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Demystifying
      DBIx::Class
                Jay Shirley
      <jshirley@coldhardcode.com>



http://our.coldhardcode.com/svn/DBIC-Beer
Mystic?
Why are ORMs scary?
Why are ORMs scary?

• Enterprise-y
Why are ORMs scary?

• Enterprise-y
• Loss of control
Why are ORMs scary?

• Enterprise-y
• Loss of control
• History (Class::DBI)
Why are ORMs scary?

• Enterprise-y
• Loss of control
• History (Class::DBI)
 • (A triumph of multiple inheritance)
Retort.
Enterprise-y
Enterprise-y


• Enterprise = Java
Enterprise-y


• Enterprise = Java
• DBIx::Class is written in perl
Loss of Control
Loss of Control

• Still programmatic
Loss of Control

• Still programmatic
• Use SQL::Abstract rather than SQL
Loss of Control

• Still programmatic
• Use SQL::Abstract rather than SQL
• Same thing
Loss of Control

• Still programmatic
• Use SQL::Abstract rather than SQL
• Same thing
 • (except patches welcome)
Class::DBI
Class::DBI


  Sorry Schwern
Why DBIx::Class?

• I like it. You’ll see why.
• TIMTOWDI:
 • Rose::DB
 • Alzabo
Objects

• Relations are only a third of an ORM
Objects

• Relations are only a third of an ORM
• What’s an object?
Objects

• Relations are only a third of an ORM
• What’s an object?
 • Database columns
Objects

• Relations are only a third of an ORM
• What’s an object?
 • Database columns
 • Table
Objects

• Relations are only a third of an ORM
• What’s an object?
 • Database columns
 • Table
 • Indexes
A Use Case
Beer
Yes, Beer.
Or...

• Beer has many distributers
• Beer has many reviews
• Beer belongs to a brewer
Which means...
package Beer::Schema::Beer;

use base 'DBIx::Class';

__PACKAGE__->load_components( qw|Core| );

__PACKAGE__->table('beer');

__PACKAGE__->add_columns(

     'pk1' =>

     { data_type => 'integer', size => 16, is_nullable => 0, is_auto_increment => 1 },

     'name' =>

     { data_type => 'varchar', size => 128, is_nullable => 0 },

     'brewer_pk1' =>

     { data_type => 'integer', size => 16, is_nullable => 0, is_foreign_key => 1 },

);

__PACKAGE__->set_primary_key('pk1');

1;
And indexes:


__PACKAGE__->add_unique_index(...);
That gives you:


• Deployable SQL (CREATE TABLE, etc)
• The foundation for relationships:
 • $beer->brewer   # DTRT
Managing Relations

• A beer is:
 • made by a brewer
 • distributed by distributers
 • reviewed by people
Simple Relationships

belongs_to is the opposite end of has_many
Simple Relationships

belongs_to is the opposite end of has_many
   has_one, might_have means just that
Simple Relationships

belongs_to is the opposite end of has_many
   has_one, might_have means just that
     many_to_many gets complicated
Creating a relation

__PACKAGE__->belongs_to(
    ‘brewer’,                # Accessor

     ‘Beer::Schema::Brewer’, # Related Class

     ‘brewer_pk1’            # My Column
);
For simplicity...


Brewers, Distributors and Beers are all easy
All the same, except Beer has a brewer
(brewer_pk1)
Using it (Manager)


use Beer::Schema;
my $schema = Beer::Schema
    ->connect( $dsn );
$schema


# Fetch a result set
my $rs = $schema->resultset(‘Beer’);
Result Sets


# Everything is a result set.
$rs->count; # How many Beers?
Everything is a
       Result Set

$rs2 = $rs->search({
    name => ‘Stout’
});
$rs2->count; # It chains together.
Chained Result Sets
  are what make
   DBIC Great
Result Sets return
     Result Sets
$rs->search->search->search-
>search->search->search ->search-
>search->search->search->search-
>search ->search->search->search-
>search->search->search ->search-
>search->search->search->search-
>search ->search->search->search-
>search->search->search ->search-
>search->search->search->search-
>search;
Why?

$rs
      ->search({ $long_query })
      ->search({ $more_filters })
      ->search({ $even_more });
Actual Use:
sub active_members {
    # All profiles that have purchased a membership.
    my $query = $rs->search(
        {
            'purchase.saved_object_key' => 'membership',
            'membership.expiration_date' => '>= NOW()'
        },
        {
            join => {
                profile_transactions => {
                     'transaction' => {
                         'link_transaction_purchase' => {
                             'purchase' => 'membership'
                         }
                     }
                },
            },
            prefetch => [
                'state', 'country',
                {
                     profile_transactions => {
                         'transaction' => {
                             'link_transaction_purchase' => {
                                 'purchase' => 'membership'
                             }
                         }
                     },
                }
            ],
             group_by => [ qw/membership_id/ ]
         }
    );
}
In SQL:

SELECT ... FROM table_profiles me LEFT JOIN profile_transaction profile_transactions ON
( profile_transactions.profile_id = me.profile_id ) JOIN nasa_transactions transaction ON
( transaction.transaction_id = profile_transactions.transaction_id ) LEFT JOIN
link_trans_pp link_transaction_purchase ON ( link_transaction_purchase.transaction_id =
transaction.transaction_id ) JOIN purchased_products purchase ON ( purchase.purchased_id =
link_transaction_purchase.purchased_id ) JOIN nasa_membership membership ON
( membership.membership_id = purchase.saved_product_id ) JOIN state_lookup state ON
( state.state_lookup_id = me.state ) JOIN country_lookup country ON
( country.country_lookup_id = me.country_id ) WHERE ( membership.expiration_date >= NOW()
AND purchase.saved_object_key = 'membership' )
Now:

my $query = $schema->resultset(‘Profile’)->active_members;


$query->count; # How many?
$query->search({ first_name => ‘Bob’ }); # All matching members named Bob
$query->search({ first_name => ‘Bob’ })->count;


while ( my $profile = $query->next ) {
    $profile->cars; # Get all of this persons cars
}


# Clean, no ugly SQL
Pretty.
Even More:
Managing your schema
Create Table
                     Statements
$schema->create_ddl_dir(

       [ 'SQLite', 'MySQL', ‘PostgreSQL’ ],

       $VERSION,

       quot;$destinationquot;

);
SQLite

CREATE TABLE beer (

  pk1 INTEGER PRIMARY KEY NOT NULL,

  name varchar(128) NOT NULL,

  brewer_pk1 integer(16) NOT NULL

);
DROP TABLE IF EXISTS `beer`;
                               MySQL
--

-- Table: `beer`

--

CREATE TABLE `beer` (

  `pk1` integer(16) NOT NULL auto_increment,

  `name` varchar(128) NOT NULL,

  `brewer_pk1` integer(16) NOT NULL,

  INDEX (`pk1`),

  INDEX (`brewer_pk1`),

  PRIMARY KEY (`pk1`),

  CONSTRAINT `beer_fk_brewer_pk1` FOREIGN KEY (`brewer_pk1`) REFERENCES `brewer`
(`pk1`) ON DELETE CASCADE ON UPDATE CASCADE

) Type=InnoDB;
PostgreSQL
--

-- Table: beer

--

DROP TABLE beer CASCADE;

CREATE TABLE beer (

  pk1 bigserial NOT NULL,

  name character varying(128) NOT NULL,

  brewer_pk1 bigint NOT NULL,

  PRIMARY KEY (pk1)

);
Get a working database


$schema->deploy; # Yes, it is this simple.
And now for tests

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Demystifying DBIx::Class

  • 1. Demystifying DBIx::Class Jay Shirley <jshirley@coldhardcode.com> http://our.coldhardcode.com/svn/DBIC-Beer
  • 3. Why are ORMs scary?
  • 4. Why are ORMs scary? • Enterprise-y
  • 5. Why are ORMs scary? • Enterprise-y • Loss of control
  • 6. Why are ORMs scary? • Enterprise-y • Loss of control • History (Class::DBI)
  • 7. Why are ORMs scary? • Enterprise-y • Loss of control • History (Class::DBI) • (A triumph of multiple inheritance)
  • 11. Enterprise-y • Enterprise = Java • DBIx::Class is written in perl
  • 13. Loss of Control • Still programmatic
  • 14. Loss of Control • Still programmatic • Use SQL::Abstract rather than SQL
  • 15. Loss of Control • Still programmatic • Use SQL::Abstract rather than SQL • Same thing
  • 16. Loss of Control • Still programmatic • Use SQL::Abstract rather than SQL • Same thing • (except patches welcome)
  • 19. Why DBIx::Class? • I like it. You’ll see why. • TIMTOWDI: • Rose::DB • Alzabo
  • 20. Objects • Relations are only a third of an ORM
  • 21. Objects • Relations are only a third of an ORM • What’s an object?
  • 22. Objects • Relations are only a third of an ORM • What’s an object? • Database columns
  • 23. Objects • Relations are only a third of an ORM • What’s an object? • Database columns • Table
  • 24. Objects • Relations are only a third of an ORM • What’s an object? • Database columns • Table • Indexes
  • 26. Beer
  • 28. Or... • Beer has many distributers • Beer has many reviews • Beer belongs to a brewer
  • 29. Which means... package Beer::Schema::Beer; use base 'DBIx::Class'; __PACKAGE__->load_components( qw|Core| ); __PACKAGE__->table('beer'); __PACKAGE__->add_columns( 'pk1' => { data_type => 'integer', size => 16, is_nullable => 0, is_auto_increment => 1 }, 'name' => { data_type => 'varchar', size => 128, is_nullable => 0 }, 'brewer_pk1' => { data_type => 'integer', size => 16, is_nullable => 0, is_foreign_key => 1 }, ); __PACKAGE__->set_primary_key('pk1'); 1;
  • 31. That gives you: • Deployable SQL (CREATE TABLE, etc) • The foundation for relationships: • $beer->brewer # DTRT
  • 32. Managing Relations • A beer is: • made by a brewer • distributed by distributers • reviewed by people
  • 33. Simple Relationships belongs_to is the opposite end of has_many
  • 34. Simple Relationships belongs_to is the opposite end of has_many has_one, might_have means just that
  • 35. Simple Relationships belongs_to is the opposite end of has_many has_one, might_have means just that many_to_many gets complicated
  • 36. Creating a relation __PACKAGE__->belongs_to( ‘brewer’, # Accessor ‘Beer::Schema::Brewer’, # Related Class ‘brewer_pk1’ # My Column );
  • 37. For simplicity... Brewers, Distributors and Beers are all easy All the same, except Beer has a brewer (brewer_pk1)
  • 38. Using it (Manager) use Beer::Schema; my $schema = Beer::Schema ->connect( $dsn );
  • 39. $schema # Fetch a result set my $rs = $schema->resultset(‘Beer’);
  • 40. Result Sets # Everything is a result set. $rs->count; # How many Beers?
  • 41. Everything is a Result Set $rs2 = $rs->search({ name => ‘Stout’ }); $rs2->count; # It chains together.
  • 42. Chained Result Sets are what make DBIC Great
  • 43. Result Sets return Result Sets $rs->search->search->search- >search->search->search ->search- >search->search->search->search- >search ->search->search->search- >search->search->search ->search- >search->search->search->search- >search ->search->search->search- >search->search->search ->search- >search->search->search->search- >search;
  • 44. Why? $rs ->search({ $long_query }) ->search({ $more_filters }) ->search({ $even_more });
  • 45. Actual Use: sub active_members { # All profiles that have purchased a membership. my $query = $rs->search( { 'purchase.saved_object_key' => 'membership', 'membership.expiration_date' => '>= NOW()' }, { join => { profile_transactions => { 'transaction' => { 'link_transaction_purchase' => { 'purchase' => 'membership' } } }, }, prefetch => [ 'state', 'country', { profile_transactions => { 'transaction' => { 'link_transaction_purchase' => { 'purchase' => 'membership' } } }, } ], group_by => [ qw/membership_id/ ] } ); }
  • 46. In SQL: SELECT ... FROM table_profiles me LEFT JOIN profile_transaction profile_transactions ON ( profile_transactions.profile_id = me.profile_id ) JOIN nasa_transactions transaction ON ( transaction.transaction_id = profile_transactions.transaction_id ) LEFT JOIN link_trans_pp link_transaction_purchase ON ( link_transaction_purchase.transaction_id = transaction.transaction_id ) JOIN purchased_products purchase ON ( purchase.purchased_id = link_transaction_purchase.purchased_id ) JOIN nasa_membership membership ON ( membership.membership_id = purchase.saved_product_id ) JOIN state_lookup state ON ( state.state_lookup_id = me.state ) JOIN country_lookup country ON ( country.country_lookup_id = me.country_id ) WHERE ( membership.expiration_date >= NOW() AND purchase.saved_object_key = 'membership' )
  • 47. Now: my $query = $schema->resultset(‘Profile’)->active_members; $query->count; # How many? $query->search({ first_name => ‘Bob’ }); # All matching members named Bob $query->search({ first_name => ‘Bob’ })->count; while ( my $profile = $query->next ) { $profile->cars; # Get all of this persons cars } # Clean, no ugly SQL
  • 50. Create Table Statements $schema->create_ddl_dir( [ 'SQLite', 'MySQL', ‘PostgreSQL’ ], $VERSION, quot;$destinationquot; );
  • 51. SQLite CREATE TABLE beer ( pk1 INTEGER PRIMARY KEY NOT NULL, name varchar(128) NOT NULL, brewer_pk1 integer(16) NOT NULL );
  • 52. DROP TABLE IF EXISTS `beer`; MySQL -- -- Table: `beer` -- CREATE TABLE `beer` ( `pk1` integer(16) NOT NULL auto_increment, `name` varchar(128) NOT NULL, `brewer_pk1` integer(16) NOT NULL, INDEX (`pk1`), INDEX (`brewer_pk1`), PRIMARY KEY (`pk1`), CONSTRAINT `beer_fk_brewer_pk1` FOREIGN KEY (`brewer_pk1`) REFERENCES `brewer` (`pk1`) ON DELETE CASCADE ON UPDATE CASCADE ) Type=InnoDB;
  • 53. PostgreSQL -- -- Table: beer -- DROP TABLE beer CASCADE; CREATE TABLE beer ( pk1 bigserial NOT NULL, name character varying(128) NOT NULL, brewer_pk1 bigint NOT NULL, PRIMARY KEY (pk1) );
  • 54. Get a working database $schema->deploy; # Yes, it is this simple.
  • 55. And now for tests