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This is not a DB
optimization talk
It’s a talk about how doing things in a specific way leads to getting way
better results by default
“Preoptimization”
 Don’t denormalize by default
 Maintenance is King (by default)
 1 Thread Performance != Parallel
Performance
MyISAM vs InnoDB
Fast != Scalable
“Preoptimization”
I’ll just tune MySQL Parameters…
 Will get you out of SOME trouble
 But not a good “default” solution, specially if the
base is flawed
 Please do tune MySQLs defaults
 Not the theme for today 
Start with your Schema
 Your schema is probably the root cause of your
“My DB doesn’t scale” problems
 The solution is not “have a loose/no schema”
 How to fake a DB Design (Curtis Ovid Poe)
 https://www.youtube.com/watch?v=y1tcbhWLiUM
Data types: how (not) to bloat your DB
 Selecting data types with a bit of care is very
productive
 It makes more data fit in less space
 Optimizes use of InnoDB Buffer Pool, MyISAM Key
Buffer, Join Buffer, Sort Buffer, Smaller indexes
Your new best friend
 http://dev.mysql.com/doc/refman/5.6/en/storage-requirements.html
 http://dev.mysql.com/doc/refman/5.5/en/storage-requirements.html
 …
DataTypes: NULL vs NOT NULL
 I don’t care about the NULL debate
 Saves Space
 Gives the DB hints
 Use NULLs wisely
Data Types: Integers
DataTypes: Integers
INT(1) == INT(10) == 4 bytes
That’s it!
DataTypes: Integer family
TINYINT: 1 byte
SMALLINT: 2 bytes
MEDIUMINT: 3 bytes
INT
BIGINT:8 bytes
UNSIGNED: “double”
the range
INTS and surrogate keys
 It’s good to have a surrogate key
 Just unique index the unique column
 Why?
 InnoDB stores the PK on the leafs of all indexes
 Indexes bloat if they’re “big keys”
Id columns for your tables
 INT by default for “things that can get big”
 Smaller INTs for smaller sets
 Do you really need a BIGINT?
 The magnitude comparison trick:
 Epochs in Unix have 4 bytes
 The epoch has been counting since 1970. Will run out in 2038
 An INT can identify ONE THING HAPPENING EVERY SECOND for 68 YEARS!
 Do you STILL need a BIGINT?
DataTypes: Integer family
TINYINT: 1 byte
SMALLINT: 2 bytes
MEDIUMINT: 3 bytes
INT
BIGINT:8 bytes
UNSIGNED: “double”
the range
DataTypes: Integer family
TINYINT: 1 byte
SMALLINT: 2 bytes
MEDIUMINT: 3 bytes
INT
BIGINT:8 bytes
UNSIGNED: “double”
the range
Data Types: Texts
DataTypes: Texts
 Texts are strings of bytes with a charset and a collation
BINARY and VARBINARY
CHAR and VARCHAR
DataTypes: Texts
BINARY(10) == 10 bytes
CHAR(10) ==? 10 bytes
DataTypes: Texts
BINARY(10) == 10 bytes
CHAR(10) ==? 10 bytes
CHAR(10) latin1: 10 bytes
CHAR(19) utf-8: 30 bytes
DataTypes: Texts
BINARY(10) == 10 bytes
CHAR(10) ==? 10 bytes
CHAR(10) latin1: 10 bytes
CHAR(19) utf-8: 30 bytes
VARBINARY(10) == 1 to 11 bytes
VARCHAR(10) ==? 1 to 11 bytes
DataTypes: Texts
BINARY(10) == 10 bytes
CHAR(10) ==? 10 bytes
CHAR(10) latin1: 10 bytes
CHAR(10) utf-8: 30 bytes
VARBINARY(10) == 1 to 11 bytes
VARCHAR(10) ==? 1 to 11 bytes
VARCHAR(10) latin 1: 1 to 11 bytes
VARCHAR(10) utf-8: 1 to 31 bytes
So I’ll just go for VARCHAR(255) on all
text columns
 “After all… I’ll just consume the number of bytes + 1”
So I’ll just go for VARCHAR(255) on all
text columns
 “After all… I’ll just consume the number of bytes + 1”
 When we need a temporary table
 https://dev.mysql.com/doc/refman/5.6/en/memory-storage-engine.html
 “MEMORY tables use a fixed-length row-storage format. Variable-length types such
as VARCHAR are stored using a fixed length”
So I’ll just go for VARCHAR(255) on all
text columns
Congrats! All your VARCHAR(255) are now
CHAR(255) in memory
That’s 255 bytes latin-1. Or 765 bytes utf-8
O_o
Note: do the maths on VARCHAR(65535)
DataTypes: BLOBS
 TEXT == BLOB == problems
 TEXT = BLOB + charset + collation
 TEXT fields are not unlimited!
 TINYTEXT and TINYBLOB (up to 256 bytes == x chars)
 TEXT / BLOB (up to 65KB == x chars)
 MEDIUMBLOB / MEDIUMTEXT (up to 16MB == x chars)
 LONGTEXT / LONGBLOB (up to 2GB == x chars)
SELECT * IS YOUR FRIEND?
 IF a SELECT contains a BLOB/TEXT column
Temporary tables go DIRECTLY to DISK
SELECT * IS YOUR FRIEND?
 IF a SELECT contains a BLOB/TEXT column
Temporary tables go DIRECTLY to DISK
Note: “Big” columns belong on a filesystem or an object store
DataTypes: Small Sets
 ENUM
 One value out of the possibilities (‘big’, ‘small’)
 SET
 A set of possible values (‘pool’,’terrace’,’fence’)
 SETS are NOT good for finding stuff
 FIND_IN_SET is a function. No indexes 
 Default to a separate table + relation
DataTypes: Dates
 YEAR = 1 byte (range from 1901 to 2155)
 DATE = 3 bytes
 TIME = 3 bytes
 DATETIME = 8 bytes
 TIMESTAMP = 4 bytes
Timestamp is an epoch. Ideal for “things that
happen now” (sold time, renewal date, etc)
Masked Data
Masked Types
An IP Address
234.34.123.92
CHAR(15)? VARCHAR(15)?
Masked Types
INT
INSERT INTO table (col) VALUES (INET_ATON(’10.10.10.10’));
SELECT INET_NTOA(col) FROM table;
Masked Types
MD5("The quick brown fox jumps over the lazy cat")
 71bd588d5ad9b6abe87b831b45f8fa95
 CHAR(32)
BINARY(16)
Masked Types
 UUIDs
 HASH functions
 Network masks
Indexes for starters
Indexes for starters
Index the two sides of relations
PK
Index the two sides of relations
Index this guy too!
Index the two sides of relations
Index this guy too!
And this guy!
PK is (contract_id, customer_id)
(Implied uniqueness)
Index “both ways”:
(customer_id, contract_id)
InnoDB optimization: Don’t index the full (customer_id, contract_id). The
index ALREADY HAS customer_id in it’s leafs. So just index (customer_id)
N-M relation: Junction tables
Don’t operate on fields
 Because they can’t use indexes
 WHERE column = ‘x’
WHERE column > 2000
WHERE column LIKE ‘prefix%’
 WHERE column + 2000 > 2013
WHERE FIND_IN_SET(column)
WHERE CONCAT(f1,f2) = “xxxx.com”
WHERE YEAR(date) = 2015
WHERE column LIKE ‘%.com’
Polish your maths: Algebra
Doesn’t use index
WHERE column + 2000 > 2013
WHERE FIND_IN_SET(‘pool’,column)
WHERE CONCAT(f1,’.’,f2) =
“xxxx.com”
WHERE YEAR(date) = 2015
WHERE column LIKE ‘%.com’
Uses index
WHERE column > 13
?
WHERE f1 = ‘xxxx’ AND f2 = ‘com’
WHERE date BETWEEN ’01-01-2015’
and ’31-12-2015’
?
The old switcheroo…
Doesn’t use index
WHERE column + 2000 > 2013
WHERE FIND_IN_SET(‘pool’,column)
WHERE CONCAT(f1,’.’,f2) =
“xxxx.com”
WHERE YEAR(date) = 2015
WHERE column LIKE ‘%.com’
Uses index
WHERE has_pool = 1
WHERE column_rev LIKE ‘moc.%’
The old switcheroo…
Doesn’t use index
WHERE column + 2000 > 2013
WHERE FIND_IN_SET(‘pool’,column)
WHERE CONCAT(f1,’.’,f2) =
“xxxx.com”
WHERE YEAR(date) = 2015
WHERE column LIKE ‘%.com’
Uses index
WHERE has_pool = 1
UPDATE t SET has_pool =
FIND_IN_SET(‘pool’,column);
WHERE column_rev LIKE ‘moc.%’
UPDATE t SET
column_rev=REVERSE(column)
CAT IS HERE
Wrap up
Schema
Data Types
How to select them
Masked Types
Indexes
Relations
Using them
Wrap up
 Smaller is better
VS
cpsd.es/SRE-job-team

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"MySQL Boosting - DB Best Practices & Optimization" by José Luis Martínez - CTO @ CAPSiDE

  • 1.
  • 2. This is not a DB optimization talk It’s a talk about how doing things in a specific way leads to getting way better results by default
  • 3. “Preoptimization”  Don’t denormalize by default  Maintenance is King (by default)  1 Thread Performance != Parallel Performance MyISAM vs InnoDB Fast != Scalable
  • 5. I’ll just tune MySQL Parameters…  Will get you out of SOME trouble  But not a good “default” solution, specially if the base is flawed  Please do tune MySQLs defaults  Not the theme for today 
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  • 7. Start with your Schema  Your schema is probably the root cause of your “My DB doesn’t scale” problems  The solution is not “have a loose/no schema”  How to fake a DB Design (Curtis Ovid Poe)  https://www.youtube.com/watch?v=y1tcbhWLiUM
  • 8. Data types: how (not) to bloat your DB  Selecting data types with a bit of care is very productive  It makes more data fit in less space  Optimizes use of InnoDB Buffer Pool, MyISAM Key Buffer, Join Buffer, Sort Buffer, Smaller indexes
  • 9. Your new best friend  http://dev.mysql.com/doc/refman/5.6/en/storage-requirements.html  http://dev.mysql.com/doc/refman/5.5/en/storage-requirements.html  …
  • 10. DataTypes: NULL vs NOT NULL  I don’t care about the NULL debate  Saves Space  Gives the DB hints  Use NULLs wisely
  • 12. DataTypes: Integers INT(1) == INT(10) == 4 bytes That’s it!
  • 13. DataTypes: Integer family TINYINT: 1 byte SMALLINT: 2 bytes MEDIUMINT: 3 bytes INT BIGINT:8 bytes UNSIGNED: “double” the range
  • 14. INTS and surrogate keys  It’s good to have a surrogate key  Just unique index the unique column  Why?  InnoDB stores the PK on the leafs of all indexes  Indexes bloat if they’re “big keys”
  • 15. Id columns for your tables  INT by default for “things that can get big”  Smaller INTs for smaller sets  Do you really need a BIGINT?  The magnitude comparison trick:  Epochs in Unix have 4 bytes  The epoch has been counting since 1970. Will run out in 2038  An INT can identify ONE THING HAPPENING EVERY SECOND for 68 YEARS!  Do you STILL need a BIGINT?
  • 16. DataTypes: Integer family TINYINT: 1 byte SMALLINT: 2 bytes MEDIUMINT: 3 bytes INT BIGINT:8 bytes UNSIGNED: “double” the range
  • 17. DataTypes: Integer family TINYINT: 1 byte SMALLINT: 2 bytes MEDIUMINT: 3 bytes INT BIGINT:8 bytes UNSIGNED: “double” the range
  • 19. DataTypes: Texts  Texts are strings of bytes with a charset and a collation BINARY and VARBINARY CHAR and VARCHAR
  • 20. DataTypes: Texts BINARY(10) == 10 bytes CHAR(10) ==? 10 bytes
  • 21. DataTypes: Texts BINARY(10) == 10 bytes CHAR(10) ==? 10 bytes CHAR(10) latin1: 10 bytes CHAR(19) utf-8: 30 bytes
  • 22. DataTypes: Texts BINARY(10) == 10 bytes CHAR(10) ==? 10 bytes CHAR(10) latin1: 10 bytes CHAR(19) utf-8: 30 bytes VARBINARY(10) == 1 to 11 bytes VARCHAR(10) ==? 1 to 11 bytes
  • 23. DataTypes: Texts BINARY(10) == 10 bytes CHAR(10) ==? 10 bytes CHAR(10) latin1: 10 bytes CHAR(10) utf-8: 30 bytes VARBINARY(10) == 1 to 11 bytes VARCHAR(10) ==? 1 to 11 bytes VARCHAR(10) latin 1: 1 to 11 bytes VARCHAR(10) utf-8: 1 to 31 bytes
  • 24. So I’ll just go for VARCHAR(255) on all text columns  “After all… I’ll just consume the number of bytes + 1”
  • 25. So I’ll just go for VARCHAR(255) on all text columns  “After all… I’ll just consume the number of bytes + 1”  When we need a temporary table  https://dev.mysql.com/doc/refman/5.6/en/memory-storage-engine.html  “MEMORY tables use a fixed-length row-storage format. Variable-length types such as VARCHAR are stored using a fixed length”
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  • 27. So I’ll just go for VARCHAR(255) on all text columns Congrats! All your VARCHAR(255) are now CHAR(255) in memory That’s 255 bytes latin-1. Or 765 bytes utf-8 O_o Note: do the maths on VARCHAR(65535)
  • 28. DataTypes: BLOBS  TEXT == BLOB == problems  TEXT = BLOB + charset + collation  TEXT fields are not unlimited!  TINYTEXT and TINYBLOB (up to 256 bytes == x chars)  TEXT / BLOB (up to 65KB == x chars)  MEDIUMBLOB / MEDIUMTEXT (up to 16MB == x chars)  LONGTEXT / LONGBLOB (up to 2GB == x chars)
  • 29. SELECT * IS YOUR FRIEND?  IF a SELECT contains a BLOB/TEXT column Temporary tables go DIRECTLY to DISK
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  • 31. SELECT * IS YOUR FRIEND?  IF a SELECT contains a BLOB/TEXT column Temporary tables go DIRECTLY to DISK Note: “Big” columns belong on a filesystem or an object store
  • 32. DataTypes: Small Sets  ENUM  One value out of the possibilities (‘big’, ‘small’)  SET  A set of possible values (‘pool’,’terrace’,’fence’)  SETS are NOT good for finding stuff  FIND_IN_SET is a function. No indexes   Default to a separate table + relation
  • 33. DataTypes: Dates  YEAR = 1 byte (range from 1901 to 2155)  DATE = 3 bytes  TIME = 3 bytes  DATETIME = 8 bytes  TIMESTAMP = 4 bytes Timestamp is an epoch. Ideal for “things that happen now” (sold time, renewal date, etc)
  • 35. Masked Types An IP Address 234.34.123.92 CHAR(15)? VARCHAR(15)?
  • 37. INT
  • 38. INSERT INTO table (col) VALUES (INET_ATON(’10.10.10.10’)); SELECT INET_NTOA(col) FROM table;
  • 39. Masked Types MD5("The quick brown fox jumps over the lazy cat")  71bd588d5ad9b6abe87b831b45f8fa95  CHAR(32)
  • 41. Masked Types  UUIDs  HASH functions  Network masks
  • 44. Index the two sides of relations PK
  • 45. Index the two sides of relations Index this guy too!
  • 46. Index the two sides of relations Index this guy too! And this guy!
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  • 49. PK is (contract_id, customer_id) (Implied uniqueness) Index “both ways”: (customer_id, contract_id) InnoDB optimization: Don’t index the full (customer_id, contract_id). The index ALREADY HAS customer_id in it’s leafs. So just index (customer_id) N-M relation: Junction tables
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  • 51. Don’t operate on fields  Because they can’t use indexes  WHERE column = ‘x’ WHERE column > 2000 WHERE column LIKE ‘prefix%’  WHERE column + 2000 > 2013 WHERE FIND_IN_SET(column) WHERE CONCAT(f1,f2) = “xxxx.com” WHERE YEAR(date) = 2015 WHERE column LIKE ‘%.com’
  • 52. Polish your maths: Algebra Doesn’t use index WHERE column + 2000 > 2013 WHERE FIND_IN_SET(‘pool’,column) WHERE CONCAT(f1,’.’,f2) = “xxxx.com” WHERE YEAR(date) = 2015 WHERE column LIKE ‘%.com’ Uses index WHERE column > 13 ? WHERE f1 = ‘xxxx’ AND f2 = ‘com’ WHERE date BETWEEN ’01-01-2015’ and ’31-12-2015’ ?
  • 53. The old switcheroo… Doesn’t use index WHERE column + 2000 > 2013 WHERE FIND_IN_SET(‘pool’,column) WHERE CONCAT(f1,’.’,f2) = “xxxx.com” WHERE YEAR(date) = 2015 WHERE column LIKE ‘%.com’ Uses index WHERE has_pool = 1 WHERE column_rev LIKE ‘moc.%’
  • 54. The old switcheroo… Doesn’t use index WHERE column + 2000 > 2013 WHERE FIND_IN_SET(‘pool’,column) WHERE CONCAT(f1,’.’,f2) = “xxxx.com” WHERE YEAR(date) = 2015 WHERE column LIKE ‘%.com’ Uses index WHERE has_pool = 1 UPDATE t SET has_pool = FIND_IN_SET(‘pool’,column); WHERE column_rev LIKE ‘moc.%’ UPDATE t SET column_rev=REVERSE(column)
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  • 57. Wrap up Schema Data Types How to select them Masked Types Indexes Relations Using them
  • 58. Wrap up  Smaller is better VS
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