Most PHP developers focus on writing code. But creating Web applications is about much more than just wrting PHP. Take a step outside the PHP cocoon and into the big PHP ecosphere to find out how small code changes can make a world of difference on servers and network. This talk is an eye-opener for developers who spend over 80% of their time coding, debugging and testing.

1. Wim Godden
Cu.be Solutions
@wimgtr
Beyond PHP :
It's not (just) about the code

2. Who am I ?
Wim Godden (@wimgtr)

3. Where I'm from

4. Where I'm from

5. Where I'm from

6. Where I'm from

7. Where I'm from

8. Where I'm from

9. My town

10. My town

11. Belgium – the traffic

12. Who am I ?
Wim Godden (@wimgtr)
Founder of Cu.be Solutions (http://cu.be)
Open Source developer since 1997
Developer of OpenX, PHPCompatibility, Nginx SLIC, ...
Speaker at PHP and Open Source conferences

13. Cu.be Solutions ?
Open source consultancy
PHP-centered
Training courses
High-speed redundant network (BGP, OSPF, VRRP)
High scalability development
Nginx + extensions
MySQL Cluster
Projects :
mostly IT & Telecom companies
lots of public-facing apps/sites

14. Who are you ?
Developers ?
Anyone setup a MySQL master-slave ?
Anyone setup a site/app on separate web and database server ?
→ How much traffic between them ?

15. The topic
Things we take for granted
Famous last words : "It should work just fine"
Works fine today
→ might fail tomorrow
Most common mistakes
PHP code ↔ PHP ecosystem

16. It starts with...
… code !
First up : database

17. Database queries – complexity
SELECT DISTINCT n.nid, n.uid, n.title, n.type, e.event_start, e.event_start AS
event_start_orig, e.event_end, e.event_end AS event_end_orig, e.timezone,
e.has_time, e.has_end_date, tz.offset AS offset, tz.offset_dst AS offset_dst,
tz.dst_region, tz.is_dst, e.event_start - INTERVAL IF(tz.is_dst, tz.offset_dst,
tz.offset) HOUR_SECOND AS event_start_utc, e.event_end - INTERVAL
IF(tz.is_dst, tz.offset_dst, tz.offset) HOUR_SECOND AS event_end_utc,
e.event_start - INTERVAL IF(tz.is_dst, tz.offset_dst, tz.offset) HOUR_SECOND +
INTERVAL 0 SECOND AS event_start_user, e.event_end - INTERVAL IF(tz.is_dst,
tz.offset_dst, tz.offset) HOUR_SECOND + INTERVAL 0 SECOND AS
event_end_user, e.event_start - INTERVAL IF(tz.is_dst, tz.offset_dst, tz.offset)
HOUR_SECOND + INTERVAL 0 SECOND AS event_start_site, e.event_end -
INTERVAL IF(tz.is_dst, tz.offset_dst, tz.offset) HOUR_SECOND + INTERVAL 0
SECOND AS event_end_site, tz.name as timezone_name FROM node n INNER
JOIN event e ON n.nid = e.nid INNER JOIN event_timezones tz ON tz.timezone =
e.timezone INNER JOIN node_access na ON na.nid = n.nid LEFT JOIN
domain_access da ON n.nid = da.nid LEFT JOIN node i18n ON n.tnid > 0 AND
n.tnid = i18n.tnid AND i18n.language = 'en' WHERE (na.grant_view >= 1 AND
((na.gid = 0 AND na.realm = 'all'))) AND ((da.realm = "domain_id" AND da.gid = 4)
OR (da.realm = "domain_site" AND da.gid = 0)) AND (n.language ='en' OR
n.language ='' OR n.language IS NULL OR n.language = 'is' AND i18n.nid IS NULL)
AND ( n.status = 1 AND ((e.event_start >= '2010-01-31 00:00:00' AND
e.event_start <= '2010-03-01 23:59:59') OR (e.event_end >= '2010-01-31 00:00:00'
AND e.event_end <= '2010-03-01 23:59:59') OR (e.event_start <= '2010-01-31
00:00:00' AND e.event_end >= '2010-03-01 23:59:59')) ) GROUP BY n.nid HAVING
(event_start >= '2010-02-01 00:00:00' AND event_start <= '2010-02-28 23:59:59')
OR (event_end >= '2010-02-01 00:00:00' AND event_end <= '2010-02-28 23:59:59')
OR (event_start <= '2010-02-01 00:00:00' AND event_end >= '2010-02-28
23:59:59') ORDER BY event_start ASC;

18. Database - indexing
'select id from stock where status = 2 order by qty'
→ aggregate index on (status, qty)
'select id from stock where status > 2 order by qty'
→ aggregate index on (status, qty) ?
→ Depends :
- Btree : yes
- Hash : range selection stops use of aggregate index
→ separate index on status and qty (since recent versions)

19. Database - indexing
Indexes make database faster
→ Let's index everything !
→ DON'T :
Insert/update/delete → Index modification
Each query → evaluation of all indexes
"Relational schema design is based on data
but index design is based on queries"
(Bill Karwin, Percona)

20. Databases – detecting problematic queries
Slow query log
→ SET GLOBAL slow_query_log = ON;
Queries not using indexes
→ In my.cnf/my.ini : 'log_queries_not_using_indexes'
General query log
→ SET GLOBAL general_log = ON;
→ Turn it off quickly !
Percona Toolkit (Maatkit)
pt-query-digest

21. Databases - pt-query-digest
# Profile
# Rank Query ID Response time Calls R/Call Apdx V/M Item
# ==== ================== ================ ===== ======= ==== ===== ==========
# 1 0x543FB322AE4330FF 16526.2542 98.2% 1208 13.6806 1.00 0.00 SELECT output_option
# 2 0xE78FEA32E3AA3221 0.8312 0.0% 6412 0.0001 1.00 0.00 SELECT poller_output poller_item
# 3 0x211901BF2E1C351E 0.6811 0.0% 6416 0.0001 1.00 0.00 SELECT poller_time
# 4 0xA766EE8F7AB39063 0.2805 0.0% 149 0.0019 1.00 0.00 SELECT wp_terms wp_term_taxonomy wp_term_relationships
# 5 0xA3EEB63EFBA42E9B 0.1999 0.0% 51 0.0039 1.00 0.00 SELECT UNION wp_pp_daily_summary wp_pp_hourly_summary
# 6 0x94350EA2AB8AAC34 0.1956 0.0% 89 0.0022 1.00 0.01 UPDATE wp_options
# MISC 0xMISC 302.8137 1.8% 3853 0.0002 NS 0.0 <147 ITEMS>

22. Databases - pt-query-digest
# Query 2: 0.26 QPS, 0.00x concurrency, ID 0x92F3B1B361FB0E5B at byte 14081299
# This item is included in the report because it matches --limit.
# Scores: Apdex = 1.00 [1.0], V/M = 0.00
# Query_time sparkline: | _^ |
# Time range: 2011-12-28 18:42:47 to 19:03:10
# Attribute pct total min max avg 95% stddev median
# ============ === ======= ======= ======= ======= ======= ======= =======
# Count 1 312
# Exec time 50 4s 5ms 25ms 13ms 20ms 4ms 12ms
# Lock time 3 32ms 43us 163us 103us 131us 19us 98us
# Rows sent 59 62.41k 203 231 204.82 202.40 3.99 202.40
# Rows examine 13 73.63k 238 296 241.67 246.02 10.15 234.30
# Rows affecte 0 0 0 0 0 0 0 0
# Rows read 59 62.41k 203 231 204.82 202.40 3.99 202.40
# Bytes sent 53 24.85M 46.52k 84.36k 81.56k 83.83k 7.31k 79.83k
# Merge passes 0 0 0 0 0 0 0 0
# Tmp tables 0 0 0 0 0 0 0 0
# Tmp disk tbl 0 0 0 0 0 0 0 0
# Tmp tbl size 0 0 0 0 0 0 0 0
# Query size 0 21.63k 71 71 71 71 0 71
# InnoDB:
# IO r bytes 0 0 0 0 0 0 0 0
# IO r ops 0 0 0 0 0 0 0 0
# IO r wait 0 0 0 0 0 0 0 0
# pages distin 40 11.77k 34 44 38.62 38.53 1.87 38.53
# queue wait 0 0 0 0 0 0 0 0
# rec lock wai 0 0 0 0 0 0 0 0
# Boolean:
# Full scan 100% yes, 0% no
# String:
# Databases wp_blog_one (264/84%), wp_blog_tw… (36/11%)... 1 more
# Hosts
# InnoDB trxID 86B40B (1/0%), 86B430 (1/0%), 86B44A (1/0%)... 309 more
# Last errno 0
# Users wp_blog_one (264/84%), wp_blog_two (36/11%)... 1 more
# Query_time distribution
# 1us
# 10us
# 100us
# 1ms
# 10ms ################################################################
# 100ms
# 1s
# 10s+
# Tables
# SHOW TABLE STATUS FROM `wp_blog_one ` LIKE 'wp_options'G
# SHOW CREATE TABLE `wp_blog_one `.`wp_options`G
# EXPLAIN /*!50100 PARTITIONS*/
SELECT option_name, option_value FROM wp_options WHERE autoload = 'yes'G

23. Databases – next step : explain
explain <query>
"How will MySQL execute the query"

24. Databases – next step : explain
+----+-------------+-----------+------+---------------+------+---------+------+--------+-------------+
| id | select_type | TABLE | TYPE | possible_keys | KEY | key_len | REF | ROWS | Extra |
+----+-------------+-----------+------+---------------+------+---------+------+--------+-------------+
| 1 | SIMPLE | employees | ALL | NULL | NULL | NULL | NULL | 299809 | USING WHERE |
+----+-------------+-----------+------+---------------+------+---------+------+--------+-------------+
+----+-------------+------------+-------+-------------------------------+---------+---------+-------+------+-------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+------------+-------+-------------------------------+---------+---------+-------+------+-------+
| 1 | SIMPLE | itdevice | const | PRIMARY,fk_device_devicetype1 | PRIMARY | 4 | const | 1 | |
| 1 | SIMPLE | devicetype | const | PRIMARY | PRIMARY | 4 | const | 1 | |
+----+-------------+------------+-------+-------------------------------+---------+---------+-------+------+-------+

25. Databases – next step : explain
Type of lookup
'system', 'const' and 'ref' = good
'ALL' = bad
Extra info
Using index = good
Using filesort = usually bad

26. For / foreach
$customers = CustomerQuery::create()
->filterByState('MN')
->find();
foreach ($customers as $customer) {
$contacts = ContactsQuery::create()
->filterByCustomerid($customer->getId())
->find();
foreach ($contacts as $contact) {
doSomestuffWith($contact);
}
}

27. Joins
$contacts = mysql_query("
select
contacts.*
from
customer
join contact
on contact.customerid = customer.id
where
state = 'MN'
");
while ($contact = mysql_fetch_array($contacts)) {
doSomeStuffWith($contact);
}
or the ORM equivalent

28. Better...
10001 → 1 query
Sadly : people still produce code with query loops
Usually :
Growth not anticipated
Internal app → Public app

29. The origins of this talk
Customers :
Projects we built
Projects we didn't build, but got pulled into
Fixes
Changes
Infrastructure migration
15 years of 'how to cause mayhem with a few lines of code'

30. Client X
Jobs search site
Monitor job views :
Daily hits
Weekly hits
Monthly hits
Which user saw which job

31. Client X
Originally : when user viewed job details
Now : when job is in search result
Search for 'php' → 50 jobs = 50 jobs to be updated
→ 50 updates for shown_today
→ 50 updates for shown_week
→ 50 updates for shown_month
→ 50 inserts for shown_user
= 200 queries for 1 search !

32. Client X : the code
foreach ($jobs as $job) {
$db->query("
insert into shown_today(
jobId,
number
) values(
" . $job['id'] . ",
1
)
on duplicate key
update
number = number + 1
");
$db->query("
insert into shown_week(
jobId,
number
) values(
" . $job['id'] . ",
1
)
on duplicate key
update
number = number + 1
");
$db->query("
insert into shown_month(
jobId,
number
) values(
" . $job['id'] . ",
1
)
on duplicate key
update
number = number + 1
");
$db->query("
insert into shown_user(
jobId,
userId,
when
) values (
" . $job['id'] . ",
" . $user['id'] . ",
now()
)
");
}

33. Client X : the graph

34. Client X : the numbers
600-1000 inserts/sec (peaks up to 1600)
400-1000 updates/sec (peaks up to 2600)
16 core machine

35. Client X : panic !
Mail : "MySQL slave is more than 5 minutes behind master"
We set it up → who did they blame ?
Wait a second !

36. Client X : what's causing those peaks ?

37. Client X : possible cause ?
Code changes ?
→ According to developers : none
Action : turn on general log, analyze with pt-query-digest
→ 50+-fold increase in 4 queries
→ Developers : 'Oops we did make a change'
After 3 days : 2,5 days behind
Every hour : 50 min extra lag

38. Client X : But why is the slave lagging ?
Master Slave
File :
master-bin-xxxx.log
File :
master-bin-xxxx.logSlave I/O thread
Binlog dump
thread
Slave
SQL
thread

39. Client X : Master

40. Client X : Slave

41. Client X : fix ?
foreach ($jobs as $job) {
$db->query("
insert into shown_today(
jobId,
number
) values(
" . $job['id'] . ",
1
)
on duplicate key
update
number = number + 1
");
$db->query("
insert into shown_week(
jobId,
number
) values(
" . $job['id'] . ",
1
)
on duplicate key
update
number = number + 1
");
$db->query("
insert into shown_month(
jobId,
number
) values(
" . $job['id'] . ",
1
)
on duplicate key
update
number = number + 1
");
$db->query("
insert into shown_user(
jobId,
userId,
when
) values (
" . $job['id'] . ",
" . $user['id'] . ",
now()
)
");
}

42. Client X : the code change
insert into shown_today values (5, 1), (8, 1), (12, 1), (18, 1), … on duplicate key … ;
insert into shown_week values (5, 1), (8, 1), (12, 1), (18, 1), … on duplicate key … ;
insert into shown_month values (5, 1), (8, 1), (12, 1), (18, 1), … on duplicate key … ;
insert into shown_user values (5, 23, "2013-11-12 12:01:00"), (8, 23, "2013-11-12
12:01:00"), … ;

43. Client X : the code change
$todayQuery = "
insert into shown_today(
jobId,
number
) values ";
foreach ($jobs as $job) {
$todayQuery .= "(" . $job['id'] . ", 1),";
}
$todayQuery = substr($todayQuery, 0, strlen($todayQuery) - 1);
$todayQuery .= "
)
on duplicate key
update
number = number + 1
";
$db->query($todayQuery);

44. Client X : the chosen solution
$db->autocommit(false);
foreach ($jobs as $job) {
$db->query("
insert into shown_today(
jobId,
number
) values(
" . $job['id'] . ",
1
)
on duplicate key
update
number = number + 1
");
$db->query("
insert into shown_week(
jobId,
number
) values(
" . $job['id'] . ",
1
)
on duplicate key
update
number = number + 1
");
$db->query("
insert into shown_month(
jobId,
number
) values(
" . $job['id'] . ",
1
)
on duplicate key
update
number = number + 1
");
$db->query("
insert into shown_user(
jobId,
userId,
when
) values (
" . $job['id'] . ",
" . $user['id'] . ",
now()
)
");
}
$db->commit();

45. Client X : conclusion
For loops are bad (we already knew that)
Add master/slave and it gets much worse
Use transactions : it will provide huge performance increase
Result : slave caught up 5 days later

46. Database → Network
Customer Y
Top 10 site in Belgium
Growing rapidly
At peak traffic :
Unexplicable latency on database
Load on webservers : minimal
Load on database servers : acceptable

47. Client Y : the network

48. Client Y : the network
60GB 700GB 700GB

49. Client Y : network overload
Cause : Drupal hooks → retrieving data that was not needed
Only load data you actually need
Don't know at the start ? → Use lazy loading
Caching :
Same story
Memcached/Redis are fast
But : data still needs to cross the network

50. Network trouble : more than just traffic
Customer Z
150.000 visits/day
News ticker :
XML feed from other site (owned by same customer)
Cached for 15 min

51. Customer Z – fetching the feed
if (filectime(APP_DIR . '/tmp/cacheFile.xml') < time() - 900) {
unlink(APP_DIR . '/tmp/cacheFile.xml');
file_put_contents(
APP_DIR . '/tmp/cacheFile.xml',
file_get_contents('http://www.scrambledsitename.be/xml/feed.xml')
);
}
$xmlfeed = ParseXmlFeed(APP_DIR . '/tmp/cacheFile.xml');
What's wrong with this code ?

52. Customer Z – no feed without the source
Feed source

53. Customer Z – no feed without the source
Feed source

54. Customer Z : timeout
default_socket_timeout : 60 sec by default
Each visitor : 60 sec wait time
People keep hitting refresh → more load
More active connections → more load
Apache hits maximum connections → entire site down

55. Customer Z : timeout fix
$context = stream_context_create(
array(
'http' => array(
'timeout' => 5
)
)
);
if (filectime(APP_DIR . '/tmp/cacheFile.xml') < time() - 900) {
unlink(APP_DIR . '/tmp/cacheFile.xml');
file_put_contents(
APP_DIR . '/tmp/cacheFile.xml',
file_get_contents('http://www.scrambledsitename.be/xml/feed.xml', false, $context)
);
}
$xmlfeed = ParseXmlFeed(APP_DIR . '/tmp/cacheFile.xml');

56. Customer Z : don't delete from cache
$context = stream_context_create(
array(
'http' => array(
'timeout' => 5
)
)
);
if (filectime(APP_DIR . '/tmp/cacheFile.xml') < time() - 900) {
unlink(APP_DIR . '/tmp/cacheFile.xml');
file_put_contents(
APP_DIR . '/tmp/cacheFile.xml',
file_get_contents('http://www.scrambledsitename.be/xml/feed.xml', false, $context)
);
}
$xmlfeed = ParseXmlFeed(APP_DIR . '/tmp/cacheFile.xml');

57. Customer Z : don't delete from cache
$context = stream_context_create(
array(
'http' => array(
'timeout' => 5
)
)
);
if (filectime(APP_DIR . '/tmp/cacheFile.xml') < time() - 900) {
file_put_contents(
APP_DIR . '/tmp/cacheFile.xml',
file_get_contents('http://www.scrambledsitename.be/xml/feed.xml', false, $context)
);
}
$xmlfeed = ParseXmlFeed(APP_DIR . '/tmp/cacheFile.xml');

58. Customer Z : don't delete from cache
$context = stream_context_create(
array(
'http' => array(
'timeout' => 5
)
)
);
if (filectime(APP_DIR . '/tmp/cacheFile.xml') < time() - 900) {
$feed = file_get_contents('http://www.scrambledsitename.be/xml/feed.xml', false, $context);
if ($feed !== false) {
file_put_contents(
APP_DIR . '/tmp/cacheFile.xml',
$feed
);
}
}
$xmlfeed = ParseXmlFeed(APP_DIR . '/tmp/cacheFile.xml');

59. Customer Z : process early
$context = stream_context_create(
array(
'http' => array(
'timeout' => 5
)
)
);
if (filectime(APP_DIR . '/tmp/cacheFile.xml') < time() - 900) {
$feed = file_get_contents('http://www.scrambledsitename.be/xml/feed.xml', false, $context);
if ($feed !== false) {
file_put_contents(
APP_DIR . '/tmp/cacheFile.xml',
ParseXmlFeed($feed)
);
}
}

60. Customer Z : file_[get|put]_contents atomicity
$context = stream_context_create(
array(
'http' => array(
'timeout' => 5
)
)
);
if (filectime(APP_DIR . '/tmp/cacheFile.xml') < time() - 900) {
$feed = file_get_contents('http://www.scrambledsitename.be/xml/feed.xml', false, $context);
if ($feed !== false) {
file_put_contents(
APP_DIR . '/tmp/cacheFile.xml',
ParseXmlFeed($feed)
);
}
}
Relying on user → concurrent request → possible corrupt data
Better : run every 15min through cronjob

61. Network resources
Use timeouts for all :
fopen
curl
SOAP
…
Data source trusted ?
→ setup a webservice
→ let them push updates when their feed changes
→ less load on data source
→ no timeout issues
Add logging → early detection

62. Logging
Logging = good
Logging in PHP using fopen
→ bad idea : locking issues
→ Use monolog : file, syslog, mail, Pushover, HipChat, Graylog,
Rollbar, ElasticSearch (and 50 more)
For Firefox : FirePHP (add-on for Firebug)
Debug logging = bad on production
Watch your logs !
Don't log on slow disks → I/O bottlenecks

63. File system : I/O bottlenecks
Causes :
Excessive writes (database updates, logfiles, swapping, …)
Excessive reads (non-indexed database queries, swapping, small file
system cache, …)
How to detect ?
top
iostat
See iowait ? Stop worrying about php, fix the I/O problem !
Cpu(s): 0.2%us, 3.0%sy, 0.0%ni, 61.4%id, 35.5%wa, 0.0%hi, 0.0%si, 0.0%st
avg-cpu: %user %nice %system %iowait %steal %idle
0.10 0.00 0.96 53.70 0.00 45.24
Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn
sda 120.40 0.00 123289.60 0 616448
sdb 2.10 0.00 4378.10 0 18215
dm-0 4.20 0.00 36.80 0 184
dm-1 0.00 0.00 0.00 0 0

64. Much more than code
DB
server
Webserver
User
Network
XML feed

65. Look beyond PHP (or Perl, Ruby, Python, ...) !

66. Questions ?

67. Questions ?

68. Contact
Twitter @wimgtr
Web http://techblog.wimgodden.be
Slides http://www.slideshare.net/wimg
E-mail wim.godden@cu.be
Please...
Rate my talk : http://joind.in/10408

69. Step-by-step : most common issues
iowait on database server
I/O reads (use iostat) ? → missing/wrong indexes
I/O writes ?
→ no transactions ?
→ too many queries ?
→ bad DB engine settings
iowait on webserver (logs ? static files ?)
CPU on database server (missing/wrong/too many indexes)
CPU on webserver (PHP)