MongoDB FabLab León
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This document provides an overview of MongoDB, including: - The speaker's credentials and agenda for the presentation - Key advantages and concepts of MongoDB like its document-oriented and schemaless nature - Products, characteristics, schema design, data modeling, installation types, and CRUD operations in MongoDB - Data analytics using the aggregation framework and tools - Topics like indexing, replica sets, sharded clusters, and scaling in MongoDB - Security, Python driver examples, and resources for learning more about MongoDB
![JSON Document MongoDB Overview
> db.customers.findOne()
{
"_id" : ObjectId("54131863041cd2e6181156ba"),
"date" : ISODate("2018-02-28T23:12:25Z"),
"first_name" : "Peter",
"last_name" : "Keil",
"address" : {
"street" : "C/Alcalá",
"number" : 123,
"location" : "Madrid",
},
"pets" : [
{
"type" : "Dog",
"breed" : "Airedale Terrier",
"name" : "Linda",
"location" : {
type : "Point",
coordinates : [ -5.724332, 40.959219 ]
}
},
{
"type" : "Dog",
...
}
]
}
>
10
_id
string
date
subdocument
number
array
geo-location](https://image.slidesharecdn.com/mongodb-fablableon-180409185632/85/MongoDB-FabLab-Leon-10-320.jpg)
![Relational Approach vs Document Model MongoDB Overview
12
Relational Approach MongoDB Document Model
{
"_id" : ObjectId("54131863041cd2e6181156ba"),
"date" : ISODate("2018-02-28T23:12:25Z"),
"first_name" : "Peter",
"last_name" : "Keil",
"address" : {
"street" : "C/Alcalá",
"number" : 123,
"location" : "Madrid",
},
"pets" : [
{
"type" : "Dog",
"breed" : "Airedale Terrier",
"name" : "Linda",
"location" : {
type : "Point",
coordinates : [ -5.724332, 40.959219 ]
}
},
{
"type" : "Dog",
...
}
]
}](https://image.slidesharecdn.com/mongodb-fablableon-180409185632/85/MongoDB-FabLab-Leon-12-320.jpg)
![# Inserting a document with fields, arrays and subdocuments
> doc =
{ <field1> : <value1>,
<field2> : [
{ <field3> : <value3>, <field4> : <value4>, <field5> : <value5>
},
{ <field6> : <value6>, <field7> : <value7> },
{ <field8> : <value8> }
]
}
> db.<collectionName>.insert( doc)
CRUD - Insert MongoDB Overview
19](https://image.slidesharecdn.com/mongodb-fablableon-180409185632/85/MongoDB-FabLab-Leon-19-320.jpg)
![Aggregation Framework - Pipeline MongoDB Overview
23
> criteria = { $match : { <field1> : <value1> } }
> group = { $group : { "$_id" : "$<field2>",
<new_field> : { <operator> : "$<field3>" } } }
> projection = { $project : { "_id" : 0,
<new_field2>: "$_id",
<new_field3>: "$<new_field>"
}
}
> sort = { $sort : { <new_field3> : 1 } }
> pipeline = [ criteria, group, projection, sort ]
> db.<collectionName>.aggregate(pipeline)](https://image.slidesharecdn.com/mongodb-fablableon-180409185632/85/MongoDB-FabLab-Leon-23-320.jpg)
![Python Driver - CRUD Examples MongoDB Overview
38
$python find_one.py
El nombre de la persona leida es: Peter
find_one.py
import pymongo
from pymongo import MongoClient
try:
connMDB = MongoClient('localhost', 27017)
except Exception as e:
print 'Error de conexion a la base de datos', type(e),
e
db = connMDB.usalfullstack
personas = db.personas
persona = personas. find_one()
print 'El nombre de la persona leida es: ', persona['name']](https://image.slidesharecdn.com/mongodb-fablableon-180409185632/85/MongoDB-FabLab-Leon-38-320.jpg)
![Python Driver - CRUD Examples MongoDB Overview
39
Insert
pedro = { 'firstname':'Pedro', 'lastname':'García' }
maria = { 'firstname':'María', 'lastname':'Pérez' }
doc = [ pedro, maria ]
customers.insert_many(doc, ordered:True)
Update
customers.update_one({'_id':customer_id},
{$set:{'city':'Huelva'}})
Remove
customers.delete_one( { '_id' : customer_id } )](https://image.slidesharecdn.com/mongodb-fablableon-180409185632/85/MongoDB-FabLab-Leon-39-320.jpg)
![Python Driver - Cursors And Exceptions MongoDB Overview
40
import pymongo
import sys
from pymongo import MongoClient
connection = MongoClient('localhost',27017)
db = connection.test
customers = db.customers
query = { 'firstname' : 'Juan' }
projection = { 'city' : 1, '_id' : 0 }
try:
cursor = customers.find(query,projection)
except Exception as e:
print 'Unexpected error: ', type(e), e
for doc in cursor:
print doc['city']](https://image.slidesharecdn.com/mongodb-fablableon-180409185632/85/MongoDB-FabLab-Leon-40-320.jpg)
MongoDB FabLab León
- 1. basicsbasics Learn all you need to know about MongoDB! April 6, 2018
- 2. Who am I? Juan Antonio Roy Couto ❏ MongoDB Master ❏ MongoDB DEV&DBA Certified ❏ MongoDB DBA at Grupo Undanet ❏ Email: [email protected] ❏ Twitter: @juanroycouto ❏ Personal site: http://www.juanroy.es 2
- 3. ❏ Advantages ❏ Concepts ❏ Products ❏ Characteristics ❏ Schema Design ❏ Data Modelling ❏ Installation Types ❏ Must Know ❏ CRUD Agenda MongoDB Overview 3 ❏ Aggregation Framework ❏ Analytics Tools ❏ Indexes ❏ Replica Set ❏ Sharded Cluster ❏ Scaling ❏ Security ❏ Python Driver Overview ❏ Resources
- 4. Advantages MongoDB Overview ❏ High Availability ❏ Data Safety ❏ Automatic Failover ❏ Scalability 4 ❏ Faster development ❏ Real time analytics ❏ Better strategic decisions ❏ Reduce costs and time to market
- 5. 5 MongoDB SQL Database Database Collection Table Document Row Embedding/$lookup Join Concepts MongoDB Overview
- 6. Products https://www.mongodb.com/products/overview MongoDB Overview 6 ❏ Atlas (Database as a Service) ❏ Stitch (Backend as a Service) ❏ Drivers ❏ Ops & Cloud Manager ❏ Compass ❏ Hadoop & Spark connector ❏ BI connector
- 7. Characteristics MongoDB Overview 7 ❏ Open Source General Purpose NoSQL Database ❏ Document Oriented ❏ Non-Structured Data ❏ Schemaless ❏ Security (Authentication & Authorization) ❏ Schema Validation ❏ Backup & Restore ❏ Automation ❏ Encryption ❏ Geo-Location ❏ Graph processing ❏ Aggregation Framework ❏ Joins ❏ Change Streams ❏ Retryable Writes ❏ Pluggable Storage Engine API ❏ Multi-document ACID transactions on June, 4.0 version
- 8. SQL Schema Design MongoDB Overview 8 ❏ Customer Key ❏ First Name ❏ Last Name Tables Customers ❏ Address Key ❏ Customer Key ❏ Street ❏ Number ❏ Location Addresses ❏ Pet Key ❏ Customer Key ❏ Type ❏ Breed ❏ Name Pets
- 9. MongoDB Schema Design MongoDB Overview 9 Customers Collection ❏ Street ❏ Number ❏ Location Addresses ❏ Type ❏ Breed ❏ Name Pets Customers Info ❏ First Name ❏ Last Name ❏ Type ❏ Breed ❏ Name
- 10. JSON Document MongoDB Overview > db.customers.findOne() { "_id" : ObjectId("54131863041cd2e6181156ba"), "date" : ISODate("2018-02-28T23:12:25Z"), "first_name" : "Peter", "last_name" : "Keil", "address" : { "street" : "C/Alcalá", "number" : 123, "location" : "Madrid", }, "pets" : [ { "type" : "Dog", "breed" : "Airedale Terrier", "name" : "Linda", "location" : { type : "Point", coordinates : [ -5.724332, 40.959219 ] } }, { "type" : "Dog", ... } ] } > 10 _id string date subdocument number array geo-location
- 11. Data Modelling MongoDB Overview 11 1:1 Employee-Resume ❏ Access frequency ❏ Documents size ❏ Data atomicity 1:N City-Citizen ❏ Two linked collections from N to 1 N:N Books-Authors ❏ Two collections linked via array 1:Few Post-Comments ❏ One collection with embedded data Limits: 16MB/doc
- 12. Relational Approach vs Document Model MongoDB Overview 12 Relational Approach MongoDB Document Model { "_id" : ObjectId("54131863041cd2e6181156ba"), "date" : ISODate("2018-02-28T23:12:25Z"), "first_name" : "Peter", "last_name" : "Keil", "address" : { "street" : "C/Alcalá", "number" : 123, "location" : "Madrid", }, "pets" : [ { "type" : "Dog", "breed" : "Airedale Terrier", "name" : "Linda", "location" : { type : "Point", coordinates : [ -5.724332, 40.959219 ] } }, { "type" : "Dog", ... } ] }
- 13. Installation Types - Standalone MongoDB Overview 13 MongoDB Client DRIVER Client DRIVER Client DRIVER
- 14. Installation Types - Replica Set MongoDB Overview 14 SecondarySecondary Primary Client DRIVER Client DRIVER Client DRIVER Replica Set
- 15. Installation Types - Sharded Cluster MongoDB Overview 15 Replica Set Secondary Secondary Primary Client DRIVER Client DRIVER Client DRIVER Secondary Secondary Primary Secondary Secondary Primary Secondary Secondary Primary mongos mongos mongos config server config server config server Shard 0 Shard 1 Shard 2 Shard N-1
- 16. ❏ In MongodB it’s not necessary to: ❏ Create a Database, simply use it! ❏ Create a Collection, simply insert one document on it! ❏ Predefine the schema of the collections, MongoDB it’s schemaless ❏ Once MongoDB is running on your machine connect to your database from the shell in this way: $ mongo Must Know MongoDB Overview 16
- 17. ❏ Find ❏ Insert ❏ Bulk inserts for massive Data Load ❏ Update ❏ Remove CRUD MongoDB Overview 17
- 18. # Select database > use usalfullstack # Select all documents on the collection > db.<collectionName>.find().pretty() # Select documents that match the criteria > criteria = { <field1> : <value1>, <field2> : <value2> } > db.<collectionName>.find( criteria) # Filtering fields > projection = { <field1> : 1, <field2> : 1 } > db.<collectionName>.find({}, projection) CRUD - Find MongoDB Overview 18
- 19. # Inserting a document with fields, arrays and subdocuments > doc = { <field1> : <value1>, <field2> : [ { <field3> : <value3>, <field4> : <value4>, <field5> : <value5> }, { <field6> : <value6>, <field7> : <value7> }, { <field8> : <value8> } ] } > db.<collectionName>.insert( doc) CRUD - Insert MongoDB Overview 19
- 20. # Updating the document that match the criteria > criteria = { <field1> : <value1 } > new_doc = { <field2> : <value2>, <field3> : <value3> } > db.<collectionName>.update( criteria, new_doc) # Updating only one field of all the documents that match the criteria > criteria = { <field1> : <value1 } > new_value = { operator : { <field3> : <value3> } } > db.<collectionName>.update( criteria, new_value, { multi : true }) CRUD - Update MongoDB Overview 20
- 21. CRUD - Remove MongoDB Overview # Removing all documents that match the criteria > criteria = { <field1> : <value1 } > db.<collectionName>.remove( criteria) 21
- 22. Data Analytics with the Aggregation Framework MongoDB Overview 22
- 23. Aggregation Framework - Pipeline MongoDB Overview 23 > criteria = { $match : { <field1> : <value1> } } > group = { $group : { "$_id" : "$<field2>", <new_field> : { <operator> : "$<field3>" } } } > projection = { $project : { "_id" : 0, <new_field2>: "$_id", <new_field3>: "$<new_field>" } } > sort = { $sort : { <new_field3> : 1 } } > pipeline = [ criteria, group, projection, sort ] > db.<collectionName>.aggregate(pipeline)
- 24. Data analytics Tools MongoDB Overview 24 ❏ Internals ❏ Aggregation Framework ❏ Map Reduce ❏ Externals ❏ Spark ❏ Hadoop ❏ Tableau (BI) ❏ ...
- 25. MongoDB Overview 25 Indexing - Types ❏ _id ❏ Single ❏ Compound ❏ Multikey ❏ Full Text ❏ GeoSpatial ❏ Hashed
- 26. MongoDB Overview 26 Indexing - Properties ❏ Unique ❏ Sparse ❏ TTL ❏ Partial
- 27. MongoDB Overview 27 Indexing - Improving Your Queries .explain() ❏ queryPlanner ❏ executionStats ❏ allPlansExecution
- 28. Replica Set ❏ High Availability ❏ Data Safety ❏ Automatic Node Recovery ❏ Read Preference ❏ Write Concern Replica Set Secondary Secondary Primary MongoDB Overview 28
- 29. ❏ Scale out ❏ Even data distribution across all of the shards based on a shard key ❏ A shard key range belongs to only one shard ❏ More efficient queries (performance) Sharded Cluster Cluster Shard 0 Shard 2Shard 1 A-I J-Q R-Z MongoDB Overview 29
- 30. Sharded Cluster - Config Servers ❏ config database ❏ Metadata: ❏ Cluster shards list ❏ Data per shard (chunk ranges) ❏ ... ❏ Replica Set MongoDB Overview 30 Replica Set config server config server config server
- 31. ❏ Receives client requests and returns results. ❏ Reads the metadata and sends the query to the necessary shard/shards. ❏ Does not store data. ❏ Keeps a cache version of the metadata. Sharded Cluster - mongos MongoDB Overview 31 Replica Set DRIVER Secondary Secondary Primary Secondary Secondary Primary mongos config server config server config server Shard 0 Shard N-1
- 32. How To Scale Your App - Shard Key MongoDB Overview 32 ❏ Monotonically Increasing ❏ Easy divisible❏ Randomness❏ Cardinality
- 33. How To Scale Your App Sharding a Collection MongoDB Overview Shard 0 Shard 1 Shard 2 Shard 3 mongos Client Migrations
- 34. How To Scale Your App - Pre-Splitting MongoDB Overview 34 ● Useful for storing data directly in the shards (massive data loads). ● Avoid bottlenecks. ● MongoDB does not need to split or migrate chunks. ● After the split, the migration must be finished before data loading. Cluster Shard 0 Shard 2Shard 1 Chunk 1 Chunk 5 Chunk 3 Chunk 4 Chunk 2
- 35. How To Scale Your App Tag-Aware Sharding MongoDB Overview 35 ● Tags are used when you want to pin ranges to a specific shard. shard0 EMEA shard1 APAC shard2 LATAM shard3 NORAM
- 36. Security MongoDB Overview 36 ● Authentication ○ Users ○ Servers ● Authorization ○ Roles ○ Privileges (actions over resources) ● Read-Only Views ● Encryption ● Auditing
- 37. Python Driver - CRUD MongoDB Overview 37 PyMongo Server Finding find find find_one findOne Inserting insert_one insert insert_many bulk Updating update_one update update_many update replace_one update Deleting delete_one remove delete_many remove
- 38. Python Driver - CRUD Examples MongoDB Overview 38 $python find_one.py El nombre de la persona leida es: Peter find_one.py import pymongo from pymongo import MongoClient try: connMDB = MongoClient('localhost', 27017) except Exception as e: print 'Error de conexion a la base de datos', type(e), e db = connMDB.usalfullstack personas = db.personas persona = personas. find_one() print 'El nombre de la persona leida es: ', persona['name']
- 39. Python Driver - CRUD Examples MongoDB Overview 39 Insert pedro = { 'firstname':'Pedro', 'lastname':'García' } maria = { 'firstname':'María', 'lastname':'Pérez' } doc = [ pedro, maria ] customers.insert_many(doc, ordered:True) Update customers.update_one({'_id':customer_id}, {$set:{'city':'Huelva'}}) Remove customers.delete_one( { '_id' : customer_id } )
- 40. Python Driver - Cursors And Exceptions MongoDB Overview 40 import pymongo import sys from pymongo import MongoClient connection = MongoClient('localhost',27017) db = connection.test customers = db.customers query = { 'firstname' : 'Juan' } projection = { 'city' : 1, '_id' : 0 } try: cursor = customers.find(query,projection) except Exception as e: print 'Unexpected error: ', type(e), e for doc in cursor: print doc['city']
- 41. Resources 41 ◆ Official MongoDB Documentation ● https://docs.mongodb.org/manual/ ◆ pymongo ● https://pypi.python.org/pypi/pymongo/3.6.0 ◆ Install MongoDB on Linux ● https://docs.mongodb.com/manual/administration/install-on-linux/ ◆ Install MongoDB on macOS ● https://docs.mongodb.com/manual/tutorial/install-mongodb-on-os-x/ ◆ Install MongoDB on Windows ● https://docs.mongodb.com/manual/tutorial/install-mongodb-on-windows/ ◆ MongoDB University ● https://university.mongodb.com/ MongoDB Overview
- 43. basicsbasics Thank you for your attention! basicsbasics Learn all you need to know about MongoDB! April 6, 2018