1. The document describes using ElasticSearch to search for hotels that meet certain criteria, providing a more flexible approach than SQL. 2. It explains how ElasticSearch allows storing and querying structured and unstructured data using a document-oriented model with an inverted index. 3. Key features discussed include ElasticSearch's distributed architecture, RESTful API, relevance scoring, and ability to handle requirements and preferences more intelligently than SQL.

1. Discovering+Elas/cSearch

2. A"li%le"about"me

3. 23#years#old

4. Jess'%boyfriend

5. Zoe's&dad

6. Mountain(biker

7. Scuba&diver

8. Scuba&biker?

9. Mar$al&Arts&Instructor

10. I'm$also$a$developer.
I"run"a"development"agency"in"Australia,"
Webcomm

11. Finally,(I'm(a(Laracon'addict
who$has$travelled
132,000&km
a"third"of"the"distance"to"the"moon.

12. Flashcard
• @ben_corle+
• h+p://github.com/bencorle+
• h+p://webcomm.com.au

13. Search'is
filtering!informa)on
and$determining$relevance

14. Picture(this(scenario

15. "I#want#to#find#hotels#called#
Renaissance#for#under+€150,#within+
500m+of+Bimhuis#so#I#am#close#to#
Laracon#EU#2014.#The#hotel#needs#to#
have#disability+access#and#ideally#
provide#Wifi#and#have#rooms#above+
ground+level."

16. Requirements
1. Name'of'hotel'called'Renaissance.
2. Under'€150.'1
3. Within'500m'of'Bimhuis.'1
4. Disability'access.
1"Perceived"requirements"may"be"flexible.

17. Wants
1. Wifi.&1
2. Rooms&above&ground&level.
1"Let's"be"honest,"this"should"be"a"requirement";)

18. If!search!is!filtering!informa1on!and!
determining!relevance
And!humans!think!with!expression!and!
emo2on,!why!do!your!apps!operate!like!
robots?
How!can!we!tailor!our!apps!to!think!like!our!
users?

19. Use$the$right$toolset;$and
Know%your%data.

20. Introducing+Elas0cSearch

21. Elas%cSearch
1. Powerful+search+and+analy3cs+engine.+1
2. Object;based+document+store+where+every+field+is+indexed+and+
searchable.
3. Distributed;+ready+to+scale.+2
1"Elas'cSearch"may"be"used"for"much"more"than"just"a"search"engine.
2"Webscalez"FTW"(trollolol).

22. SQL$vs.$Elas+cSearch

23. SQL$and$Elas+cSearch;$a$comparison
• SQL%is%a%rela,onal%database,%Elas,cSearch%is%a%search%engine.
• Where%SQL%is%great%at%filtering%on%a%binary%level,%Elas,cSearch%
thrives%on%both%binary%data%and%full%text%relevance.
• SQL%indexes%are%always%up%to%date%with%your%primary%store,%
Elas,cSearch%needs%to%be%synced.
• Elas,cSearch%is%very%easy%to%horizontally%scale%for%performance%
and%redundancy.

24. SQL$and$Elas+cSearch;$a$comparison
SQL$uses$the$following$structure$for$its$data$store:
database > table > row
Elas%cSearch+has+a+different,+yet+comparable+structure:
index > type > document

25. Elas%cSearch+101

26. It's%all%about%documents
1. Elas'cSearch-is-document5oriented.
2. Documents-are-represented-using-JSON.
3. Data-can-be-in-nested-JSON-objects,-arrays-and-is-all-searchable.

27. It's%all%about%documents
{
"name": "Renaissance Hotel Amsterdam",
"company": "Marriott",
"location": [52.3712561, 4.9005577],
"floor_levels": 6,
"features": [
"disability_access",
"wifi",
"smoking_allowed",
"pool"
]
}

28. Elas%cSearch+Requires
Java
You$have$3$seconds$to$sulk$and$complain,$then$shutup.

29. Installa'on)is)easy
1. Install)Java.
2. Download)and)run)Elas4cSearch)in)3)bash)commands.)1
3. Debian)or)RPM)packages)available.
4. Puppet)&)chef)scripts)available.
1"h$p://www.elas.csearch.org/guide/en/elas.csearch/reference/
current/_installa.on.html

30. Scaling(isn't(scary
1. Near'zero*configura0on*to*build*a*cluster*of*Elas0cSearch*
instances.
2. Easy*to*scale*horizontally.
3. Each*Elas0cSearch*instance*is*referred*to*as*a*node.
4. Any*node*is*capable*of*handling*any*request*and*delega0ng*load.

31. In#very#basic#terms,#horizontal*scaling#is#adding
more%servers
to#build#a#cluster,#or#cloud...

32. ...where&ver$cal(scaling&is&throwing
more%resources
at#an#individual#server.

33. Elas%cSearch+exposes+a
RESTful(API

34. Win.

35. Communica)ng+with+Elas)cSearch
1. HTTP&verbs&,&GET,&POST,&PUT,&DELETE,&etc...
2. Send&&&receive&JSON&payloads.
:VERB /:index/:type/:document
{
"key": "value",
"complex": ["foo", "bar"]
}

36. Crea%ng(a(document
POST /myapp/hotel
{
"name": "Renaissance Hotel Amsterdam",
"company": "Marriott",
"location": [52.3712561, 4.9005577],
"floor_levels": 6,
"features": [
"disability_access",
"wifi",
"smoking_allowed",
"pool"
]
}

37. Upda%ng(a(document
PUT /myapp/hotel/1 # ^1
{
"name": "Renaissance Hotel Amsterdam",
"company": "Marriott",
"location": [52.3712561, 4.9005577],
"floor_levels": 10,
"features": [
"disability_access",
"wifi",
"pool",
"restaurant"
]
}
1"Actually"an"upsert;"create"or"update"depending"on"existance.

38. Dele$ng'a'document
DELETE /myapp/hotel/1

39. There's'lots'more'to'documents
1. Par&al(document(upda&ng.
2. Document(versioning.
3. Conflict(resolu&on(for(distributed(documents.
4. Bulk(CRUD(methods(to(avoid(HTTP(boEleneck.
See#h%p://www.elas.csearch.org/guide/en/elas.csearch/reference/
current/docs.html

40. Elas%cSearch+makes
searching*fun

41. Searching*in*Elas.cSearch
1. Every(single(field(can(be(searchable.
2. Perform(structured(queries(or(filters,(against(fields.1
3. Perform(full(text(queries(to(find(documents.
4. Queries(and(filters(represented(using(JSON.
5. Organise(results(by(relevance.
1"SQL&like"approach.

42. Index
1. Index&(noun)#$#refers#to#the#equivalent#of#a#database#in#an#SQL#
system.
2. Index&(verb)#$#refers#to#the#process#of#storing(a(document#in#an#
index.
3. Inverted&index#$#list#of#all#terms#inside#Elas@cSearch#and#the#
documents#in#which#they#appear.

43. Analysis
• Character(filters"simplify"data,"such"as"changing:
• "&""to""and".
• "é""to""e".
• Data"is"split"into"terms"through"a"process"called"tokenisa1on.

44. Analysis
• Token&filters"tweak"and"normalise"terms,"such"as:
• Cast"to"lowercase.
• Remove&stop3words"like""a""or""the"
• Add"synonyms.

45. Inverted(index
1. Analysis#process#extremely#configurable.1
2. Mul7lingual#support#(33#languages#in#total),#interchangeable#per#
index.
3. Any#fields#not#indexed#are#not#searchable.
4. The+same+analysis+process+occurs+at+search+3me.
1"h$p://www.elas.csearch.org/guide/en/elas.csearch/reference/
current/analysis.html

46. Example(inverted(index
Consider)the)two)following)sentences:
"The%quick%brown%fox%jumped%over%the%lazy%dog"
"Quick%brown%foxes%leap%over%lazy%dogs%in%summer"

47. Example(inverted(index
Term Doc_1 Doc_2
-------------------------
brown | X | X
dog | X | X
fox | X | X
in | | X
jump | X | X
lazy | X | X
over | X | X
quick | X | X
summer | | X
the | X | X
------------------------

48. Scoring
1. Term%frequency#$#the#more#o+en#a#term#appears#in#a#field,#the#
more%relevant.
2. Inverted%document%frequency#$#the#more#o+en#a#term#appears#
in#the#inverted#index,#the#less%relevant.
3. Field%length%norm#$#the#longer#the#field,#the#less#relevant#each#
term#in#it#is.

49. Scoring
1. Fields)are)"boostable")to)increase)relevance.
2. Func5ons)(inbuilt)and)scripted))can)be)used)to)increase/decrease)
relevance.
3. Altering)analysis)to)fine?tune)scoring.
4. Very)important)to)know%your%data.

50. Queries'and'filters
1. Both'are'modular;'think'of'building(blocks.
2. Both'can'be'nested'inside'one'another.
3. Syntax'does'not'change,'regardless'of'posi?on'or'nes?ng.
4. En?re'JSON'object'is'the'Elas/cSearch(Query(DSL.

51. Querying)in)Elas.cSearch
1. There'37'queries'(as'of'August'2014).'1
2. Queries'are'intelligent;'they'score'all'results'according'to'a'
relevance'algorithm.
3. Any'nesBng'passes'relevance'back'to'parents.
1"h$p://www.elas.csearch.org/guide/en/elas.csearch/guide/current/
relevance9intro.html

52. Filters
1. You&will&find&27&filters&(as&of&August&2014).&1
2. Filters&are&binary;&either&a&field&matches&or&it&doesn't.
3. Filters&don't&affect&relevance&scoring.
1"h$p://www.elas.csearch.org/guide/en/elas.csearch/reference/
current/query;dsl;filters.html

53. Querying)in)Elas.cSearch
GET /myapp/hotel/_search
{
"query": {
"match": "Renaissance"
}
}
This%is%a%match%query.%It%is%the%go1to%full%text%query.

54. Querying)in)Elas.cSearch
GET /myapp/hotel/_search
{
"query": {
"filtered": {
"filter": {
"term": {
"features": "disability_access"
}
}
}
}
}
This%is%a%filtered%query,%containing%a%term%filter.

55. Back%to%our%scenario

56. "I#want#to#find#hotels#called#
Renaissance#for#under+€150,#within+
500m+of+Bimhuis#so#I#am#close#to#
Laracon#EU#2014.#The#hotel#needs#to#
have#disability+access#and#ideally#
provide#Wifi#and#have#rooms#above+
ground+level."

57. Two$approaches
1. Possible*with*both*SQL*and*Elas5cSearch.
2. Much*easier*Elas5cSearch.
3. Elas5cSearch*understands*the*concept*of*relevance.
4. Elas5cSearch*can*severely*outperform*SQL.

58. SQL$approach

59. First,'we'll'build'the'obvious...
select *
from `hotels`
where `name` like "%Renaissance%"
and `price` <= 150
and `disability_access` = 1

60. Performance*&*relevance
Consider)the)following:
select *
from `hotels`
where `name` like "%Renaissance%"
1. This'query'will'be'slow.
2. This'query'accounts'for'terms'which'contain'the'(correctly)'spelt'
Renaissance.

61. Full$text$search
1. Add%a%full%text%index.%1
2. Alter%the%query,%and%search%across%both%name%and%company.
select *
from `hotels`
where match (`name`, `company`) against ("Renaissance")
and `price` <= 150
and `disability_access` = 1
1"h$p://dev.mysql.com/doc/refman/5.0/en/fulltext<search.html

62. Checklist
1. Name'of'hotel'called'Renaissance
2. Under'€150.
3.Within&500m&of&Bimhuis.
4. Disability'access.
5.Wifi.
6. Above&ground&level.

63. Adding&"wants"&in
select *, if (`floor_levels` > 1, 1, 0) as `has_multiple_floor_levels`
from `hotels`
where match (`name`, `company`) against ("Renaissance")
and `price` <= 150
and `disability_access` = 1
order by `wifi` desc, `has_multiple_floor_levels` desc -- ^1
1"We're"priori*sing"Wifi"over"mul*ple"floor"levels...

64. Checklist
1. ~Name(of(hotel(called(Renaissance.
2. Under(€150.
3.Within&500m&of&Bimhuis.
4. Disability(access.
5. Wifi.
6. Rooms(above(ground(level.

65. Spacial'awareness...
1. Not&so&easy.
2. PostGIS&for&PostgreSQL.&1
3. Possible&with&MySQL&with&MyISAM&tables&only.&2
4. Very&finite;&either&a&match&or&not&a&match.
5. Outside&the&scope&of&this&talk.
1"h$p://postgis.net
2"Possible"with"other"engines"in"new"versions"of"MySQL

66. Checklist
1. ~Name(of(hotel(called(Renaissance.
2. Under(€150.
3. Within(500m(of(Bimhuis.
4. Disability(access.
5. Wifi.
6. Rooms(above(ground(level.

67. What%if...
1. Somebody*searched*for*"Residence*Inn"*as*the*hotel*name?
2. There*was*an*appropriate*hotel*for*€151?
3. A*brilliant*candidate*could*be*found*501m*away*from*Bimhuis?
4. Somebody*cared*more*haveing*rooms*above*ground*level*than*
being*provided*Wifi?

68. Elas%cSearch+approach

69. Popula'ng*Elas'cSearch
POST /myapp/hotel
{
"name": "Renaissance Hotel Amsterdam",
"company": "Marriott",
"location": [52.3712561, 4.9005577],
"floor_levels": 10,
"features": [
"disability_access",
"wifi",
"pool",
"restaurant"
]
}
Rince&and&repeat&for&as&many&hotels&as&required

70. The$bool$query
{
"bool": {
"must": {},
"must_not": {},
"should": {}
}
}
We#specify#condi-ons#which#must#and#must%not#match.#Terms#that#
should#match#make#a#document#more#relevant.

71. Prepare&a&bool&query
{
"bool": {
"must": {
"multi_match": {"query": "Renaissance", "fields": ["name^2", "company"]},
"term": {"features": "disability_access"},
},
"should": {
"term": {"features": "wifi"},
"range": {"floor_levels": {"gt": 1}}
}
}
}
A"field"boost"of"2"was"applied"to"name"to"increase"relevance.

72. Checklist
1. ~Name(of(hotel(called(Renaissance.
2. Under&€150.
3.Within&500m&of&Bimhuis.
4. Disability(access.
5. Wifi.
6. Have(rooms(above(ground(level.

73. What%if...
1. There'was'an'appropriate'hotel'for'€151?
2. A'brilliant'candidate'could'be'found'501m'away'from'Bimhuis?

74. This%is%all%possible%with%Elas/cSearch, plus%it's%easy.

75. Controlling)relevance
{
"gauss": {
"location": {
"origin": "52.3712561,4.9005577",
"offset": "0.5km",
"decay": 20
}
}
}
Set$the$origin$to$Bimhuis,$allowing$loca4ons$
of$hotels$within$500m.$Outside$that,$a$steep$
decay$of$relevance$occurs.

76. Controlling)relevance
{
"gauss": {
"price": {
"origin": 0,
"offset": 100,
"decay": 20
}
}
}
Any$price$over$€100$suffers$a$similar,$severe$
relevance$penalty.

77. {
"query": {
"function_score": {
"query": {
"bool": {
"must": {
"multi_match": {"query": "Renaissance", "fields": ["name", "company"]},
"term": {"features": "disability_access"},
},
"should": {
"term": {"features": "wifi"},
"range": {"floor_levels": {"gt": 1}}
}
}
},
"functions": [
{
"gauss": {
"location": {
"origin": "52.3712561,4.9005577",
"offset": "0.5km",
"decay": 20
}
}
},
{
"gauss": {
"price": {
"origin": 0,
"offset": 100,
"decay": 20
}
}
}
]
}
}
}

78. See#example#in#detail#over#at
h"p://git.io/V4Hm6w

79. Integra(ng)with
WordPress
*Joking*

80. Integra(ng)with Laravel

81. Install'via'Composer
{
"require": {
"elasticsearch/elasticsearch": "1.1.*"
}
}

82. Crea%ng(/(upda%ng(documents
$client = new ElasticsearchClient();
$client->index([
'index' => 'myapp',
'type' => 'hotel',
'id' => '1',
'body' => [
'name' => 'Renaissance Hotel Amsterdam',
'company' => 'Marriott',
'location' => [52.3712561, 4.9005577],
'floor_levels' => 10,
'features' => ['disability_access', 'wifi', 'pool', 'restaurant'],
],
]);
You$can$create$or$update$in$the$same$request.

83. Par$ally'upda$ng'documents
$client = new ElasticsearchClient();
$client->update([
'index' => 'myapp',
'type' => 'hotel',
'id' => '1',
'body' => [
'floor_levels' => 11,
],
]);

84. Dele$ng'documents
$client = new ElasticsearchClient();
$client->delete([
'index' => 'myapp',
'type' => 'hotel',
'id' => '1',
]);

85. Searching*documents
$client = new ElasticsearchClient();
$client->search([
'index' => 'myapp',
'type' => 'hotel',
'body' => [
'query' => [
'match' => 'Renaissance',
],
],
]);

86. Create/update/delete+eloquent+documents
Hotel::created(function ($hotel) {
$client = new ElasticsearchClient();
$client->index([
'index' => 'myapp',
'type' => 'hotel',
'id' => $hotel->id,
'body' => $hotel->toArray(),
]);
});

87. Create/update/delete+eloquent+documents
Hotel::updated(function ($hotel) {
$client = new ElasticsearchClient();
$client->index([
'index' => 'myapp',
'type' => 'hotel',
'id' => $hotel->id,
'body' => $hotel->toArray(),
]);
});

88. Create/update/delete+eloquent+documents
Hotel::deleted(function ($hotel) {
$client = new ElasticsearchClient();
$client->delete([
'index' => 'myapp',
'type' => 'hotel',
'id' => $hotel->id,
]);
});

89. Searching*+*two*approaches
1. Acceptable#have#a#search()#method#directly#on#Eloquent#to#
use#Elas6cSearch
2. Be*er#approach#is#to#decorate#a#repository;#decouple#and#
remove#vendor#lock<in.

90. Eloquent)repository
class EloquentHotelRepository implements HotelRepository
{
public function create($name)
{
// Create and save the model
}
public function search($name, array $filters)
{
// Perform search as best you can without ElasticSearch...
}
// Truncated for brevity...
}

91. Decora'ng*the*repository
class ElasticSearchHotelRepository implements HotelRepository
{
protected $eloquent;
public function __construct(EloquentHotelRepository $eloquent)
{
$this->eloquent = $eloquent;
}
public function create($name)
{
$this->eloquent->create($name);
}
public function search($name, array $filters)
{
// Truncated for brevity...
}
}

92. Decora'ng*the*repository
class ElasticSearchHotelRepository implements HotelRepository
{
public function search($name, array $filters)
{
$results = $client->search([
// ...
]);
return array_map(function ($result) {
$hotel = new Hotel([
//
]);
$hotel->exists = true;
return $hotel;
}, $results);
}
}

93. To#dig#deeper,#please#visit
h"p://git.io/CRW6Mg01
1"Repository"will"be"live"soon

94. Why$I$chose$Elas-cSearch
1. Built(for(real.me(search(applica.ons.
2. Handles(concurrent(read/write(much(be;er(than(compe.tors.
3. Download(an(execute(a(single(binary(as(a(bare(minimum.
4. Easy(to(configure;(you(don't(need(to(configure(anything.
5. JSON(over(a(RESTful(API.(Need(I(say(more?

95. Why$I$chose$Elas-cSearch$over$"X"
1. Solr#$#I#dislike#how#you#communicate#with#it;#maybe#I'm#not#
enterprise+enough#for#XML.#I#also#don't#like#it's#real>me#
performance.1
2. Sphinx#$#query#language#was#peculiar,#SQL$like.#Was#never#built#
as#a#real>me#search#engine.
1"h$p://blog.socialcast.com/real5me6search6solr6vs6elas5csearch/

96. Things'I'haven't'told'you'about
1. Par&al(matching(0(matching(par&al(words(using(ngrams.
2. How(easy(and(fast(autocomplete(can(be.
3. Fuzzy1search(0(misspelt(words.
4. Fine0tuning(analysis(for(specific(data(sets.
5. Analy5cs(0(aggrega&ng(sta&s&cs(to(produce(things(like(reports(
or(faceted8filtering(0(part(of(a(query.

97. One$more$thing...

98. Elas%cSearch+is+coming+soon+to
Laravel'Homestead
Run$vagrant box update$to$get$the$awesomeness.

99. Further'learning
1. h$p://www.elas-csearch.org
2. h$p://shop.oreilly.com/product/0636920028505.do
3. h$p://git.io/CRW6Mg

100. h"p://joind.in/11691
h"ps://github.com/bencorle"/laracon5eu52014