Superficial MongoDB

charsyam@naver.com

MongoDB NoSQL

Document

BSON

Document-Oriented Storage Full Index Support

Replication & High Availability

Auto Sharding Querying Fast In-Place Updates Map/Reduce GridFS

Document-Oriented Storage Full Index Support

Replication & High Availability

Auto Sharding Querying Fast In-Place Updates Map/Reduce GridFS

Document-Oriented > db.users.insert( { _id : "alex", name: { first:"Alex", last:"Benisson" }, karma : 1.0 } )

> db.posts.findOne() { _id : ObjectId("4e77bb3b8a3e000000004f7a"), when : Date("2011-09-19T02:10:11.3Z", author : "alex", title : "No Free Lunch", text : "This is the text of the post. It could be very long.", tags : [ "business", "ramblings" ], votes : 5, voters : [ "jane", "joe", "spencer", "phyllis", "li" ], comments : [ { who : "jane", when : Date("2011-09-19T04:00:10.112Z"), comment : "I agree." }, { who : "meghan", when : Date("2011-09-20T14:36:06.958Z"), comment : "You must be joking. etc etc ..." } ] }

Full-Index Support > db.things.ensureIndex({j:1});

> db.things.ensureIndex({"address.city": 1})

> db.things.ensureIndex({j:1, name:-1});

> db.factories.insert( { name: "xyz", metro: { city: "New York", state: "NY" } } ); > db.factories.ensureIndex( { metro : 1 } ); // this query can use the above index: > > db.factories.find( { metro: { city: "New York", state: "NY" } } ); // this one too, as {city:"New York"} < {city:"New York",state:"NY"} > db.factories.find( { metro: { $gte : { city: "New York" } } } ); // this query does not match the document because the order of fields is significant > db.factories.find( { metro: { state: "NY" , city: "New York" } } );

Replication Asynchronous Replication

HA & FailOver Only Write to Primary Can read from Secondary

Op Ordinal: Increasing ordinal to represent each operation

Using Server ID + Op Ordinal

Picking Primary 1. Get Max LocalOpOrdinal from each Server 2. if a majority of servers are not up (from this server's POV), remain in Secondary mode and stop. 3. if the last op time seems very old, stop and await human intervention. 4. else, using a consensus protocol, pick the server with the highest maxLocalOpOrdinal as the Primary.

TIPs.

Use 64bit Machine MongoDB Use Memory-Mapped File

In 32bit. DB Size can’t over 2.5GB

MongoDB is needed Big Memory

Use Replica Set Use Replica Set and Journaling

Use Lastest Version 2.0.2 is better than 1.8.x

MongoDB has global Lock

1.8.x uses global Write Lock 2.0.x uses write with yield.

Not supports db or collection lock

Use Big Memory Disk Op is slower than Memory Op

Shard

Shard Architecture

Basic

Replication unit is chunk.

Chunk: 64mb or 100,000 objects

Chunk Count > 9

Data is split up into Chunks

Mongod

Replica Set(3 mongod)

Data Store

Mongos

StateLess

Routing to Shard

Proxy

Mongod configSvr

Can’t use Replica Set or M/A

1(test) or 3(real)

mongod

Mongod configSvr

Changes are made with 2PC

If any are down, meta data goes read only

System is online as long as 1/3 is up

Use Scale Up than Sharding

Difficult to find good Shard Key.

Not Support Data Center awareness Add memory and hdd, ssd

Object Id_

Object Id_

12 bytes

Replica Set

Operations

Default: Write/read operation goes to master

Can read from slaves.

Thank you!