000}}).sort({gamertag: 1}) Range after Sort

107. #MDBLocal Operator Type Check Some operators are simple $eq: Equality $gte: Range Others are trickier

108. #MDBLocal Operator Type Check - Inequality Inequality Operators: E, S, or R? • $ne:123 • $nin:[1,2] Range!

109. #MDBLocal Operator Type Check - Inequality Inequality Operators: E, S, or R? • $ne:123 • $nin:[1,2] Range! How do you know?

110. #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]" ] }

111. #MDBLocal Operator Type Check - Inequality Range! "indexBounds" : { "x" : [ "[MinKey, 123.0)", "(123.0, MaxKey]" ] } 50 123 999

114. #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! planecar racecar

119. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range! p???ecar racecar

120. #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! raincarry

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 Carpool

127. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range! raincarry Carpool Since the regex is left anchored, can’t we skip the middle tree?

128. #MDBLocal Operator Type Check - Regex Regex Operators: E, S, or R? • {str:/car/} • {str:/^car/i} Range! raincarry Carpool 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! cArrycarry Carpool 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 Carpool 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 Carpool

132. #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

133. #MDBLocal Operator Type Check - $in .find({field:{$in:[1,3]}})

134. #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]}}) .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})

141. #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 BS 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}) ? 1 2 3 C G B F A D 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}) "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]" ] } "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})

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 ? 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 {2} {4} {1} {3} Sort Merge db.coll.createIndex({field:1, sortField:1})

159. #MDBLocal BS S M Operator Type Check - $in

161. #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” })

162. #MDBLocal Consecutive Index Keys .find({ gamertag:"Ace", game: "Halo” })

163. #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})

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” }) "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})

176. #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, date:1, game:1})

177. #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, date:1, game:1})

178. #MDBLocal R E E E E E E Consecutive Index Keys R Look familiar? This is equality after range!

180. #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})

181. #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})

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 {} {} {} "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "score" : [ "[MinKey, MaxKey]" ], "date" : [ "[2019.0, inf.0]" ] } {1} {2} db.games.createIndex({gamertag:1, score:1, date:1})

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 {} {} {} "executionStats" : { "nReturned" : 2, "executionTimeMillis" : 23, "totalKeysExamined" : 9001, "totalDocsExamined" : 2, {1} {2} db.games.createIndex({gamertag:1, score:1, date:1})

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

198. #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 db.games.createIndex({gamertag:1, date:1})

199. #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 "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[2019.0, inf.0]" ] } db.games.createIndex({gamertag:1, date:1})

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} 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, "indexBounds" : { "gamertag" : [ "["Ace", "Ace"]" ], "date" : [ "[2019.0, inf.0]" ] } db.games.createIndex({gamertag:1, date:1})

205. #MDBLocal Exceptions ……… … BS S R E R E

206. Summary

207. #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: • Indexing is important from day one, things get slow as the data grows • 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 M201: Performance in MongoDB university.mongodb.com

208. THANK YOU

MongoDB .local Munich 2019: Tips and Tricks++ for Querying and Indexing MongoDB

MongoDB .local Munich 2019: Tips and Tricks++ for Querying and Indexing MongoDB

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MongoDB .local Munich 2019: Tips and Tricks++ for Querying and Indexing MongoDB