Marcus Ramberg > DBIx-Class-0.05999_04 > DBIx::Class::Manual::Cookbook

Download:
DBIx-Class-0.05999_04.tar.gz

Annotate this POD (8)

CPAN RT

New  12
Open  18
Stalled  11
View/Report Bugs
Source   Latest Release: DBIx-Class-0.082810

NAME ^

DBIx::Class::Manual::Cookbook - Miscellaneous recipes

RECIPES ^

Searching

Paged results

When you expect a large number of results, you can ask DBIx::Class for a paged resultset, which will fetch only a small number of records at a time:

  my $rs = $schema->resultset('Artist')->search(
    undef,
    {
      page => 1,  # page to return (defaults to 1)
      rows => 10, # number of results per page
    },
  );

  return $rs->all(); # all records for page 1

The page attribute does not have to be specified in your search:

  my $rs = $schema->resultset('Artist')->search(
    undef,
    {
      rows => 10,
    }
  );

  return $rs->page(1); # DBIx::Class::ResultSet containing first 10 records

In either of the above cases, you can return a Data::Page object for the resultset (suitable for use in e.g. a template) using the pager method:

  return $rs->pager();

Complex WHERE clauses

Sometimes you need to formulate a query using specific operators:

  my @albums = $schema->resultset('Album')->search({
    artist => { 'like', '%Lamb%' },
    title  => { 'like', '%Fear of Fours%' },
  });

This results in something like the following WHERE clause:

  WHERE artist LIKE '%Lamb%' AND title LIKE '%Fear of Fours%'

Other queries might require slightly more complex logic:

  my @albums = $schema->resultset('Album')->search({
    -or => [
      -and => [
        artist => { 'like', '%Smashing Pumpkins%' },
        title  => 'Siamese Dream',
      ],
      artist => 'Starchildren',
    ],
  });

This results in the following WHERE clause:

  WHERE ( artist LIKE '%Smashing Pumpkins%' AND title = 'Siamese Dream' )
    OR artist = 'Starchildren'

For more information on generating complex queries, see "WHERE CLAUSES" in SQL::Abstract.

Using specific columns

When you only want selected columns from a table, you can use cols to specify which ones you need:

  my $rs = $schema->resultset('Artist')->search(
    undef,
    {
      columns => [qw/ name /]
    }
  );

  # Equivalent SQL:
  # SELECT artist.name FROM artist

Using database functions or stored procedures

The combination of select and as can be used to return the result of a database function or stored procedure as a column value. You use select to specify the source for your column value (e.g. a column name, function, or stored procedure name). You then use as to set the column name you will use to access the returned value:

  my $rs = $schema->resultset('Artist')->search(
    undef,
    {
      select => [ 'name', { LENGTH => 'name' } ],
      as     => [qw/ name name_length /],
    }
  );

  # Equivalent SQL:
  # SELECT name name, LENGTH( name ) name_length
  # FROM artist

If your alias exists as a column in your base class (i.e. it was added with add_columns), you just access it as normal. Our Artist class has a name column, so we just use the name accessor:

  my $artist = $rs->first();
  my $name = $artist->name();

If on the other hand the alias does not correspond to an existing column, you can get the value using the get_column accessor:

  my $name_length = $artist->get_column('name_length');

If you don't like using get_column, you can always create an accessor for any of your aliases using either of these:

  # Define accessor manually:
  sub name_length { shift->get_column('name_length'); }
    
  # Or use DBIx::Class::AccessorGroup:
  __PACKAGE__->mk_group_accessors('column' => 'name_length');

SELECT DISTINCT with multiple columns

  my $rs = $schema->resultset('Foo')->search(
    undef,
    {
      select => [
        { distinct => [ $source->columns ] }
      ],
      as => [ $source->columns ]
    }
  );

SELECT COUNT(DISTINCT colname)

  my $rs = $schema->resultset('Foo')->search(
    undef,
    {
      select => [
        { count => { distinct => 'colname' } }
      ],
      as => [ 'count' ]
    }
  );

Grouping results

DBIx::Class supports GROUP BY as follows:

  my $rs = $schema->resultset('Artist')->search(
    undef,
    {
      join     => [qw/ cds /],
      select   => [ 'name', { count => 'cds.cdid' } ],
      as       => [qw/ name cd_count /],
      group_by => [qw/ name /]
    }
  );

  # Equivalent SQL:
  # SELECT name, COUNT( cds.cdid ) FROM artist me
  # LEFT JOIN cd cds ON ( cds.artist = me.artistid )
  # GROUP BY name

Using joins and prefetch

You can use the join attribute to allow searching on, or sorting your results by, one or more columns in a related table. To return all CDs matching a particular artist name:

  my $rs = $schema->resultset('CD')->search(
    {
      'artist.name' => 'Bob Marley'    
    },
    {
      join => [qw/artist/], # join the artist table
    }
  );

  # Equivalent SQL:
  # SELECT cd.* FROM cd
  # JOIN artist ON cd.artist = artist.id
  # WHERE artist.name = 'Bob Marley'

If required, you can now sort on any column in the related tables by including it in your order_by attribute:

  my $rs = $schema->resultset('CD')->search(
    {
      'artist.name' => 'Bob Marley'
    },
    {
      join     => [qw/ artist /],
      order_by => [qw/ artist.name /]
    }
  };

  # Equivalent SQL:
  # SELECT cd.* FROM cd
  # JOIN artist ON cd.artist = artist.id
  # WHERE artist.name = 'Bob Marley'
  # ORDER BY artist.name

Note that the join attribute should only be used when you need to search or sort using columns in a related table. Joining related tables when you only need columns from the main table will make performance worse!

Now let's say you want to display a list of CDs, each with the name of the artist. The following will work fine:

  while (my $cd = $rs->next) {
    print "CD: " . $cd->title . ", Artist: " . $cd->artist->name;
  }

There is a problem however. We have searched both the cd and artist tables in our main query, but we have only returned data from the cd table. To get the artist name for any of the CD objects returned, DBIx::Class will go back to the database:

  SELECT artist.* FROM artist WHERE artist.id = ?

A statement like the one above will run for each and every CD returned by our main query. Five CDs, five extra queries. A hundred CDs, one hundred extra queries!

Thankfully, DBIx::Class has a prefetch attribute to solve this problem. This allows you to fetch results from related tables in advance:

  my $rs = $schema->resultset('CD')->search(
    {
      'artist.name' => 'Bob Marley'
    },
    {
      join     => [qw/ artist /],
      order_by => [qw/ artist.name /],
      prefetch => [qw/ artist /] # return artist data too!
    }
  );

  # Equivalent SQL (note SELECT from both "cd" and "artist"):
  # SELECT cd.*, artist.* FROM cd
  # JOIN artist ON cd.artist = artist.id
  # WHERE artist.name = 'Bob Marley'
  # ORDER BY artist.name

The code to print the CD list remains the same:

  while (my $cd = $rs->next) {
    print "CD: " . $cd->title . ", Artist: " . $cd->artist->name;
  }

DBIx::Class has now prefetched all matching data from the artist table, so no additional SQL statements are executed. You now have a much more efficient query.

Note that as of DBIx::Class 0.04, prefetch cannot be used with has_many relationships. You will get an error along the lines of "No accessor for prefetched ..." if you try.

Also note that prefetch should only be used when you know you will definitely use data from a related table. Pre-fetching related tables when you only need columns from the main table will make performance worse!

Multi-step joins

Sometimes you want to join more than one relationship deep. In this example, we want to find all Artist objects who have CDs whose LinerNotes contain a specific string:

  # Relationships defined elsewhere:
  # Artist->has_many('cds' => 'CD', 'artist');
  # CD->has_one('liner_notes' => 'LinerNotes', 'cd');

  my $rs = $schema->resultset('Artist')->search(
    {
      'liner_notes.notes' => { 'like', '%some text%' },
    },
    {
      join => {
        'cds' => 'liner_notes'
      }
    }
  );

  # Equivalent SQL:
  # SELECT artist.* FROM artist
  # JOIN ( cd ON artist.id = cd.artist )
  # JOIN ( liner_notes ON cd.id = liner_notes.cd )
  # WHERE liner_notes.notes LIKE '%some text%'

Joins can be nested to an arbitrary level. So if we decide later that we want to reduce the number of Artists returned based on who wrote the liner notes:

  # Relationship defined elsewhere:
  # LinerNotes->belongs_to('author' => 'Person');

  my $rs = $schema->resultset('Artist')->search(
    {
      'liner_notes.notes' => { 'like', '%some text%' },
      'author.name' => 'A. Writer'
    },
    {
      join => {
        'cds' => {
          'liner_notes' => 'author'
        }
      }
    }
  );

  # Equivalent SQL:
  # SELECT artist.* FROM artist
  # JOIN ( cd ON artist.id = cd.artist )
  # JOIN ( liner_notes ON cd.id = liner_notes.cd )
  # JOIN ( author ON author.id = liner_notes.author )
  # WHERE liner_notes.notes LIKE '%some text%'
  # AND author.name = 'A. Writer'

Multi-step prefetch

From 0.04999_05 onwards, prefetch can be nested more than one relationship deep using the same syntax as a multi-step join:

  my $rs = $schema->resultset('Tag')->search(
    undef,
    {
      prefetch => {
        cd => 'artist'
      }
    }
  );

  # Equivalent SQL:
  # SELECT tag.*, cd.*, artist.* FROM tag
  # JOIN cd ON tag.cd = cd.cdid
  # JOIN artist ON cd.artist = artist.artistid

Now accessing our cd and artist relationships does not need additional SQL statements:

  my $tag = $rs->first;
  print $tag->cd->artist->name;

Transactions

As of version 0.04001, there is improved transaction support in DBIx::Class::Storage::DBI and DBIx::Class::Schema. Here is an example of the recommended way to use it:

  my $genus = $schema->resultset('Genus')->find(12);

  my $coderef1 = sub {
    my ($schema, $genus, $code) = @_;
    $genus->add_to_species({ name => 'troglodyte' });
    $genus->wings(2);
    $genus->update;
    $schema->txn_do($code, $genus); # Can have a nested transation
    return $genus->species;
  };

  my $coderef2 = sub {
    my ($genus) = @_;
    $genus->extinct(1);
    $genus->update;
  };

  my $rs;
  eval {
    $rs = $schema->txn_do($coderef1, $schema, $genus, $coderef2);
  };

  if ($@) {                             # Transaction failed
    die "the sky is falling!"           #
      if ($@ =~ /Rollback failed/);     # Rollback failed

    deal_with_failed_transaction();
  }

Nested transactions will work as expected. That is, only the outermost transaction will actually issue a commit to the $dbh, and a rollback at any level of any transaction will cause the entire nested transaction to fail. Support for savepoints and for true nested transactions (for databases that support them) will hopefully be added in the future.

Many-to-many relationships

This is straightforward using DBIx::Class::Relationship::ManyToMany:

  package My::DB;
  # ... set up connection ...

  package My::User;
  use base 'My::DB';
  __PACKAGE__->table('user');
  __PACKAGE__->add_columns(qw/id name/);
  __PACKAGE__->set_primary_key('id');
  __PACKAGE__->has_many('user_address' => 'My::UserAddress', 'user');
  __PACKAGE__->many_to_many('addresses' => 'user_address', 'address');

  package My::UserAddress;
  use base 'My::DB';
  __PACKAGE__->table('user_address');
  __PACKAGE__->add_columns(qw/user address/);
  __PACKAGE__->set_primary_key(qw/user address/);
  __PACKAGE__->belongs_to('user' => 'My::User');
  __PACKAGE__->belongs_to('address' => 'My::Address');

  package My::Address;
  use base 'My::DB';
  __PACKAGE__->table('address');
  __PACKAGE__->add_columns(qw/id street town area_code country/);
  __PACKAGE__->set_primary_key('id');
  __PACKAGE__->has_many('user_address' => 'My::UserAddress', 'address');
  __PACKAGE__->many_to_many('users' => 'user_address', 'user');

  $rs = $user->addresses(); # get all addresses for a user
  $rs = $address->users(); # get all users for an address

Setting default values for a row

It's as simple as overriding the new method. Note the use of next::method.

  sub new {
    my ( $class, $attrs ) = @_;

    $attrs->{foo} = 'bar' unless defined $attrs->{foo};

    $class->next::method($attrs);
  }

Stringification

Employ the standard stringification technique by using the overload module. Replace foo with the column/method of your choice.

  use overload '""' => 'foo', fallback => 1;

Disconnecting cleanly

If you find yourself quitting an app with Control-C a lot during development, you might like to put the following signal handler in your main database class to make sure it disconnects cleanly:

  $SIG{INT} = sub {
    __PACKAGE__->storage->disconnect;
  };

Schema import/export

This functionality requires you to have SQL::Translator (also known as "SQL Fairy") installed.

To create a DBIx::Class schema from an existing database:

 sqlt --from DBI
      --to DBIx::Class::File
      --prefix "MySchema" > MySchema.pm

To create a MySQL database from an existing DBIx::Class schema, convert the schema to MySQL's dialect of SQL:

  sqlt --from DBIx::Class --to MySQL --DBIx::Class "MySchema.pm" > Schema1.sql

And import using the mysql client:

  mysql -h "host" -D "database" -u "user" -p < Schema1.sql

Easy migration from class-based to schema-based setup

You want to start using the schema-based approach to DBIx::Class (see SchemaIntro.pod), but have an established class-based setup with lots of existing classes that you don't want to move by hand. Try this nifty script instead:

  use MyDB;
  use SQL::Translator;
  
  my $schema = MyDB->schema_instance;
  
  my $translator           =  SQL::Translator->new( 
      debug                => $debug          ||  0,
      trace                => $trace          ||  0,
      no_comments          => $no_comments    ||  0,
      show_warnings        => $show_warnings  ||  0,
      add_drop_table       => $add_drop_table ||  0,
      validate             => $validate       ||  0,
      parser_args          => {
         'DBIx::Schema'    => $schema,
                              },
      producer_args   => {
          'prefix'         => 'My::Schema',
                         },
  );
  
  $translator->parser('DBIx::Class');
  $translator->producer('DBIx::Class::File');
  
  my $output = $translator->translate(@args) or die
          "Error: " . $translator->error;
  
  print $output;

You could use Module::Find to search for all subclasses in the MyDB::* namespace, which is currently left as an excercise for the reader.

Schema versioning

The following example shows simplistically how you might use DBIx::Class to deploy versioned schemas to your customers. The basic process is as follows:

  1. Create a DBIx::Class schema
  2. Save the schema
  3. Deploy to customers
  4. Modify schema to change functionality
  5. Deploy update to customers

Create a DBIx::Class schema

This can either be done manually, or generated from an existing database as described under Schema import/export.

Save the schema

Use sqlt to transform your schema into an SQL script suitable for your customer's database. E.g. for MySQL:

  sqlt --from DBIx::Class
       --to MySQL
       --DBIx::Class "MySchema.pm" > Schema1.mysql.sql

If you need to target databases from multiple vendors, just generate an SQL script suitable for each. To support PostgreSQL too:

  sqlt --from DBIx::Class
       --to PostgreSQL
       --DBIx::Class "MySchema.pm" > Schema1.pgsql.sql

Deploy to customers

There are several ways you could deploy your schema. These are probably beyond the scope of this recipe, but might include:

  1. Require customer to apply manually using their RDBMS.
  2. Package along with your app, making database dump/schema update/tests all part of your install.

Modify the schema to change functionality

As your application evolves, it may be necessary to modify your schema to change functionality. Once the changes are made to your schema in DBIx::Class, export the modified schema as before, taking care not to overwrite the original:

  sqlt --from DBIx::Class
       --to MySQL
       --DBIx::Class "Anything.pm" > Schema2.mysql.sql

Next, use sqlt-diff to create an SQL script that will update the customer's database schema:

  sqlt-diff --to MySQL Schema1=MySQL Schema2=MySQL > SchemaUpdate.mysql.sql

Deploy update to customers

The schema update can be deployed to customers using the same method as before.

Setting limit dialect for SQL::Abstract::Limit

In some cases, SQL::Abstract::Limit cannot determine the dialect of the remote SQL-server by looking at the database-handle. This is a common problem when using the DBD::JDBC, since the DBD-driver only know that in has a Java-driver available, not which JDBC-driver the Java component has loaded. This specifically sets the limit_dialect to Microsoft SQL-server (Se more names in SQL::Abstract::Limit -documentation.

  __PACKAGE__->storage->sql_maker->limit_dialect('mssql');

The JDBC-bridge is one way of getting access to a MSSQL-server from a platform that Microsoft doesn't deliver native client libraries for. (e.g. Linux)

Setting quotes for the generated SQL.

If the database contains columnames with spaces and/or reserved words, the SQL-query needs to be quoted. This is done using:

  __PACKAGE__->storage->sql_maker->quote_char([ qw/[ ]/] );
  __PACKAGE__->storage->sql_maker->name_sep('.');

The first sets the quotesymbols. If the quote i "symmetric" as " or '

  __PACKAGE__->storage->sql_maker->quote_char('"');

is enough. If the left qoute differs form the right quote, the first notation should be used. name_sep needs to be set to allow the SQL generator to put the quotes the correct place.

syntax highlighting: