Building Your First Java Application with MongoDB

Building your first Java app with MongoDB

Today’s webinar
• Introduction to MongoDB.

• Use a location-based surf report app as an
example.

• Basic data modelling, queries (inc
geospatial) and aggregation.

• MongoDB JS shell and Java code examples.

What is MongoDB?
• MongoDB is a scalable, high-performance,
open source NoSQL database.
• Document-oriented storage
• Full index support - including geospatial
• Querying
• Fast in-place updates
• Map-Reduce and Aggregation
• Replication and high availability
• Horizontal scaling with auto-sharding
• GridFS

Open source
• MongoDB is an open source project
• On GitHub
• Licensed under the AGPL
• Started & sponsored by 10gen
• Commercial licenses available
• Contributions welcome

High performance
• Written in C++
• Extensive use of memory-mapped files
i.e. read-through write-through memory
caching.
• Runs nearly everywhere
• Data serialized as BSON (fast parsing)
• Full support for primary & secondary indexes
• Document model = less work

Example document
{
"_id" :
ObjectId("4c4ba5c0672c685e5e8aabf3"),
"reporter" : "Hergé",
"date" : ISODate("2012-02-
02T11:52:27.442Z"),
"location" : {
"name" : "Watergate Bay",
"state" : "Cornwall",
"country" : "UK”
}

Let’s build a location-based surf reporting app!


• Report current conditions


• Get current local conditions


• Get current local conditions
• Determine best conditions per beach

Document structure
{
"_id" : ObjectId("504ceb3d30042d707af96fef"),
"reporter" : "matt",
"location" : {
"coordinates" : [
-50.46667,
5.05
],
"county" : "Cornwall"
},
"conditions" : {
"height" : 3,
"period" : 13,
"rating" : 5
},
"date" : ISODate("2011-11-16T20:17:17.277Z")
}

Document structure
{
"_id" : ObjectId("504ceb3d30042d707af96fef"), Primary Key,
Unique,
"location" : {
"coordinates" : [ Auto-indexed
-50.46667,
5.05
],
},
"conditions" : {
"height" : 3,
"period" : 13,
"rating" : 5
},
"date" : ISODate("2011-11-16T20:17:17.277Z")
}

Document structure
{
Unique,
"location" : {
-50.46667,
5.05
], Geospatial
Compound Index
},
"conditions" : {
"height" : 3,
"period" : 13,
"rating" : 5
},
"date" : ISODate("2011-11-16T20:17:17.277Z")
}

Document structure
{
Unique,
"location" : {
-50.46667,
5.05
], Geospatial
Compound Index
},
"conditions" : {
"height" : 3,
"period" : 13,
"rating" : 5 Indexed for
}, Time-To-Live
"date" : ISODate("2011-11-16T20:17:17.277Z")
}

Java: DBObjects
BasicDBObject report = new BasicDBObject();
report.put("reporter", "matt");
report.put("date", new Date());

BasicDBObject location = new BasicDBObject();
location.put("name", "Watergate Bay");
location.put("county", "Cornwall");
location.put("country", "UK");
location.put("coordinates", new double[] {-50.46667, 5.05});

report .put("location", location);

BasicDBObject conditions = new BasicDBObject();
conditions .put("height", 3);
conditions .put("period", 13);
conditions.put("rating", 5);

report .put("conditions", conditions);

Connecting to MongoDB
Mongo m = new Mongo(Arrays.asList(
new ServerAddress("localhost", 27017),
new ServerAddress("localhost", 27018),
new ServerAddress("localhost", 27019)));

DB db = m.getDB( ”SurfReports” );
DBCollection coll = db. getCollection(“reports”);

Inserting and finding a document
coll.insert(report);

DBObject report2 = coll.findOne();
System.out.println(report2);

{ "_id" : ObjectId("504ceb3d30042d707af96fef"), "reporter" : "matt”, "location" : {
"coordinates" : [-50.46667, 5.05], "name" : "Watergate Bay”, "county" : "Cornwall" },
"conditions" : { "height" : 3, "period" : 13, "rating" : 5}, "date" : ISODate("2011-11-
16T20:17:17.277Z”)}

Get local surf conditions - shell
> db.reports.find(
{
"location.coordinates" : { $near : [50.41, -5.08] ,
$maxDistance : 0.5},
date : { $gte : new Date(2012, 11, 21)}
},
{"location.name" :1, _id : 0, "conditions" :1}
).sort({"conditions.rating" : -1})

> db.reports.find(
{
date : { $gte : new Date(2012, 11, 21)}
},

• Get local reports

> db.reports.find(
{
date : { $gte : new Date(2012, 11, 21)}
},

• Get today’s reports

> db.reports.find(
{
date : { $gte : new Date(2012, 11, 21)}
},

• Return only the relevant info

> db.reports.find(
{
date : { $gte : new Date(2012, 11, 21)}
},

• Return only the relevant info
• Show me the best surf first

Local surf conditions results
{ "location" : { "name" : ”Watergate Bay" }, "conditions" : { "height" : 3, "period" : 13, "rating" : 5 } }
{ "location" : { "name" : "Watergate Bay" }, "conditions" : { "height" : 2.5, "period" : 9, "rating" :4 } }
{ "location" : { "name" : ”Fistral North" }, "conditions" : { "height" : 3, "period" : 15, "rating" : 3 } }
{ "location" : { "name" : "Fistral North" }, "conditions" : { "height" : 3, "period" : 16, "rating" : 2 } }
{ "location" : { "name" : "Fistral North" }, "conditions" : { "height" : 0, "period" : 8, "rating" : 1 } }
{ "location" : { "name" : ”Little Fistral" }, "conditions" : { "height" : 3, "period" : 10, "rating" : 1 } }
{ "location" : { "name" : "Little Fistral" }, "conditions" : { "height" : 1, "period" : 15, "rating" : 1 } }
{ "location" : { "name" : ”Cribbar" }, "conditions" : { "height" : 5, "period" : 6, "rating" : 1 } }
{ "location" : { "name" : "Cribbar" }, "conditions" : { "height" : 1, "period" : 6, "rating" : 1 } }
{ "location" : { "name" : "Cribbar" }, "conditions" : { "height" : 0, "period" : 10, "rating" : 1 } }

Analysis feature:
Aggregation framework

What are the best conditions for my beach?

• Process a stream of documents
• Original input is a collection
• Final output is a result document
• Series of operators
• Filter or transform data
• Input/output chain

ps ax | grep mongod | head -n 1

Pipelining operations
$match Match “Fistral North”

$project Only interested in conditions

Group by rating, average
$group
wave height and wave period

$sort Order by best conditions

{ "aggregate" : "reports" ,
"pipeline" : [
{ "$match" : { "location.name" : ”Fistral North"}} ,
{ "$project" : { "conditions" : 1}} ,
{ "$group" : {
"_id" : "$conditions.rating" ,
"average height" : { "$avg" : "$conditions.height"} ,
"average period" : { "$avg" : "$conditions.period"}}} ,
{ "$sort" : { "_id" : -1}}
]
}

"pipeline" : [
{ "$group" : {
{ "$sort" : { "_id" : -1}}
]
}

Match “Fistral North”

"pipeline" : [
{ "$group" : {
{ "$sort" : { "_id" : -1}}
]
}

Only interested in conditions

"pipeline" : [
{ "$group" : {
{ "$sort" : { "_id" : -1}}
]
}

Group by rating and average conditions

"pipeline" : [
{ "$group" : {
{ "$sort" : { "_id" : -1}}
]
}

Show the best conditions first

High availability: Replica sets
• Initialize -> Election
• Primary + data replication from primary to secondary

Node 1 Node 2
Secondary Heartbeat Secondary

Node 3
Primary Replication
Replication

Replica Set - failure
• Primary down/network failure
• Automatic election of new primary if majority exists

Primary Election
Node 1 Node 2
Secondary Heartbeat Secondary

Node 3
Primary

Replica Set - failover
• New primary elected
• Replication established from new primary

Node 1 Node 2
Secondary Heartbeat Primary

Node 3
Primary

Durability
• WriteConcern.SAFE
• WriteConcern.JOURNAL_SAFE
• WriteConcern.FSYNC_SAFE
• WriteConcern.REPLICAS_SAFE
• WriteConcern.MAJORITY
• WriteConcern.NORMAL
• WriteConcern.NONE

m.setWriteConcern(WriteConcern.SAFE);
coll.save(dbObj,WriteConcern.SAFE);

Read preferences
• ReadPreference.primary()
• ReadPreference.primaryPreferred()
• ReadPreference.secondary()
• ReadPreference.secondaryPreferred()
• ReadPreference.nearest()

ReadPreference preference = ReadPreference.primaryPreferred();
DBCursor cur = new DBCursor(collection, query, null, preference);

Sharding
• Automatic partitioning and management

• Range based

• Convert to sharded system with no downtime

• Fully consistent

• No code changes required

Scaling MongoDB

MongoDB

Single Instance
or
Replica Set
Client
Application

Scaling MongoDB

Client
Application

Mechanism of sharding
Complete data set

Define shard key on location name

Cribbar Fistral Little Sennen Watergate
North Fistral Bay

Chunk Chunk

Define shard key on location name

North Fistral Bay

Chunk Chunk Chunk Chunk

North Fistral Bay

Chunk Chunk Chunk Chunk

Shard 1 Shard 2 Shard 3 Shard 4


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Query: Watergate Bay
Client
Application
config
config
config
mongos

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48

Query: Cribbar
Client
Application
config
config
config
mongos

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49

More information
Resource Location

MongoDB Downloads www.mongodb.org/download

Free Online Training education.10gen.com

Webinars and Events www.10gen.com/events

White Papers www.10gen.com/white-papers

Customer Case Studies www.10gen.com/customers

Presentations www.10gen.com/presentations

Documentation docs.mongodb.org

Additional Info info@10gen.com

Building Your First Java Application with MongoDB

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