This document contains the slides from a webinar on building a basic MongoDB application. It introduces MongoDB concepts and terminology, shows how to install MongoDB, create a basic blogging application with articles, users and comments, and add and query data. Key steps include installing MongoDB, launching the mongod process, connecting with the mongo shell, inserting documents, finding and querying documents, and updating documents by adding fields and pushing to arrays.

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3. Back to Basics 2016 : Webinar 2
Votre première application MongoDB
Rémi Forest
Senior Solution Architect
MongoDB
#back2basics
V1.0

4. 4
Résumé de la partie 1
• Pourquoi NoSQL existe
• Les différents types de bases NoSQL
• Principales caractéristiques de MongoDB
• Durabilité des données avec MongoDB – Replica Sets
• Scalabilité avec MongoDB - Sharding

5. 5
Agenda
• Concepts et terminologie
• Installation de MongoDB
• Une application basique de blogging
• Ajouter un index
• Optimisation des requêtes avec Explain()

6. 6
Concepts et terminologie
Relational MongoDB
Database Database
Table Collection
Row Document
Index Index
Join Lookup
Foreign Key Reference
Multi-table transaction Single document transaction

7. 7
Installation de MongoDB
$ curl -O https://fastdl.mongodb.org/osx/mongodb-osx-x86_64-3.2.6.tgz
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
100 60.9M 100 60.9M 0 0 2730k 0 0:00:22 0:00:22 --:--:-- 1589k
$ tar xzvf mongodb-osx-x86_64-3.2.6.tgz
x mongodb-osx-x86_64-3.2.6/README
x mongodb-osx-x86_64-3.2.6/THIRD-PARTY-NOTICES
x mongodb-osx-x86_64-3.2.6/MPL-2
x mongodb-osx-x86_64-3.2.6/GNU-AGPL-3.0
x mongodb-osx-x86_64-3.2.6/bin/mongodump
x mongodb-osx-x86_64-3.2.6/bin/mongorestore
x mongodb-osx-x86_64-3.2.6/bin/mongoexport
x mongodb-osx-x86_64-3.2.6/bin/mongoimport
x mongodb-osx-x86_64-3.2.6/bin/mongostat
x mongodb-osx-x86_64-3.2.6/bin/mongotop
x mongodb-osx-x86_64-3.2.6/bin/bsondump
x mongodb-osx-x86_64-3.2.6/bin/mongofiles
x mongodb-osx-x86_64-3.2.6/bin/mongooplog
x mongodb-osx-x86_64-3.2.6/bin/mongoperf
x mongodb-osx-x86_64-3.2.6/bin/mongosniff
x mongodb-osx-x86_64-3.2.6/bin/mongod
x mongodb-osx-x86_64-3.2.6/bin/mongos
x mongodb-osx-x86_64-3.2.6/bin/mongo
$ ln -s mongodb-osx-x86_64-3.2.6 mongodb

8. 8
Lancer Mongod
JD10Gen:mongodb jdrumgoole$ ./bin/mongod --dbpath /data/b2b
2016-05-23T19:21:07.767+0100 I CONTROL [initandlisten] MongoDB starting : pid=49209 port=27017 dbpath=/data/b2b 64-
bit host=JD10Gen.local
2016-05-23T19:21:07.768+0100 I CONTROL [initandlisten] db version v3.2.6
2016-05-23T19:21:07.768+0100 I CONTROL [initandlisten] git version: 05552b562c7a0b3143a729aaa0838e558dc49b25
2016-05-23T19:21:07.768+0100 I CONTROL [initandlisten] allocator: system
2016-05-23T19:21:07.768+0100 I CONTROL [initandlisten] modules: none
2016-05-23T19:21:07.768+0100 I CONTROL [initandlisten] build environment:
2016-05-23T19:21:07.768+0100 I CONTROL [initandlisten] distarch: x86_64
2016-05-23T19:21:07.768+0100 I CONTROL [initandlisten] target_arch: x86_64
2016-05-23T19:21:07.768+0100 I CONTROL [initandlisten] options: { storage: { dbPath: "/data/b2b" } }
2016-05-23T19:21:07.769+0100 I - [initandlisten] Detected data files in /data/b2b created by the 'wiredTiger'
storage engine, so setting the active storage engine to 'wiredTiger'.
2016-05-23T19:21:07.769+0100 I STORAGE [initandlisten] wiredtiger_open config:
create,cache_size=4G,session_max=20000,eviction=(threads_max=4),config_base=false,statistics=(fast),log=(enabled=true
,archive=true,path=journal,compressor=snappy),file_manager=(close_idle_time=100000),checkpoint=(wait=60,log_size=2GB)
,statistics_log=(wait=0),
2016-05-23T19:21:08.837+0100 I CONTROL [initandlisten]
2016-05-23T19:21:08.838+0100 I CONTROL [initandlisten] ** WARNING: soft rlimits too low. Number of files is 256,
should be at least 1000
2016-05-23T19:21:08.840+0100 I NETWORK [HostnameCanonicalizationWorker] Starting hostname canonicalization worker
2016-05-23T19:21:08.840+0100 I FTDC [initandlisten] Initializing full-time diagnostic data capture with directory
'/data/b2b/diagnostic.data'
2016-05-23T19:21:08.841+0100 I NETWORK [initandlisten] waiting for connections on port 27017
2016-05-23T19:21:09.148+0100 I NETWORK [initandlisten] connection accepted from 127.0.0.1:59213 #1 (1 connection now
open)

9. 9
Connection au shell
$ ./bin/mongo
MongoDB shell version: 3.2.6
connecting to: test
Server has startup warnings:
2016-05-17T11:46:03.516+0100 I CONTROL [initandlisten]
2016-05-17T11:46:03.516+0100 I CONTROL [initandlisten] ** WARNING: soft rlimits too low. Number of
files is 256, should be at least 1000
>

10. 10
Insérer son premier enregistrement
> show databases
local 0.000GB
> use test
switched to db test
> show databases
local 0.000GB
> db.demo.insert( { "key" : "value" } )
WriteResult({ "nInserted" : 1 })
> show databases
local 0.000GB
test 0.000GB
> show collections
demo
> db.demo.findOne()
{ "_id" : ObjectId("573af7085ee4be80385332a6"), "key" : "value" }
>

11. 11
Object ID
573af7085ee4be80385332a6
TS------ID----PID-Count-

12. 12
Une application basique
• Créons une application de blogging qui contient:
– Articles
– Users
– Commentaires

13. 13
Typical Entity Relation Diagram

14. 14
Représentation dans MongoDB
> use blog
switched to db blog
> db.users.insert( { "username" : "jdrumgoole", "password" : "top secret", "lang" : "EN" } )
WriteResult({ "nInserted" : 1 })
> db.users.findOne()
{
"_id" : ObjectId("573afff65ee4be80385332a7"),
"username" : "jdrumgoole",
"password" : "top secret",
"lang" : "EN"
}

15. 15
Comment coder ça ?
'''
Created on 17 May 2016
@author: jdrumgoole
'''
import pymongo
#
# client defaults to localhost and port 27017. eg MongoClient('localhost', 27017)
client = pymongo.MongoClient()
blogDatabase = client[ "blog" ]
usersCollection = blogDatabase[ "users" ]
usersCollection.insert_one( { "username" : "jdrumgoole",
"password" : "top secret",
"lang" : "EN" })
user = usersCollection.find_one()
print( user )

16. 16
Next up Articles
…
articlesCollection = blogDatabase[ "articles" ]
author = "jdrumgoole"
article = { "title" : "This is my first post",
"body" : "The is the longer body text for my blog post. We can add lots of text here.",
"author" : author,
"tags" : [ "joe", "general", "Ireland", "admin" ]
}
#
# Lets check if our author exists
#
if usersCollection.find_one( { "username" : author }) :
articlesCollection.insert_one( article )
else:
raise ValueError( "Author %s does not exist" % author )

17. 17
Création d’un nouveau type d’article
#
# Lets add a new type of article with a posting date and a section
#
author = "jdrumgoole"
title = "This is a post on MongoDB"
newPost = { "title" : title,
"body" : "MongoDB is the worlds most popular NoSQL database. It is a document
database",
"author" : author,
"tags" : [ "joe", "mongodb", "Ireland" ],
"section" : "technology",
"postDate" : datetime.datetime.now(),
}
#
# Lets check if our author exists
#
if usersCollection.find_one( { "username" : author }) :
articlesCollection.insert_one( newPost )

18. 18
Création d’articles - 1
import pymongo
import string
import datetime
import random
def randomString( size, letters = string.letters ):
return "".join( [random.choice( letters ) for _ in xrange( size )] )
client = pymongo.MongoClient()
def makeArticle( count, author, timestamp ):
return { "_id" : count,
"title" : randomString( 20 ),
"body" : randomString( 80 ),
"author" : author,
"postdate" : timestamp }
def makeUser( username ):
return { "username" : username,
"password" : randomString( 10 ) ,
"karma" : random.randint( 0, 500 ),
"lang" : "EN" }

19. 19
Création d’articles - 2
blogDatabase = client[ "blog" ]
usersCollection = blogDatabase[ "users" ]
articlesCollection = blogDatabase[ "articles" ]
bulkUsers = usersCollection.initialize_ordered_bulk_op()
bulkArticles = articlesCollection.initialize_ordered_bulk_op()
ts = datetime.datetime.now()
for i in range( 1000000 ) :
#username = randomString( 10, string.ascii_uppercase ) + "_" + str( i )
username = "USER_" + str( i )
bulkUsers.insert( makeUser( username ) )
ts = ts + datetime.timedelta( seconds = 1 )
bulkArticles.insert( makeArticle( i, username, ts ))
if ( i % 500 == 0 ) :
bulkUsers.execute()
bulkArticles.execute()
bulkUsers = usersCollection.initialize_ordered_bulk_op()
bulkArticles = articlesCollection.initialize_ordered_bulk_op()
bulkUsers.execute()
bulkArticles.execute()

20. 20
Trouver un User
> db.users.findOne()
{
"_id" : ObjectId("5742da5bb26a88bc00e941ac"),
"username" : "FLFZQLSRWZ_0",
"lang" : "EN",
"password" : "vTlILbGWLt",
"karma" : 448
}
> db.users.find( { "username" : "VHXDAUUFJW_45" } ).pretty()
{
"_id" : ObjectId("5742da5bb26a88bc00e94206"),
"username" : "VHXDAUUFJW_45",
"lang" : "EN",
"password" : "GmRLnCeKVp",
"karma" : 284
}

21. 21
Trouver les Users avec un Karma élevé
> db.users.find( { "karma" : { $gte : 450 }} ).pretty()
{
"_id" : ObjectId("5742da5bb26a88bc00e941ae"),
"username" : "JALLFRKBWD_1",
"lang" : "EN",
"password" : "bCSKSKvUeb",
"karma" : 487
}
{
"_id" : ObjectId("5742da5bb26a88bc00e941e4"),
"username" : "OTKWJJBNBU_28",
"lang" : "EN",
"password" : "HAWpiATCBN",
"karma" : 473
}
{
…

22. 22
Utiliser la projection
> db.users.find( { "karma" : { $gte : 450 }}, { "_id" : 0, username : 1, karma : 1 } )
{ "username" : "JALLFRKBWD_1", "karma" : 487 }
{ "username" : "OTKWJJBNBU_28", "karma" : 473 }
{ "username" : "RVVHLKTWHU_31", "karma" : 493 }
{ "username" : "JBNESEOOEP_48", "karma" : 464 }
{ "username" : "VSTBDZLKQQ_51", "karma" : 487 }
{ "username" : "UKYDTQJCLO_61", "karma" : 493 }
{ "username" : "HZFZZMZHYB_106", "karma" : 493 }
{ "username" : "AAYLPJJNHO_113", "karma" : 455 }
{ "username" : "CXZZMHLBXE_128", "karma" : 460 }
{ "username" : "KKJXBACBVN_134", "karma" : 460 }
{ "username" : "PTNTIBGAJV_165", "karma" : 461 }
{ "username" : "PVLCQJIGDY_169", "karma" : 463 }

23. 23
Ajouter des commentaires - 1
> db.articles.find( { "_id" : 19 } ).pretty()
{
"_id" : 19,
"body" :
"nTzOofOcnHKkJxpjKAyqTTnKZMFzzkWFeXtBRuEKsctuGBgWIrEBrYdvFIVHJWaXLUTVUXblOZZgUq
Wu",
"postdate" : ISODate("2016-05-23T12:02:46.830Z"),
"author" : "ASWTOMMABN_19",
"title" : "CPMaqHtAdRwLXhlUvsej"
}
> db.articles.update( { _id : 18 }, { $set : { comments : [] }} )
WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })

24. 24
Ajouter des commentaires - 2
> db.articles.find( { _id :18 } ).pretty()
{
"_id" : 18,
"body" :
"KmwFSIMQGcIsRNTDBFPuclwcVJkoMcrIPwTiSZDYyatoKzeQiKvJkiVSrndXqrALVIYZxGpaMjucgX
UV",
"postdate" : ISODate("2016-05-23T16:04:39.497Z"),
"author" : "USER_18",
"title" : "wTLreIEyPfovEkBhJZZe",
"comments" : [ ]
}
>

25. 25
Ajouter des commentaires - 3
> db.articles.update( { _id : 18 }, { $push : { comments : { username : "joe",
comment : "hey first post" }}} )
WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
> db.articles.find( { _id :18 } ).pretty()
{
"_id" : 18,
"body" :
"KmwFSIMQGcIsRNTDBFPuclwcVJkoMcrIPwTiSZDYyatoKzeQiKvJkiVSrndXqrALVIYZxGpaMjucgXUV"
,
"postdate" : ISODate("2016-05-23T16:04:39.497Z"),
"author" : "USER_18",
"title" : "wTLreIEyPfovEkBhJZZe",
"comments" : [
{
"username" : "joe",
"comment" : "hey first post"
}
]
}
>

26. 26
Supprimer un Article
> db.articles.remove( { "_id" : 25 } )
WriteResult({ "nRemoved" : 1 })
> db.articles.remove( { "_id" : 25 } )
WriteResult({ "nRemoved" : 0 })
> db.articles.remove( { "_id" : { $lte : 5 }} )
WriteResult({ "nRemoved" : 6 })
• Les supressions laissent des trous
• Supprimer une collection est plus efficace que de supprimer
l’ensemble de ses éléments un par un.

27. 27
A Quick Look at Users and Articles Again
> db.users.findOne()
{
"_id" : ObjectId("57431c07b26a88bf060e10cb"),
"username" : "USER_0",
"lang" : "EN",
"password" : "kGIxPxqKGJ",
"karma" : 266
}
> db.articles.findOne()
{
"_id" : 0,
"body" :
"hvJLnrrfZQurmtjPfUWbMhaQWbNjXLzjpuGLZjsxHXbUycmJVZTeOZesTnZtojThrebRcUoiYwivjpwG"
,
"postdate" : ISODate("2016-05-23T16:04:39.246Z"),
"author" : "USER_0",
"title" : "gpNIoPxpfTAxWjzAVoTJ"
}
>

28. 28
Trouver un User
> db.users.find( { "username" : "ABOXHWKBYS_199" } ).explain()
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "blog.users",
"indexFilterSet" : false,
"parsedQuery" : {
"username" : {
"$eq" : "ABOXHWKBYS_199"
}
},
"winningPlan" : {
"stage" : "COLLSCAN",
"filter" : {
"username" : {
"$eq" : "ABOXHWKBYS_199"
}
},
"direction" : "forward"
},
"rejectedPlans" : [ ]
},
"serverInfo" : {
"host" : "JD10Gen.local",
"port" : 27017,
"version" : "3.2.6",
"gitVersion" : "05552b562c7a0b3143a729aaa0838e558dc49b25"
},
"ok" : 1
}

29. 29
Trouver un User – Execution Stats
> db.users.find( {"username" : "USER_999999" } ).explain( "executionStats" ).executionStats
{
"executionSuccess" : true,
"nReturned" : 1,
"executionTimeMillis" : 433,
"totalKeysExamined" : 0,
"totalDocsExamined" : 1000000,
"executionStages" : {
"stage" : "COLLSCAN",
"filter" : {
"username" : {
"$eq" : "USER_999999"
}
},
"nReturned" : 1,
"executionTimeMillisEstimate" : 330,
"works" : 1000002,
"advanced" : 1,
"needTime" : 1000000,
"needYield" : 0,
"saveState" : 7812,
"restoreState" : 7812,
"isEOF" : 1,
"invalidates" : 0,
"direction" : "forward",
"docsExamined" : 1000000

30. 30
Il faut un Index !
> db.users.createIndex( { username : 1 } )
{
"createdCollectionAutomatically" : false,
"numIndexesBefore" : 1,
"numIndexesAfter" : 2,
"ok" : 1
}
>

31. 31
Indexes Overview
• Parameters
– Background : Create an index in the background as opposed to locking the database
– Unique : All keys in the collection must be unique. Duplicate key insertions will be
rejected with an error.
– Name : explicitly name an index. Otherwise the index name is autogenerated from the
index field.
• Deleting an Index
– db.users.dropIndex({ “username” : 1 })
• Get All the Indexes on a collection
– db.users.getIndexes()

32. 32
Query Plan Execution Stages
• COLLSCAN : scan de toute la collection
• IXSCAN : scan d’un indexe
• FETCH : récupération de documents
• SHARD_MERGE : fusionne les

33. 33
Ajouter un Index
> db.users.find( {"username" : "USER_999999”} ).explain("executionStats”).executionStats
{
"executionSuccess" : true,
"nReturned" : 1,
"executionTimeMillis" : 0,
"totalKeysExamined" : 1,
"totalDocsExamined" : 1,
…

34. 34
Execution Stage
"executionStages" : {
"stage" : "FETCH",
"nReturned" : 1,
"executionTimeMillisEstimate" : 0,
"docsExamined" : 1,,
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 1,
"executionTimeMillisEstimate" : 0,
"keyPattern" : {
"username" : 1
},
"indexName" : "username_1",
"isMultiKey" : false,
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 1,
"direction" : "forward",
"indexBounds" : {
"username" : [
"["USER_999999", "USER_999999"]"
]
},
"keysExamined" : 1,
"seenInvalidated" : 0
}
}
}

35. 35
Drivers et Frameworks
Morphia
MEAN Stack

36. 36
Ce que nous avons appris
• Comment créer une database et une collection
• Comment insérer du contenu dans cette collection
• Comment requêter une collection
• Comment mettre à jour un document
• Comment supprimer un document
• Comment évaluer la performance d’une requête
• Comment ajouter un index
• Comment vérifier si un index est utilisé lors d’une requête

37. 37
Prochain Webinar : Penser “Document”
• Plutôt que de normaliser, il faut considérer une approche hybride
de schéma pour proposer une relation cohérente entre les objets
dans l’application et dans la base de données.
• Nous optimiserons ensuite ce schéma en fonction des patterns de
requêtes que nous nous attendons à trouver.
• Enfin, nous verrons comment les schémas dynamiques et la
validation des schémas permettent de faire évoluer le schéma de
façon contrôlée .
23 Juin 2016, 14:00 CET.

38. Q&A