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Wim Godden
Cu.be Solutions
Beyond PHP :
It's not (just) about the code
Who am I ?
Wim Godden (@wimgtr)
Founder of Cu.be Solutions (http://cu.be)
Open Source developer since 1997
Developer of OpenX
Zend Certified Engineer
Zend Framework Certified Engineer
MySQL Certified Developer
Cu.be Solutions ?
Open source consultancy
PHP-centered
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
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 ?
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
How-to & How-NOT-to
It starts with...
… code !
First up : database
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;
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) ?
→ No : range selection stops use of aggregate index
→ separate index on status and qty
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)
Databases – more queries, we want moooore !
Example : default Drupal install
→ 70-150 queries/page
→ Duplicates
Bigger picture : lots of tools and frameworks
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
Databases - pt-query-digest
# Profile
# Rank Query ID Response time Calls R/Call Apdx V/M Item
# ==== ================== ================ ===== ======= ==== ===== ==========
# 1 0x543FB322AE4330FF 16526.2542 62.0% 1208 13.6806 1.00 0.00 SELECT output_option
# 2 0xE78FEA32E3AA3221 0.8312 10.3% 6412 0.0001 1.00 0.00 SELECT poller_output poller_item
# 3 0x211901BF2E1C351E 0.6811 8.4% 6416 0.0001 1.00 0.00 SELECT poller_time
# 4 0xA766EE8F7AB39063 0.2805 3.5% 149 0.0019 1.00 0.00 SELECT wp_terms wp_term_taxonomy wp_term_relationships
# 5 0xA3EEB63EFBA42E9B 0.1999 2.5% 51 0.0039 1.00 0.00 SELECT UNION wp_pp_daily_summary wp_pp_hourly_summary
# 6 0x94350EA2AB8AAC34 0.1956 2.4% 89 0.0022 1.00 0.01 UPDATE wp_options
# MISC 0xMISC 0.8137 10.0% 3853 0.0002 NS 0.0 <147 ITEMS>
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
Databases – pt-query-digest – Digest UI
Databases – next step : explain
explain <query>
"How will MySQL execute the query"
Shows :
Indexes available
Indexes used (do you see one ?)
Number of rows scanned
Type of lookup
'system', 'const' and 'ref' = good
'ALL' = bad
Extra info
Using index = good
Using filesort = usually bad
Databases – when to use / not to use
Good at :
Fetching data
Storing data
Searching through data
Bad at :
select `someField` from `bigTable` where `hash` = crc32("something")
→ full table scan
→ select `someField` from `bigTable` where `hash` = "09da31fb"
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);
}
}
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
Better...
10001 → 1 query
Sadly : people still produce code with query loops
Usually :
Growth not anticipated
Internal app → Public app
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'
Client X
Jobs search site
Monitor job views :
Daily hits
Weekly hits
Monthly hits
Which user saw which job
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
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'] . ",
" . $user['id'] . ",
now()
)
");
}
Client X : the graph
Client X : the numbers
600-1000 updates/sec (peaks up to 1600)
400-1000 updates/sec (peaks up to 2600)
16 core machine
Client X : panic !
Mail : "MySQL slave is more than 5 minutes behind master"
We set it up → who did they blame ?
Wait a second !
Client X : what's causing those peaks ?
Client X : possible cause ?
Code changes ?
→ According to developers : none
Action : turn on general log, analyze with pt-query-digest
→ 50+-fold increase in queries
→ Developers : 'Oops we did make a change'
After 3 days : 2,5 days behind
Every hour : 50 min extra lag
Client X : But why is the slave lagging ?
Master Slave
File :
master-bin-xxxx.log
File :
master-bin-xxxx.logSlave I/O thread
Binlog dump
thread
Slave
SQL
thread
Client X : Master
Client X : Slave
Client X : fix ?
foreach ($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()
)
");
}
Client X : the code change
$todayQuery = "
insert into shown_today(
jobId,
number
) values ";
foreach ($jobs as $job) {
$todayQuery .= "(" . $job['id'] . ", 1),";
}
$todayQuery = substr($todayQuery, -1);
$todayQuery .= "
)
on duplicate key
update
number = number + 1
";
$db->query($todayQuery);
Careful : max_allowed_packet !
Client X : another option
$startQuery = "
insert into shown_today(
jobId,
number
) values ";
$endQuery .= "
)
on duplicate key
update
number = number + 1
";
$todayQuery = $startQuery;
for ($x = 0; $x < count($jobs); $x = $x + 1) {
$todayQuery .= "(" . $jobs[$x]['id'] . ", 1),";
if ($x % 10 == 0 && $x > 0) {
$todayQuery = substr($todayQuery, -1);
$db->query($todayQuery . $endQuery);
$todayQuery = $startQuery;
}
}
$db->query($todayQuery . $endQuery);
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();
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
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
Client Y : the network
Client Y : the network
60GB 700GB 700GB
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
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
Customer Z – fetching the feed
if (filectime(APP_DIR . '/tmp/ScrambledSiteName.xml') < time() - 900) {
unlink(APP_DIR . '/tmp/ScrambledSiteName.xml');
file_put_contents(
APP_DIR . '/tmp/ScrambledSiteName.xml',
file_get_contents('http://www.scrambledsitename.be/xml/feed.xml')
);
}
$xmlfeed = ParseXmlFeed(APP_DIR . '/tmp/ScrambledSiteName.xml');
What's wrong with this code ?
Customer Z – no feed without the source
Feed source
Customer Z – no feed without the source
Feed source
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
Customer Z : timeout fix
$context = stream_context_create(
array(
'http' => array(
'timeout' => 5
)
)
);
if (filectime(APP_DIR . '/tmp/ScrambledSiteName.xml') < time() - 900) {
unlink(APP_DIR . '/tmp/ScrambledSiteName.xml');
file_put_contents(
APP_DIR . '/tmp/ScrambledSiteName.xml',
file_get_contents('http://www.scrambledsitename.be/xml/feed.xml', false, $context)
);
}
$xmlfeed = ParseXmlFeed(APP_DIR . '/tmp/ScrambledSiteName.xml');
Customer Z : don't delete from cache
$context = stream_context_create(
array(
'http' => array(
'timeout' => 5
)
)
);
if (filectime(APP_DIR . '/tmp/ScrambledSiteName.xml') < time() - 900) {
unlink(APP_DIR . '/tmp/ScrambledSiteName.xml');
file_put_contents(
APP_DIR . '/tmp/ScrambledSiteName.xml',
file_get_contents('http://www.scrambledsitename.be/xml/feed.xml', false, $context)
);
}
$xmlfeed = ParseXmlFeed(APP_DIR . '/tmp/ScrambledSiteName.xml');
Network resources
Use timeouts for all :
fopen
curl
SOAP
…
Data source trusted ?
→ setup a webservice
→ let them push updates when their feed changes
→ less load on data source
→ no timeout issues
Add logging → early detection
Logging
Logging = good
Logging in PHP using fopen
→ bad idea : locking issues
→ Use file_put_contents($filename, $data, FILE_APPEND)
For Firefox : FirePHP (add-on for Firebug)
Debug logging = bad on production
Watch your logs !
Don't log on slow disks → I/O bottlenecks
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 !
File system
Worst of all : NFS
PHP files → lstat calls
Templates → same
Sessions
→ locking issues
→ corrupt data
→ store sessions in database, Memcached, Redis, ...
Much more than code
DB
server
Webserver
User
Network
XML feed
Questions ?
Questions ?
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/8204
Thanks !
Please...
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Beyond PHP - It's not (just) about the code

  • 1. Wim Godden Cu.be Solutions Beyond PHP : It's not (just) about the code
  • 2. Who am I ? Wim Godden (@wimgtr) Founder of Cu.be Solutions (http://cu.be) Open Source developer since 1997 Developer of OpenX Zend Certified Engineer Zend Framework Certified Engineer MySQL Certified Developer
  • 3. Cu.be Solutions ? Open source consultancy PHP-centered 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
  • 4. 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 ?
  • 5. 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 How-to & How-NOT-to
  • 6. It starts with... … code ! First up : database
  • 7. 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;
  • 8. 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) ? → No : range selection stops use of aggregate index → separate index on status and qty
  • 9. 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)
  • 10. Databases – more queries, we want moooore ! Example : default Drupal install → 70-150 queries/page → Duplicates Bigger picture : lots of tools and frameworks
  • 11. 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
  • 12. Databases - pt-query-digest # Profile # Rank Query ID Response time Calls R/Call Apdx V/M Item # ==== ================== ================ ===== ======= ==== ===== ========== # 1 0x543FB322AE4330FF 16526.2542 62.0% 1208 13.6806 1.00 0.00 SELECT output_option # 2 0xE78FEA32E3AA3221 0.8312 10.3% 6412 0.0001 1.00 0.00 SELECT poller_output poller_item # 3 0x211901BF2E1C351E 0.6811 8.4% 6416 0.0001 1.00 0.00 SELECT poller_time # 4 0xA766EE8F7AB39063 0.2805 3.5% 149 0.0019 1.00 0.00 SELECT wp_terms wp_term_taxonomy wp_term_relationships # 5 0xA3EEB63EFBA42E9B 0.1999 2.5% 51 0.0039 1.00 0.00 SELECT UNION wp_pp_daily_summary wp_pp_hourly_summary # 6 0x94350EA2AB8AAC34 0.1956 2.4% 89 0.0022 1.00 0.01 UPDATE wp_options # MISC 0xMISC 0.8137 10.0% 3853 0.0002 NS 0.0 <147 ITEMS>
  • 13. 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
  • 15. Databases – next step : explain explain <query> "How will MySQL execute the query" Shows : Indexes available Indexes used (do you see one ?) Number of rows scanned Type of lookup 'system', 'const' and 'ref' = good 'ALL' = bad Extra info Using index = good Using filesort = usually bad
  • 16. Databases – when to use / not to use Good at : Fetching data Storing data Searching through data Bad at : select `someField` from `bigTable` where `hash` = crc32("something") → full table scan → select `someField` from `bigTable` where `hash` = "09da31fb"
  • 17. 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); } }
  • 18. 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
  • 19. Better... 10001 → 1 query Sadly : people still produce code with query loops Usually : Growth not anticipated Internal app → Public app
  • 20. 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'
  • 21. Client X Jobs search site Monitor job views : Daily hits Weekly hits Monthly hits Which user saw which job
  • 22. 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
  • 23. 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'] . ", " . $user['id'] . ", now() ) "); }
  • 24. Client X : the graph
  • 25. Client X : the numbers 600-1000 updates/sec (peaks up to 1600) 400-1000 updates/sec (peaks up to 2600) 16 core machine
  • 26. Client X : panic ! Mail : "MySQL slave is more than 5 minutes behind master" We set it up → who did they blame ? Wait a second !
  • 27. Client X : what's causing those peaks ?
  • 28. Client X : possible cause ? Code changes ? → According to developers : none Action : turn on general log, analyze with pt-query-digest → 50+-fold increase in queries → Developers : 'Oops we did make a change' After 3 days : 2,5 days behind Every hour : 50 min extra lag
  • 29. Client X : But why is the slave lagging ? Master Slave File : master-bin-xxxx.log File : master-bin-xxxx.logSlave I/O thread Binlog dump thread Slave SQL thread
  • 30. Client X : Master
  • 31. Client X : Slave
  • 32. Client X : fix ? foreach ($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() ) "); }
  • 33. Client X : the code change $todayQuery = " insert into shown_today( jobId, number ) values "; foreach ($jobs as $job) { $todayQuery .= "(" . $job['id'] . ", 1),"; } $todayQuery = substr($todayQuery, -1); $todayQuery .= " ) on duplicate key update number = number + 1 "; $db->query($todayQuery); Careful : max_allowed_packet !
  • 34. Client X : another option $startQuery = " insert into shown_today( jobId, number ) values "; $endQuery .= " ) on duplicate key update number = number + 1 "; $todayQuery = $startQuery; for ($x = 0; $x < count($jobs); $x = $x + 1) { $todayQuery .= "(" . $jobs[$x]['id'] . ", 1),"; if ($x % 10 == 0 && $x > 0) { $todayQuery = substr($todayQuery, -1); $db->query($todayQuery . $endQuery); $todayQuery = $startQuery; } } $db->query($todayQuery . $endQuery);
  • 35. 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();
  • 36. 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
  • 37. 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
  • 38. Client Y : the network
  • 39. Client Y : the network 60GB 700GB 700GB
  • 40. 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
  • 41. 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
  • 42. Customer Z – fetching the feed if (filectime(APP_DIR . '/tmp/ScrambledSiteName.xml') < time() - 900) { unlink(APP_DIR . '/tmp/ScrambledSiteName.xml'); file_put_contents( APP_DIR . '/tmp/ScrambledSiteName.xml', file_get_contents('http://www.scrambledsitename.be/xml/feed.xml') ); } $xmlfeed = ParseXmlFeed(APP_DIR . '/tmp/ScrambledSiteName.xml'); What's wrong with this code ?
  • 43. Customer Z – no feed without the source Feed source
  • 44. Customer Z – no feed without the source Feed source
  • 45. 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
  • 46. Customer Z : timeout fix $context = stream_context_create( array( 'http' => array( 'timeout' => 5 ) ) ); if (filectime(APP_DIR . '/tmp/ScrambledSiteName.xml') < time() - 900) { unlink(APP_DIR . '/tmp/ScrambledSiteName.xml'); file_put_contents( APP_DIR . '/tmp/ScrambledSiteName.xml', file_get_contents('http://www.scrambledsitename.be/xml/feed.xml', false, $context) ); } $xmlfeed = ParseXmlFeed(APP_DIR . '/tmp/ScrambledSiteName.xml');
  • 47. Customer Z : don't delete from cache $context = stream_context_create( array( 'http' => array( 'timeout' => 5 ) ) ); if (filectime(APP_DIR . '/tmp/ScrambledSiteName.xml') < time() - 900) { unlink(APP_DIR . '/tmp/ScrambledSiteName.xml'); file_put_contents( APP_DIR . '/tmp/ScrambledSiteName.xml', file_get_contents('http://www.scrambledsitename.be/xml/feed.xml', false, $context) ); } $xmlfeed = ParseXmlFeed(APP_DIR . '/tmp/ScrambledSiteName.xml');
  • 48. Network resources Use timeouts for all : fopen curl SOAP … Data source trusted ? → setup a webservice → let them push updates when their feed changes → less load on data source → no timeout issues Add logging → early detection
  • 49. Logging Logging = good Logging in PHP using fopen → bad idea : locking issues → Use file_put_contents($filename, $data, FILE_APPEND) For Firefox : FirePHP (add-on for Firebug) Debug logging = bad on production Watch your logs ! Don't log on slow disks → I/O bottlenecks
  • 50. 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 !
  • 51. File system Worst of all : NFS PHP files → lstat calls Templates → same Sessions → locking issues → corrupt data → store sessions in database, Memcached, Redis, ...
  • 52. Much more than code DB server Webserver User Network XML feed
  • 55. 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/8204
  • 56. Thanks ! Please... Rate my talk : http://joind.in/8204

Hinweis der Redaktion

  1. 5kbit/sec or 100Mbit/sec ?
  2. Let&apos;s talk about code Without : we don&apos;t exist What are most common mistakes in ecosystem Let&apos;s start with the database
  3. time spent per query pattern how many queries of that query pattern
  4. Get back to what I said Lots of people use ORM - easier - don&apos;t need to write queries - object-oriented but people start doing this Imagine 10000 customers → 10001 queries
  5. Not best code Uses deprecated mysql extension no error handling
  6. Master : 16 CPU cores 12 cores for SQL 1 core for binlog dump rest for system Slave : 16 CPU cores 1 core for slave I/O 1 core for slave SQL
  7. Grouping Works fine, but : maximum size of string ? PHP = no limit MySQL = max_allowed_packet
  8. Will work Messy Processing data in PHP → DB should do this Also : still 1 commit per query
  9. All in a single commit Note : transaction has max. size Possible : combination with previous solution
  10. took few moments to figure out No network monitoring → iptraf → 100Mbit/sec limit → packets dropped → connections dropped Customer : upgrade switch Us : why 100Mbit/sec ?
  11. Databases → network What other network related issues ?
  12. Server on which feed located : crashed Fine for few minutes (cache) 15 minutes : file_get_contents uses default_socket_timeout
  13. Better, not perfect. What else is wrong ? Multiple visitors hit expiring cache → file delete → xml feed hit a lot
  14. Better, not perfect. What else is wrong ? Multiple visitors hit expiring cache → file delete → xml feed hit a lot
  15. How do you treat your data : - where do you get it - how long did you have to wait to get it - how is it transported - how is it processed minimize the amount of data : retrieved transported processed, sent to db and users