Este es el segundo seminario web de la serie Conceptos básicos, en la que se realiza una introducción a la base de datos MongoDB. En este seminario web mostraremos cómo construir una aplicación de creación de blogs en MongoDB.

3. Back to Basics 2016: Webinar 2
Su primera aplicación MongoDB
Rubén Terceño
Senior Solutions Architect, EMEA
ruben@mongodb.com
@rubenTerceno

4. ¡Bienvenidos!

5. Agenda del Curso
Date Time Webinar
25-Mayo-2016 16:00 CEST Introducción a NoSQL
7-Junio-2016 16:00 CEST Su primera aplicación MongoDB
21-Junio-2016 16:00 CEST Diseño de esquema orientado a documentos
07-Julio-2016 16:00 CEST Indexación avanzada, índices de texto y geoespaciales
19-Julio-2016 16:00 CEST Introducción al Aggregation Framework
28-Julio-2016 16:00 CEST Despliegue en producción

6. Resumen del webinar 1
• ¿Porqué existe NoSQL?
• Tipos de bases de datos NoSQL
• Características clave de MongoDB
• Tolerancia a fallos y persistencia de datos en MongoDB
• Escalabilidad en MongoDB

7. Agenda
• Vocabulario básico
• Instalación de MongoDB
• Construcción de una aplicación básica
• Creación de índices
• Optimización de queries con explain()

8. Concepts
Relational MongoDB
Database Database / Base de datos
Table Collection / Colección
Row Document / Documento
Index Index / Índice
Join Lookup
Foreign Key Reference / Referencia
Multi-table transaction Single document transaction

9. Installing MongoDB
$ curl -O https://fastdl.mongodb.org/osx/mongodb-osx-x86_64-3.2.6.tgz
$ 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
$ mkdir /data/CB

10. Running Mongod
Rubens-MacBook-Pro:mongodb-osx-x86_64-3.2.6 Ruben$ ./bin/mongod -dbpath /data/CB
2016-06-05T14:44:49.564+0200 I CONTROL [initandlisten] MongoDB starting : pid=21526 port=27017
dbpath=/data/CB 64-bit host=Rubens-MacBook-Pro.local
2016-06-05T14:44:49.564+0200 I CONTROL [initandlisten] db version v3.2.6
2016-06-05T14:44:49.564+0200 I CONTROL [initandlisten] git version:
05552b562c7a0b3143a729aaa0838e558dc49b25
2016-06-05T14:44:49.564+0200 I CONTROL [initandlisten] allocator: system
2016-06-05T14:44:49.564+0200 I CONTROL [initandlisten] modules: none
2016-06-05T14:44:49.564+0200 I CONTROL [initandlisten] build environment:
2016-06-05T14:44:49.564+0200 I CONTROL [initandlisten] distarch: x86_64
2016-06-05T14:44:49.564+0200 I CONTROL [initandlisten] target_arch: x86_64
2016-06-05T14:44:49.564+0200 I CONTROL [initandlisten] options: { storage: { dbPath: "/data/CB" }
}
2016-06-05T14:44:49.565+0200 I STORAGE [initandlisten] wiredtiger_open config:
create,cache_size=9G,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=10000
0),checkpoint=(wait=60,log_size=2GB),statistics_log=(wait=0),
2016-06-05T14:44:50.316+0200 I NETWORK [HostnameCanonicalizationWorker] Starting hostname
canonicalization worker
2016-06-05T14:44:50.316+0200 I FTDC [initandlisten] Initializing full-time diagnostic data
capture with directory '/data/CB/diagnostic.data'
2016-06-05T14:44:50.511+0200 I NETWORK [initandlisten] waiting for connections on port 27017

11. Connecting Via The Shell
Ruben$ ./mongodb-osx-x86_64-3.2.6/bin/mongo
MongoDB shell version: 3.2.6
connecting to: test
> show databases
local 0.000GB

12. Inserting your first record
> use CB
switched to db CB
> show databases
local 0.000GB
> db.demo.insert({"nombre": "Rubén", "altura": 178})
WriteResult({ "nInserted" : 1 })
> show databases
CB 0.000GB
local 0.000GB
> show collections
demo
> db.demo.findOne()
{
"_id" : ObjectId("575420c87a75dbb02b4f45cb"),
"nombre" : "Rubén",
"altura" : 178
}
>

13. Object ID
575420c87a75dbb02b4f45cb
TS------ID----PID-Count-

14. A Simple Blog Application
• Lets create a blogging application with:
• Articles
• Users
• Comments

15. 15
Typical Entity Relation Diagram

16. In MongoDB we build organically
> use blog
switched to db blog
> db.users.insert( { "username" : ”rterceno",
"password" : "top secret", "lang" : "ES" } )
WriteResult({ "nInserted" : 1 })
> db.users.findOne()
{
"_id" : ObjectId("573afff65ee4be80385332a7"),
"username" : "rterceno",
"password" : "top secret",
"lang" : "ES"
}

17. How do we do this in a program?
package com.mongodb.rterceno;
import com.mongodb.MongoClient;
import com.mongodb.client.MongoCollection;
import com.mongodb.client.MongoDatabase;
import org.bson.Document;
public class Demo {
public static void main(String[] args) {
MongoClient client = new MongoClient();
MongoDatabase blog = client.getDatabase("blog");
MongoCollection<Document> users = blog.getCollection("users");
Document user = new Document("user","rterceno")
.append("lang", "ES");
users.insertOne(user);
}
}

18. Next up Articles
import [+]
import static java.util.Arrays.asList;
public class Demo {
public static void main(String[] args) {
MongoClient client = new MongoClient();
MongoDatabase blog = client.getDatabase("blog");
MongoCollection<Document> articulos = blog.getCollection("articles");
String myName = "rterceno";
Document articulo = new Document("título","My article")
.append("autor", myName)
.append("texto", "Lorem ipsum dolor sit amet, […] commodo consequat.")
.append("tags", asList("demo","español","MongoDB"));
articulos.insertOne(articulo);
}
}

19. Create a new type of article
public class Demo {
static DateFormat format = new SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ss'Z'"
, Locale.ENGLISH);
public static void main(String[] args) {
MongoClient client = new MongoClient();
MongoDatabase blog = client.getDatabase("blog");
MongoCollection<Document> articulos = blog.getCollection("articles");
String myName = "rterceno";
Document articulo = new Document("título","My article")
.append("autor", myName)
.append("texto", "Lorem ipsum dolor sit amet […] commodo
consequat.")
.append("tags", asList("demo", "español", "MongoDB"))
.append("fecha", new Date());
articulos.insertOne(articulo);
}
}

20. Make a lot of articles
public class Demo {
static DateFormat format = new SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ss'Z'"
, Locale.ENGLISH);
public static void main(String[] args) {
MongoClient client = new MongoClient();
MongoDatabase blog = client.getDatabase("blog");
MongoCollection<Document> articulos = blog.getCollection("articles");
List<Document> list = new ArrayList<Document>();
for (int i=0; i<1000000; i++){
Document articulo = new Document("título”, "Mi artículo " + i)
.append("autor", "USER_" + Math.round(Math.random()*10000))
.append("texto", "Lorem ipsum dolor sit amet, […] ex ea commodo consequat.")
.append("tags", asList("demo", "español", "MongoDB"))
.append("fecha", new Date());
list.add(articulo);
if (i % 5000 == 4999){
articulos.insertMany(list);
list.clear();
}
}
}
}

21. Find a 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
}

22. Find Users with high Karma
> 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
}
{

23. Using 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 }

24. Using sort
> db.users.find({"karma”: {$gte: 450}},{"_id”: 0, username: 1, karma:
1}).sort({"karma”: 1})
{ "username" : "JALLFRKBWD_1", "karma" : 493 }
{ "username" : "OTKWJJBNBU_28", "karma" : 493 }
{ "username" : "RVVHLKTWHU_31", "karma" : 487 }
{ "username" : "JBNESEOOEP_48", "karma" : 474}
{ "username" : "VSTBDZLKQQ_51", "karma" : 473 }
{ "username" : "UKYDTQJCLO_61", "karma" : 468 }
{ "username" : "HZFZZMZHYB_106", "karma" : 464 }
{ "username" : "AAYLPJJNHO_113", "karma" : 461 }
{ "username" : "CXZZMHLBXE_128", "karma" : 461 }
{ "username" : "KKJXBACBVN_134", "karma" : 460 }
{ "username" : "PTNTIBGAJV_165", "karma" : 458 }
{ "username" : "PVLCQJIGDY_169", "karma" : 455 }

25. Article update: adding comments 1
> db.articles.find( { "_id" : 19 } ).pretty()
{
"_id" : 19,
"body" :
"nTzOofOcnHKkJxpjKAyqTTnKZMFzzkWFeXtBRuEKsctuGBgWIrEBrYdvFI
VHJWaXLUTVUXblOZZgUqWu",
"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 })

26. Article update: adding comments 2
> db.articles.find( { _id :18 } ).pretty()
{
"_id" : 18,
"body" :
"KmwFSIMQGcIsRNTDBFPuclwcVJkoMcrIPwTiSZDYyatoKzeQiKvJ
kiVSrndXqrALVIYZxGpaMjucgXUV",
"postdate" : ISODate("2016-05-
23T16:04:39.497Z"),
"author" : "USER_18",
"title" : "wTLreIEyPfovEkBhJZZe",
"comments" : [ ]
}
>

27. Article update: adding comments 3
> db.articles.update( { _id : 18 }, { $push : { comments : { username : ”USER_123456",
comment : "Primer!" }}} )
WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
> db.articles.find( { _id :18 } ).pretty()
{
"_id" : 18,
"body" :
"KmwFSIMQGcIsRNTDBFPuclJkoMcrIPwTiSZDYyatoKzeQiKvJkiVSrndXqrALVIYZxGpaMjucgXUV",
"postdate" : ISODate("2016-05-23T16:04:39.497Z"),
"author" : "USER_18",
"title" : "wTLreIEyPfovEkBhJZZe",
"comments" : [
{
"username" : "USER_123456",
"comment" : ”Primer!"
}
]
}

28. Article delete
> 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 })
• Deletion leaves holes
• Dropping a collection is cheaper than deleting a large collection element
by element

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

30. Find a User
> db.users.find( { "username" : "USER_123456" } ).explain()
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "blog.users",
"indexFilterSet" : false,
"parsedQuery" : {
"username" : {
"$eq" : ”USER_123456"
}
},
"winningPlan" : {
"stage" : "COLLSCAN",
"filter" : {
"username" : {
"$eq" : ”USER_123456"
}
},
"direction" : "forward"
},
"rejectedPlans" : [ ]
} "ok" : 1
}

31. Find a 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

32. We need an index
> db.users.createIndex( { username : 1 } )
{
"createdCollectionAutomatically" : false,
"numIndexesBefore" : 1,
"numIndexesAfter" : 2,
"ok" : 1
}

33. 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 selfgenerated from the
index fields.
• Deleting an Index
• db.users.dropIndex({ “username” : 1 })
• Get All the Indexes on a collection
• db.users.getIndexes()

34. Query Plan Execution Stages
• COLLSCAN : for a collection scan
• IXSCAN : for scanning index keys
• FETCH : for retrieving documents
• SHARD_MERGE : for merging results from shards

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

36. Execution Stage
"executionStages" : {
"stage" : "FETCH",
"nReturned" : 1,
"executionTimeMillisEstimate" : 0,
"docsExamined" : 1,,
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 1,
"executionTimeMillisEstimate" : 0,
"keyPattern" : {
"username" : 1},
"indexName" : "username_1",
"indexVersion" : 1,
"direction" : "forward",
"indexBounds" : {
"username" : [
"["USER_999999", "USER_999999"]”]},
"keysExamined" : 1,
"seenInvalidated" : 0 } } }

37. Drivers and Frameworks

38. ¿Qué hemos aprendido?
• Cómo crear una base de datos y una colección
• Como insertar documentos
• Cómo realizar búsquedas
• Como hacer modificaciones de los documentos existentes
• Cómo borrar documentos
• Cómo comprobar la eficiencia de una operación
• Cómo crear índices
• Cómo averiguar los índices que se utilizan en una operación

39. Próximo Webinar
Diseño de esquema orientado a documentos
• 21 de Junio 2016 – 16:00 CEST, 11:00 ART, 9:00
• ¡Regístrese si aún no lo ha hecho!
• Las bases de datos de documentos requieren un enfoque distinto con
respecto a la organización de los datos.
• ¡Sin normalización!  Creamos esquemas adaptados a nuestra aplicación
• Optimizaremos dichos esquemas a los patrones de acceso.
• Demostraremos que es fácil controlar estos esquemas.
• Regístrese en : https://www.mongodb.com/webinars
• Denos su opinión, por favor: back-to-basics@mongodb.com

40. ¿Preguntas?