The document discusses common causes of slow database performance in PHP applications and strategies for improving performance. It outlines issues like making too many database queries, missing caching opportunities, and inefficient query design. It emphasizes that slow performance does not necessarily mean the database itself is slow, and encourages developers to understand how databases work and profile queries to identify hotspots. The document also covers topics like indexing, separating databases for read/write, and the importance of collaboration between developers and database administrators.

1. Slow database in your PHP stack?
Don’t blame the DBA!
harald.zeitlhofer@dynatrace.com
@HZeitlhofer

2. Harald Zeitlhofer – who's that?
• Technology Strategist at Dynatrace
• Database and Web Development
• Father of 2
• Love climbing, music, cooking, photography
• Love to discover new things

3. PHP and databases
• Connectivity
• Abstraction Layers
• Caching
• Access Patterns
• Performance
-> Relational SQL databases

4. Connectivity via DB extensions
• mysql (deprecated in 5.5, removed in 7.0)
• mysqli
• oracle
• PDO
• …

5. Connectivity via ORM layer
• Object Relational Mapper
• Doctrine
• Propel, RedBeanPHP, Spot
• Complete abstraction of persistence layer
• Caching
• Limited flexibility

8. Let the blame game start!
Web Server Application Server Database
DEV Team DBA Team
Blame the database for
all performance issues
Blame the SW/HW or
system administrators
Network?

9. function roomReservationReport($room) {
$reservations = loadDataForRoom($room->id);
generateReport($room, $reservations);
}
Slow Report

10. function roomReservationReport($room) {
$tstart = microtime(true);
$reservations = loadDataForRoom($room->id);
$dataLoadTime = microtime(true) - $tstart;
generateReport($room, $reservations);
}
DEV team add log output

11. 45s
DEV team result

13. < 1ms
DBA team looks at DB stats per query

16. Excessive SQL: 24889!
Calls to Database
Database Heavy:
66.51% (40.27s)
Time Spent in SQL Execs

17. Database Performance Hotspots
Application Design Database Infrastructure

19. http://apmblog.dynatrace.com/2015/06/25/when-old-jira-tickets-killed-our-productivityuser-experience/
Too many database queries

20. Entity Framework lazy loading
$schools = new SchoolEntities();
foreach ($schools as $school) {
foreach ($school->departments as $department) {
foreach ($department->courses as $course) {
echo $department->name . ": " . $course->title);
}
}
}

21. N+1 problem
• 10 schools
• 20 departments per school
• 50 curses per department
=> 10 x 20 x 50 = 10001 single database statements !!!

22. Use a JOIN query
$rows = $db->query ("
select department.name as department, course.title as course
from school
join department on school_id = school.id
join course on department_id = department.id
");
foreach ($rows as $row) {
echo $row->department . ": " . $row->course);
}
=> ONE database statement !!!

23. Traditional code
$author_id = get_author_id( 'Jack London' );
$books = get_books( $author_id );
foreach ($books as $book_id) {
$book = get_book( $book_id );
var_dump( $book );
}
=> N+1 Problem !!!

24. Traditional code
function get_author_id( $name ){
global $db;
$res = $db->query( "SELECT id FROM authors WHERE name=?", array( $name ) );
$id = null;
while( $res->fetchInto( $row ) ) { $id = $row[0]; }
return $id;
}
function get_books( $id ){
global $db;
$res = $db->query( "SELECT id FROM books WHERE author_id=?", array( $id ) );
$ids = array();
while( $res->fetchInto( $row ) ) { $ids []= $row[0]; }
return $ids;
}
function get_book( $id ){
global $db;
$res = $db->query( "SELECT * FROM books WHERE id=?", array( $id ) );
while( $res->fetchInto( $row ) ) { return $row; }
return null;
}
=> N+1 Problem !!!

25. Retrieving too many records

26. Retrieving too many records
$schools = new SchoolEntities();
foreach ($schools->departments as $department) {
foreach ($department->courses as $course) {
if ($course->category == "SQL" &&
$course->level == "expert")) {
echo $department->name . ": " . $course->title);
}
}
}
=> 3 records, still 10001 queries

27. Use a JOIN query
$rows = $db->query ("
select department.name as department, course.title as course
from school
join department on school_id = school.id
join course on department_id = department.id
where course.category = 'SQL' and course.level = 'expert'
");
foreach ($rows as $row) {
echo $department . ": " . $course);
}
=> ONE database statement !!!

28. Reduce the number of queries
Reduce the amount of data retrieved
Profile the generated queries!

29. I'm a developer for business
logic! I don't have to
understand what the
database does and I do not
care at all!
I'm a developer for business
logic! My code can be much
more efficient if I understand
what the database does and
how it works!

30. Make developers self-sufficient

31. Make developers self-sufficient

32. Make developers self-sufficient

33. Slow Single SQL query –
tuning/indexing might be required
Make developers self-sufficient

34. Indexes

35. Indexes are data structures for
referencing a search value (in an
indexed column) to a row in the
target table

38. Indexes are used to find records in a
table when a where clause is used

40. Indexes are also used to join tables in
a query, where multiple tables are
used

42. Index Killer
where … in (…)

43. Better
• Join tables
• Use where exists (…)

44. What’s the overall Execution
Time of different SQL Types
(SELECT, INSERT, DELETE, …)
Indexing – Read v/s Write

45. Analyzing SQLs by Type (SELECT, INSERT,
UPDATE,DELETE)
Which Types take how long? When do you have spikes?
When do we see # of SQL spikes? Spikes related to
INSERT, UPDATE, DELETE? Any job running?

46. Different databases
for read and write???

47. Different databases for read and write
• Data Warehouse
• Document oriented NoSQL
• Separate logic for data transfer needed

48. Useful commands in MySQL
explain select ...
show indexes for table_name

49. Caching

50. Application Data Cache
• Caching layer inside the application
• Application logic required to get data from and store in cache

51. MySQL Query Cache
• Caches query results in memory

52. Oracle SQL Cache
• Oracle SQL cache stores the execution plan for a SQL statement
• Even different plans a stored for different bind variable values
• No parsing required
• Parsing is the most CPU consuming process
• Cache key is full SQL query text

53. Oracle SQL Cache
<?php
$db = new PDO('oci:dbname=sid', 'username', 'password');
$data = Array();
$data[] = $db->query("select * from country where code = 'AT'");
$data[] = $db->query("select * from country where code = 'AU'");
$data[] = $db->query("select * from country where code = 'NZ'");
$data[] = $db->query("select * from country where code = 'ES'");
?>

54. Oracle SQL Cache
<?php
$db = new PDO('oci:dbname=sid', 'username', 'password');
$data = Array();
$ps = $db->prepare("select * from emp where code = :code");
$data[] = $ps->exec(array("code" => "AT"));
$data[] = $ps->exec(array("code" => "AU"));
$data[] = $ps->exec(array("code" => "NZ"));
$data[] = $ps->exec(array("code" => "ES"));
?>

56. Database Health

57. Horizontally scaled environments

60. Performance problem after upscaling

64. Database Access
• Size server (cluster) appropriately for maximum number of connected
instances
• Reduce connections
• Reduce SQL statements
• Leverage caching

66. Working together, looking at the same data
Web Server Application Server Database

67. Takeaways
• Much time spent in database does not necessarily mean database is slow!
• Performance hotspots
• Too many SQL statements
• Missing caching
• Bad query design
• Index (mis)usage
• Undersized database server
• Let developers know what’s happening in the database
• The DBA is our friend!

68. Harald Zeitlhofer
Performance Advocate
@HZeitlhofer
harald.zeitlhofer@dynatrace.com
http://blog.dynatrace.com
Dynatrace Free Trial
Free Personal License
http://bit.ly/monitoring-2016