Come and hear more about our new full-text search operator for MongoDB Atlas. This is a significant enhancement to MongoDB search features and is the easiest and most powerful full-text search solution for databases on MongoDB Atlas. This talk is important for anyone who has implemented search or is considering a search feature in their MongoDB application. You will see a demo of $searchBeta, learn about how it works, discover specific features to help you deliver relevant search results, and learn how you can start using full-text search in your application today.

1. #MDBlocal#MDBlocal
Still Haven’t Found What You’re Looking For?
Use MongoDB’s Full Text Search
Karen Huaulmé, Developer Advocate
YOUOLDMAID
MUNICH

2. #MDBLocal#MDBLocal
Safe Harbor Statement
This presentation contains “forward-looking statements” within the meaning of Section 27A of the Securities Act of
1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. Such forward-looking
statements are subject to a number of risks, uncertainties, assumptions and other factors that could cause actual
results and the timing of certain events to differ materially from future results expressed or implied by the
forward-looking statements. Factors that could cause or contribute to such differences include, but are not limited
to, those identified our filings with the Securities and Exchange Commission. You should not rely upon forward-
looking statements as predictions of future events. Furthermore, such forward-looking statements speak only as
of the date of this presentation.
In particular, the development, release, and timing of any features or functionality described for MongoDB
products remains at MongoDB’s sole discretion. This information is merely intended to outline our general product
direction and it should not be relied on in making a purchasing decision nor is this a commitment, promise or legal
obligation to deliver any material, code, or functionality. Except as required by law, we undertake no obligation to
update any forward-looking statements to reflect events or circumstances after the date of such statements.

3. #MDBLocal#MDBLocal
{
“name”: “Karen Huaulmé”,
“MongoDB”: {
“positions”: [“Developer Advocate”, “Solutions Architect”],
“since” : new Date (“2018-01”),
},
“Pre-MongoDB”: {
“positions”: [“Solutions Architect”, “Integration Engineer”, “Dev Rel”],
“companies”: [ “Twitch”, “Amazon”, “Nvidia”]
},
“likes”: [“running”, “gleitschirmfliegen”, “butchering languages” ]
}
About Me

4. #MDBLocal#MDBLocal
AGENDA
Why Full
Text
Search?
Atlas
Search
Features
Demos &
How it
works
Architecture

5. Why Full-Text Search?
Search is a requirement
for most applications

6. #MDBLocal#MDBLocal
Why didn’t
[thing I want]
show up first?

7. #MDBLocal#MDBLocal
Developer: “This result doesn’t
match the most terms.”
Marketing: “Why isn’t the promo on
top?”
Product: “Just get rid of junk
results.”
CEO: “Change the top result right
NOW!”
Customer: “Je ne trouve pas ce que
je cherche…”
Relevance is Complicated…

8. #MDBLocal#MDBLocal
RelevanceisCritical

9. #MDBLocal#MDBLocal
So, build the best
search for your
application
$searchBeta

10. Searching with $text
db.movies.find(
{ $text : { $search : ‘football’ }},
{ score : { $meta : ‘textScore’ }},
{ title : 1, fullplot : 1 })
.sort({ score : {$meta : ‘textScore’ }})
.pretty()

11. #MDBLocal#MDBLocal
Sync

12. Features
What can you do with $searchBeta?

13. #MDBLocal#MDBLocal
Atlas Search Features
Native
Powered by
Performant
Text Indexes
Powerful
Query
Operators
Configurable
Language
Analyzers
Built-in
Highlighting
Flexible
Scoring

14. #MDBLocal#MDBLocal
MongoDB +
• Pre-existing functionality
• Highlights, Fuzzy-matching, Query-time scoring and
more
• Analyzers
• Language support
• Western languages: English, French, etc.
• Eastern Languages: CJK, bigram/unigram support
• Inverted index structure = fast searches

15. #MDBLocal#MDBLocal
DEMO:
Movie Search Engine
http://bit.ly/AtlasSearch_Movies
Atlas Sample Data:
- sample_mflix.movies

16. #MDBLocal#MDBLocal
How do I use it?
Create a cluster
on MongoDB
Atlas 4.2 RC
(M30+)
Create a
database and
collection
Create a full text
index on that
collection in
Atlas
Query via
$searchBeta
aggregation
pipeline

17. #MDBLocal#MDBLocal
Full Text Search Index
Creation
Dynamic Mapping
Static Mapping

18. $searchBeta aggregation pipeline stage
db.movies.aggregate([
{ $searchBeta: {
search: { query : ’football',
path : ‘fullplot’ },
highlight: { path : 'fullplot’ }}},
{ $project: {
fullplot: 1,
title: 1,
score: { $meta: 'searchScore' },
highlight: { $meta: 'searchHighlights’. }}},
{ $limit: 10 }
])

19. $searchBeta aggregation pipeline stage
{ $searchBeta : {
search : { query : ‘football’ ,
path : 'fullplot’
},
highlight : { path:'fullplot’ }}},

20. $searchBeta aggregation pipeline stage
{ $project: {
fullplot: 1,
title: 1,
score: { $meta: 'searchScore' },
highlight: { $meta: 'searchHighlights’ }}},
{ $limit: 10 }
])
$meta
$limit

21. $searchBeta Results
{ title : { “The Football Factory”,
score : 18.341075897216797,
highlight: [[{
path : 'fullplot’,
texts: [{ value : “The”
type : “text” },
{ value : “Football”
type : “hit” },
{ value : “Factory is more than just a study of the English…”
type : “text” },
score : 1.564455
])
texts.value
texts.type

22. Query-Time Scoring
Pre - Atlas Search
db.movies.aggregate([
{ $match: {
"title": "The Godfather"
}},
{ $sort : { title: 1 }}
$searchBeta in Atlas Search
db.movies.aggregate([
{ $searchBeta : {
"search": {
query : "The Godfather",
path: "title",
score: { boost: { value: 3 }}
])
Sort occurs after filter Sort occurs during filter

23. Query-Time Scoring
db.movies.aggregate([
{ $searchBeta : { compound : {
must : {
"search": { query : "The Godfather",
path : "title",
score : { boost : { value : 3 }}},
should : {
"search": { query : "The Godfather",
path : "fullplot" }
])

24. #MDBLocal#MDBLocal
DEMO:
Build a Champion
Football Team

25. #MDBLocal#MDBLocal

26. #MDBLocal#MDBLocal

27. #MDBLocal#MDBLocal
Placeholder –
photos from the Arsenal Match
Mbappé

28. #MDBLocal#MDBLocal
Messi

29. #MDBLocal#MDBLocal
Zidane

30. #MDBLocal#MDBLocal
Schweinsteiger

31. #MDBLocal#MDBLocal
Rooney

32. #MDBLocal#MDBLocal
Rafael Nadal

33. #MDBLocal#MDBLocal
Placeholder –
photos from the Arsenal Match

34. #MDBLocal#MDBLocal
Zlatan Ibrahimović

35. #MDBLocal#MDBLocal
DEMO:
Build a Champion
Football Team

37. What we just saw
Type-ahead – function – actually wasn’t complicated – phrase – the front of that phrase
Fuzzy matching
Wildcard…

38. #MDBLocal#MDBLocal
Index defintions
Static and Dynamic
Multi-mapping – alternative index mechanisms
Talk about Analyzers
Index Definitions

39. #MDBLocal#MDBLocal
Analyzers
Specialized Text Processors
Language specific
Various Content Formats

40. #MDBLocal#MDBLocal
Advanced Search
Features

41. "compound": {
“must” : {},
"mustNot": {},
”filter” : {},
"should": []
}
compound: operator – complex recursive queries
Must Match (scored)
Must not match(not scored)
Must match(not scored)
Should match(scored)
Operators can be other operator: [term, span, search, queryString, exists, or even
another compound]

42. Architecture
How FTS works on MongoDB Atlas

43. #MDBLocal#MDBLocal
MongoDB +
• Pre-existing functionality
• Highlights, Fuzzy-matching, Query-time scoring and
more
• Analyzers
• Language support
• Western languages: English, French, etc.
• Eastern Languages: CJK, bigram/unigram support
• Inverted index structure = fast searches

44. #MDBLocal#MDBLocal
Inverted Index
{ _id: 1,
S: “The quick brown fox jumped over the lazy dog” }
{ _id: 2,
S: “Quick brown foxes leap over lazy dogs in summer” }
TERM DOC
The 1
Quick 2
brown 1, 2
dog 1
dogs 2
jumped 1
leap 2
TERM DOC
the 1
brown 1, 2
dog 1, 2
fox 1, 2
in 2
jump 1, 2
over 1, 2
STEMMING,SYNONYMS

45. #MDBLocal#MDBLocal
Inverted Indexing and Analyzers
“_id”: 3,
“title” : “Planes, Trains & Automobiles”
{
“planes” : [3, …],
“trains” : [3, …],
“automobiles” : [3, … ]
},
lucene.simple lucene.english
{
“plane” : [3, …],
“train” : [3, …],
“automobile” : [3, …],
}
lucene.keyword
{
“Planes, Trains &
Automobiles” : [3, …]
},

46. #MDBLocal#MDBLocal
Querying and Analyzers
search: { query: “planes trains”,
path: “title” }
term(“plane”) OR
term(“train”)
term: { query: “planws”,
path: { value: “title”,
multi: ”simple”},
fuzzy: {maxEdits: 1 } }
Fuzzy(“planws”,
maxEdits: 1)
term: { query: “Planes(.*)”,
path: { value: “title”,
multi: ”keyword”},
regex: true} }
Regex(“Planes(.*)”
lucene.keyword lucene.simple lucene.english

47. #MDBLocal#MDBLocal
MongoDB Atlas FTS components
mongod mongos mongot (NEW!)
● $searchBeta aggregation
pipeline stage
● Talks mongodb wire protocol to
mongot
● Shard aware implementation
● scatter-gather queries
● Based on Apache Lucene 8
● Integrated into MongoDB Atlas
● Separate java process from
mongod
● collocated with mongod

48. #MDBLocal#MDBLocal
FTS Indexing: Initial Sync
MongoDB Atlas
Query
Index Definition
Automation Agent
mongotmongod
Collection Scan
Complete!

49. #MDBLocal#MDBLocal
FTS Indexing: Steady State
Documents
mongotmongod
changestream
MongoDB Atlas
(per node)
mongot watches
the changestream
continuously and
updates the
search index

50. #MDBLocal#MDBLocal
Query Lifecycle
Wire Protocol
(over internet to
MongoDB Atlas) aggregate([ {$searchBeta: {
search: {
path: “name”,
query: “star wars”
}
}}]
mongod
Wire protocol
(localhost)
Lucene booleanQuery:
(should
(term(“name”, “star”),
term(“name”, wars”))
search: {
path: “name”,
query: “star wars”
}
[ { _id: “123”,score:
1.23,highlights: […] },
{…}]
{ “name” :
{ “star” : [123,124],
“wars” :
[123,125,…]}}
Lookup([{_id: “123”],
{…}])
mongot
db.col.aggregate([
{$searchBeta: {
search: {
path: “name”,
query: “star wars”
}
}}])
app
[ { _id: “123”, title:
“Star Wars”}, {…}]
MongoDB Atlas Host

51. #MDBLocal#MDBLocal
Sharding
• Merge
• Sort by score
mongos
request
result
per shard
per shard
• Scatter/gather
(each shard)
mongot,
mongod
mongot,
mongod
Primary Secondaries
Query

52. What’s next?
Feature Roadmap

53. #MDBLocal#MDBLocal
Ø Expanded data type support
Nums, dates, geo
Ø Synonyms
Ø Improved operators/syntax
Ø Architecture & performance
improvements
2019 Roadmap
We’d love to hear from YOU!

54. #MDBLocal#MDBLocal
Feedback

55. DEMODEMO
http://bit.ly/AtlasSearch_Movies
YouOldMaid
THANK YOU

56. Questions?
kwh@mongodb.com
YouOldMaid

57. THANK YOU