MongoDB Use Cases and Roadmap

Use Cases and Roadmap

Norberto Leite

Senior Solutions Architect, [email protected]

@nleite

Thursday, 25 October 12

mailto:[email protected]

mailto:[email protected]

Agenda

•Use Cases•Roadmap•Future


Use Cases


Big Data = MongoDB = Solved

User Data Management High Volume Data Feeds

Content Management Operational Intelligence E-Commerce

Mobile


Location Based Service

•Problem:•Location based social networking service needs to scale to high number of users and check-ins

•Solution:•Used MongoDB deployed on EC2•8 clusters, 40 machines, 15k QPS, 2.3 billion records•Auto-sharding and geo-spatial indexing are key

•Results:•To date have scaled to 9m users, 3m check-ins per day, 750m total check-ins, 20m places, 400k merchants


•Problem:•Business needed modern data store for rapid development and scale

•Solution:•Used PHP and MongoDB

•Results:•RealTime estatistics•All data, images etc store together•No need for complex migrations•Enable very rapid development and growth


•Problem:•Deal with massive data volume across all customers

•Solution:•Use MongoDB to replace Google Analytics / Omniture

•Results:•Less than one week to build prototype and POC•Rapid deployment of new features


•Problem:•Lots of friction with RDMS for archiving storage•Needed to more scalable archive storage database

•Solution:•Keep MySQL for active data ( 100 Million )•MongoDB for archive ( 2 Billion )

•Results:•No more alter tables statements taking over 2 months•Sharding fixed vertical scale problem•Very happily looking for other ways to use MongoDB


How Telefónica uses MongoDBM2M Event Acquisition

MNOn

Operator Network

MNO1MNO2

Event acquisition

Event notification

BOSS

Event Gateway

Event Storage

Event Notifier Portal

MngPlatform

MngStorage

API

Core

Apps

Mng


And many others ...


Roadmap


The Evolution of MongoDB

2.2Aug ‘12

2.4 winter ‘12

2.0Sept ‘11

1.8March ‘11

Journaling

Sharding and Replica set enhancements

Spherical geo search

Index enhancements to improve size and performance

Authentication with sharded clusters

Replica Set Enhancements

Concurrency improvements

Aggregation Framework

Multi-Data Center Deployments

Improved Performance and Concurrency


• Concurrency: yielding + db level locking • New aggregation framework• TTL Collections• Improved free list implementation• Tag aware sharding• Read Preferences

• http://docs.mongodb.org/manual/release-notes/2.2/

2.2 Release August 2012


Yielding + DB Locking

• improved yielding on page fault• breaking down the global level lock• Lock per Database in 2.2• Lock per Collection post 2.2


Aggregation Framework• pipeline model (a bit like unix pipes)• like a "group by"–Operators–$project, $group, $match, $limit, $skip, $unwind, $sort

– Expressions–Logical Expressions: $and, $not, $or, $cmp ...–Math Expressions: $add, $divide, $mod ...–String Expressions: $strcasecmp, $substr, $toLower ...–Date/Time Expressions: $dayOfMonth, $hour...–Multi-Expressions: $ifNull, $cond

• Use Cases: Real-time / inline analytics


Example - For each "tag", list the authors{ title : "my tech blog" , author : "bob" , tags : [ "fun" , "good" , "tech" ] ,}

{ title : "cool tech" , author : "jim" , tags : [ "awesome" , "tech" ] ,}


Aggregate Command

db.blogs.aggregate( { $project : { author : 1, tags : 1 } }, { $unwind : "$tags" }, { $group : { _id : { tags : "$tags" }, authors : { $addToSet : "$author" } } });


Time To Live (TTL)Collections• auto expire data out of a collection• must be on a date datatype• single value is evaluated• Use Cases: data retention, cache expiration

db.events.ensureIndex( { "timestamp": 1 }, { expireAfterSeconds: 3600 } )


Tag aware sharding

• Distribute data based on a Tag• Use Cases: Locality for Data by Data Center

sh.addShardTag("shard0000", "dc-emea")

sh.addTagRange("mydb.users", { country: "uk"}, { country: "ul"}, "dc-emea");

sh.addTagRange("mydb.users", { country: "by"},{ country: "bz"}, "dc-emea");


Read Preferences

• Mode• PRIMARY, PRIMARY_PREFERRED• SECONDARY, SECONDARY_PREFERRED• NEAREST

• Tag Sets• Uses Replica Set tags• Passed Tag is used to find matching members


2.4 Roadmap

Must• Kerberos integration• LDAP/AD integration

Nice To Have• Hash Shard Key• Background Index Build on Secondaries• V8 for Map/Reduce (replaces Spider Monkey)• Geo: intersecting polygons, Geo shard key• Agg: $out, more functions, speed improvements


And beyond

• Full Text Search• Collection / Extent level locking• Field level security• Audit


MongoDB Use Cases and Roadmap

Technology

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