scaling with mongo db - sf mongo user group 7-19-2011

Scaling with MongoDB

Jared Rosoff (jsr@10gen.com) - @forjared

How do we do it today?

• We use a relational database but … – We don’t use joins – We don’t use transactions – We add read-only slaves– We added a caching layer– We de-normalized our data– We implemented custom sharding– We buy bigger servers

HOW’S THAT WORKING OUT FOR YOU?

Costs go up

Launch

+30

Days

+90

Days

+6

Months

+1 Year

Productivity goes downProject Start

De-normalize data model

Stop using joins

Custom caching layer

Custom sharding

By engineers, for engineers

The landscape

Depth of functionality

Sca

labi

lity

& P

erfo

rma

nce

MemcachedKey / Value

RDBMS

Scaling your app

1. Use documents 2. Indexes make me happy3. Knowing your working set4. Disks are the bottleneck5. Replication makes reading fun6. Sharding for profit

SCALING YOUR DATA MODEL

Documents

{ author : "roger", date : "Sat Jul 24 2010 19:47:11 GMT-0700 (PDT)", text : "Spirited Away", tags : [ "Tezuka", "Manga" ], comments : [ { author : "Fred", date : "Sat Jul 24 2010 20:51:03 GMT-0700 (PDT)", text : "Best Movie Ever” } ]}

Disk Seeks & Data Locality

Seek = 5+ ms Read = really really fast

Disk Seeks & Data Locality

Post

AuthorCommen

t

Disk Seeks & Data LocalityPost

Author

Comment

Comment

Comment

Comment

Comment

OPTIMIZED INDEXES

Table scans

1 2 3 4 5 6 7

Looked at 7 objects

Find where x equals 7

Tree Lookup

7

6

5

4

3

2

1

Looked at 3 objects

Find where x equals 7

Random Index

Entire index must fit in RAM

Right AlignedOnly small portion in

RAM

WORKING SET SIZE

Disk

Working Set

RAM

Active Documents

+ Used Indexes

Disk

Page Fault

RAM

App

1

23

4

5

1. App requests document

2. Document not in memory

3. Evict a page from memory

4. Read block from disk

5. Return document from memory

Figuring out working Set> db.foo.stats() {

"ns" : "test.foo","count" : 1338330,"size" : 46915928,"avgObjSize" : 35.05557523181876,"storageSize" : 86092032,"numExtents" : 12,"nindexes" : 2,"lastExtentSize" : 20872960,"paddingFactor" : 1,"flags" : 0,"totalIndexSize" : 99860480,"indexSizes" : {

"_id_" : 55877632,"x_1" : 43982848

},"ok" : 1

}

Size of data

Size on disk (and in

memory!)

Size of all indexes

Average document

size

Size of each index

DISK CONFIGURATIONS

Single Disk

~200 seeks / second

RAID0

~200 seeks / second ~200 seeks / second ~200 seeks / second

RAID10

~400 seeks / second ~400 seeks / second ~400 seeks / second

REPLICATION

Replica Sets

Primary

Secondary

Secondary

Read / Write

Read

Read

Replica SetsPrimary

Secondary

Secondary

Read / Write

Read

Read

Secondary

SecondaryRead

Read

SHARDING

Shard 10..10

Shard 210..20

Shard 320..30

Shard 430..40

Primary

Secondary

Secondary

Primary

Secondary

Secondary

Primary

Secondary

Secondary

Primary

Secondary

Secondary

MongoS MongoS

400GB Index?

Shard 10..10

Shard 210..20

Shard 320..30

Shard 430..40

400GB Index?

100GBIndex!

100GBIndex!

100GBIndex!

100GBIndex!

SUMMARY

Summary

1. Use documents to your advantage!2. Optimize your indexes 3. Understand your working set4. Use a sane disk configuratino5. Use replicas to scale reads 6. Use sharding to scale writes &

working RAM