Query Optimization with MySQL 8.0 and MariaDB 10.3: The Basics

Query Optimization with MySQL 8.0 and MariaDB 10.3: The Basics
© 2018 Jaime Crespo. http://jynus.com. License: CC-BY-SA-4.0
Query Optimization With MySQL
8.0 and MariaDB 10.3:
The Basics
Jaime Crespo
Percona Live Europe 2018
-Frankfurt, 5 Nov 2018-
dbahire.com/pleu18

2
Agenda
1. Introduction 6. Joins
2. Query Profiling 7. Subqueries
3. Access Types and Basic
Indexing Techniques
8. FULLTEXT, Geodata Search
and JSON support
4. Multi-Column Indexing 9. Conclusions
5. Break

3
INTRODUCTION
Query Optimization with MySQL 8.0 and MariaDB
10.3: The Basics

4
This is me fighting bad query
performance
●
Sr. Database Administrator
at Wikimedia Foundation
●
Used to work as a trainer
for Oracle (MySQL), as a
Consultant (Percona) and
as a Freelance
administrator
(DBAHire.com)

5
Example Application (I)
• Wiktionary (and all Wikimedia projects’ data) is
licensed under the Creative Commons BY-SA-3.0
License and is Copyright its Contributors

6
Example Application (II)
• OSM Database is licensed under the Open
DataBase License and is Copyright OpenStreetMap
Contributors

7
Install the example databases
●
Downloads and instructions at:
http://dbahire.com/pleu18
– Requirements: a MySQL 8.0 or MariaDB 10.3
installation
– The Wiktionary and OSM extracts
●
Import them by doing:
$ tar xf <file> && cd <dir> && myloader -d .

8
Alternative: Query the Live
Database
●
https://quarry.wmflabs.org/

9
QUERY PROFILING
10.3: The Basics

10
Which Queries Should I Optimize
First?
●
Tools:
– Application-level profiling
– General monitoring metrics (CPU, IO, etc.)
– Aggregated PROCESSLIST
– pt-query-digest
– PERFORMANCE_SCHEMA
●
They are not exclusive to each other

11
Application-Level profiling

12
General Monitoring Metrics
New index added
at 15:30h

13
pt-query-digest
• It is a 3rd party tool written in Perl, originally
created by Baron Schwartz
• It requires activation of the slow log:
– SET GLOBAL slow_query_log = 1;
– SET long_query_time = 0;
• In Percona Server and MariaDB it can provide extra
information:
– SHOW GLOBAL VARIABLES like 'log_slow_verbosity';
Be careful
with extra
IO and
latency!
Be careful
with extra
IO and
latency!

14
pt-query-digest Execution (I)
# 1094.7s user time, 9.4s system time, 141.22M rss, 205.21M vsz
# Current date: Wed Jul 1 07:32:28 2015
# Hostname: db1018
# Files: STDIN
# Overall: 4.66M total, 640 unique, 53.47 QPS, 0.02x concurrency _________
# Time range: 2015-06-30 07:00:10 to 2015-07-01 07:11:37
# Attribute total min max avg 95% stddev median
# ============ ======= ======= ======= ======= ======= ======= =======
# Exec time 1320s 1us 3s 283us 332us 3ms 152us
# Lock time 238s 0 13ms 51us 93us 39us 52us
# Rows sent 5.02M 0 4.16k 1.13 1.96 8.69 0.99
# Rows examine 9.50M 0 232.93k 2.14 3.89 261.15 0.99
# Merge passes 0 0 0 0 0 0 0
# Query size 1.06G 17 67.89k 243.89 511.45 368.99 192.76
# Boolean:
# Filesort 8% yes, 91% no
# Full scan 94% yes, 5% no
# Priority que 3% yes, 96% no
# Tmp table 29% yes, 70% no
# Tmp table on 1% yes, 98% no
Actual execution
on Wikipedia
production
servers
Actual execution
on Wikipedia
production
servers

15
pt-query-digest Execution (II)
# Profile
# Rank Query ID Response time Calls R/Call V/M Item
# ==== ================== ============== ======= ====== ===== ============
# 1 0xSANITIZED 242.2765 18.4% 691005 0.0004 0.00 SELECT revision page user
# 3 0xSANITIZED 162.8476 12.3% 1025179 0.0002 0.00 SELECT page
# 5 0xSANITIZED 66.8302 5.1% 354562 0.0002 0.00 SELECT page revision
# 6 0xSANITIZED 57.0374 4.3% 211631 0.0003 0.00 SELECT page revision
# 7 0xSANITIZED 44.0751 3.3% 6925 0.0064 0.07 SELECT page categorylinks
category
# 8 0xSANITIZED 35.0655 2.7% 9689 0.0036 0.00 SELECT text
# 9 0xSANITIZED 29.4363 2.2% 152259 0.0002 0.00 SELECT page
# 10 0xSANITIZED 24.1864 1.8% 176927 0.0001 0.00 SELECT msg_resource
# 11 0xSANITIZED 23.7016 1.8% 144807 0.0002 0.00 SELECT page_restrictions
# 12 0xSANITIZED 16.6547 1.3% 10135 0.0016 0.03 SELECT revision
# 13 0xSANITIZED 15.0564 1.1% 263809 0.0001 0.00 SET

16
pt-query-digest Execution (III)
# Query 1: 7.93 QPS, 0.00x concurrency, ID 0xSANITIZED at byte 1553864032
# This item is included in the report because it matches –limit.
# Scores: V/M = 0.00
# Time range: 2015-06-30 07:00:10 to 2015-07-01 07:11:37
# Attribute pct total min max avg 95% stddev median
# ============ === ======= ======= ======= ======= ======= ======= =======
# Count 14 691005
# Exec time 18 242s 163us 91ms 350us 348us 563us 301us
# Lock time 26 63s 47us 7ms 91us 103us 14us 84us
# Rows sent 12 657.18k 0 1 0.97 0.99 0.16 0.99
# Rows examine 6 657.18k 0 1 0.97 0.99 0.16 0.99
# Query size 31 345.42M 501 749 524.16 537.02 9.22 511.45
# String:
# Databases itwiki (225976/32%), enwiktiona... (219461/31%)... 15 more
# Hosts
# Users wikiuser
# Query_time distribution
# 1us
# 10us
# 100us ################################################################
# 1ms #
# 10ms #
# 100ms
# 1s
# 10s+
# Tables
# SHOW TABLE STATUS FROM ènwiktionary` LIKE 'revision'G
# SHOW CREATE TABLE ènwiktionary`.`revision`G
# SHOW TABLE STATUS FROM ènwiktionary` LIKE 'page'G
# SHOW CREATE TABLE ènwiktionary`.`page`G
# SHOW TABLE STATUS FROM ènwiktionary` LIKE 'user'G
# SHOW CREATE TABLE ènwiktionary`.ùser`G
# EXPLAIN /*!50100 PARTITIONS*/
SELECT /* Revision::fetchFromConds SANITIZED */ * FROM `revision`
INNER JOIN `page` ON ((page_id = rev_page)) LEFT JOIN ùser` ON
((rev_user != 0) AND (user_id = rev_user)) WHERE page_namespace = '0' AND
page_title = 'SANITIZED' AND (rev_id=page_latest) LIMIT 1G

17
PERFORMANCE_SCHEMA
• Monitoring schema (engine) enabled by
default since MySQL 5.6
– performance_schema = 1 (it is not dynamic)
• Deprecates the old query profiling
• It is way more user-friendly when combined
with the SYS schema/ps_helper (a set of
views and stored procedures created by Mark
Leith)
– Included by default since 5.7.7

18
Installation of the SYS Schema
<5.7/MariaDB
$ git clone https://github.com/MarkLeith/mysql-sys.git
Cloning into 'mysql-sys'...
remote: Counting objects: 926, done.
remote: Compressing objects: 100% (73/73), done.
remote: Total 926 (delta 35), reused 6 (delta 2)
Receiving objects: 100% (926/926), 452.19 KiB | 225.00
KiB/s, done.
Resolving deltas: 100% (584/584), done.
$ cd mysql-sys/
$ mysql < sys_56.sql

20
Example Usage: Slow Queries
(ordered by server time)
*************** 1. row ***************
query: SELECT `way_id` AS
`id` , `v` FROM `way_tags` WHERE `v` LIKE ?
db: osm
full_scan: *
exec_count: 15
err_count: 0
warn_count: 0
total_latency: 7.83 s
max_latency: 1.33 s
avg_latency: 521.84 ms
lock_latency: 17.94 ms
rows_sent: 6779
rows_sent_avg: 452
mysql (osm) > SELECT * FROM sys.statement_analysis LIMIT 10G
rows_examined: 20152155
rows_examined_avg: 1343477
rows_affected: 0
rows_affected_avg: 0
tmp_tables: 0
tmp_disk_tables: 0
rows_sorted: 0
sort_merge_passes: 0
digest:
21f90695b1ebf20a5f4d4c1e5e860f58
first_seen: 2014-11-01 17:04:51
last_seen: 2014-11-01 17:05:22

21
Example Usage: Top Queries
Creating Temporary Tables
mysql (osm) > SELECT * FROM sys.statements_with_temp_tables
WHERE db = 'osm' LIMIT 10G
*************************** 1. row ***************************
query: SELECT ? AS TYPE , `node_id` A ... gs` WHERE `k` = ? AND `v` = ?
db: osm
exec_count: 11
total_latency: 7.57 s
memory_tmp_tables: 11
disk_tmp_tables: 0
avg_tmp_tables_per_query: 1
tmp_tables_to_disk_pct: 0
first_seen: 2014-11-01 17:33:55
last_seen: 2014-11-01 17:34:45
digest: 5e6e82799b7c7c0e5c57cfe63eb98d5d

23
ACCESS TYPES AND BASIC
INDEXING TECHNIQUES
10.3: The Basics

24
EXPLAIN
●
Essential to understand the execution plan of our
queries
– Works on SELECTs, INSERTs, UPDATEs,
REPLACEs, DELETEs and connections
– Fully documented on:
https://dev.mysql.com/doc/refman/8.0/en/expl
ain-output.html

26
EXPLAIN Example (vertical
format)
MariaDB [dewiktionary]> EXPLAIN SELECT * FROM page WHERE
page_title = 'German'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: page
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 778885
Extra: Using where
Use G for
vertical
formatting
Use G for
vertical
formatting

27
EXPLAIN Example (id)
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: page
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 778885
Extra: Using where
Indicates nesting level,
not execution order
Indicates nesting level,
not execution order

28
EXPLAIN Example (select_type)
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: page
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 778885
Extra: Using where
Not a subquery or a
UNION
Not a subquery or a
UNION

29
EXPLAIN Example (table)
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: page
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 778885
Extra: Using where
Table scanned for
this step
Table scanned for
this step

30
EXPLAIN Example (type)
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: page
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 778885
Extra: Using where
All rows are read for
this table (FULL
TABLE SCAN)
All rows are read for
this table (FULL
TABLE SCAN)

31
EXPLAIN Example (rows)
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: page
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 778885
Extra: Using where
Estimated number
of rows to be read
(all table rows)
Estimated number
of rows to be read
(all table rows)

32
How to improve performance?
●
Let's add an index on page.page_title:
MariaDB [dewiktionary]> ALTER TABLE page ADD INDEX
page_title (page_title);
Query OK, 0 rows affected (22.70 sec)
Records: 0 Duplicates: 0 Warnings: 0
MariaDB [dewiktionary]> SELECT * FROM page

33
Index creation results (type)
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: page
type: ref
possible_keys: page_title
key: page_title
key_len: 257
ref: const
rows: 1
Extra: Using index condition
type: ref means that an
equality comparison will
be checked against an
index and several results
could be returned
type: ref means that an
equality comparison will
be checked against an
index and several results
could be returned

34
Index creation results
(possible_keys and key)
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: page
type: ref
key: page_title
key_len: 257
ref: const
rows: 1
index(es) that the
optimizer considered
potentially useful, and
final index chosen
index(es) that the
optimizer considered
potentially useful, and
final index chosen

35
Index creation results (ref)
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: page
type: ref
key: page_title
key_len: 257
ref: const
rows: 1
Index is compared
with a constant, not
with another table
Index is compared
with a constant, not
with another table

36
Index creation results (rows)
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: page
type: ref
key: page_title
key_len: 257
ref: const
rows: 1
Only 1 row read. In this
case, estimation is exact
(thanks to index dive)
Only 1 row read. In this
case, estimation is exact
(thanks to index dive)

37
Index creation results (query
time)
MariaDB [dewiktionary]> SELECT * FROM page
1 row in set (0.00 sec) Query time has been
reduced substantially
Query time has been
reduced substantially

38
Types of indexes
●
BTREE
– B-TREE in MyISAM, B+TREE in InnoDB
●
HASH
– Only available for MEMORY and NDB
●
FULLTEXT
– Inverted indexes in MyISAM and InnoDB
●
SPATIAL
– RTREEs in MyISAM and InnoDB

39
Finding “German” with a BTREE
GoalGoal
NastyNasty
BossBoss
EtchEtch
LeekLeek
SchoolSchool
AvastAvast
GolfGolf
LandscapeLandscape
RoverRover
GermanGerman
HarlemHarlem
MaelstromMaelstrom
WalrusWalrus
TABLETABLE
IcebergIceberg

40
Finding “German” with a BTREE
AvastAvast
GolfGolf
LandscapeLandscape
RoverRover
GermanGerman
HarlemHarlem
MaelstromMaelstrom
WalrusWalrus
TABLETABLE
GoalGoal
NastyNasty
BossBoss
EtchEtch
LeekLeek
SchoolSchool
IcebergIceberg

41
Do indexes always work? (1/2)
●
Can we use an index to make this query
faster?
SELECT * FROM page WHERE page_title like 'Spa%';

42
It is a range
page_title like 'Spa%'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: page
type: range
key: page_title
key_len: 257
ref: NULL
rows: 563
Despite not being an
equality, we can use the
index to find the values
quickly
Despite not being an
equality, we can use the
index to find the values
quickly

43
EtchEtch
BTREE Indexes can be used for
ranges, too
AvastAvast
GolfGolf
LandscapeLandscape
RoverRover
GermanGerman
HarlemHarlem
MaelstromMaelstrom
WalrusWalrus
TABLETABLE
GoalGoal
NastyNasty
BossBoss
LeekLeek
SchoolSchool
IcebergIceberg

44
Do indexes always work? (2/2)
●
What about this other query?
SELECT * FROM page WHERE page_title like '%erman';

45
Let's check with EXPLAIN
page_title like '%erman'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: page
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 778885
Extra: Using where
No index can be used
for filtering. A full
table scan is
performed.
No index can be used
for filtering. A full
table scan is
performed.

46
BTREE Index
AvastAvast
GolfGolf
LandscapeLandscape
RoverRover
GermanGerman
HarlemHarlem
MaelstromMaelstrom
WalrusWalrus
TABLETABLE
?
GoalGoal
NastyNasty
BossBoss
EtchEtch
LeekLeek
SchoolSchool
IcebergIceberg

47
Btree indexes usage (I)
●
Filtering (“WHERE”)
– Equality (operator '=')
– Ranges (BETWEEN … AND, >, <, >=, <=, like
'prefix%')
– “EXISTS” operators: IN, OR on the same column
●
Ordering
– ORDER BY (indexed columns)
– GROUP BY (indexed columns)

48
Btree indexes usage (II)
●
Returning values directly from the index
– Covering index
– Functions like max(), min(), etc.
●
Reduced contention (writes)
– Locking less rows, increasing concurrency

49
type: const
MariaDB [dewiktionary]> EXPLAIN SELECT * FROM revision WHERE
rev_id = 2G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: const
possible_keys: PRIMARY
key: PRIMARY
key_len: 4
ref: const
rows: 1
Extra:
'const' is a special case of 'ref',
when the index can assure
that only 1 result can be
returned (equality + primary
key or unique key). It is faster.
'const' is a special case of 'ref',
when the index can assure
that only 1 result can be
returned (equality + primary
key or unique key). It is faster.

50
type: NULL
rev_id = -1G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: NULL
type: NULL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: NULL
Extra: Impossible WHERE noticed after reading const
tables
'NULL' is not really a plan,
just an optimization that
allows immediately
discarding impossible
conditions
'NULL' is not really a plan,
just an optimization that
allows immediately
discarding impossible
conditions

51
type: ref_or_null
MariaDB [osm]> EXPLAIN SELECT * FROM nodes WHERE tile = 1 or
tile is nullG
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: nodes
type: ref_or_null
possible_keys: nodes_tile_idx
key: nodes_tile_idx
key_len: 5
ref: const
rows: 2
Extra: Using index condition; Using where
Equivalent to 'ref', but
also takes into account
NULL values
Equivalent to 'ref', but
also takes into account
NULL values

52
type: range (using IN / OR)
page_title IN ('German', 'English', 'Spanish')G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: page
type: range
key: page_title
key_len: 257
ref: NULL
rows: 4
Despite being a range, its
execution is very
different from ranges
using like, between or
inequality operators
Despite being a range, its
execution is very
different from ranges
using like, between or
inequality operators

53
Is this a bug? (1/2)
page_namespace > 200G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: page
type: ref
possible_keys: name_title
key: name_title
key_len: 4
ref: const
rows: 50
Extra:
An index is used to
return pages with
namespace>200
An index is used to
return pages with
namespace>200

54
Is this a bug? (2/2)
page_namespace < 200G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: page
type: ALL
possible_keys: name_title
key: NULL
key_len: NULL
ref: NULL
rows: 778885
Extra: Using where
The index is not used
with ns=0
The index is not used
with ns=0

55
Using an index is sometimes
suboptimal
This point is not
fixed, and
depends on the
hardware and
buffer state
This point is not
fixed, and
depends on the
hardware and
buffer state

56
What index should we add to
make this query faster?
left(rev_timestamp, 6) = '201809'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 1376651
Extra: Using where

57
The table has already an index on
rev_timestamp
MariaDB [dewiktionary]> SHOW CREATE TABLE revisionG
*************************** 1. row ***************************
Table: revision
Create Table: CREATE TABLE `revision` (
...
KEY `rev_timestamp` (`rev_timestamp`),

58
We need to rewrite the query
rev_timestamp >= '201509' and rev_timestamp < '201510'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: range
possible_keys: rev_timestamp
key: rev_timestamp
key_len: 14
ref: NULL
rows: 24588

59
This transformation is not trivial
or even possible in all cases
substr(rev_timestamp, 5, 2) = '09'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
Rows: 1376651
Extra: Using where
Can you think of a way
to improve this query?
Can you think of a way
to improve this query?

60
Indexes for Ordering
MariaDB [dewiktionary]> EXPLAIN SELECT * FROM page ORDER BY
page_touched DESC LIMIT 10G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: page
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 778885
Extra: Using filesort
"Using filesort" indicates that
an ordering is needed before
returning the results
"Using filesort" indicates that
an ordering is needed before
returning the results

61
If that is frequent, we can create
an index on page_touched...[dewiktionary]> ALTER TABLE page ADD INDEX page_page_touched(page_touched);
[dewiktionary]> EXPLAIN SELECT * FROM page ORDER BY page_touched DESC LIMIT
10G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: page
type: index
possible_keys: NULL
key: page_page_touched
key_len: 16
ref: NULL
rows: 10
Extra:
The index does not produce any
advantage for filtering
advantage for filtering
However, it is very effective by
helping to avoid the sort phase
However, it is very effective by
helping to avoid the sort phase

62
It can return data in index order
faster
AvastAvast
GolfGolf
LandscapeLandscape
RoverRover
GermanGerman
HarlemHarlem
MaelstromMaelstrom
WalrusWalrus
TABLETABLE
GoalGoal
NastyNasty
BossBoss
EtchEtch
LeekLeek
SchoolSchool
IcebergIceberg

63
Trick: ORDER BY NULL avoids
filesortMariaDB [dewiktionary]> EXPLAIN SELECT * FROM revision GROUP BY substr(rev_timestamp, 5,
2) = '09'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 1376651
Extra: Using temporary; Using filesort
MariaDB [nlwiktionary]> EXPLAIN SELECT * FROM revision GROUP BY substr(rev_timestamp, 5,
2) = '09' ORDER BY NULLG
*************************** 1. row ***************************
...
rows: 1376651
Extra: Using temporary
The advantage is not too big, but
it avoids the filesort
The advantage is not too big, but
it avoids the filesort
There is no good index in this
case
There is no good index in this
case

64
Does LIMIT improve the
performance? (I)
MariaDB [dewiktionary]> ALTER TABLE page ADD INDEX page_touched (page_touched); […]
MariaDB [dewiktionary]> EXPLAIN SELECT * FROM page ORDER BY page_touchedG
*************************** 1. row ***************************
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 783231
MariaDB [dewiktionary]> EXPLAIN SELECT * FROM page ORDER BY page_touched LIMIT 10G
*************************** 1. row ***************************
type: index
possible_keys: NULL
key: page_page_touched
key_len: 16
ref: NULL
rows: 10
Extra:
In some cases it can be
essential to allow
effective usage of the
indexes
In some cases it can be
essential to allow
effective usage of the
indexes

65
performance? (II)MariaDB [dewiktionary]> EXPLAIN SELECT * FROM revision ORDER BY rev_commentG
*************************** 1. row ***************************
[...] type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 817636
MariaDB [dewiktionary]> EXPLAIN SELECT * FROM revision ORDER BY rev_comment LIMIT 10G
*************************** 1. row ***************************
[…] table: revision
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 817636
In other cases, it has no
effect on the scanned
rows (just on the
returned ones)
In other cases, it has no
effect on the scanned
rows (just on the
returned ones)

66
performance? (III)MariaDB [nlwiktionary]> EXPLAIN SELECT * FROM page ORDER BY page_title LIMIT 100G
*************************** 1. row ***************************
type: index
possible_keys: NULL
key: page_title
key_len: 257
ref: NULL
rows: 100
Extra:
MariaDB [nlwiktionary]> EXPLAIN SELECT * FROM page ORDER BY page_title LIMIT 10000, 100G
*************************** 1. row ***************************
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 90956
In this case,
performance will vary
depending on the
offset (not ideal)
In this case,
performance will vary
depending on the
offset (not ideal)

67
Indexes and GROUP BY (no
indexes)
MariaDB [dewiktionary]> EXPLAIN SELECT rev_page, count(*) FROM
revision IGNORE INDEX(rev_page_id, page_timestamp,
page_user_timestamp) GROUP BY rev_pageG
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 1376651
Extra: Using temporary; Using filesort
Without indexes, a temporary
table is created to order results
Without indexes, a temporary
table is created to order results

68
Indexes and GROUP BY
(rev_page_id)
MariaDB [dewiktionary]> EXPLAIN SELECT rev_page, count(*) FROM
revision GROUP BY rev_pageG
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: index
possible_keys: NULL
key: rev_page_id
key_len: 8
ref: NULL
rows: 1376651
Extra: Using index
advantage for filtering (there is
no WHERE clause)
advantage for filtering (there is
no WHERE clause)
However, thanks to it we avoid a
sort and a temporary table
However, thanks to it we avoid a
sort and a temporary table

69
type: index, loose index scan and
covering index (1/3)
node_id version k v
234234344545 1 leaves deciduous
234234344546 3 name Northolt Road
234234344548 5 gps:latitude 490018321N
234234344549 6 access uncontrolled
234234344550 1 editor JOSM
234234344551 9 name Big Ben
234234344552 1 source survey
234234344557 1 name London Plane
CarlsbergCarlsberg
recyclingrecycling
Accurate as
of 2010
Accurate as
of 2010
Gwynne
Place
Gwynne
Place
Manor PlaceManor Place
treetree
490018321N490018321N
deciduousdeciduous
London PlaneLondon Plane
surveysurvey
Big BenBig Ben
JOSMJOSM
Northolt RoadNortholt Road
uncontrolleduncontrolled
London
Borough of
Southwark
London
Borough of
Southwark
With 'type:index', all rows are
read in index order (full index
scan)
With 'type:index', all rows are
read in index order (full index
scan)

70
node_id version k v
234234344548 5 gps:latitude 490018321N
234234344550 1 editor JOSM
234234344551 9 name Big Ben
CarlsbergCarlsberg
recyclingrecycling
Accurate as
of 2010
Accurate as
of 2010
Gwynne
Place
Gwynne
Place
treetree
490018321N490018321N
deciduousdeciduous
surveysurvey
Big BenBig Ben
JOSMJOSM
London
Borough of
Southwark
London
Borough of
Southwark
If we have in addition 'Using
index for group-by' we have the
loose index scan optimization
index for group-by' we have the
loose index scan optimization

71
Loose Index Scan Example
MariaDB [dewiktionary]> EXPLAIN SELECT rev_page,
max(rev_timestamp) FROM revision GROUP BY rev_pageG
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: range
possible_keys: NULL
key: page_timestamp
key_len: 4
ref: NULL
rows: 80980
Extra: Using index for group-by

72
CarlsbergCarlsberg
recyclingrecycling
Accurate as
of 2010
Accurate as
of 2010
Gwynne
Place
Gwynne
Place
treetree
490018321N490018321N
deciduousdeciduous
surveysurvey
Big BenBig Ben
JOSMJOSM
London
Borough of
Southwark
London
Borough of
Southwark
index' we have the covering index
optimization
index' we have the covering index
optimization
node_id version k v
234234344548 5 gps:latitude 490018321N
234234344550 1 editor JOSM
234234344551 9 name Big Ben

73
Covering Index Example (1/3)
MariaDB [dewiktionary]> ALTER TABLE revision DROP INDEX rev_page_id, drop index page_timestamp,
drop index page_user_timestamp;
MariaDB [dewiktionary]> EXPLAIN SELECT count(DISTINCT rev_user) FROM revision WHERE rev_page =
31579G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 1376651
Extra: Using where
MariaDB [dewiktionary]> SELECT count(DISTINCT rev_user) FROM revision WHERE rev_page = 31579G
*************************** 1. row ***************************
count(DISTINCT rev_user): 1
Let's start with no indexesLet's start with no indexes

74
MariaDB [dewiktionary]> ALTER TABLE revision ADD INDEX revision_rev_page(rev_page);
MariaDB [dewiktionary]> EXPLAIN SELECT count(DISTINCT rev_user) FROM revision WHERE rev_page =
31579G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: ref
possible_keys: revision_rev_page
key: revision_rev_page
key_len: 4
ref: const
rows: 4038
Extra:
*************************** 1. row ***************************
Adding an index on rev_page
increases the speed due to
improved filtering
Adding an index on rev_page
increases the speed due to
improved filtering

75
MariaDB [dewiktionary]> ALTER TABLE revision ADD INDEX revision_rev_page_rev_user(rev_page,
rev_user);
MariaDB [dewiktionary]> EXPLAIN SELECT count(DISTINCT rev_user) FROM revision WHERE rev_page = 31579
G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: ref
possible_keys: revision_rev_page,revision_rev_page_rev_user
key: revision_rev_page_rev_user
key_len: 4
ref: const
rows: 4038
Extra: Using index
*************************** 1. row ***************************
rev_page, rev_user does not
increase the index
selectiveness, but allows
returning results directly
from the index
rev_page, rev_user does not
increase the index
selectiveness, but allows
returning results directly
from the index
The speed difference can be hugeThe speed difference can be huge

76
MULTI-COLUMN INDEXES
10.3: The Basics

77
In many cases, conditions are
applied on more than one column
rev_page = 31579 and rev_timestamp < '2008'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 1376651
Extra: Using where
Assuming there were no previously
created indexes, which would the
optimal one be?
Assuming there were no previously
created indexes, which would the
optimal one be?

78
Options for indexes
●
1 index on column (rev_page)
●
1 index on column (rev_timestamp)
●
2 indexes, 1 on (rev_page) and another on
(rev_timestamp)
●
1 multi-column index on (rev_page, rev_timestamp)
●
1 multi-column index on (rev_timestamp,rev_page)
Are these last 2 different from each other?
Would it depend on the query order?
Are these last 2 different from each other?
Would it depend on the query order?

79
A brief reminder about query parsing
SELECT * FROM revision WHERE rev_page = 31579 and rev_timestamp < '2008'
SELECTSELECT
FieldsFields FROMFROM
revision.
rev_page
revision.
rev_page
==
(int constant)
31579
(int constant)
31579
revision.
rev_timest
amp
revision.
rev_timest
amp
<<
(string
constant)
'2008'
(string
constant)
'2008'
WHEREWHERE
revision.
rev_id
revision.
rev_id
... revisionrevision
Order in the query is not
important
Order in the query is not
important

80
Index on (rev_page)
MariaDB [dewiktionary]> ALTER TABLE revision ADD INDEX rev_page (rev_page);
MariaDB [dewiktionary]> EXPLAIN SELECT * FROM revision WHERE rev_page = 31579 and
rev_timestamp < '2008'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: ref
possible_keys: rev_page
key: rev_page
key_len: 4
ref: const
rows: 4038
Extra: Using where
Query time improves
significantly with this
index
Query time improves
significantly with this
index
Fewer rows are
scanned
Fewer rows are
scanned

81
Adding (rev_timestamp)
MariaDB [dewiktionary]> ALTER TABLE revision ADD INDEX rev_timestamp
(rev_timestamp);
MariaDB [dewiktionary]> EXPLAIN SELECT * FROM revision WHERE rev_page =
31579 and rev_timestamp < '2008'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: ref
possible_keys: rev_page,rev_timestamp
key: rev_page
key_len: 4
ref: const
rows: 4038
Extra: Using where
rev_page is preferred
over rev_timestamp
rev_page is preferred
over rev_timestamp
In general, only one index can
be used per table access
In general, only one index can
be used per table access

82
Forcing the use of
(rev_timestamp)
MariaDB [dewiktionary]> EXPLAIN SELECT * FROM revision FORCE
INDEX(rev_timestamp) WHERE rev_page = 31579 and rev_timestamp
< '2008'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: range
possible_keys: rev_timestamp
key: rev_timestamp
key_len: 14
ref: NULL
rows: 688325
It is a range
access
It is a range
access
A lot more accessed
rows
A lot more accessed
rows
Forcing the index is worse than type:ALL!Forcing the index is worse than type:ALL!

83
Adding (rev_page,
rev_timestamp)MariaDB [dewiktionary]> ALTER TABLE revision ADD INDEX
rev_page_rev_timestamp(rev_page, rev_timestamp);
31579 and rev_timestamp < '2008'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: range
possible_keys: rev_page,rev_timestamp,rev_page_rev_timestamp
key: rev_page_rev_timestamp
key_len: 18
ref: NULL
rows: 530
Reduced number of
rows scanned
Reduced number of
rows scanned

84
Is (rev_timestamp, rev_page) a
better option?MariaDB [dewiktionary]> ALTER TABLE revision ADD INDEX rev_timestamp_rev_page
(rev_timestamp, rev_page);
MariaDB [dewiktionary]> EXPLAIN SELECT * FROM revision WHERE rev_page = 31579 and
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: range
possible_keys: rev_page,rev_timestamp,rev_page_rev_timestamp,rev_timestamp_rev_page
key_len: 18
ref: NULL
rows: 530
Previous index is still
preferred, why?

85
Forcing (rev_timestamp,
rev_page)
INDEX(rev_timestamp_rev_page) WHERE rev_page = 31579 and
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: range
possible_keys: rev_timestamp_rev_page
key: rev_timestamp_rev_page
key_len: 18
ref: NULL
rows: 688325
Only the 1st column* is being
used effectively for filtering

86
A compound index produces a single
tree ordered by the 2 values
(12301,
'2018')
(12301,
'2018')
(31579,
'2005')
(31579,
'2005')
(8005,
'2016')
(8005,
'2016')
(15444,
'2011')
(15444,
'2011')
(31579,
'2003')
(31579,
'2003')
(31579,
'2017')
(31579,
'2017')
(4611, '2015')(4611, '2015')
(12702, '2014')(12702, '2014')
(30024, '2003')(30024, '2003')
(31579, '2008')(31579, '2008')
(11771, '2013')(11771, '2013')
(23305, '2006')(23305, '2006')
(31579, '2004')(31579, '2004')
(428105, '2015')(428105, '2015')
TABLETABLE
(23443,
'2016')
(23443,
'2016')
rev_page = 31579 and
rev_timestamp > '2008'
(rev_page,
rev_timestamp)
(rev_page,
rev_timestamp)

87
The alternative index cannot be used
in such an effective way
('2008', 800)('2008', 800)
('2016', 24)('2016', 24)
('2004', 107)('2004', 107)
('2008',
55765)
('2008',
55765)
('2014', 999)('2014', 999)
('2018',
31579)
('2018',
31579)
('2001', 355)('2001', 355)
('2008', 31579)('2008', 31579)
('2012', 791)('2012', 791)
('2018', 1784)('2018', 1784)
('2008', 206)('2008', 206)
('2009', 201)('2009', 201)
('2015', 31579)('2015', 31579)
('2018', 79405)('2018', 79405)
TABLETABLE
('2011',
13605)
('2011',
13605)
(rev_timestamp,
rev_page)
(rev_timestamp,
rev_page)
rev_page = 31579 and
rev_timestamp > '2008'

88
Order and column selection
• Range access using >, <, >=, <=, BETWEEN
can only be filtered once effectively, at the
end of an index
• When selecting indexes, prefer columns with
high cardinality (very selective)
– The optimal index can depend on the constants used

89
Can we filter and sort at the same
time using indexes?
rev_comment='' ORDER BY rev_timestamp ASCG
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 817636
Extra: Using where; Using filesort
This query is slow
because a) the full
table scan
This query is slow
because a) the full
table scan
b) Required sort
after filtering
b) Required sort
after filtering

90
Adding an index on
(rev_comment, rev_timestamp)MariaDB [dewiktionary]> ALTER TABLE revision ADD INDEX
rev_comment_rev_timestamp (rev_comment, rev_timestamp);
MariaDB [dewiktionary]> EXPLAIN SELECT * FROM revision WHERE rev_comment=''
ORDER BY rev_timestamp ASCG
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: ref
possible_keys: rev_comment_rev_timestamp
key: rev_comment_rev_timestamp
key_len: 769
ref: const
rows: 266462
Both ‘type: ALL’
and ‘filesort’ have
disappeared
Both ‘type: ALL’
and ‘filesort’ have
disappeared

91
This is not always possible
rev_len > 5500 ORDER BY rev_timestamp ASCG
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: range
possible_keys: rev_len_rev_timestamp
key: rev_len_rev_timestamp
key_len: 5
ref: NULL
rows: 38744
Extra: Using index condition; Using filesort
The range makes impossible
to use the index optimally
for the ORDER BY: either we
filter (rev_len) or sort
(rev_timestamp)
The range makes impossible
to use the index optimally
for the ORDER BY: either we
filter (rev_len) or sort
(rev_timestamp)

92
A Strange Game. The Only
Winning Move is Not to Play
mysql (osm) > SELECT * FROM nodes FORCE INDEX(version_idx)
WHERE version < 15 ORDER BY changeset_id;
/* type: range, Using filesort */
2859673 rows in set (30.58 sec)
mysql (osm) > SELECT * FROM nodes FORCE
INDEX(changeset_id_idx) WHERE version < 15 ORDER BY
changeset_id;
/* type: index */
2859673 rows in set (30.92 sec)
mysql (osm) > SELECT * FROM nodes WHERE version < 15 ORDER BY
changeset_id;
/* type: ALL, Using filesort */
2859673 rows in set (16.54 sec)

95
DESC Indexes (new in 8.0)
●
Regular indexes could also be used to scan
rows in inverse order
– It had a penalty
– It improves certain queries combining
DESC and ASC order
mysql-8.0 [dewiktionary]> ALTER TABLE page ADD INDEX
`page_redirect_namespace_len_DESC`
(`page_is_redirect`,`page_namespace`,`page_len` DESC);
Query OK, 0 rows affected, 1 warning (3.96 sec)

96
Descending Indexes in Action
mysql-8.0 [dewiktionary]> EXPLAIN SELECT * FROM page WHERE
page_is_redirect = 1 ORDER BY page_namespace, page_len DESCG
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: page
type: ref
possible_keys:
page_redirect_namespace_len,page_redirect_namespace_len_DESC
key: page_redirect_namespace_len
key_len: 1
ref: const
rows: 2404
Extra: Using where
Filesort
avoided
Filesort
avoided

97
Index Condition Pushdown
MariaDB [dewiktionary]> ALTER TABLE revision ADD INDEX
rev_len_rev_timestamp(rev_len, rev_timestamp);
MariaDB [dewiktionary]> SET optimizer_switch='index_condition_pushdown=on'; EXPLAIN
SELECT * FROM revision WHERE rev_timestamp < '2008' AND rev_len > 10000G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: range
possible_keys: rev_timestamp,rev_timestamp_rev_page,rev_len_rev_timestamp
key: rev_len_rev_timestamp
key_len: 5
ref: NULL
rows: 180270
Index condition pushdown
(ICP) enables the engines to
use extra parts of the index
while avoiding costly row
movements to and from the
SQL layer
Index condition pushdown
(ICP) enables the engines to
use extra parts of the index
while avoiding costly row
movements to and from the
SQL layer

98
ICP optimizations
●
Differences in execution time are more significant
when the extra column condition is very selective
(getting 5x the original performance)
●
ICP is ignored when using covering Index,
potentially making the performance worse

99
Use of "Handler_*" statistics
• They are post-execution statistics at row level
– Unlike EXPLAIN's "rows" column, they are exact, not a
guess
– They allow comparison of query execution
performance in a deterministic way, independently of
the execution time

100
"Handler" Stats (indexed)
mysql> SHOW SESSION STATUS like 'Hand%';
+----------------------------+----------+
| Variable_name | Value |
+----------------------------+----------+
| Handler_commit | 80 |
| Handler_delete | 0 |
| Handler_discover | 0 |
| Handler_external_lock | 166 |
| Handler_mrr_init | 0 |
| Handler_prepare | 0 |
| Handler_read_first | 23 |
| Handler_read_key | 736212 |
| Handler_read_last | 0 |
| Handler_read_next | 22208001 |
| Handler_read_prev | 0 |
| Handler_read_rnd | 665215 |
| Handler_read_rnd_next | 14223297 |
| Handler_rollback | 0 |
| Handler_savepoint | 0 |
| Handler_savepoint_rollback | 0 |
| Handler_update | 66970 |
| Handler_write | 2869409 |
+----------------------------+----------+
Number of times that the first entry
of an index was read. It may indicate
the number of full index scans
Number of times that the first entry
of an index was read. It may indicate
the number of full index scans
Number of times a row
has been retrieved
using an index
Number of times a row
has been retrieved
using an index
Next row has been requested
in index order (typical for
index scans or ranges)
Next row has been requested
in index order (typical for
index scans or ranges)

101
"Handler" Stats (unindexed)
mysql> SHOW SESSION STATUS like 'Hand%';
+----------------------------+----------+
+----------------------------+----------+
+----------------------------+----------+
A row has been requested in a
specific position (typical for joins
or order by without indexes)
A row has been requested in a
specific position (typical for joins
or order by without indexes)
Request to read the
next row in “table
order” (typical for full
table scans)
Request to read the
next row in “table
order” (typical for full
table scans)
Insertions in SELECTS may
indicate temporary tables
Insertions in SELECTS may
indicate temporary tables

102
Comparing statistics of the
previous indexes (no indexes)MariaDB [dewiktionary]> FLUSH STATUS;
MariaDB [dewiktionary]> SELECT * FROM revision IGNORE INDEX(rev_page, rev_timestamp, rev_page_rev_timestamp,
rev_timestamp_rev_page) WHERE rev_page = 31579 and rev_timestamp < '2008';
MariaDB [dewiktionary]> SHOW STATUS like 'Hand%';
+----------------------------+---------+
+----------------------------+---------+
…
| Handler_read_rnd_deleted | 0 |
…
+----------------------------+---------+
Typical result for a
full table scan
Typical result for a
full table scan

103
Index on (rev_page)
+----------------------------+-------+
+----------------------------+-------+
…
…
+----------------------------+-------+
Then, scan them one by one in
index order
index order
Using the index, request the
first row with rev_page=31579
Using the index, request the
first row with rev_page=31579

104
Index on (rev_timestamp)
+----------------------------+---------+
+----------------------------+---------+
…
…
+----------------------------+---------+
index order (more are matched)
index order (more are matched)
Using the index, request the first
row where rev_timestamp<2008
Using the index, request the first
row where rev_timestamp<2008
ICP will be explained later,
let's ignore it for now
ICP will be explained later,
let's ignore it for now

105
Index on (rev_page,
rev_timestamp)MariaDB [dewiktionary]> SHOW STATUS like 'Hand%';
+----------------------------+-------+
+----------------------------+-------+
…
…
+----------------------------+-------+
Rows scanned == Rows returnedRows scanned == Rows returned
With both conditions covered, we
can find the actual first row that
matches the condition using the
index
With both conditions covered, we
can find the actual first row that
matches the condition using the
index

106
Index on (rev_timestamp,
rev_page), no ICPMariaDB [dewiktionary]> SHOW STATUS like 'Hand%';
+----------------------------+---------+
+----------------------------+---------+
…
…
+----------------------------+---------+
Assuming no ICP, exact same
results as with (rev_timestamp).
The extra column does not help.
Also, EXPLAIN's row count was
very off.
Assuming no ICP, exact same
results as with (rev_timestamp).
The extra column does not help.
Also, EXPLAIN's row count was
very off.

107
Index on (rev_timestamp,
rev_page), with ICPMariaDB [dewiktionary]> SHOW STATUS like 'Hand%';
+----------------------------+--------+
+----------------------------+--------+
…
| Handler_icp_attempts | 452539 |
| Handler_icp_match | 530 |
…
…
+----------------------------+--------+
ICP reduces the number of
‘ENGINE API calls’ significantly,
although making it work more
internally
ICP reduces the number of
‘ENGINE API calls’ significantly,
although making it work more
internally

108
Redundant Indexes
●
Creating all 4 previous indexes in production is
not a great idea
– "Left-most index prefix" allows, for example
(rev_page, rev_timestamp) doing everything
you can do with (rev_page)
– If two indexes have equal selectivity, MySQL
chooses the shortest one

109
"Left-most index" Example
INDEX(rev_page_rev_timestamp) WHERE rev_page = 31579G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: ref
possible_keys: rev_page_rev_timestamp
key_len: 4
ref: const
rows: 4038
Extra:
Only the first column is usedOnly the first column is used

110
Duplicate Indexes
●
It is very easy to create indexes with the same
exact definition (same columns and ordering)
– Set a convention for index naming (e.g
tablename_column1_column2_idx) – MySQL does
not allow 2 indexes with the same identifier
– Since MySQL 5.6, an warning is thrown if a
duplicate index is created:
Duplicate index 'page_random2' defined on the table
'dewiktionary.page'. This is deprecated and will be disallowed
in a future release.
Still a warning on 8.0Still a warning on 8.0

111
pt-duplicate-index-checker
$ pt-duplicate-key-checker h=localhost,u=root,D=dewiktionary
[…]
# rev_timestamp is a left-prefix of rev_timestamp_rev_page
# Key definitions:
# KEY `rev_timestamp` (`rev_timestamp`),
# KEY `rev_timestamp_rev_page` (`rev_timestamp`,`rev_page`)
# Column types:
# `rev_timestamp` binary(14) not null default '00000000000000'
# `rev_page` int(10) unsigned not null
# To remove this duplicate index, execute:
ALTER TABLE `dewiktionary`.`revision` DROP INDEX `rev_timestamp`;
# rev_page is a left-prefix of rev_page_rev_timestamp
# Key definitions:
# KEY `rev_page` (`rev_page`),
# KEY `rev_page_rev_timestamp` (`rev_page`,`rev_timestamp`),
# Column types:
# `rev_page` int(10) unsigned not null
# `rev_timestamp` binary(14) not null default '00000000000000'
# To remove this duplicate index, execute:
ALTER TABLE `dewiktionary`.`revision` DROP INDEX `rev_page`;
# ############################################# Summary of indexes ########################################
# Size Duplicate Indexes 47836942
# Total Duplicate Indexes 4
# Total Indexes 285
Simple tool to check
redundant and
duplicate indexes
Simple tool to check
redundant and
duplicate indexes

112
Invisible Indexes (new in 8.0)
●
Before removing a (believed) redundant or
duplicate index, make it “invisible” to
prevent long-running outages:
mysql-8.0 [dewiktionary]> ALTER TABLE page ALTER INDEX
page_len INVISIBLE;
mysql-8.0 [dewiktionary]> SELECT * FROM page FORCE
INDEX(page_len);
ERROR 1176 (42000): Key 'page_len' doesn't exist in table
'page'

113
"OR"-style conditions over the
same column
rev_page = 790 OR rev_page = 795 OR rev_page = 1024G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: range
possible_keys: rev_page,rev_page_rev_timestamp
key: rev_page
key_len: 4
ref: NULL
rows: 201
Equivalent to:
SELECT * FROM revision WHERE
rev_page IN (790, 795, 1024)
Equivalent to:
SELECT * FROM revision WHERE
rev_page IN (790, 795, 1024)

114
Handlers on "IN" / "OR"
conditions over the same column+----------------------------+-------+
+----------------------------+-------+
…
…
+----------------------------+-------+
Despite identifying themselves
as “range”s, the execution is
slightly different, one index dive
(similar to a ref) is done per
value. This can be an issue in
conditions with thousands of
items.
Despite identifying themselves
as “range”s, the execution is
slightly different, one index dive
(similar to a ref) is done per
value. This can be an issue in
conditions with thousands of
items.

115
"OR"-style conditions over
different columns
●
We cannot use a single index efficiently for
both conditions
– We can scan both conditions separately
and mix the results, discarding duplicates
– Or use an index for one condition and not
for the other
– Index merge allows the use of two indexes
for a single table access simultaneously

116
Index Merge Example
rev_page = 790 or rev_timestamp < '2004'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: index_merge
possible_keys: rev_page,rev_timestamp,rev_page_rev_timestamp,
rev_timestamp_rev_page
key: rev_page,rev_timestamp
key_len: 4,14
ref: NULL
rows: 190
Extra: Using sort_union(rev_page,rev_timestamp); Using
where
Both indexes are used, then
combined using the "union"
operation
Both indexes are used, then
combined using the "union"
operation

117
INDEX_MERGE Issues
●
Sometimes it is faster to to execute the
sentence using UNION:
– This is especially true with (UNION ALL)
since MySQL 5.7, if you do not care or
expect duplicates
●
There are also intersection merges, but
multi-column indexes are preferred

118
Disabling optimizer features (I)
●
The optimizer_switch variable allows enabling and
disabling globally or per session many query
optimizer features:
MariaDB [nlwiktionary]> SHOW VARIABLES like 'optimizer_switch'G
*************************** 1. row ***************************
Variable_name: optimizer_switch
Value:
index_merge=on,index_merge_union=on,index_merge_sort_union=on,index_merge_intersection=
on,index_merge_sort_intersection=off,engine_condition_pushdown=off,index_condition_push
down=on,derived_merge=on,derived_with_keys=on,firstmatch=on,loosescan=on,materializatio
n=on,in_to_exists=on,semijoin=on,partial_match_rowid_merge=on,partial_match_table_scan=
on,subquery_cache=on,mrr=off,mrr_cost_based=off,mrr_sort_keys=off,outer_join_with_cache
=on,semijoin_with_cache=on,join_cache_incremental=on,join_cache_hashed=on,join_cache_bk
a=on,optimize_join_buffer_size=off,table_elimination=on,extended_keys=on,exists_to_in=o
n,orderby_uses_equalities=on,condition_pushdown_for_derived=on,split_materialized=on

119
Disabling optimizer features (II)
MariaDB [dewiktionary]> SET optimizer_switch='index_merge_sort_union=off';
790 or rev_timestamp < '2004'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: ALL
possible_keys:
rev_page,rev_timestamp,rev_page_rev_timestamp,rev_timestamp_rev_page
key: NULL
key_len: NULL
ref: NULL
rows: 1376651
Extra: Using where
This will only have effect for
the current session.
This will only have effect for
the current session.

120
What happens if we have two
ranges?
●
As seen previously, we cannot use efficiently two
range types on the same table access. Alternatives:
– Use only one index for the most selective column
– Use index condition pushdown to get an
advantage
– Change one of the two ranges into a discrete "IN"
comparison/bucketize with a new column
– Use quadtrees or R-TREEs (spatial indexing)

121
Example of Bucketizing (I)
MariaDB [dewiktionary]> ALTER TABLE revision DROP INDEX
rev_len_rev_timestamp;
MariaDB [dewiktionary]> EXPLAIN SELECT count(*) FROM revision
WHERE rev_timestamp < '2008' AND rev_len > 5500G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: ALL
possible_keys: rev_timestamp,rev_timestamp_rev_page
key: NULL
key_len: NULL
ref: NULL
rows: 1376651
Extra: Using where
Looks like only an index on
(rev_timestamp) or (rev_len)
would be useful as we have 2
ranges.
Looks like only an index on
(rev_timestamp) or (rev_len)
would be useful as we have 2
ranges.

122
Example of Bucketizing (II)
MariaDB [dewiktionary]> ALTER TABLE revision ADD COLUMN
rev_len_cat int;
MariaDB [dewiktionary]> UPDATE revision set rev_len_cat =
IF(rev_len < 10000, rev_len div 1000, 10);
Rows matched: 1430042 Changed: 1430042 Warnings: 0
MariaDB [dewiktionary]> ALTER TABLE revision ADD INDEX
rev_len_cat_rev_timestamp (rev_len_cat, rev_timestamp);
8.0/10.3
instant
alter-nice!
8.0/10.3
instant
alter-nice!

123
Example of Bucketizing (III)
MariaDB [dewiktionary]> EXPLAIN SELECT count(*) FROM revision WHERE
rev_timestamp < '2008' AND rev_len > 5500 AND rev_len_cat IN (5, 6,
7, 8, 9, 10)G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: range
possible_keys:
rev_timestamp,rev_timestamp_rev_page,rev_len_cat_rev_timestamp
key: rev_len_cat_rev_timestamp
key_len: 19
ref: NULL
rows: 77601
Extra: Using where
We did some transformations
to both the structure and the
query.
query.

124
Even better: Functional Indexes
(I)
MariaDB [dewiktionary]> ALTER TABLE revision
DROP INDEX rev_len_cat_rev_timestamp,
DROP COLUMN rev_len_cat,
ADD COLUMN rev_len_cat_virtual int as (IF(rev_len < 10000,
rev_len div 1000, 10)) VIRTUAL,
ADD INDEX rev_len_cat_virtual_rev_timestamp
(rev_len_cat_virtual, rev_timestamp);
Query OK, 1430042 rows affected (1 min 42.35 sec)
Storing the extra content
may be a waste of resources,
lets make it a virtual column
Storing the extra content
may be a waste of resources,
lets make it a virtual column
Indexing
virtual
columns,
new in 10.3
Indexing
virtual
columns,
new in 10.3

125
Even better: Functional Indexes
(II)
MariaDB [dewiktionary]> EXPLAIN SELECT count(*) FROM revision WHERE
rev_timestamp < '2008' AND rev_len > 5500 AND rev_len_cat_virtual IN
(5, 6, 7, 8, 9, 10)G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: revision
type: range
possible_keys:
rev_timestamp,rev_timestamp_rev_page,rev_len_cat_virtual_rev_timestamp
key: rev_len_cat_virtual_rev_timestamp
key_len: 19
ref: NULL
rows: 78649
Extra: Using where
query.
query.

126
MyISAM Internals
node_id versio k v
(empty row)
234234344548 5 gps:latitude 490018321N
(empty row)
234234344551 9 name Big Ben
CarlsbergCarlsberg
recyclingrecycling
Accurate as
of 2010
Accurate as
of 2010
Gwynne
Place
Gwynne
Place
treetree
490018321N490018321N
deciduousdeciduous
surveysurvey
Big BenBig Ben
JOSMJOSM
London
Borough of
Southwark
London
Borough of
Southwark
Data (revision.MYD)Index (part of revision.MYI)

127
InnoDB Internals (PRIMARY)
Data
clustered
always
using the
primary
key
Data
clustered
always
using the
primary
key
244
208
105
476
356
702
605
811
771
702
476
244
version k v
1 leaves deciduous
3 name Northolt Road
5 gps:latitu 490018321N
6 access uncontrolled
1 editor JOSM
9 name Big Ben
2 source survey
1 name London Plane
7 amenity pub

128
InnoDB Internals (Secondary)
6
3
1
1
1
1
3
2
6
5
9
7
PK
356
105
702
811
476
208
Secondary
indexes
contain the
primary key
value
Secondary
indexes
contain the
primary key
value
PK / DataIndex
(version)
244
208
105
476
356
702
605
811
771
702
476
244
version k v
1 leaves deciduous
3 name Northolt Road
5 gps:latitu 490018321N
6 access uncontrolled
1 editor JOSM
9 name Big Ben
2 source survey
1 name London Plane
7 amenity pub
605
244
771

129
Consequences of using InnoDB (I)
●
Every table should have a primary key
– If one is not defined, MySQL will choose an
available NOT NULL unique key
– If that is not possible, an internal 6-byte row
identifier will be generated (not user-accesible)

130
Consequences of using
InnoDB (II)
●
Inserting in primary key order is much faster
– Less fragmentation/page-split
– Usage of "batch" mode, improving insert speed
●
Using auto-increment keys as primary keys can be
a good idea for InnoDB

131
Consequences of using
InnoDB (III)
• A very long primary key may increment
substantially the size of secondary keys
– Int or bigint types are recommended instead of UUIDs
or other long strings

132
Differences in size
mysql (osm) > CREATE TABLE
pk_int (id int PRIMARY KEY
auto_increment,
a int,
b int,
c int,
d int);
Query OK, 0 rows affected
(0.16 sec)
mysql (osm) > CREATE TABLE
pk_uuid (id char(36)
PRIMARY KEY,
a int,
b int,
c int,
d int);
Query OK, 0 rows affected
(0.04 sec)
pk_int pk_uuid
0
8500000
17000000
25500000
34000000
42500000
12,582,912
20,971,520
13,631,488
32,505,856
.ibd size (no secondary indexes) .ibd size (with secondary indexes)
bytes

133
Extended primary key
optimization
●
As the primary key is part of all secondary keys,
this can be used “for free”:
– For row filtering (since MySQL 5.6)
– To return results in primary key order
– To avoid reading data from the table (covering
index)

134
Extended Primary Key Example
mysql (osm) > EXPLAIN SELECT node_id FROM nodes WHERE
changeset_id = 24284 and node_id <> 146472942G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: nodes
type: range
possible_keys: PRIMARY,changeset_id_idx
key: changeset_id_idx
key_len: 16
ref: NULL
rows: 50
Extra: Using where; Using index

135
JOINS
10.3: The Basics

136
(Block) Nested Loop Join
●
Until MySQL 5.5 there was only one algorithm to
execute a JOIN:
node_id version lat lon
1 1 52 0.5
1 2 52 0.5
2 1 51 1
3 1 53 1.5
node_id version k v
1 1 name Big Benn
1 1 tourism attraction
1 2 name Big Ben
3 1 name London Eye

137
Extra Access type: eq_ref
mysql (osm) > EXPLAIN SELECT * FROM nodes JOIN node_tags
USING(node_id, version) WHERE node_tags.v= 'Big Ben'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: node_tags
type: ref
possible_keys: PRIMARY,v_idx
key: v_idx
key_len: 767
ref: const
rows: 1
*************************** 2. row ***************************
id: 1
select_type: SIMPLE
table: nodes
type: eq_ref
possible_keys: PRIMARY,version_idx
key: PRIMARY
key_len: 16
ref: osm.node_tags.node_id,osm.node_tags.version
rows: 1
Extra: NULL
eq_ref is similar to ref, but
allows faster JOINS
because, by using a unique
key, it only has to search
one row for each previous
result
eq_ref is similar to ref, but
allows faster JOINS
because, by using a unique
key, it only has to search
one row for each previous
result

138
JOIN Optimization
●
Two main goals:
– Perform an effective filtering on each table
access, if possible using indexes
– Perform the access in the most efficient table
order
●
When joining 3 or more tables in a star schema,
the "covering index" strategy can have a huge
impact

139
Example: optimize this JOIN (I)
SELECT n.node_id, n.latitude, n.longitude
FROM way_nodes w_n
JOIN way_tags w_t
ON w_n.way_id = w_t.way_id and
w_n.version = w_t.version
JOIN nodes n
ON w_n.node_id = n.node_id
JOIN node_tags n_t
ON n.node_id = n_t.node_id and
n.version = n_t.version
WHERE w_t.k = 'building' and
n_t.k = 'entrance' and
n_t.v = 'main';
We start without
secondary indexes
We start without
secondary indexes

140
Example: optimize this JOIN (II)
************************ 1. row ************************
id: 1
select_type: SIMPLE
table: w_t
type: index
key: PRIMARY
key_len: 783
ref: NULL
rows: 1335702
************************ 2. row ************************
id: 1
select_type: SIMPLE
table: w_n
type: ref
key: PRIMARY
key_len: 16
ref: osm.w_t.way_id,osm.w_t.version
rows: 3
Extra: NULL
mysql (osm) > SELECT …
************************ 3. row ************************
id: 1
select_type: SIMPLE
table: n_t
type: ref
key: PRIMARY
key_len: 8
ref: osm.w_n.node_id
rows: 1
Extra: Using where
************************ 4. row ************************
id: 1
select_type: SIMPLE
table: n
type: eq_ref
key: PRIMARY
key_len: 16
ref: osm.w_n.node_id,osm.n_t.version
rows: 1
Extra: Using index

141
Example: optimize this JOIN (III)
mysql (osm) > ALTER TABLE way_tags
ADD INDEX k_idx(k);
Creating an index
on way_tags.k
Creating an index
on way_tags.k

142
Example: optimize this JOIN (IV)
********************** 1. row **********************
id: 1
select_type: SIMPLE
table: w_t
type: ref
possible_keys: PRIMARY,k_idx
key: k_idx
key_len: 767
ref: const
rows: 452274
********************** 2. row **********************
id: 1
select_type: SIMPLE
table: w_n
type: ref
key: PRIMARY
key_len: 16
rows: 3
Extra: NULL
It seems like the index
is not very useful
It seems like the index
is not very useful
********************** 3. row **********************
id: 1
select_type: SIMPLE
table: n_t
type: ref
key: PRIMARY
key_len: 8
rows: 1
Extra: Using where
********************** 4. row **********************
id: 1
select_type: SIMPLE
table: n
type: eq_ref
key: PRIMARY
key_len: 16
rows: 1
Extra: NULL

143
Example: optimize this JOIN (V)
mysql (osm) > ALTER TABLE node_tags
ADD INDEX k_idx(k);
The order does not seem
to be adequate, let's try
adding an index to start
by accessing node_tags
The order does not seem
to be adequate, let's try
adding an index to start
by accessing node_tags

144
Example: optimize this JOIN (VI)
********************** 1. row **********************
id: 1
select_type: SIMPLE
table: w_t
type: ref
key: k_idx
key_len: 767
ref: const
rows: 452274
********************** 2. row **********************
id: 1
select_type: SIMPLE
table: w_n
type: ref
key: PRIMARY
key_len: 16
rows: 3
Extra: NULL
********************** 3. row **********************
id: 1
select_type: SIMPLE
table: n_t
type: ref
key: PRIMARY
key_len: 8
rows: 1
Extra: Using where
********************** 4. row **********************
id: 1
select_type: SIMPLE
table: n
type: eq_ref
key: PRIMARY
key_len: 16
rows: 1
Extra: NULL
It keeps using
the wrong
order, even if
we delete the
w_t.k_idx
index
It keeps using
the wrong
order, even if
we delete the
w_t.k_idx
index

145
Example: optimize this JOIN (VII)
SELECT STRAIGHT_JOIN n.node_id, n.latitude, n.longitude
FROM node_tags n_t
JOIN nodes n
ON n.node_id = n_t.node_id and
n.version = n_t.version
JOIN way_nodes w_n
ON w_n.node_id = n.node_id
JOIN way_tags w_t
ON w_n.way_id = w_t.way_id and
w_n.version = w_t.version
WHERE w_t.k = 'building' and
n_t.k = 'entrance' and
n_t.v = 'main';
Let's see why rewriting it
into this query
Let's see why rewriting it
into this query

146
Example: optimize this JOIN (VIII)
********************** 1. row **********************
id: 1
select_type: SIMPLE
table: n_t
type: ref
key: k_idx
key_len: 767
ref: const
rows: 2390
********************** 2. row **********************
id: 1
select_type: SIMPLE
table: n
type: eq_ref
key: PRIMARY
key_len: 16
ref: osm.n_t.node_id,osm.n_t.version
rows: 1
Extra: NULL
There is no index
on w_n that would
allow efficient
access
There is no index
on w_n that would
allow efficient
access
********************** 3. row **********************
id: 1
select_type: SIMPLE
table: w_n
type: ALL
key: NULL
key_len: NULL
ref: NULL
rows: 3597858
Extra: Using where; Using join buffer (Block
Nested Loop)
********************** 4. row **********************
id: 1
select_type: SIMPLE
table: w_t
type: eq_ref
key: PRIMARY
key_len: 783
ref: osm.w_n.way_id,osm.w_n.version,const
rows: 1

147
Example: optimize this JOIN (IX)
mysql (osm) > ALTER TABLE way_nodes
ADD INDEX node_id_idx(node_id);

148
Example: optimize this JOIN (X)
********************** 1. row **********************
id: 1
select_type: SIMPLE
table: n_t
type: ref
key: k_idx
key_len: 767
ref: const
rows: 2390
********************** 2. row **********************
id: 1
select_type: SIMPLE
table: n
type: eq_ref
key: PRIMARY
key_len: 16
rows: 1
Extra: NULL
Now it starts with
the right table
(without
STRAIGHT_JOIN)
Now it starts with
the right table
(without
STRAIGHT_JOIN)
********************** 3. row **********************
id: 1
select_type: SIMPLE
table: w_n
type: ref
possible_keys: PRIMARY,node_id_idx
key: node_id_idx
key_len: 8
ref: osm.n_t.node_id
rows: 1
Extra: Using index
********************** 4. row **********************
id: 1
select_type: SIMPLE
table: w_t
type: eq_ref
key: PRIMARY
key_len: 783
rows: 1

149
Example: optimize this JOIN (XI)
************************* 1. row *************************
id: 1
select_type: SIMPLE
table: n_t
type: ref
possible_keys: PRIMARY,k_idx,k_v_idx
key: k_v_idx
key_len: 1534
ref: const,const
rows: 900
************************* 2. row *************************
id: 1
select_type: SIMPLE
table: n
type: eq_ref
key: PRIMARY
key_len: 16
rows: 1
Extra: NULL
mysql (osm) > SELECT ...
An index on (k,v) is
even better
An index on (k,v) is
even better
************************ 3. row ************************
id: 1
select_type: SIMPLE
table: w_n
type: ref
possible_keys: PRIMARY,node_id_idx
key: node_id_idx
key_len: 8
ref: osm.n_t.node_id
rows: 1
Extra: Using index
************************ 4. row ************************
id: 1
select_type: SIMPLE
table: w_t
type: eq_ref
key: PRIMARY
key_len: 783
rows: 1

150
“New” JOIN methods
●
MySQL 5.6 added:
– Batch Key Access
●
MariaDB has since 5.3:
– Batch Key Access
– Hash Joins
– Slightly modified versions of the above ones
(with “incremental” buffers to join 3 or more
tables)

151
Multi-range read
• This optimization orders results obtained
from a secondary key in primary key/physical
order before accessing the rows
– It may help execution time of queries when disk-bound
– It requires tuning of the read_rnd_buffer_size (size of
the buffer used for ordering the results)
• BKA JOINs are based on the mrr optimization

152
MRR Example (I)
mysql (osm) > EXPLAIN SELECT * FROM nodes WHERE timestamp >= '2013-07-
01 00:00:00' AND timestamp < '2014-01-01 00:00:00'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: nodes
type: range
possible_keys: nodes_timestamp_idx
key: nodes_timestamp_idx
key_len: 5
ref: NULL
rows: 429684
Extra: Using index condition; Using MRR

153
MRR example (II)
[restart]
mysql> SET optimizer_switch='mrr=off';
mysql> SELECT * FROM nodes WHERE timestamp >= '2013-07-01 00:00:00' AND timestamp <
'2014-01-01 00:00:00';
'2014-01-01 00:00:00';
[restart]
mysql> SET read_rnd_buffer_size=50 * 1024 * 1024;
'2014-01-01 00:00:00';
'2014-01-01 00:00:00';
“Cold” results are
significantly better with
mrr (but it can impact
negatively, too)
“Cold” results are
significantly better with
mrr (but it can impact
negatively, too)

154
Batch Key Access
1 1 52 0.5
1 2 52 0.5
2 1 51 1
3 1 53 1.5
node_id version k v
1 1 name Big Benn
1 2 name Big Ben
3 1 amenity cafe
Buffer
sorted in
physical/PK
order

155
Hash Joins
• Only work for equi-joins
1 1 52 0.5
1 2 52 0.5
2 1 51 1
3 1 53 1.5
node_id version k v
1 1 name Big Benn
1 2 name Big Ben
3 1 amenity cafe
Hash table
for faster
access to
rows

156
MySQL Configuration
• BKA requires changes of default optimizer
configuration:
mysql-8.0 (osm) > SET optimizer_switch= 'mrr=on';
mysql-8.0 (osm) > SET optimizer_switch= 'mrr_cost_based=off';
mysql-8.0 (osm) > SET optimizer_switch= 'batch_key_access=on';
– Additionally, configuring the join_buffer_size adequately

157
MariaDB configuration
mariadb-10.3 (osm) > SET optimizer_switch = 'join_cache_incremental=on';
mariadb-10.3 (osm) > SET optimizer_switch = 'join_cache_hashed=on';
mariadb-10.3 (osm) > SET optimizer_switch = 'join_cache_bka=on';
- Enabled by default
mariadb-10.3 (osm) > SET join_cache_level = 3 (for hash joins)
mariadb-10.3 (osm) > SET join_cache_level = 5 (for BKA)
- Also, configure join_buffer_size appropriately.
- Hash joins, like BKA, are highly dependent on disk-bound DBs to be
effective due to the extra overhead

158
Nested Loop Join (cold buffers
buffer_pool=100MB, join_buffer=4M)
mariadb-10.3 (osm) > EXPLAIN SELECT changeset_id,
count(*) FROM changesets JOIN nodes on
changesets.id = nodes.changeset_id GROUP BY
visibleG
******************** 1. row ********************
id: 1
select_type: SIMPLE
table: changesets
type: index
key: PRIMARY
key_len: 8
ref: NULL
rows: 69115
Extra: Using index; Using temporary; Using
filesort
******************** 2. row ********************
id: 1
select_type: SIMPLE
table: nodes
type: ref
possible_keys: changeset_id
key: changeset_id
key_len: 8
ref: osm.changesets.id
rows: 19
Extra:
mariadb-10.3 (osm) > SELECT visible, count(*) FROM
changesets JOIN nodes on changesets.id =
nodes.changeset_id GROUP BY visible;
+---------+----------+
| visible | count(*) |
+---------+----------+
| 1 | 2865312 |
+---------+----------+

159
Hash Join (cold buffers,
buffer_pool=100M, join_buffer=4M)
mariadb-10.3 (osm) > EXPLAIN SELECT
changeset_id, count(*) FROM changesets JOIN
nodes on changesets.id = nodes.changeset_id
GROUP BY visibleG
******************* 1. row *******************
id: 1
select_type: SIMPLE
table: changesets
type: index
key: PRIMARY
key_len: 8
ref: NULL
rows: 69115
Extra: Using index; Using temporary;
Using filesort
******************** 2. row ********************
id: 1
select_type: SIMPLE
table: nodes
type: hash_ALL
key: #hash#changeset_id
key_len: 8
rows: 2781732
Extra: Using join buffer (flat, BNLH join)
mariadb-10.3 (osm) > SELECT visible, count(*) FROM
changesets JOIN nodes on changesets.id =
nodes.changeset_id GROUP BY visible;
+---------+----------+
| visible | count(*) |
+---------+----------+
| 1 | 2865312 |
+---------+----------+

160
SUBQUERIES
10.3: The Basics

161
Access types:
unique_subquery/index_subquery
mysql-8.0 (osm) > EXPLAIN SELECT *
FROM node_tags WHERE v = 'Big Ben'
and node_id NOT IN (SELECT node_id
FROM nodes WHERE tile < 100000000)G
************** 1. row **************
id: 1
select_type: PRIMARY
table: node_tags
type: ref
possible_keys: v_idx
key: v_idx
key_len: 767
ref: const
rows: 1
Extra: Using where; Using
index
Unique
subquery
is similar,
but using a
unique or
primary
key
Unique
subquery
is similar,
but using a
unique or
primary
key
************** 2. row **************
id: 2
select_type: DEPENDENT SUBQUERY
table: nodes
type: index_subquery
possible_keys: PRIMARY,nodes_tile_idx
key: PRIMARY
key_len: 8
ref: func
rows: 1
Extra: Using where

162
Subqueries in MySQL
●
MySQL versions traditionally had very bad press
regarding subquries
– It was common to recommend rewriting them
(when possible) into JOINS
●
Since MySQL 5.6, its query execution plans have
improved significantly

163
Lazy Materialization of derived
tables
●
Option available since MySQL 5.6
– Improves the execution time of EXPLAIN (it no
longer needs to execute subqueries)
– Derived tables can be indexed automatically at
execution time to improve its performance

165
A Common 5.5 Performance
Problemmysql-5.5.40 (osm) > EXPLAIN SELECT * FROM nodes
WHERE nodes.changeset_id IN (
SELECT changesets.id
FROM changesets
JOIN users
ON changesets.user_id = users.id and users.display_name = 'Steve');
+----+--------------------+------------+--------+--------------------------------+------------------------+---------+-------+---------+-------------+
+----+--------------------+------------+--------+--------------------------------+------------------------+---------+-------+---------+-------------+
| 1 | PRIMARY | nodes | ALL | NULL | NULL | NULL | NULL | 2865521 | Using where |
| 2 | DEPENDENT SUBQUERY | users | const | PRIMARY,users_display_name_idx | users_display_name_idx | 767 | const | 1 | Using index |
| 2 | DEPENDENT SUBQUERY | changesets | eq_ref | PRIMARY | PRIMARY | 8 | func | 1 | Using where |
+----+--------------------+------------+--------+--------------------------------+------------------------+---------+-------+---------+-------------+
mysql-5.5.40 (osm) > SELECT ...;
+-----------+-----------+-----------+--------------+---------+---------------------+------------+---------+
| node_id | latitude | longitude | changeset_id | visible | timestamp | tile | version |
+-----------+-----------+-----------+--------------+---------+---------------------+------------+---------+
| 99890 | 515276425 | -1497621 | 552 | 1 | 2005-10-25 00:35:24 | 2062268512 | 1 |
| 109174 | 515364532 | -1457329 | 1875 | 1 | 2006-01-20 00:01:27 | 2062268519 | 1 |
| 276538 | 515324296 | -2094688 | 810 | 1 | 2005-11-25 21:42:53 | 2062267078 | 1 |
| 442987 | 515449207 | -1275650 | 1941 | 1 | 2006-01-22 23:50:28 | 2062268628 | 1 |
| 442988 | 515449741 | -1272860 | 1941 | 1 | 2006-01-22 23:50:29 | 2062268628 | 1 |
| 498803 | 515438432 | -1269436 | 2171 | 1 | 2006-02-03 21:55:17 | 2062268628 | 1 |
| 138212838 | 513010180 | -1699929 | 7757299 | 1 | 2011-04-03 18:14:14 | 2062220563 | 6 |
+-----------+-----------+-----------+--------------+---------+---------------------+------------+---------+
This means that
the subquery is
executed almost
3 million times
This means that
the subquery is
executed almost
3 million times

166
Semijoin Optimization
●
The only way to execute certain IN subqueries was to
execute them with poor strategy
– This forced rewriting of certain queries into JOINS or scalar subqueries,
when possible
●
There are now several additional options (many
automatic):
– Convert to a JOIN
– Materialization (including index creation)
– FirstMatch
– LooseScan
– Duplicate Weedout

167
The Previous Query is Not a Problem
in 5.6+/MariaDB 5.3+
mysql-8.0 (osm) > EXPLAIN SELECT * FROM nodes
WHERE nodes.changeset_id IN (
SELECT changesets.id
FROM change sets
JOIN users
ON changesets.user_id = users.id and users.display_name = 'Steve');
+----+-------------+------------+-------+--------------------------------+------------------------+---------+-------------------+-------+-------------+
+----+-------------+------------+-------+--------------------------------+------------------------+---------+-------------------+-------+-------------+
| 1 | SIMPLE | users | const | PRIMARY,users_display_name_idx | users_display_name_idx | 767 | const | 1 | Using index |
| 1 | SIMPLE | changesets | ALL | PRIMARY | NULL | NULL | NULL | 70917 | Using where |
| 1 | SIMPLE | nodes | ref | changeset_id | changeset_id | 8 | osm.changesets.id | 21 | NULL |
+----+-------------+------------+-------+--------------------------------+------------------------+---------+-------------------+-------+-------------+
mysql-8.0 (osm) > SELECT ...;
+-----------+-----------+-----------+--------------+---------+---------------------+------------+---------+
| node_id | latitude | longitude | changeset_id | visible | timestamp | tile | version |
+-----------+-----------+-----------+--------------+---------+---------------------+------------+---------+
| 99890 | 515276425 | -1497621 | 552 | 1 | 2005-10-25 00:35:24 | 2062268512 | 1 |
...
| 138212838 | 513010180 | -1699929 | 7757299 | 1 | 2011-04-03 18:14:14 | 2062220563 | 6 |
+-----------+-----------+-----------+--------------+---------+---------------------+------------+---------+
Executed as
a regular
JOIN
Executed as
a regular
JOIN

168
First Match Strategy
mysql-8.0 (osm) > EXPLAIN SELECT * FROM changesets WHERE id IN (SELECT changeset_id FROM nodes)G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: changesets
partitions: NULL
type: ALL
key: NULL
key_len: NULL
ref: NULL
rows: 70917
filtered: 100.00
Extra: NULL
*************************** 2. row ***************************
id: 1
select_type: SIMPLE
table: nodes
partitions: NULL
type: ref
key: changeset_id
key_len: 8
rows: 33
filtered: 100.00
Extra: Using index; FirstMatch(changesets)
It is converting
the ref into an
eq_ref, shot-
circuiting the
execution
It is converting
the ref into an
eq_ref, shot-
circuiting the
execution

169
Enabling and disabling
materialization, semijoin, etc
mysql-8.0 (osm) > SHOW VARIABLES like 'optimizer_switch'G
*************************** 1. row ***************************
Variable_name: optimizer_switch
Value:
index_merge=on,index_merge_union=on,index_merge_sort_union=on,index_merge_in
tersection=on,engine_condition_pushdown=on,index_condition_pushdown=on,mrr=o
n,mrr_cost_based=on,block_nested_loop=on,batched_key_access=off,materializat
ion=on,semijoin=on,loosescan=on,firstmatch=on,duplicateweedout=on,subquery_m
aterialization_cost_based=on,use_index_extensions=on,condition_fanout_filter
=on,derived_merge=on

170
FULLTEXT, GEODATA
SEARCH AND JSON SUPPORT
10.3: The Basics

171
Fuzzy Search of “hotel/Grand
Hotel/Hotel X/etc”
●
“Typical” way to solve this:
mysql (osm) >
SELECT way_id as id, v
FROM way_tags
WHERE v like '%otel%';
Too slowToo slow

172
Let’s Add an Index
mysql (osm) > ALTER TABLE way_tags ADD INDEX(v);
mysql (osm) > SELECT ...;
mysql (osm) > EXPLAIN SELECT way_id as id, v FROM way_tags
WHERE v like '%otel%';
+----+.+-------+---------------+------+---------+------+---------+----------+--------------------------+
| id |.| type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+.+-------+---------------+------+---------+------+---------+----------+--------------------------+
| 1 |.| index | NULL | v | 769 | NULL | 8964000 | 11.11 | Using where; Using index |
+----+.+-------+---------------+------+---------+------+---------+----------+--------------------------+
1 row in set, 1 warning (0.01 sec)
Still slow, why?Still slow, why?

173
Fulltext Index
mysql (osm) > ALTER TABLE way_tags add FULLTEXT index(v);
mysql (osm) > SELECT 'way' as type, way_id as id, v FROM
way_tags WHERE MATCH(v) AGAINST ('+hotel*' IN BOOLEAN MODE);
mysql (osm) > EXPLAIN …;
+----+.+----------+---------------+------+---------+-----+------+----------+-----------------------------------+
| id |.| type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+.+----------+---------------+------+---------+-----+------+----------+-----------------------------------+
| 1 |.| fulltext | v | v | 0 | | 1 | 100.00 | Using where; Ft_hints: no_ranking |
+----+.+----------+---------------+------+---------+-----+------+----------+-----------------------------------+
Some fields are
useless for FULTEXT
Some fields are
useless for FULTEXT

174
‘Newer’ Fulltext Optimizations
mysql-5.5 (osm) > EXPLAIN SELECT count(*) FROM way_tags_myisam WHERE MATCH(v) AGAINST('hotel');
+----+-------------+-----------------+----------+---------------+------+---------+------+------+-------------+
+----+-------------+-----------------+----------+---------------+------+---------+------+------+-------------+
| 1 | SIMPLE | way_tags_myisam | fulltext | v | v | 0 | | 1 | Using where |
+----+-------------+-----------------+----------+---------------+------+---------+------+------+-------------+
mysql-5.5 (osm) > SHOW STATUS like 'Hand%';
+----------------------------+-------+
+----------------------------+-------+
...
...
+----------------------------+-------+

176
Open Issues and Limitations
●
No postfix support (wildcards)
●
Simple Ranking (and different from MyISAM)
●
No stemming support
●
Some multi-language limitations
More on FULLTEXT InnoDB support:
http://www.drdobbs.com/database/full-text-search-with-innodb/231902587

177
Alternatives
●
Apache Lucene
– Solr
– Elasticsearch
●
Sphinx
– SphinxSE

178
Find the Closest Starbucks
(Spatial Search)mysql (osm) > SET @lat:=50.11745057; SET @lon:= 8.62699463;
mysql (osm) > SELECT n.node_id,
n.longitude/10000000 as longitude,
n.latitude/10000000 as latitude,
sqrt(pow((latitude/10000000 - @lat) * 111231.29, 2) +
pow((longitude/10000000 - @lon) * 71520.91, 2))
as `distance in metres`
FROM nodes n
JOIN node_tags n_t1
ON n.node_id = n_t1.node_id
JOIN node_tags n_t2
WHERE
n_t1.k = 'amenity' and
n_t1.v = 'cafe' and
n_t2.k = 'name' and
n_t2.v like 'Starbucks%'
ORDER BY `distance in metres` ASC
LIMIT 1;
+------------+-----------+----------+--------------------+
| node_id | longitude | latitude | distance in metres |
+------------+-----------+----------+--------------------+
| 3136353405 | 8.6523 | 50.1093 | 2023.6465372574328 |
+------------+-----------+----------+--------------------+
1 row in set, 36 warnings (0.81 sec)
You are hereYou are here

179
This Query is Slow
mysql [osm]> EXPLAIN SELECT ...G
**************** 1. row ***************
Id: 1
select_type: SIMPLE
table: n_t1
type: ALL
key: NULL
key_len: NULL
ref: NULL
rows: 2210950
Extra: Using where;
Using temporary; Using filesort
*********************** 2. row ***********************
id: 1
select_type: SIMPLE
table: n_t2
type: ref
key: PRIMARY
key_len: 8
ref: osm.n_t1.node_id
rows: 1
Extra: Using where
*********************** 3. row ***********************
id: 1
select_type: SIMPLE
table: n
type: ref
key: PRIMARY
key_len: 8
ref: osm.n_t1.node_id
rows: 1
Extra:

180
Can We Optimize it?
• We could add a bounding box:
mysql (osm) > ALTER TABLE nodes ADD INDEX (latitude, longitude);
mysql (osm) > SELECT n.node_id,
n.longitude/10000000 as longitude,
n.latitude/10000000 as latitude,
sqrt(pow((latitude/10000000 - @lat) * 111231.29, 2) +
pow((longitude/10000000 - @lon) * 71520.91, 2))
as `distance in metres`
FROM nodes n
JOIN node_tags n_t1
JOIN node_tags n_t2
WHERE
n_t1.v = 'cafe' and
n_t2.k = 'name' and
n_t2.v like 'Starbucks%' and
n.latitude BETWEEN ((@lat - 1000/111231.29) * 10000000)
AND ((@lat + 1000/111231.29) * 10000000) and
n.longitude BETWEEN ((@lon - 1000/71520.91) * 10000000)
AND ((@lon + 1000/71520.91) * 10000000)
ORDER BY `distance in metres` ASC
LIMIT 1;
This is not a
square, only an
approximation
This is not a
square, only an
approximation

181
We Create an Index… and Force It
mysql-8.0 (osm) > EXPLAIN SELECT ...;
+----+-------------+-------+------------+------+----------+---------+------+------------------+---------+----------+------------------+
| id | select_type | table | partitions | type | possible | key | key_ | ref | rows | filtered | Extra |
| | | | | | _keys | | len | | | | |
+----+-------------+-------+------------+------+----------+---------+------+------------------+---------+----------+------------------+
| 1 | SIMPLE | n_t1 | NULL | ALL | PRIMARY | NULL | NULL | NULL | 2210950 | 0.00 | Using where; |
| | | | | | | | | | | | Using temporary; |
| | | | | | | | | | | | Using filesort |
| 1 | SIMPLE | n | NULL | ref | PRIMARY, | PRIMARY | 8 | osm.n_t1.node_id | 1 | 5.00 | Using where |
| | | | | | latitude | | | | | | |
| 1 | SIMPLE | n_t2 | NULL | ref | PRIMARY | PRIMARY | 8 | osm.n_t1.node_id | 1 | 1.41 | Using where |
+----+-------------+-------+------------+------+----------+---------+------+------------------+---------+----------+------------------+
mysql-8.0 (osm) > EXPLAIN SELECT ... FROM nodes n FORCE INDEX(latitude) ...;
+----+-------------+-------+------------+-------+----------+----------+------+---------------+--------+----------+------------------+
| id | select_type | table | partitions | type | possible | key | key_ | ref | rows | filtered | Extra |
| | | | | | _keys | | len | | | | |
+----+-------------+-------+------------+-------+----------+----------+------+---------------+--------+----------+------------------+
| 1 | SIMPLE | n | NULL | range | latitude | latitude | 8 | NULL | 949370 | 11.11 | Using where; |
| | | | | | | | | | | | Using index; |
| | | | | | | | | | | | Using filesort |
| 1 | SIMPLE | n_t1 | NULL | ref | PRIMARY | PRIMARY | 8 | osm.n.node_id | 1 | 1.41 | Using where |
| 1 | SIMPLE | n_t2 | NULL | ref | PRIMARY | PRIMARY | 8 | osm.n.node_id | 1 | 1.41 | Using where |
+----+-------------+-------+------------+-------+----------+----------+------+---------------+--------+----------+------------------+
Mysql-8.0 (osm) > SELECT ... FROM nodes n FORCE INDEX(latitude) ...;
Still many
rows are
examined
Still many
rows are
examined
Most of the gain
comes from the
covering index, not
the filtering
Most of the gain
comes from the
covering index, not
the filtering
MySQL ignores the
newly created index,
why?
MySQL ignores the
newly created index,
why?
Performance
improvement is
not great
Performance
improvement is
not great

182
Multiple Range Scans Cannot Be
Optimized with BTREE Indexes
●
We need quadtrees or R-TREE Indexes for
indexing in multiple dimensions
– The latter are implemented in MySQL with
the name “SPATIAL indexes”, as they only
apply to GIS types
●
Spatial indexing is available on MySQL since
5.7.5

183
Creating a Spatial Index
mysql (osm) > ALTER TABLE nodes
ADD COLUMN coord GEOMETRY NOT NULL SRID 4326;
mysql (osm) > UPDATE nodes
SET coord = point(longitude/10000000,
latitude/10000000);
Query OK, 20216490 rows affected (7 min 10.28 sec)
Rows matched: 20216490 Changed: 20216490 Warnings: 0
mysql (osm) > ALTER TABLE nodes add SPATIAL index(coord);
Query OK, 0 rows affected (1 hour 7 min 13.29 sec)
This is new since
5.7
This is new since
5.7
Instant, yay!
(or create it
VIRTUAL)
Instant, yay!
(or create it
VIRTUAL)

184
New Query
mysql> SET @area := ST_Envelope(linestring(POINT(@lon - 500/71520.91, @lat - 500/111231.29), POINT(@lon +
500/71520.91, @lat + 500/111231.29)));
mysql> SELECT n.node_id,
x(n.coord) as longitude,
y(n.coord) as latitude,
st_distance(POINT(@lon, @lat), coord) as distance
FROM nodes n
JOIN node_tags n_t1
JOIN node_tags n_t2
WHERE
n_t1.v = 'cafe' and
n_t2.k = 'name' and
n_t2.v like 'Starbucks%' and
st_within(coord, @area)
ORDER BY st_distance(POINT(@lon, @lat), coord) ASC
LIMIT 1;
We can use any
shape we want
thanks to 5.6
improvements
We can use any
shape we want
thanks to 5.6
improvements
Also substitute
functions like
Envelope with
ST_Envelope
since 5.7
Also substitute
functions like
Envelope with
ST_Envelope
since 5.7

186
Better Filtering
Not using the index:
+----------------------------+--------+
+----------------------------+--------+
+----------------------------+--------+
mysql-8.0 (osm) > SHOW STATUS LIKE 'Hand%';
Using the BTREE index:
+----------------------------+--------+
+----------------------------+--------+
+----------------------------+--------+
Using the SPATIAL index:
+----------------------------+-------+
+----------------------------+-------+
+----------------------------+-------+

187
Geohash Functions
mysql (osm) > SELECT ST_GeoHash(@lon, @lat, 10);
+----------------------------+
| ST_GeoHash(@lon, @lat, 10) |
+----------------------------+
| u0yjh79gr9 |
+----------------------------+
• Useful to index coordinates with a BTREE
– It could be specially useful combined with indexed STORED
columns (emulating quadtrees)
More on Geohashing: http://mysqlserverteam.com/geohash-functions/

188
GeoJSON Functions
mysql (osm) > SELECT nm.v, ST_AsGeoJson(n.coord)
FROM node_tags n_t
JOIN nodes n USING (node_id, version)
JOIN node_tags nm USING (node_id, version)
WHERE n_t.k='tourism' AND
n_t.v='attraction' AND
nm.k='name';
+-------------------------+------------------------------------------------------------+
| v | ST_AsGeoJson(n.coord) |
+-------------------------+------------------------------------------------------------+
| Schießbuckel | {"type": "Point", "coordinates": [8.4938556, 49.6351754]} |
| AKW Informationszentrum | {"type": "Point", "coordinates": [8.4175585, 49.7060227]} |
| Burg Gleiberg | {"type": "Point", "coordinates": [8.6344314, 50.6150329]} |
| Brüderkirche | {"type": "Point", "coordinates": [9.5042975, 51.3149351]} |
| Römer | {"type": "Point", "coordinates": [8.6816587, 50.1104684]} |
.
.

189
GeoJSON Functions (cont.)
$ mysql osm -B -e "SET NAMES utf8; SET SESSION group_concat_max_len = 10000; SELECT
CONCAT('{"type":"FeatureCollection", "features":[ ',
GROUP_CONCAT(CONCAT('{"type":"Feature", "geometry":', ST_AsGeoJson(n.coord),
',"properties":{"name":"',nm.v,'"}}')), ' ]}') FROM node_tags n_t JOIN nodes n USING
(node_id, version) JOIN node_tags nm USING (node_id, version) WHERE n_t.k='tourism' and
n_t.v='attraction' AND nm.k='name'"
http://geojsonlint.com/

190
Older Issues
• Before MySQL 8.0, SRID could be set and retrieved, but all
operations were done in squared euclidean coordinates:
mysql-5.7.5 (osm) > SET @p1 := GeomFromText('POINT(8 50)', 4326);
mysql-5.7.5 (osm) > SELECT srid(@p1);
+-----------+
| srid(@p1) |
+-----------+
| 4326 |
+-----------+
mysql-5.7.5 (osm) > SELECT st_distance(@p1, @p2);
+-----------------------+
| st_distance(@p1, @p2) |
+-----------------------+
| 1 |
+-----------------------+
mysql-5.7.5 (osm) > SELECT st_distance(@p1, @p3);
+-----------------------+
+-----------------------+
| 1 |
+-----------------------+

191
New 8.0 SRID Support !
mysql-8.0 (osm) > SET @p1 := ST_GeomFromText('POINT(8 50)',
4326);
4326);
4326);
mysql-8.0 (osm) > SELECT ST_srid(@p1);
+--------------+
| ST_srid(@p1) |
+--------------+
| 4326 |
+--------------+
mysql-8.0 (osm) > SELECT st_distance(@p1, @p2);
+-----------------------+
+-----------------------+
| 110243.2689139409 |
+-----------------------+
mysql-8.0 (osm) > SELECT st_distance(@p1, @p3);
+-----------------------+
+-----------------------+
| 110592.12831394037 |
+-----------------------+
Answers in
meters- The
world is no
longer flat!
Answers in
meters- The
world is no
longer flat!
I expected
something around
71-72 Km, did I do
something wrong?
I expected
something around
71-72 Km, did I do
something wrong?

192
JSON Native Data Type
●
Since 5.7.8, MySQL allows columns defined with
the JSON data type:
mysql-8.0 > CREATE TABLE json_test(id int PRIMARY KEY auto_increment,
content JSON);
mysql-8.0 > INSERT INTO json_test (content) VALUES ('{"type":
"correct_json"}');
Query OK, 1 row affected (0.00 sec)
mysql-8.0 > INSERT INTO json_test (content) VALUES ('{"type":
"incorrect_json}');
ERROR 3140 (22032): Invalid JSON text: "Missing a closing quotation
mark in string." at position 24 in value (or column) '{"type":
"incorrect_json}'.
They get
validated on
insert
They get
validated on
insert
MariaDB
supports it
only as a
BLOB/LONGT
EXT alias
MariaDB
supports it
only as a
BLOB/LONGT
EXT alias

193
JSON functions
●
MySQL includes almost all functions to
manipulate JSON that you may think of:
– Validation test: JSON_TYPE
– Object creation: JSON_ARRAY, JSON_MERGE, ...
– Searching: JSON_EXTRACT
– Modifying: JSON_SET, JSON_INSERT, ...

194
Indexing JSON
●
JSON Columns cannot be indexed:
mysql [localhost] {msandbox} (test) > ALTER TABLE
json_test ADD INDEX(content);
ERROR 3152 (42000): JSON column 'content' cannot be
used in key specification.
●
However, they can be compared with regular
fields and use indexes thanks to virtual columns

195
CONCLUSIONS
10.3: The Basics

196
8.0/10.3 Recently released
• They are mature enough to be used in production
• Latest release doesn’t have as many new features
related to query optimization
– But they have a lot of other features and quality of
life improvements
– They also fix long outstanding query performance
bugs
– MariaDB also catches up with MySQL in some areas

197
MySQL 8.0 New Features
• MySQL 5.6 seemed Percona Server-inspired
• MySQL 5.7 seemed MariaDB-inspired
• MySQL 8.0 seems Galera and Oracle DB-inspired
– Competition is always good for consumer

198
Modern SQL is now part of
MySQL!
●
Window functions, recursive CTEs:
WITH RECURSIVE cte (cl_from, cl_type) AS
(
SELECT cl_from, cl_type FROM categorylinks WHERE cl_to = 'Database_management_systems'
-- starting category
UNION
SELECT categorylinks.cl_from, categorylinks.cl_type FROM cte JOIN page ON cl_from =
page_id JOIN categorylinks ON page_title = cl_to WHERE cte.cl_type = 'subcat' --
subcat addition on each iteration
)
SELECT page_title FROM cte JOIN page ON cl_from = page_id WHERE page_namespace = 0
ORDER BY page_title; -- printing only articles in the end, ordered by title
Scan Wikipedia
categories,
page links
recursively!
Scan Wikipedia
categories,
page links
recursively!

199
Many Optimizer Advantages Have to
Be Manually Enabled
●
Modifying on a per-query basis:
SET optimizer_switch='batched_key_access=on';
SET join_cache_level=8; # for MariaDB
in order to take advantage of them, making
some of features useless unless you are fine-
tuning
– I expect that to change in the future

200
I Herby Declare MyISAM as Dead
• All major MyISAM-only features are
now on MySQL 5.7/8.0
– FULLTEXT
– GIS
– Transportable tables
• Previous blockers such as grant tables (new
InnoDB data dictionary) and temporary tables
are now in InnoDB format

201
Benchmarks
●
Do not trust first party
benchmarks
– In fact, do not trust 3rd
party benchmarks either
●
Only care about the
performance of your
application running on your hardware

202
Q&A

203
Not to Miss
●
Operations track:
TLS for MySQL at Large Scale:
How we do relational data on-
the-wire encryption at the
Wikimedia Foundation
●
Do you want to do query
optimization for a website with
20 Billion views per month?
https://wikimediafoundation.org/about/jobs/

204
Thank You for Attending!
●
Do not forget, after the session finishes,
to please login with your Percona Live
app and “Rate This Session”
●
Special thanks to in order by rand() to: Ariel
Glenn, Manuel Arostegui, Morgan Tocker, Sean
Pringle, David Hildebrandt, Bill Karwin, Domas
Mituzas, Mark Callaghan, Shlomi Noach, Valerii
Kravchuk, Miguel Ángel Nieto, Dimitri Kravtchuk,
Olav Sandstå and the whole Wikimedia Team,
and all people at the MariaDB, Percona and
MySQL/Oracle teams, and the Percona Live
Organization and Sponsors

Query Optimization with MySQL 8.0 and MariaDB 10.3: The Basics

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Query Optimization with MySQL 8.0 and MariaDB 10.3: The Basics