MongoDB - Back to Basics - La tua prima Applicazione

Back to Basics 2017 : Webinar 2
La Tua Prima Applicazione
Massimo Brignoli
Principal Solution Architect
MongoDB
massimo@mongodb.com
@massimobrignoli
V1.0

3
Riassunto della Parte 1
• Perché esistono i NoSQL
• I vari tipi di database NoSQL
• Le caratteristiche principali di MongoDB

4
Agenda
• I concetti base
• Installare MongoDB
• Costruire un’applicazione base di blogging
• Aggiungere gli indici
• Ottimizzare le query con l’explain

5
Concetti
Relational MongoDB
Database Database
Table Collection
Row Document
Index Index
Join Lookup
Foreign Key Reference
Multi-table transaction Single document transaction

6
Document Store
{
name : “Massimo Brignoli”,
title : “Principal Solutions Architect”,
Address : {
address1 : “Via Paleocapa 7”,
address2 : “c/o Regus”,
zipcode: “20121”,
}
expertise: [ “MongoDB”, “Python”, “Javascript” ],
employee_number : 334,
location : [ 53.34, -6.26 ]
}

7
I Documenti di MongoDB Sono Tipizzati
{
name : “Massimo Brignoli”,
title : “Principal Solutions Architect”,
Address : {
address1 : “Via Paleocapa 7”,
address2 : “c/o Regus”,
zipcode: “20121”,
}
expertise: [ “MongoDB”, “Python”, “Javascript” ],
employee_number : 334,
location : [ 53.34, -6.26 ]
}
Strings
Nested Document
Array
Integer
Geo-spatial Coordinates

8
MongoDB Drivers
http://bsonspec.org/spec.html

9
Installare MongoDB
$ curl -O https://fastdl.mongodb.org/osx/mongodb-osx-ssl-x86_64-3.4.1.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

10
Eseguire mongod
JD10Gen:mongodb mbrignoli$ ./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 v3.4.1
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)

11
Connettersi Via Shell
$ ./bin/mongo
MongoDB shell version: 3.4.1
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
>

12
Inserire il Vostro Primo Record
> 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" }
>

13
Object ID
573af7085ee4be80385332a6
TS------ID----PID-Count-

15
Una Semplice Applicazione di Blog
• Creiamo una applicazione di blogging con questi dati:
– Articles
– Users
– Comments

16
Un Tipico Diagramma Entità - Relazioni

17
In MongoDB possiamo farlo in modo organico
> use blog
switched to db blog
> db.users.insert( { "username" : ”mbrignoli", "password" : "top secret", "lang" : ”IT" } )
WriteResult({ "nInserted" : 1 })
> db.users.findOne()
{
"_id" : ObjectId("573afff65ee4be80385332a7"),
"username" : ”mbrignoli",
"password" : "top secret",
"lang" : ”IT"
}

18
Come lo facciamo in un programma?
'''
Created on 17 May 2016
@author: mbrignoli
'''
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" : ”mbrignoli",
"password" : "top secret",
"lang" : “IT" })
user = usersCollection.find_one()
print( user )

19
Passiamo agli Articles
…
articlesCollection = blogDatabase[ "articles" ]
author = ”mbrignoli"
article = { "title" : ”Questo è il mio primo post",
"body" : ”Questo è il contenuto del mio post, posso aggiungere un sacco di testo qua.",
"author" : author,
"tags" : [ ”massimo", "general", ”Italia", "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 )

20
Creiamo un nuovo tipo di articolo
#
# Lets add a new type of article with a posting date and a section
#
author = ”mbrignoli"
title = ”Questo è un post su MongoDB"
newPost = { "title" : title,
"body" : ”MongoDB è il database NoSQL più popolare del mondo. E’ un database a
documenti.",
"author" : author,
"tags" : [ ”massimo", "mongodb", ”Italia" ],
"section" : "technology",
"postDate" : datetime.datetime.now(),
}
#
# Lets check if our author exists
#
if usersCollection.find_one( { "username" : author }) :
articlesCollection.insert_one( newPost )

21
Facciamo un po’di articoli
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" }

22
Facciamo un po’di articoli
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()

23
Trovare un Utente
{
"_id" : ObjectId("5742da5bb26a88bc00e941ac"),
"username" : USER_1,
"lang" : "EN",
"password" : "vTlILbGWLt",
"karma" : 448
}
> db.users.find( { "username" : ”USER_45" } ).pretty()
{
"_id" : ObjectId("5742da5bb26a88bc00e94206"),
"username" : ”USER_45",
"lang" : "EN",
"password" : "GmRLnCeKVp",
"karma" : 284
}

24
Trovare gli Utenti con un alto Karma
> db.users.find( { "karma" : { $gte : 450 }} ).pretty()
{
"_id" : ObjectId("5742da5bb26a88bc00e941ae"),
"username" : "USER_1",
"lang" : "EN",
"password" : "bCSKSKvUeb",
"karma" : 487
}
{
"_id" : ObjectId("5742da5bb26a88bc00e941e4"),
"username" : »USER_28",
"lang" : "EN",
"password" : "HAWpiATCBN",
"karma" : 473
}
{
…

25
Usare la Projection
> db.users.find( { "karma" : { "$gte" : 450 }}, { "_id" : 0, "username" : 1 , "karma" : 1 })
{ "username" : "USER_1", "karma" : 461 }
…

26
Aggiornare un Articolo per Aggiungere Commenti
> db.articles.find( { "_id" : 18 } ).pretty()
{
"_id" : 18,
"body" :
"nTzOofOcnHKkJxpjKAyqTTnKZMFzzkWFeXtBRuEKsctuGBgWIrEBrYdvFIVHJWaXLUTVUXblOZZgUq
Wu",
"postdate" : ISODate("2016-05-23T12:02:46.830Z"),
"author" : “USER_18",
"title" : "CPMaqHtAdRwLXhlUvsej"
}
> db.articles.update( { _id : 18 }, { $set : { comments : [] }} )
WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })

27
> db.articles.find( { _id :18 } ).pretty()
{
"_id" : 18,
"body" :
"KmwFSIMQGcIsRNTDBFPuclwcVJkoMcrIPwTiSZDYyatoKzeQiKvJkiVSrndXqrALVIYZxGpaMjucgX
UV",
"author" : "USER_18",
"title" : "wTLreIEyPfovEkBhJZZe",
"comments" : [ ]
}
>

28
> db.articles.update( { _id : 18 }, { $push : { comments : { username : ”max", comment :
"hey first post" }}} )
WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
> db.articles.find( { _id :18 } ).pretty()
{
"_id" : 18,
"body" :
"KmwFSIMQGcIsRNTDBFPuclwcVJkoMcrIPwTiSZDYyatoKzeQiKvJkiVSrndXqrALVIYZxGpaMjucgXUV",
"title" : "wTLreIEyPfovEkBhJZZe",
"comments" : [
{
"username" : ”max",
"comment" : "hey first post"
}
]
}
>

29
Cancellare un articolo
> db.articles.remove( { "_id" : 25 } )
WriteResult({ "nRemoved" : 1 })
> db.articles.remove( { "_id" : 25 } )
> db.articles.remove( { "_id" : { $lte : 5 }} )
• Le cancellazioni lasciare degli spazi vuoti
• Gli spazi vuoti vengono riutilizzati

30
Riguardiamo gli utenti e gli articoli
{
"_id" : ObjectId("57431c07b26a88bf060e10cb"),
"username" : "USER_0",
"lang" : "EN",
"password" : "kGIxPxqKGJ",
"karma" : 266
}
> db.articles.findOne()
{
"_id" : 0,
"body" :
"hvJLnrrfZQurmtjPfUWbMhaQWbNjXLzjpuGLZjsxHXbUycmJVZTeOZesTnZtojThrebRcUoiYwivjpwG"
,
"title" : "gpNIoPxpfTAxWjzAVoTJ"
}
>

31
Explain: Trova un utente
> db.users.find( { "username" : "USER_99" } ).explain()
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "blog.users",
"indexFilterSet" : false,
"parsedQuery" : {
"username" : {
"$eq" : "USER_99"
}
},
"winningPlan" : {
"stage" : "COLLSCAN",
"filter" : {
"username" : {
"$eq" : "USER_99"
}
},
"direction" : "forward"
},
},
}

32
Explain: Trova un Utente – execution stats
> db.users.find( { "username" : "USER_99" } ).explain( "executionStats" ).executionStats
{
"executionSuccess" : true,
"nReturned" : 1,
"executionTimeMillis" : 412,
"totalKeysExamined" : 0,
"totalDocsExamined" : 1000000,
"executionStages" : {
"stage" : "COLLSCAN",
"filter" : {
"username" : {
"$eq" : "USER_99"
}
},
"nReturned" : 1,
"executionTimeMillisEstimate" : 302,
"works" : 1000002,
"advanced" : 1,
"needTime" : 1000000,
"needYield" : 0,
"saveState" : 7823,
"restoreState" : 7823,
"isEOF" : 1,
"invalidates" : 0,
"direction" : "forward",
"docsExamined" : 1000000
}
}

33
Abbiamo Bisogno di un Indice
> db.users.createIndex( { username : 1 } )
{
"createdCollectionAutomatically" : false,
"numIndexesBefore" : 1,
"numIndexesAfter" : 2,
"ok" : 1
}
>

34
Overview degli Indici
• Parametri
– Background : Crea un indice in background senza lockare il db
– Unique : Tutte le chiavi nella collection devono essere uniche.
– Name : Da un nome all’indice, altrimenti il nome sarà generato automaticamente
• Cancellare un indice
– db.users.dropIndex({ “username” : 1 })
• Mostrare tutti gli indici
– db.users.getIndexes()

35
Passaggi nell’esecuzione del Query Plan
• COLLSCAN : full scan di una collection
• IXSCAN : Scansione di un indice
• FETCH : per leggere i documenti
• SHARD_MERGE : Per unire i risultati dagli shard

36
Aggiungere un Indice
> db.users.find( {"username" : "USER_999999”} ).explain("executionStats”).executionStats
{
"executionSuccess" : true,
"nReturned" : 1,
"executionTimeMillis" : 0,
"totalKeysExamined" : 1,
"totalDocsExamined" : 1,
…

37
Execution stage
"executionStages" : {
"stage" : "FETCH",
"nReturned" : 1,
"docsExamined" : 1,,
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 1,
"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
}
}
}

38
Cosa Abbiamo Imparato
• Come creare un database e una collection
• Come inserire contenuto in una collection
• Come interrogare una collection
• Come aggiornare un documento
• Come cancellare un documento
• Come controllare l’efficienza di una query
• Come aggiungere un indice
• Come controllare che un indice sia usato durante una
query

39
Prossimo Webinar : Introduzione ai Replica Sets
• Come assicurare che I vostri dati sia durabili
• Come recuperare da failure automaticamente
• Come scrivere codice sicuro lato clienti
Martedì, 20 Giugno 2017, 11:00 CET.

MongoDB - Back to Basics - La tua prima Applicazione

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