The cost model is one of the core components of the MySQL optimizer. This presentation gives an overview over the MySQL Optimizer Cost Model, what is new in 5.7 and some ideas for further improvements.

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MySQL
Cost
Model
Olav
Sandstå
Senior
Principal
Engineer
MySQL
OpFmizer
Team,
Oracle
October
1,
2014

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Program
Agenda
IntroducFon
Cost
Based
OpFmizaFon
Cost
Model
Improvements
in
MySQL
5.7
Evolving
the
Cost
Model
1
2
3
4

4. Cost
Model
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MySQL
OpFmizer
SELECT
a,
b
FROM
t1,
t2,
t3
WHERE
t1.a
=
t2.b
AND
t2.b
=
t3.c
AND
t2.d
>
20
AND
t2.d
<
30;
MySQL
Server
Cost
based
opFmizaFons
HeurisFcs
OpFmizer
Table/index
info
(data
dicFonary)
StaFsFcs
(storage
engines)
t2
t3
Table
scan
t1
Range
scan
JOIN
Ref
access
JOIN

5. MoFvaFon
for
Improving
the
MySQL
Cost
Model
• Produce
more
correct
cost
esFmates
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– Becer
decisions
by
the
opFmizer
should
improve
performance
• Adapt
to
new
hardware
architectures
– SSD,
larger
memories,
caches
• More
maintainable
cost
model
implementaFon
– Avoid
hard
coded
“cost
constants”
– Refactoring
of
exisFng
cost
model
code
• Configurable
and
tunable
• Make
more
of
the
opFmizer
cost-­‐based
Faster
queries

6. Cost-­‐based
OpFmizaFon
Op0mizer
Cost
Model
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7. Cost-­‐based
Query
OpFmizaFon
General
idea:
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• Assign
cost
to
operaFons
• Assign
cost
to
parFal
or
alternaFve
plans
• Search
for
plan
with
lowest
cost
t2
t3
Table
scan
t1
Range
scan
JOIN
Ref
access
JOIN

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Cost-­‐based
OpFmizaFons
The
main
cost-­‐based
opFmizaFons:
• Index
and
access
method:
– Table
scan
– Index
scan
– Range
scan
– Index
lookup
(ref
access)
• Join
order
• Join
buffering
strategy
• Subquery
strategy
t2
t3
Table
scan
t1
Range
scan
JOIN
Ref
access
JOIN

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OpFmizer
Cost
Model
t1
Cost
esFmate
Row
esFmate
Cost
Model
Cost
formulas
Access
methods
Join
Subquery
Cost
constants
CPU
IO
Metadata:
-­‐ Index
informaFon
-­‐ Uniqueness
-­‐ Nullability
StaFsFcs:
-­‐ Table
size
-­‐ Cardinality
-­‐ Range
esFmates
Cost
Model
configuraFon
Range
scan
JOIN

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• The
cost
for
execu0ng
a
query
• Cost
unit:
– “read
of
a
random
data
page”
• Main
cost
factors:
– IO
cost:
• #pages
read
from
table
• #pages
read
from
index
– CPU
cost:
• EvaluaFng
query
condiFons
• Comparing
keys/records
• SorFng
keys
• Main
cost
constants:
Cost
EsFmates
Cost
Cost
value
Reading
a
random
page
1.0
EvaluaFng
query
condiFon
0.2
Comparing
key/record
0.1

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• IO-­‐cost:
– EsFmates
from
storage
engine
based
on
number
of
pages
to
read
– Both
index
and
data
pages
• Schema
(data
dic0onary):
– Length
of
records
and
keys
– Uniqueness
for
indexes
– Nullability
• Sta0s0cs:
– Number
of
records
in
table
– Key
distribuFon/Cardinality:
• Average
number
of
records
per
key
value
• Only
for
indexed
columns
– Number
of
records
in
an
index
range
– Size
of
tables
and
indexes
Input
to
Cost
Model

12. Example:
Cost
Model
for
Table
Scan
SELECT * FROM t1 WHERE a BETWEEN 20 AND 23;
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Cost
model:
• IO-­‐cost:
#pages
in
table
*
IO_BLOCK_READ_COST
• CPU
cost:
#records
*
ROW_EVALUATE_COST
• Example:
– IO-­‐cost:
193408
page
*
1.0
– CPU-­‐cost:
9829537
records
*
0.2
– Total
cost:
2159315
10
million
records

13. Example:
Cost
Model
for
Range
Scan
SELECT * FROM t1 WHERE a BETWEEN 20 AND 23;
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Range
scan
(on
secondary
index):
• IO-­‐cost:
#records_in_range
*
IO_BLOCK_READ_COST
• CPU
cost:
#records_in_range
*
ROW_EVALUATE_COST
+
#records_in_range
*
ROW_EVALUATE_COST
• Example:
– IO
cost:
80506
*
1.0
– CPU
cost:
80506
*
0.2
+
80506
*
0.2
– Total
cost:
112709
Returns
80000
records
Evaluate
range
condiFon
Evaluate
WHERE
condiFon

14. Example:
Cost
Model
for
JOIN
SELECT * FROM t1 JOIN t2 ON t1.i1 = t2.i2;
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• Table
Secondary
key
scan
on
t1:
#blocks
*
IO_BLOCK_READ_COST
+
#records
*ROW_EVALUATE_COST
• Ref
access
on
t2:
#records_from_t1
*
#records_per_key
*
(IO_BLOCK_READ_COST
+
ROW_EVALUATE_COST)
t1
t2
Access
Method
Number
of
records
read
from
t1
Number
of
records
to
read
from
t2

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• Total
cost
for
query
• Cost
per
table:
– Cost
for
reading
data
– Cost
for
evaluaFng
condiFons
• Cost
for
“join
prefix”
• Output
Cost
in
Explain
JSON
EXPLAIN
FORMAT=JSON
SELECT
*
FROM
t1
WHERE
a
BETWEEN
20
AND
23;
{
"query_block":
{
"select_id":
1,
"cost_info":
{
"query_cost":
"112709.41"
},
"table":
{
"table_name":
"t1",
"access_type":
"range",
"possible_keys":
[
”idx1"
],
….
"rows_examined_per_scan":
80506,
"rows_produced_per_join":
80506,
"filtered":
100,
"index_condiFon":
"(`test`.`t1`.`a`
between
20
and
23)",
"cost_info":
{
"read_cost":
"96608.21",
"eval_cost":
"16101.20",
"prefix_cost":
"112709.41",
"data_read_per_join":
"19M"
},
}
}

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Cost
in
OpFmizer
Trace
• Contains
rows
and
cost
esFmates
• Contains
the
result
from
the
cost
evaluaFon
"rows_esFmaFon":
[
{
"table":
"`t1`",
"range_analysis":
{
"table_scan":
{
"rows":
9575168,
"cost":
2.11e6
},
...
"analyzing_range_alternaFves":
{
"range_scan_alternaFves":
[
{
"index":
”idx",
"ranges":
[
"20
<=
a
<=
23"
],
...
"rows":
80506,
"cost":
96608,
"chosen":
true
}
],
},
SET optimizer_trace=“enabled=ON”;
SELECT * FROM t1 WHERE a BETWEEN 20 AND 23;
SELECT *
FROM INFORMATION_SCHEMA.OPTIMIZER_TRACE;

17. Cost
Model
Improvements
MySQL
5.7
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18. Cost
Model
Improvements
in
MySQL
5.7
• Improved
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record
esFmates
– Cost
model
for
WHERE
condiFons
(condiFon
filtering
effect)
– Improved
index
staFsFcs
• Configurable
“cost
constants”
• Cost
esFmates
in
Explain
JSON
• Refactoring
• Fixed
a
number
of
“cost
model”
bugs

19. Cost
Model
for
WHERE
condiFons
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Condi0on
filtering
effect
• Goal:
Low-­‐fanout
tables
should
be
early
in
the
join
order
• Problem:
The
WHERE
condiFon
is
not
taken
into
account
when
calculaFng
fanout
esFmate
for
a
table
• Solu0on:
New
way
to
calculate
fanout:
– In
5.6:
• Fanout=
#rows
esFmated
from
access
method
– In
5.7:
• Calculate
filtering
effect
of
query
condiFons
NOT
used
by
the
access
method
• Fanout=
#rows
from
access
method
*
condiFon
filter
effect

20. Record
EsFmates
for
JOIN
in
MySQL
5.6
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• tx
JOIN
tx+1
• Important
for
the
accuracy
of
cost
esFmate:
– EsFmated
number
of
records
produced
by
tx
– EsFmated
number
of
records
to
be
read
from
tx+1
tx
tx+1
Access
Method
Number
of
records
read
from
tx
Both
are
improved
in
5.7

21. Example:
Two
Table
JOIN
in
MySQL
5.6
What
is
the
best
join
order?
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CREATE TABLE employee (
id INTEGER PRIMARY KEY,
office_id INTEGER,
name VARCHAR(20),
hire_date DATE,
INDEX office(office_id)
);
CREATE TABLE office (
id INTEGER PRIMARY KEY,
office_name VARCHAR(20)
);
10000
rows
100
rows
SELECT office_name
FROM office JOIN employee ON office.id = employee.office_id
WHERE employee.name LIKE “John” AND
employee.hire_date BETWEEN “2014-01-01” AND “2014-06-01”;

22. Example:
Two
Table
JOIN
in
MySQL
5.6,
cont.
What
is
the
best
join
order?
SELECT office_name
FROM office JOIN employee ON office.id = employee.office_id
WHERE employee.name LIKE “John” AND
employee.hire_date BETWEEN “2014-01-01” AND “2014-06-01”;
Table
Type
Possible
keys
Key
Ref
Rows
Filtered
Extra
office
ALL
PRIMARY
NULL
NULL
100
100.00
NULL
employee
ref
office
office
office.id
99
100.00
Using
where
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Explain:
Total
cost
=
cost(scan
office)
+
100
*
cost(ref_access
employee)

23. Record
EsFmates
for
JOIN
in
MySQL
5.7
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• tx
JOIN
tx+1
• The
esFmate
for
number
of
records
produced
by
tX
takes
into
account
the
enFre
query
condiFon
• The
cost
esFmate
for
tX+1
should
be
more
correct
Condi0on
filter
effect
tx
tx+1
Access
Method
Number
of
records
read
from
tx
CondiFon
filter
effect
Records
passing
the
table
condiFons
on
tx

24. How
to
Calculate
CondiFon
Filter
Effect,
step
1
SELECT office_name
FROM office JOIN employee
WHERE office.id = employee.office_id AND
employee.name = “John” AND
employee.first_office_id <> office.id;
A
condiFon
contributes
to
filter
for
table
t
only
if:
– It
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references
a
field
in
table
t
– It
is
not
used
by
the
access
method
– It
depends
on
an
available
value:
• employee.name
=
“John”
will
always
contribute
to
filter
on
employee
• employee.first_office_id
<>
office.id;
depends
on
JOIN
order

25. How
to
Calculate
CondiFon
Filter
Effect,
step
2
SELECT *
FROM office JOIN employee ON office.id = employee.office_id
WHERE office_name = “San Francisco” AND
employee.name = “John” AND age > 21 AND
hire_date BETWEEN “2014-01-01” AND “2014-06-01”;
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Filter
esFmate
based
on
what
is
available:
1. Range
esFmate
2. Index
staFsFcs
3. GuessFmate
Will
like
be
adjusted
=
MAX(0.005,
1/row
count)
<=,<,>,>=
1/3
BETWEEN
1/9
NOT
<op>
1
–
SEL(<op>)
AND
P(A
and
B)
=
P(A)
*
P(B)
OR
P(A
or
B)
=
P(A)
+
P(B)
–
P(A
and
B)
…
…

26. CalculaFng
Filter
Effect
for
Tables
SELECT *
FROM office JOIN employee ON office.id = employee.office_id
WHERE office_name = “San Francisco” AND
employee.name = “John” AND age > 21 AND
hire_date BETWEEN “2014-01-01” AND “2014-06-01”;
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Filter
effect
for
tables:
– office:
0.03
– employee:
0.005
*
0.11
*
0.89
Example
0.005
(guessFmate)
0.89
(range)
0.11
(guessFmate)
0.03
(index)

27. Example:
Two
Table
JOIN
in
MySQL
5.7
SELECT office_name
FROM office JOIN employee ON office.id = employee.office
WHERE employee.name LIKE “John” AND
employee.hire_date BETWEEN “2014-01-01” AND “2014-06-01”;
Table
Type
Possible
keys
Key
Ref
Rows
Filtered
Extra
office
ALL
PRIMARY
NULL
NULL
100
100.00
NULL
employee
ref
office
office
office.id
99
100.00
Using
where
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Explain
for
5.6:
Explain
for
5.7:
Table
Type
Possible
keys
Key
Ref
Rows
Filtered
Extra
employee
ALL
NULL
NULL
NULL
9991
1.23
NULL
office
eq_ref
PRIMARY
PRIMARY
employee.office
1
100.00
Using
where
GuesFmate
JOIN
ORDER
HAS
CHANGED!

28. Performance
improvements:
DBT-­‐3
(SF10,
CPU
bound)
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100
80
60
40
20
0
Q3
Q7
Q8
Q9
Q12
Execu0on
0me
rela0ve
to
5.6
(%)
5
out
of
22
queries
get
an
improved
query
plan
MySQL
5.6
MySQL
5.7

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Disable
CondiFon
Filtering
• In
case
of
performance
regressions:
SET optimizer_switch=`condition_fanout_filter=OFF`;

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Improved
Index
StaFsFcs
• Index
staFsFcs
(cardinality)
is
calculated
by
storage
engines
as:
– Number
of
records
per
key
value
– In
5.6:
an
integer
value
– In
5.7:
replaced
with
a
floaFng
point
number
• Why:
– More
accurate
fan-­‐out
and
cost
esFmates
when
using
floaFng
point
numbers
instead
of
using
integer
values
– Becer
choice
of
index
for
join
when
two
indexes
have
similar
cardinality
esFmates

31. Index
StaFsFcs
and
Index
SelecFon
Example
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CREATE TABLE employee (
id INTEGER PRIMARY KEY,
name VARCHAR(20),
car_id INTEGER,
preferred_car_model INTEGER
);
CREATE TABLE cars (
model INTEGER,
car_id INTEGER,
INDEX model(model),
INDEX car_id(car_id)
);
Cardinality:
300
Records/key:
3.3
Cardinality:
1000
Records/key:
1.0
SELECT name
FROM employee JOIN cars
WHERE employee.car_id = cars.car_id AND
employee.preferred_car_model = cars.model;
Which
index
should
be
used
for
this
JOIN?

32. Index
StaFsFcs
and
Index
SelecFon
employee.preferred_car_model = cars.model;
Table
Type
Possible
keys
Key
Ref
Rows
Filtered
Extra
employee
ALL
NULL
NULL
NULL
1000
100.00
Using
where
cars
ref
model,
car_id
model
employee.preferred_car_model
1
100.00
Using
where
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Example
SELECT name
FROM employee JOIN cars
WHERE employee.car_id = cars.car_id AND
Explain
for
5.6:
Explain
for
5.7:
Table
Type
Possible
keys
Key
Ref
Rows
Filtered
Extra
employee
ALL
NULL
NULL
NULL
1000
100.00
Using
where
cars
ref
model,
car_id
car_id
employee.car_id
1
5.00
Using
where
Correct
esFmate
is
3.3

33. Performance
improvements:
DBT-­‐3
(SF10)
100
80
60
40
20
0
Disk
bound
Q2
Q18
Execu0on
0me
rela0ve
to
5.6
(%)
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100
80
60
40
20
0
Q2
Q18
Execu0on
0me
rela0ve
to
5.6
(%)
CPU
bound
5.6
5.7
2
out
of
22
queries
get
an
improved
query
plan
5.6
5.7

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Configurable
Cost
Model
• Replaced
hard-­‐coded
“cost
constants”
with
configurable
“cost
constants”
• Stored
in
“mysql”
database:
– server_cost
– engine_cost
• “Cost
constants”
are
changed
by
updaFng
these
tables
Cost
model
server_
cost
engine_
cost
OpFmizer

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Name
Default
value
row_evalute_cost
0.2
key_compare_cost
0.1
memory_temptable_create_cost
2.0
memory_temptable_row_cost
0.2
disk_temptable_create_cost
40.0
disk_temptable_row_cost
1.0
io_block_read_cost
1.0
Online
update
of
cost
constants:
• New
sessions
will
use
the
new
“cost
constant”
value
– Old
sessions
will
use
the
previous
“cost
constant”
value
Configurable
Cost
Constants
UPDATE mysql.server_cost
SET cost_value=0.1
WHERE cost_name=“row_evaluate_cost”;
FLUSH OPTIMIZER_COSTS;

36. Engine
Specific
Cost
Constants
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Example
• Storage
engines
can
specify
their
own
cost
constants,
both
engine
specific
values
and
add
new
cost
constants:!
cost_name
engine_name
cost_value
io_block_read_cost
Default
1.0
io_block_read_cost
InnoDB
0.9
io_block_read_cost
MyISAM
1.2
transfer_cost_mb
NDB
0.002

37. Copyright
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2014,
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and/or
its
affiliates.
All
rights
reserved.
|
Other
changes
in
MySQL
5.7
• Refactoring:
– Added
internal
Cost
Model
API
– New
handler
funcFons
for
cost
esFmates
• Cost
representaFon:
– Internal
cost
representaFon
in
handler
interface
and
range
opFmizer
records
IO
cost
and
CPU
cost
separately
• Cost
esFmates
added
to
EXPLAIN
JSON
Cost
constants
OpFmizer
Cost
Model
API
Cost
Model
configuraFon
handler
API
Storage
engines

38. Evolving
the
Cost
Model
Future
work
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|

39. Goals
for
Improving
the
Cost
Model
1. The
cost
model
should
adapt
to:
– New
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its
affiliates.
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|
server
and
storage
technologies
– Large
memory
buffers
2. Produce
more
accurate
esFmates
– Provide
becer
and
more
up
to
date
defaults
for
cost
constants
– UFlize
more
staFsFcs
about
the
data
3. More
configurable
and
tunable

40. Copyright
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2014,
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and/or
its
affiliates.
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rights
reserved.
|
New
Storage
Technologies
• Time
to
do
a
table
scan
of
10
million
records:
Memory
5
s
SSD
20
-­‐
146
s
Hard
disk
32
-­‐
1465
s
• Adjust
cost
model
to
support
different
storage
technologies
• Provide
configurable
cost
constants
for
different
storage
technologies
Provide
a
program
that
could
measure
performance
and
suggest
good
cost
constant
configuraFon
for
a
running
MySQL
server?

41. Memory
Buffer
Aware
Cost
EsFmates
SELECT * FROM t1 WHERE a > “constant”;
6
5
4
3
2
1
0
In
InnoDB
buffer
pool
1
2
3
4
5
6
7
8
9
10
11
12
Time
(s)
Percentage
of
data
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rights
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4500
4000
3500
3000
2500
2000
1500
1000
500
0
On
harddisk
1
2
3
4
5
6
7
8
9
10
11
12
Time
(s)
Percentage
of
data
Range
scan
on
secondary
key

42. Memory
Buffer
Aware
Cost
EsFmates
Query
executor
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its
affiliates.
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rights
reserved.
|
• Storage
engines:
– EsFmate
for
how
much
of
data
and
indexes
are
in
a
memory
buffer
– EsFmate
for
hit
rate
for
memory
buffer
• OpFmizer
cost
model:
– Take
into
account
whether
data
is
already
in
memory
or
need
to
be
read
from
disk
Server
Storage
engine
Disk
data
Database
buffer

43. 6
5
4
3
2
1
In
InnoDB
buffer
pool
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rights
reserved.
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4500
4000
3500
3000
2500
2000
1500
1000
500
0
On
harddisk
1
2
3
4
5
6
7
8
9
10
11
12
Time
(s)
Percentage
of
data
0
1
2
3
4
5
6
7
8
9
10
11
12
Time
(s)
Percentage
of
data
Memory
Buffer
Aware
Cost
EsFmates
Goal:
• Select
becer
point
for
changing
between
alternaFve
access
methods:

44. OpFmizer
Index
staFsFcs
Storage
Engine
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rights
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Histogram
Improved
StaFsFcs
• The
more
informaFon
the
opFmizer
has
about
the
data
in
tables,
the
becer
choices
can
the
opFmizer
make
• New
staFsFcs:
– StaFsFcs
for
non-­‐indexed
columns
– Histograms
Table
Index
Column
staFsFcs

45. Copyright
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2014,
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and/or
its
affiliates.
All
rights
reserved.
|
QuesFons?

46. Copyright
©
2014,
Oracle
and/or
its
affiliates.
All
rights
reserved.
|
Thank
You!