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![MongoDB: The Leading NoSQL Database
Document
Data Model
Open-
Source
Fully Featured
High Performance
Scalable
{
name: “John Smith”,
pfxs: [“Dr.”,”Mr.”],
address: “10 3rd St.”,
phones: [
{ number: “555-1212”,
type: “land” },
{ number: “444-1212”,
type: “mobile” }
]
}](https://image.slidesharecdn.com/learnmdbmug20160107-160108020149/85/Introduction-to-MongoDB-4-320.jpg)
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![{
_id: “123”,
title: "MongoDB: The Definitive Guide",
authors: [
{ _id: "kchodorow", name: "Kristina Chodorow“ },
{ _id: "mdirold", name: “Mike Dirolf“ }
],
published_date: ISODate(”2010-09-24”),
pages: 216,
language: "English",
thumbnail: BinData(0,"AREhMQ=="),
publisher: {
name: "O’Reilly Media",
founded: 1980,
locations: ["CA”, ”NY” ]
}
}
The Data Is The Schema](https://image.slidesharecdn.com/learnmdbmug20160107-160108020149/85/Introduction-to-MongoDB-9-320.jpg)
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![> db.authors.find()
{
_id: ”X12",
name: { first: "Kristina”, last: “Chodorow” },
personalData: {
favoritePets: [ “bird”, “dog” ],
awards: [ {name: “Hugo”, when: 1983}, {name: “SSFX”,
when: 1992} ]
}
}
{
_id: ”Y45",
name: { first: ”Mike”, last: “Dirolf” } ,
personalData: {
dob: ISODate(“1970-04-05”)
}
}
Treat Your Data More Like Objects](https://image.slidesharecdn.com/learnmdbmug20160107-160108020149/85/Introduction-to-MongoDB-10-320.jpg)
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![// Java: maps
DBObject query = new BasicDBObject(”publisher.founded”, 1980));
Map m = collection.findOne(query);
Date pubDate = (Date)m.get(”published_date”); // java.util.Date
List locs = (List)m.get(”locations”);
// Javascript: objects
m = collection.findOne({”publisher.founded” : 1980});
pubDate = m.published_date; // ISODate
year = pubDate.getUTCFullYear();
# Python: dictionaries
m = coll.find_one({”publisher.founded” : 1980 });
pubDate = m[”pubDate”].year # datetime.datetime
Documents Natively Map to Language](https://image.slidesharecdn.com/learnmdbmug20160107-160108020149/85/Introduction-to-MongoDB-11-320.jpg)
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![21
Verify Operation
$ mongodb-osx-x86_64-enterprise-3.2.0/bin/mongo
MongoDB shell version: 3.2.0
connecting to: 127.0.0.1:27017/test
Server has startup warnings:
2016-01-01T12:44:01.646-0500 I CONTROL [initandlisten]
2016-01-01T12:44:01.646-0500 I CONTROL [initandlisten] ** WARNING:
soft rlimits too low. Number of files is 256, should be at least
1000
MongoDB Enterprise > use mug
switched to db mug
MongoDB Enterprise > db.foo.insert({name:”bob”,hd: new ISODate()});
MongoDB Enterprise > db.foo.insert({name:"buzz"});
MongoDB Enterprise > db.foo.insert({pets:["dog","cat"]});
MongoDB Enterprise > db.foo.find();
{ "_id" : ObjectId("5686cef538ea4981e63111dd"), "name" : "bob", "hd"
: ISODate("2016-01-01T19:09:41.442Z") }
{ "_id" : ObjectId("5686…79d5"), "name" : "buzz" }
{ "_id" : ObjectId("5686…79d6"), "pets" : [ "dog", "cat" ] }](https://image.slidesharecdn.com/learnmdbmug20160107-160108020149/85/Introduction-to-MongoDB-21-320.jpg)
![22
The Simple Java App
import com.mongodb.client.*;
import com.mongodb.*;
import java.util.Map;
public class mug1 {
public static void main(String[] args) {
try {
MongoClient mongoClient = new MongoClient();
MongoDatabase db = mongoClient.getDatabase("mug”);
MongoCollection coll = db.getCollection("foo");
MongoCursor c = coll.find().iterator();
while(c.hasNext()) {
Map doc = (Map) c.next();
System.out.println(doc);
}
} catch(Exception e) {
// ...
}
}
}](https://image.slidesharecdn.com/learnmdbmug20160107-160108020149/85/Introduction-to-MongoDB-22-320.jpg)
![23
Compile and Run!
$ curl -o mongodb-driver-3.0.4.jar
https://oss.sonatype.org/content/repositories/releases/org
/mongodb/mongodb-driver/3.0.4/mongodb-driver-3.0.4.jar
$ javac –cp mongo-java-driver-3.0.4.jar:. mug1.java
$ java –cp mongo-java-driver-3.0.4.jar:. mug1
(logger output)
Document{{_id=5686cef538ea4981e63111dd, name=bob,
hd=Fri Jan 01 14:09:41 EST 2016}}
Document{{_id=5686c71338ea4981e63111d6, name=buzz}}
Document{{_id=5686c71938ea4981e63111d7, pets=[dog, cat]}}](https://image.slidesharecdn.com/learnmdbmug20160107-160108020149/85/Introduction-to-MongoDB-23-320.jpg)
![24
The Same App in python
from pymongo import MongoClient
client = MongoClient()
db = client.mug
coll = db.foo
for c in coll.find():
print c
$ python mug1.py
{u'_id': ObjectId('5686cef538ea4981e63111dd'), u'name': u'bob',
u'hd': datetime.datetime(2016, 1, 1, 19, 9, 41, 442000)}
{u'_id': ObjectId('5686f54b38ea4981e631124c'), u'name': u'buzz'}
{u'_id': ObjectId('5686f55138ea4981e631124d'), u'pets': [u'dog',
u'cat']}](https://image.slidesharecdn.com/learnmdbmug20160107-160108020149/85/Introduction-to-MongoDB-24-320.jpg)
![25
…and, as expected in Perl…
$ perl -MMongoDB -MData::Dumper –e 'my $c =
MongoDB::MongoClient->new()->get_database("mug")-
>get_collection("foo")->find(); while($c->has_next()) {
print Dumper($c->next()); }’
$VAR1 = { '_id' => bless( {'value' => '5686cef538ea4981e63111dd’},
'MongoDB::OID' ),
'hd' => bless( {
'local_rd_secs' => 68981,
'rd_nanosecs' => 442000000, // etc
}, 'DateTime' ),
'name' => 'bob'
};
$VAR1 = { '_id' => bless( {'value' => '5686c71338ea4981e63111d6’},
'MongoDB::OID' ),
'name' => 'buzz'
};
$VAR1 = { 'pets' => [ 'dog’,'cat’],
'_id' => bless( {'value' => '5686c71938ea4981e63111d7’},
'MongoDB::OID' )
};](https://image.slidesharecdn.com/learnmdbmug20160107-160108020149/85/Introduction-to-MongoDB-25-320.jpg)
![Document Validation: Stronger Than
Schema…?
> db.createCollection(”contacts", { "validator":
{ $or: [
{ $and: [ { “vers": 1},
{ ”customer_id": {$type: “string”} }
]
},
{ $and: [ { "vers": 2},
{ ”customer_id": {$type: “string”} },
{ $or: [
{ ”name.f": {$type: “string”},
”name.l": {$type: “string”}}
,
{ ”ssn": {$type: “string”}}
]
}
]
}]});](https://image.slidesharecdn.com/learnmdbmug20160107-160108020149/85/Introduction-to-MongoDB-27-320.jpg)
![A Slightly Bigger Example
Relational MongoDB
{ vers: 1,
customer_id : 1,
name : {
“f”:"Mark”,
“l”:"Smith” },
city : "San Francisco",
phones: [ {
number : “1-212-777-1212”,
dnc : true,
type : “home”
},
{
number : “1-212-777-1213”,
type : “cell”
}]
}
Customer
ID
First Name Last Name City
0 John Doe New York
1 Mark Smith San Francisco
2 Jay White Dallas
3 Meagan White London
4 Edward Daniels Boston
Phone Number Type DNC
Customer
ID
1-212-555-1212 home T 0
1-212-555-1213 home T 0
1-212-555-1214 cell F 0
1-212-777-1212 home T 1
1-212-777-1213 cell (null) 1
1-212-888-1212 home F 2](https://image.slidesharecdn.com/learnmdbmug20160107-160108020149/85/Introduction-to-MongoDB-28-320.jpg)
![29
MongoDB Queries Are Expressive
SQL select A.did, A.lname, A.hiredate, B.type,
B.number from contact A left outer join phones B
on (B.did = A.did) where b.type = ’home' or
A.hiredate > '2014-02-02'::date
MongoDB CLI db.contacts.find({"$or”: [
{"phones.type":”home”},
{"hiredate": {”$gt": new ISODate("2014-
02-02")}}
]});
Find all contacts with at least one home phone or
hired after 2014-02-02](https://image.slidesharecdn.com/learnmdbmug20160107-160108020149/85/Introduction-to-MongoDB-29-320.jpg)
![30
MongoDB Aggregation Is Powerful
Sum the different types of phones and create a list
of the owners if there is more than 1 of that type
> db.contacts.aggregate([
{$unwind: "$phones"}
,{$group: {"_id": "$phones.t", "count": {$sum:1},
"names": {$push: "$name"} }}
,{$match: {"count": {$gt: 1}}}
]);
{ "_id" : "home", "count" : 2, "names" : [
{ "f" : "John", "l" : "Doe" },
{ "f" : "Mark", "l" : "Smith" } ] }
{ "_id" : "cell", "count" : 4, "names" : [
{ "f" : "John", "l" : "Doe" },
{ "f" : "Meagan", "l" : "White" },
{ "f" : "Edward", "l" : "Daniels” }
{ "f" : "Mark", "l" : "Smith" } ] }](https://image.slidesharecdn.com/learnmdbmug20160107-160108020149/85/Introduction-to-MongoDB-30-320.jpg)
![31
$lookup: “Left Outer Join++”
> db.leases.aggregate([ ]);
{
"_id" : ObjectId("5642559e0d4f2076a43584fc"),
"leaseID" : "A5",
"sku" : "GD652",
"origDate" : ISODate("2010-01-01T00:00:00Z"),
"histDate" : ISODate("2010-10-28T00:00:00Z"),
"monthlyDue" : 10,
"vers" : 11,
"delinq" : { "d30" : 10, "d60" : 10, "d90" : 60
},
"credit" : 0
}
// 66 more ….
Step 1: Get a sense of the raw material](https://image.slidesharecdn.com/learnmdbmug20160107-160108020149/85/Introduction-to-MongoDB-31-320.jpg)
![32
$lookup: “Left Outer Join++”
Step 2: Group leases by SKU and capture count and max value of 90
day delinquency
> db.leases.aggregate([
{$group: { _id: "$sku", n:{$sum:1},
max90:{$max:"$delinq.d90"} }}
]);
{ "_id" : "AC775", "n" : 27, "max90" : 20 }
{ "_id" : "AB123", "n" : 26, "max90" : 5 }
{ "_id" : "GD652", "n" : 14, "max90" : 80 }](https://image.slidesharecdn.com/learnmdbmug20160107-160108020149/85/Introduction-to-MongoDB-32-320.jpg)
![33
$lookup: “Left Outer Join++”
Step 3: Reverse sort and then limit to the top 2
> db.leases.aggregate([
{$group: { _id: "$sku", n:{$sum:1},
max90:{$max:"$delinq.d90"} }}
,{$sort: {max90:-1}}
,{$limit: 2}
]);
{ "_id" : "GD652", "n" : 14, "max90" : 80 }
{ "_id" : "AC775", "n" : 27, "max90" : 20 }](https://image.slidesharecdn.com/learnmdbmug20160107-160108020149/85/Introduction-to-MongoDB-33-320.jpg)
![34
$lookup: “Left Outer Join++”
Step 4: $lookup to product collection and assign to new field
> db.leases.aggregate([
{$group: { _id: "$sku", n:{$sum:1},
max90:{$max:"$delinq.d90"} }}
,{$sort: {max90:-1}}
,{$limit: 2}
,{$lookup: { from: "products", localField: "_id", foreignField:
"productSKU", as:"productData"}}
]);
{ "_id" : "GD652”, "n" : 14, "max90" : 80,
"productData" : [
{
"_id" : ObjectId("5642559e0d4f2076a43584b5"),
"productType" : "rigidDumptruck",
"productSKU" : "GD652",
"properties" : {
"model" : "TR45",
"payload" : {
"std" : 45,
"unit" : "UStons"
},](https://image.slidesharecdn.com/learnmdbmug20160107-160108020149/85/Introduction-to-MongoDB-34-320.jpg)
![35
$lookup: “Left Outer Join++”
Step 5: Trim excess data away, leaving just type
> db.leases.aggregate([
{$group: { _id: "$sku", n:{$sum:1},
max90:{$max:"$delinq.d90"} }}
,{$sort: {max90:-1}}
,{$limit: 2}
,{$lookup: { from: "products", localField: "_id",
foreignField: "productSKU", as:"productData"}}
,{$project: { _id:1, n:1, max90:1, type:
"$productData.productType"}}
]);
{"_id”:"GD652”,"n”:14,"max90”:80,"type”:[”dumptruck”]}
{"_id”:"AC775”,"n”:27,"max90”:20,"type”:["loader”]}](https://image.slidesharecdn.com/learnmdbmug20160107-160108020149/85/Introduction-to-MongoDB-35-320.jpg)
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Introduction to MongoDB
The document presents an introduction to MongoDB by Buzz Moschetti, outlining its features as a leading NoSQL database, including high performance, scalability, and its document data model. It covers various use cases such as big data, mobile apps, and security, along with deployment instructions and examples in different programming languages. Additionally, it highlights MongoDB's advancements, such as enhanced document validation and the $lookup feature for database queries.
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