F4 - Photo Storage at Facebook

https://www.youtube.com/watch?v=34e_g-Ji_30

F4 - Photo Storage at Facebook



F4 - photo storage at Facebook

world's largest photo storage


BLOB "hotness" 

Haystack: 2008

Hot storage design goals

HIgh throughput
- in memory index
- single I/o per request!
- Multiple copies


Failure tolerant

RAIDS
Multiple copies

RAID 6
2 Redudant drivers
2 of 12 = 1.2x replication
Over 3 arrays = 3.6x


RAID 2, RAID 3, RAID 4, RAID 6 explained with diagram

https://www.thegeekstuff.com/2011/11/raid2-raid3-raid4-raid6/

Haystack   warm storage

- Redundancy = replcation 
Read throughput = replication

Total replication = 3.6x

Warm storage

Redundancy still required
Read throughput the ...


RS Encoding:

Reduundancy 


upload request -> web server -> Storage router -> haystack

                                                   F4

haystack -> Migration -> F4



Read request -> CDN -> Storage router -> F4 


f4: What are we solving

Warm storage problem:
- Need to store (warm) data efficiently
- Storage must be highly fault tolerant
- Read latency should be comparable to haystack
- Load is NOT primary concern

Solution: f4
- 2.x replication factor compared to haystack's 3.6x
- yet more fault tolerant than haystack(!!)

f4: Data splitting RS(5,2)

10G Haystack volume

1G Data blocks

Data blocks
Parity blocks

f4: RS Rebuild

RS decoding 

Data blocks   parity blocks

f4: Block placement policy

Blocks of each stripe is placed in different racks(=> hosts)
RS(10,4) is used in practice (1.4x)
Tolerant 4 racks(-> 4 disks/hosts) failures

f4 Cell anatomy

f4 storage consists of a set of cells.
One cell resides completely in one data center
Cell consists of 3 kind of nodes: storage, compute, coordinator
The index is distributed across storage needs

f4 Reads

user request -> router -> index read (1), storage nodes, compute, cell

  Data read (2)

REads with datacenter failures (2.1X)

Router1, router2, router3

Datacenter1
Datacenter2
Datacenter3

Volume1
volume2
xorVolume