Online classified web site Leboncoin.fr is one of the success stories of the French Web. 1/3 of the total internet population in France uses the site each month. The growth has been spectacular and swift, and was made possible by a robust and performant software platform. At the heart of the platform is a large PostgreSQL infrastructure, part of it running on some of the largest PC-class hardware available. In this presentation, we will show how we have grown our infrastructure. In particular, the amazing vertical scalability of PG will be showcased with hard numbers (IOPS, transactions/seconds, etc). We will also cover some of the hard lessons we have learned along the way, including near-disasters. Finally, we will look into how innovative features from the PostgreSQL ecosystem enable new approaches to our scalability challenge.

1. 2TB of RAM ought to be enough for
anybody
PG Nordic Day 2014

2. The Presenter
1
Renaud Bruyeron - @brew_your_own
Paris, France

3. The Presenter – short bio
2
• 1998-1999: W3C @ MIT
• 1999-2013: FullSIX
• Top 3 Web agency in FR
• Strong focus on PHP, Java, and Oracle…
• 2013-present: CTO of

4. Schibsted Classified Media
From 1 to 30+ Countries in 7 years
3

5. 4

6. Templated deployment in 30 countries w/ shared
technology
5
• Technology originally
inherited from
Blocket.se
• Has since evolved to
power all 30 sites
• Focus on performance
and ease of local
modificationsPostgreSQL
Middleware
(data access, business
rules)
Index
Presentation layer
APIs Web
Search C
C
C
PHP
C/PHP
C
PL/SQL

7. PostgreSQL in the SCM Platform
6
100+ servers running PostgreSQL
8TB of data
50+ million classified ads

8. Schibsted Classified Media & PostgreSQL
married…and in love 
7

9. #1 Classified Web site in France
8

10. History
9
Project initiated in 2006
Site launch: early 2007
Based on technology
from 1 to 230 people, challenger to #1 in 7 years

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14. Explosive growth…with a few bumps along the way!
13

15. Big Audience
14
250M page views / day
5M unique visitors / day
18M UV / month
That’s 1/3 of French internet population…
600000+ new ads / day
25M live ads
#7 most visited Website in France

16. Big Ops
15
300+ servers in 2 DCs
20 servers hosting PG databases
(in production)

17. Built on SCM Technology
16
PostgreSQL
Middleware
(data access, business
rules)
Index
Presentation layer
APIs Web
Search

18. Built on SCM Technology
17
Website Data
Master
Slave
(hot
standby)
Slave
(short
queries)
Slave
(Long
queries)
Middleware
(data access, business
rules)
Index
Presentation layer
APIs Web
Search

19. Built on SCM Technology
18
Website Data
Master
Slave
(hot
standby)
Slave
(short
queries)
Slave
(Long
queries)
Middleware
(data access, business
rules)
Index
Presentation layer
APIs Web
Search
+15 support DBs

20. Website Data
+15 support DBs
We use PostgreSQL everywhere!
19
Backoffice & Analytics
Master
Slave
(hot
standby)
Slave
(short
queries)
Slave
(Long
queries)
ODS
OLAP
BI & CRM Middleware
(data access, business
rules)
Index
Presentation layer
APIs Web
Search

21. We try to limit writes!
20
• Index/Search acting as a structured cache
• Master DB workload = 70% writes
• Slaves used to offload read queries
• Main database = 6TB on disk…
• +4TB archived away…
• 20K LOCs of PL/SQL
Website Data
+15 support DBs
Master
Slave
(hot
standby)
Slave
(short
queries)
Slave
(Long
queries)
Index
Search

22. PostgreSQL works beautifully as a DW!
21
Website DataBackoffice & Analytics
Master
Slave
(hot
standby)
Slave
(short
queries)
Slave
(Long
queries)
ODS
OLAP
ETL moving
500GB / day into
the DW
2.2TB
Adding
6GB/day

23. Big Iron: HP DL980, 2TB of RAM, 64-80 cores
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24. HTOP on the Master 
23

25. Physical storage for the main PostgreSQL instances
24
DL980 DL980
3Par
V800
(SAN)
Fusion-IO
DL980DL980
3Par
V800
(SAN)
Fusion-IO
Fiber
Channel
Fiber
Channel
Master Slave SlaveSlave
DC 1 DC 2

26. Big Iron: 3Par V800 SAN
25

27. Big Iron: thin provisioning with mix of SSD and FC disks
26

28. Big Iron: high performance…
27

29. Bragging about it ;)
28

30. Despite the caches and the search engine, we get
impressive workloads on the master DB
29
600 tx/sec

31. How did we get there?
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2x DL980 w/
Fusion-IO
2x 3Par V800
2x DL980 w/
FC to the
V800s

32. We did go through growing pains and near disasters
31
The « Big
One »

33. Our own « worst day of our lives »: March 1st 2013 (1/2)
32
Master DB is slowing down dramatically
We find that Slony replication is the culprit
We don’t know what to do…
Until we find a solution on the net that involves cleaning up slony metadata…
…(you know where this is going)…
We fumble. We notice. The slave is borked.
Rebuilding the Slave with slony brings the Master down. Oh. God…
We take the Master off the stack, and start rebuilding the slave w/ Slony
…5 days later, we are done (!)…

34. Our own « worst day of our lives »: March 1st 2013 (2/2)
33
…but we are not out of the woods yet!...
Pent up demand is bringing the site down!
We decide to switch to native replication!
…but the network cards are maxed out by the replication data…
…triggering a kernel bug…
…(Murphy, could you please step out of the room?)…
We implement network card bonding, and start moving support tables off the main
instance
…and we are done!

35. What’s Next?
34

36. Vertical Scalability has limits!
35
We are already running on the biggest HW money can buy
Past certain volume levels, execution plans can change radically
Huge instances are difficult to maintain & backup safely
Rebuilding the slave in March 2013 took a full 5 days…
Although we are maxing out the HW available to us, especially
on the writes/s,
We are committed to PostgreSQL at the heart of our platform

37. Key ideas to take our platform to the next level
36
Sharding
Unbundling of
the schema
PGQ
Spread the reads & writes horizontally
Move parts of the schema (that can be
decoupled) to other instances. Spread the
workload
Reduce application-level transaction
interleaving by moving parts of the
transactions to asynchronous workers

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