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Man Pages

Manual Reference Pages  -  DBIX::CLASS::MANUAL::COOKBOOK (3)

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



    Paged results

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

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

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

  return $rs->page(2); # records for page 2

You can get 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 ? AND title LIKE ?

And the following bind values for the placeholders: %Lamb%, %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.

    Retrieve one and only one row from a resultset

Sometimes you need only the first top row of a resultset. While this can be easily done with $rs->first, it is suboptimal, as a full blown cursor for the resultset will be created and then immediately destroyed after fetching the first row object. $rs->single is designed specifically for this case - it will grab the first returned result without even instantiating a cursor.

Before replacing all your calls to first() with single() please observe the following CAVEATS:
o While single() takes a search condition just like search() does, it does _not_ accept search attributes. However one can always chain a single() to a search():

  my $top_cd = $cd_rs->search({}, { order_by => rating })->single;

o Since single() is the engine behind find(), it is designed to fetch a single row per database query. Thus a warning will be issued when the underlying SELECT returns more than one row. Sometimes however this usage is valid: i.e. we have an arbitrary number of cd’s but only one of them is at the top of the charts at any given time. If you know what you are doing, you can silence the warning by explicitly limiting the resultset size:

  my $top_cd = $cd_rs->search ({}, { order_by => rating, rows => 1 })->single;

    Arbitrary SQL through a custom ResultSource

Sometimes you have to run arbitrary SQL because your query is too complex (e.g. it contains Unions, Sub-Selects, Stored Procedures, etc.) or has to be optimized for your database in a special way, but you still want to get the results as a DBIx::Class::ResultSet.

This is accomplished by defining a ResultSource::View for your query, almost like you would define a regular ResultSource.

  package My::Schema::Result::UserFriendsComplex;
  use strict;
  use warnings;
  use base qw/DBIx::Class::Core/;


  # For the time being this is necessary even for virtual views

  # ->add_columns, etc.

  # do not attempt to deploy() this view

    SELECT u.* FROM user u
    INNER JOIN user_friends f ON = f.user_id
    WHERE f.friend_user_id = ?
    SELECT u.* FROM user u
    INNER JOIN user_friends f ON = f.friend_user_id
    WHERE f.user_id = ?

Next, you can execute your complex query using bind parameters like this:

  my $friends = $schema->resultset( UserFriendsComplex )->search( {},
      bind  => [ 12345, 12345 ]

... and you’ll get back a perfect DBIx::Class::ResultSet (except, of course, that you cannot modify the rows it contains, e.g. cannot call update or delete on it).

Note that you cannot have bind parameters unless is_virtual is set to true.

If you’re using the old deprecated $rsrc_instance->name(\( SELECT ...) method for custom SQL execution, you are highly encouraged to update your code to use a virtual view as above. If you do not want to change your code, and just want to suppress the deprecation warning when you call deploy in DBIx::Class::Schema, add this line to your source definition, so that deploy will exclude this table:

  sub sqlt_deploy_hook { $_[1]->schema->drop_table ($_[1]) }

    Using specific columns

When you only want specific columns from a table, you can use columns to specify which ones you need. This is useful to avoid loading columns with large amounts of data that you aren’t about to use anyway:

  my $rs = $schema->resultset(Artist)->search(
      columns => [qw/ name /]

  # Equivalent SQL:
  # SELECT FROM artist

This is a shortcut for select and as, see below. columns cannot be used together with select and as.

    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(
      select => [ name, { LENGTH => name } ],
      as     => [qw/ name name_length /],

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

Note that the as attribute <B>has absolutely nothing to doB> with the SQL syntax SELECT foo AS bar (see the documentation in ATTRIBUTES in DBIx::Class::ResultSet). You can control the AS part of the generated SQL via the -as field attribute as follows:

  my $rs = $schema->resultset(Artist)->search(
      join => cds,
      distinct => 1,
      +select => [ { count => cds.cdid, -as => amount_of_cds } ],
      +as => [qw/num_cds/],
      order_by => { -desc => amount_of_cds },

  # Equivalent SQL
  # SELECT me.artistid,, me.rank, me.charfield, COUNT( cds.cdid ) AS amount_of_cds
  #   FROM artist me LEFT JOIN cd cds ON cds.artist = me.artistid
  # GROUP BY me.artistid,, me.rank, me.charfield
  # ORDER BY amount_of_cds DESC

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 have to fetch 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);

See also Using SQL functions on the left hand side of a comparison.

    SELECT DISTINCT with multiple columns

  my $rs = $schema->resultset(Artist)->search(
      columns => [ qw/artist_id name rank/ ],
      distinct => 1

  my $rs = $schema->resultset(Artist)->search(
      columns => [ qw/artist_id name rank/ ],
      group_by => [ qw/artist_id name rank/ ],

  # Equivalent SQL:
  # SELECT me.artist_id,, me.rank
  # FROM artist me
  # GROUP BY artist_id, name, rank


  my $rs = $schema->resultset(Artist)->search(
      columns => [ qw/name/ ],
      distinct => 1

  my $rs = $schema->resultset(Artist)->search(
      columns => [ qw/name/ ],
      group_by => [ qw/name/ ],

  my $count = $rs->count;

  # Equivalent SQL:

    Grouping results

DBIx::Class supports GROUP BY as follows:

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

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

Please see ATTRIBUTES in DBIx::Class::ResultSet documentation if you are in any way unsure about the use of the attributes above ( join , select , as and group_by ).


You can write subqueries relatively easily in DBIC.

  my $inside_rs = $schema->resultset(Artist)->search({
    name => [ Billy Joel, Brittany Spears ],

  my $rs = $schema->resultset(CD)->search({
    artist_id => { -in => $inside_rs->get_column(id)->as_query },

The usual operators ( ’=’, ’!=’, -in, -not_in, etc.) are supported.

<B>NOTEB>: You have to explicitly use ’=’ when doing an equality comparison. The following will <B>notB> work:

  my $rs = $schema->resultset(CD)->search({
    artist_id => $inside_rs->get_column(id)->as_query,  # does NOT work


Subqueries are supported in the where clause (first hashref), and in the from, select, and +select attributes.

Correlated subqueries

  my $cdrs = $schema->resultset(CD);
  my $rs = $cdrs->search({
    year => {
      = => $cdrs->search(
        { artist_id => { -ident => me.artist_id } },
        { alias => sub_query }

That creates the following SQL:

  SELECT me.cdid, me.artist, me.title, me.year, me.genreid, me.single_track
    FROM cd me
  WHERE year = (
    SELECT MAX(sub_query.year)
      FROM cd sub_query
    WHERE artist_id = me.artist_id

    Predefined searches

You can define frequently used searches as methods by subclassing DBIx::Class::ResultSet:

  package My::DBIC::ResultSet::CD;
  use strict;
  use warnings;
  use base DBIx::Class::ResultSet;

  sub search_cds_ordered {
      my ($self) = @_;

      return $self->search(
          { order_by => name DESC },


If you’re using load_namespaces in DBIx::Class::Schema, simply place the file into the ResultSet directory next to your Result directory, and it will be automatically loaded.

If however you are still using load_classes in DBIx::Class::Schema, first tell DBIx::Class to create an instance of the ResultSet class for you, in your My::DBIC::Schema::CD class:

  # class definition as normal
  use base DBIx::Class::Core;

  # tell DBIC to use the custom ResultSet class

Note that resultset_class must be called after load_components and table, or you will get errors about missing methods.

Then call your new method in your code:

   my $ordered_cds = $schema->resultset(CD)->search_cds_ordered();

    Using SQL functions on the left hand side of a comparison

Using SQL functions on the left hand side of a comparison is generally not a good idea since it requires a scan of the entire table. (Unless your RDBMS supports indexes on expressions - including return values of functions - and you create an index on the return value of the function in question.) However, it can be accomplished with DBIx::Class when necessary by resorting to literal SQL:

    \[ YEAR(date_of_birth) = ?, 1979 ]

  # Equivalent SQL:
  # SELECT * FROM employee WHERE YEAR(date_of_birth) = ?

To include the function as part of a larger search, use the ’-and’ keyword to collect the search conditions:

  $rs->search({ -and => [
    name => Bob,
    \[ YEAR(date_of_birth) = ?, 1979 ]

  # Equivalent SQL:
  # SELECT * FROM employee WHERE name = ? AND YEAR(date_of_birth) = ?

Note: the syntax for specifying the bind value’s datatype and value is explained in DBIC BIND VALUES in DBIx::Class::ResultSet.

See also Literal SQL with placeholders and bind values (subqueries) in SQL::Abstract.

    Software Limits

When your RDBMS does not have a working SQL limit mechanism (e.g. Sybase ASE) and GenericSubQ is either too slow or does not work at all, you can try the software_limit DBIx::Class::ResultSet attribute, which skips over records to simulate limits in the Perl layer.

For example:

  my $paged_rs = $rs->search({}, {
    rows => 25,
    page => 3,
    order_by => [ me.last_name ],
    software_limit => 1,

You can set it as a default for your schema by placing the following in your

  __PACKAGE__->default_resultset_attributes({ software_limit => 1 });

<B>WARNING:B> If you are dealing with large resultsets and your DBI or ODBC/ADO driver does not have proper cursor support (i.e. it loads the whole resultset into memory) then this feature will be extremely slow and use huge amounts of memory at best, and may cause your process to run out of memory and cause instability on your server at worst, beware!


    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.

This requires that you have defined the DBIx::Class::Relationship. For example :

  My::Schema::CD->has_many( artists => My::Schema::Artist, artist_id);

To return all CDs matching a particular artist name, you specify the name of the relationship (’artists’):

  my $rs = $schema->resultset(CD)->search(
    { => Bob Marley
      join => artists, # join the artist table

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

In that example both the join, and the condition use the relationship name rather than the table name (see DBIx::Class::Manual::Joining for more details on aliasing ).

If required, you can now sort on any column in the related tables by including it in your order_by attribute, (again using the aliased relation name rather than table name) :

  my $rs = $schema->resultset(CD)->search(
    { => Bob Marley
      join     => artists,
      order_by => [qw/ /]

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

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 = ?

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(
    { => Bob Marley
      join     => artists,
      order_by => [qw/ /],
      prefetch => artists # return artist data too!

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

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.

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!

    Multiple joins

In the examples above, the join attribute was a scalar. If you pass an array reference instead, you can join to multiple tables. In this example, we want to limit the search further, using LinerNotes:

  # Relationships defined elsewhere:
  # CD->belongs_to(artist => Artist);
  # CD->has_one(liner_notes => LinerNotes, cd);
  my $rs = $schema->resultset(CD)->search(
    { => Bob Marley
      liner_notes.notes => { like, %some text% },
      join     => [qw/ artist liner_notes /],
      order_by => [qw/ /],

  # Equivalent SQL:
  # SELECT cd.*, artist.*, liner_notes.* FROM cd
  # JOIN artist ON cd.artist =
  # JOIN liner_notes ON =
  # WHERE = Bob Marley AND liner_notes.notes LIKE %some text%

    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
  # LEFT JOIN cd ON = cd.artist
  # LEFT JOIN liner_notes ON =
  # 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% }, => A. Writer
      join => {
        cds => {
          liner_notes => author

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

    Multi-step and multiple joins

With various combinations of array and hash references, you can join tables in any combination you desire. For example, to join Artist to CD and Concert, and join CD to LinerNotes:

  # Relationships defined elsewhere:
  # Artist->has_many(concerts => Concert, artist);

  my $rs = $schema->resultset(Artist)->search(
    { },
      join => [
          cds => liner_notes

  # Equivalent SQL:
  # SELECT artist.* FROM artist
  # LEFT JOIN cd ON = cd.artist
  # LEFT JOIN liner_notes ON =
  # LEFT JOIN concert ON = concert.artist

    Multi-step prefetch

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

  my $rs = $schema->resultset(Tag)->search(
      prefetch => {
        cd => artist

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

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

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


    Retrieving a result object’s Schema

It is possible to get a Schema object from a result object like so:

  my $schema = $cd->result_source->schema;
  # use the schema as normal:
  my $artist_rs = $schema->resultset(Artist);

This can be useful when you don’t want to pass around a Schema object to every method.

    Getting the value of the primary key for the last database insert

AKA getting last_insert_id

Thanks to the core component PK::Auto, this is straightforward:

  my $foo = $rs->create(\%blah);
  # do more stuff
  my $id = $foo->id; # foo->my_primary_key_field will also work.

If you are not using autoincrementing primary keys, this will probably not work, but then you already know the value of the last primary key anyway.


Employ the standard stringification technique by using the overload module.

To make an object stringify itself as a single column, use something like this (replace name with the column/method of your choice):

  use overload "" => sub { shift->name}, fallback => 1;

For more complex stringification, you can use an anonymous subroutine:

  use overload "" => sub { $_[0]->name . ", " .
                             $_[0]->address }, fallback => 1;

Stringification Example

Suppose we have two tables: Product and Category. The table specifications are:

  Product(id, Description, category)
  Category(id, Description)

category is a foreign key into the Category table.

If you have a Product object $obj and write something like

  print $obj->category

things will not work as expected.

To obtain, for example, the category description, you should add this method to the class defining the Category table:

  use overload "" => sub {
      my $self = shift;

      return $self->Description;
  }, fallback => 1;

    Want to know if find_or_create found or created a row?

Just use find_or_new instead, then check in_storage:

  my $obj = $rs->find_or_new({ blah => blarg });
  unless ($obj->in_storage) {
    # do whatever else you wanted if it was a new row

    Static sub-classing DBIx::Class result classes

AKA adding additional relationships/methods/etc. to a model for a specific usage of the (shared) model.

<B>Schema definitionB>

    package My::App::Schema;

    use base DBIx::Class::Schema;

    # load subclassed classes from My::App::Schema::Result/ResultSet

    # load classes from shared model
        My::Shared::Model::Result => [qw/


<B>Result-Subclass definitionB>

    package My::App::Schema::Result::Baz;

    use strict;
    use warnings;
    use base My::Shared::Model::Result::Baz;

    # WARNING: Make sure you call table() again in your subclass,
    # otherwise DBIx::Class::ResultSourceProxy::Table will not be called
    # and the class name is not correctly registered as a source

    sub additional_method {
        return "Im an additional method only needed by this app";


    Dynamic Sub-classing DBIx::Class proxy classes

AKA multi-class object inflation from one table

DBIx::Class classes are proxy classes, therefore some different techniques need to be employed for more than basic subclassing. In this example we have a single user table that carries a boolean bit for admin. We would like to give the admin users objects (DBIx::Class::Row) the same methods as a regular user but also special admin only methods. It doesn’t make sense to create two separate proxy-class files for this. We would be copying all the user methods into the Admin class. There is a cleaner way to accomplish this.

Overriding the inflate_result method within the User proxy-class gives us the effect we want. This method is called by DBIx::Class::ResultSet when inflating a result from storage. So we grab the object being returned, inspect the values we are looking for, bless it if it’s an admin object, and then return it. See the example below:

<B>Schema DefinitionB>

    package My::Schema;

    use base qw/DBIx::Class::Schema/;



<B>Proxy-Class definitionsB>

    package My::Schema::Result::User;

    use strict;
    use warnings;
    use base qw/DBIx::Class::Core/;

    ### Define what our admin class is, for ensure_class_loaded()
    my $admin_class = __PACKAGE__ . ::Admin;


    __PACKAGE__->add_columns(qw/user_id   email    password
                                firstname lastname active


    sub inflate_result {
        my $self = shift;
        my $ret = $self->next::method(@_);
        if( $ret->admin ) {### If this is an admin, rebless for extra functions
            $self->ensure_class_loaded( $admin_class );
            bless $ret, $admin_class;
        return $ret;

    sub hello {
        print "I am a regular user.\n";
        return ;


    package My::Schema::Result::User::Admin;

    use strict;
    use warnings;
    use base qw/My::Schema::Result::User/;

    # This line is important

    sub hello
        print "I am an admin.\n";

    sub do_admin_stuff
        print "I am doing admin stuff\n";
        return ;


<B>Test FileB>

    use warnings;
    use strict;
    use My::Schema;

    my $user_data = { email    =>,
                      password => pass1,
                      admin    => 0 };

    my $admin_data = { email    =>,
                       password => pass2,
                       admin    => 1 };

    my $schema = My::Schema->connection(dbi:Pg:dbname=test);

    $schema->resultset(User)->create( $user_data );
    $schema->resultset(User)->create( $admin_data );

    ### Now we search for them
    my $user = $schema->resultset(User)->single( $user_data );
    my $admin = $schema->resultset(User)->single( $admin_data );

    print ref $user, "\n";
    print ref $admin, "\n";

    print $user->password , "\n"; # pass1
    print $admin->password , "\n";# pass2; inherited from User
    print $user->hello , "\n";# I am a regular user.
    print $admin->hello, "\n";# I am an admin.

    ### The statement below will NOT print
    print "I can do admin stuff\n" if $user->can(do_admin_stuff);
    ### The statement below will print
    print "I can do admin stuff\n" if $admin->can(do_admin_stuff);

Alternatively you can use DBIx::Class::DynamicSubclass that implements exactly the above functionality.

    Skip result object creation for faster results

DBIx::Class is not built for speed, it’s built for convenience and ease of use, but sometimes you just need to get the data, and skip the fancy objects.

To do this simply use DBIx::Class::ResultClass::HashRefInflator.

 my $rs = $schema->resultset(CD);


 my $hash_ref = $rs->find(1);

Wasn’t that easy?

Beware, changing the Result class using result_class in DBIx::Class::ResultSet will replace any existing class completely including any special components loaded using load_components, eg DBIx::Class::InflateColumn::DateTime.

    Get raw data for blindingly fast results

If the HashRefInflator solution above is not fast enough for you, you can use a DBIx::Class to return values exactly as they come out of the database with none of the convenience methods wrapped round them.

This is used like so:

  my $cursor = $rs->cursor
  while (my @vals = $cursor->next) {
      # use $val[0..n] here

You will need to map the array offsets to particular columns (you can use the select in DBIx::Class::ResultSet attribute of search in DBIx::Class::ResultSet to force ordering).


    Getting Schema from a ResultSet

To get the DBIx::Class::Schema object from a ResultSet, do the following:


    Getting Columns Of Data

AKA Aggregating Data

If you want to find the sum of a particular column there are several ways, the obvious one is to use search:

  my $rs = $schema->resultset(Items)->search(
       select => [ { sum => Cost } ],
       as     => [ total_cost ], # remember this as is for DBIx::Class::ResultSet not SQL
  my $tc = $rs->first->get_column(total_cost);

Or, you can use the DBIx::Class::ResultSetColumn, which gets returned when you ask the ResultSet for a column using get_column:

  my $cost = $schema->resultset(Items)->get_column(Cost);
  my $tc = $cost->sum;

With this you can also do:

  my $minvalue = $cost->min;
  my $maxvalue = $cost->max;

Or just iterate through the values of this column only:

  while ( my $c = $cost->next ) {
    print $c;

  foreach my $c ($cost->all) {
    print $c;

ResultSetColumn only has a limited number of built-in functions. If you need one that it doesn’t have, then you can use the func method instead:

  my $avg = $cost->func(AVERAGE);

This will cause the following SQL statement to be run:


Which will of course only work if your database supports this function. See DBIx::Class::ResultSetColumn for more documentation.

    Creating a result set from a set of rows

Sometimes you have a (set of) result objects that you want to put into a resultset without the need to hit the DB again. You can do that by using the set_cache method:

 my @uploadable_groups;
 while (my $group = $groups->next) {
   if ($group->can_upload($self)) {
     push @uploadable_groups, $group;
 my $new_rs = $self->result_source->resultset;
 return $new_rs;


    Create a new row in a related table

  my $author = $book->create_related(author, { name => Fred});

    Search in a related table

Only searches for books named ’Titanic’ by the author in $author.

  my $books_rs = $author->search_related(books, { name => Titanic });

    Delete data in a related table

Deletes only the book named Titanic by the author in $author.

  $author->delete_related(books, { name => Titanic });

    Ordering a relationship result set

If you always want a relation to be ordered, you can specify this when you create the relationship.

To order $book->pages by descending page_number, create the relation as follows:

  __PACKAGE__->has_many(pages => Page, book, { order_by => { -desc => page_number} } );

    Filtering a relationship result set

If you want to get a filtered result set, you can just add to $attr as follows:

 __PACKAGE__->has_many(pages => Page, book, { where => { scrap => 0 } } );

    Many-to-many relationship bridges

This is straightforward using ManyToMany:

  package My::User;
  use base DBIx::Class::Core;
  __PACKAGE__->add_columns(qw/id name/);
  __PACKAGE__->has_many(user_address => My::UserAddress, user);
  __PACKAGE__->many_to_many(addresses => user_address, address);

  package My::UserAddress;
  use base DBIx::Class::Core;
  __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 DBIx::Class::Core;
  __PACKAGE__->add_columns(qw/id street town area_code country/);
  __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

  my $address = $user->add_to_addresses(    # returns a My::Address instance,
                                            # NOT a My::UserAddress instance!
      country => United Kingdom,
      area_code => XYZ,
      town => London,
      street => Sesame,

    Relationships across DB schemas

Mapping relationships across DB schemas is easy as long as the schemas themselves are all accessible via the same DBI connection. In most cases, this means that they are on the same database host as each other and your connecting database user has the proper permissions to them.

To accomplish this one only needs to specify the DB schema name in the table declaration, like so...

  package MyApp::Schema::Result::Artist;
  use base qw/DBIx::Class::Core/;

  __PACKAGE__->table(database1.artist); # will use "database1.artist" in FROM clause

  __PACKAGE__->add_columns(qw/ artist_id name /);
  __PACKAGE__->has_many(cds => MyApp::Schema::Result::Cd);


Whatever string you specify there will be used to build the FROM clause in SQL queries.

The big drawback to this is you now have DB schema names hardcoded in your class files. This becomes especially troublesome if you have multiple instances of your application to support a change lifecycle (e.g. DEV, TEST, PROD) and the DB schemas are named based on the environment (e.g. database1_dev).

However, one can dynamically map to the proper DB schema by overriding the connection method in your Schema class and building a renaming facility, like so:

  package MyApp::Schema;
  use Moose;

  extends DBIx::Class::Schema;

  around connection => sub {
    my ( $inner, $self, $dsn, $username, $pass, $attr ) = ( shift, @_ );

    my $postfix = delete $attr->{schema_name_postfix};


    if ( $postfix ) {

  sub append_db_name {
    my ( $self, $postfix ) = @_;

    my @sources_with_db
        = grep
            { $_->name =~ /^\w+\./mx }
                { $self->source($_) }

    foreach my $source (@sources_with_db) {
        my $name = $source->name;
        $name =~ s{^(\w+)\.}{${1}${postfix}\.}mx;



By overriding the connection method and extracting a custom option from the provided \%attr hashref one can then simply iterate over all the Schema’s ResultSources, renaming them as needed.

To use this facility, simply add or modify the \%attr hashref that is passed to connection, as follows:

  my $schema
    = MyApp::Schema->connect(
        schema_name_postfix => _dev
        # ... Other options as desired ...

Obviously, one could accomplish even more advanced mapping via a hash map or a callback routine.


    Transactions with txn_do

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

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

  my $coderef2 = sub {

  my $coderef1 = sub {
    $genus->add_to_species({ name => troglodyte });
    $schema->txn_do($coderef2); # Can have a nested transaction. Only the outer will actualy commit
    return $genus->species;

  use Try::Tiny;
  my $rs;
  try {
    $rs = $schema->txn_do($coderef1);
  } catch {
    # Transaction failed
    die "the sky is falling!"           #
      if ($_ =~ /Rollback failed/);     # Rollback failed


Note: by default txn_do will re-run the coderef one more time if an error occurs due to client disconnection (e.g. the server is bounced). You need to make sure that your coderef can be invoked multiple times without terrible side effects.

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.

    Nested transactions and auto-savepoints

If savepoints are supported by your RDBMS, it is possible to achieve true nested transactions with minimal effort. To enable auto-savepoints via nested transactions, supply the auto_savepoint = 1 connection attribute.

Here is an example of true nested transactions. In the example, we start a big task which will create several rows. Generation of data for each row is a fragile operation and might fail. If we fail creating something, depending on the type of failure, we want to abort the whole task, or only skip the failed row.

  my $schema = MySchema->connect("dbi:Pg:dbname=my_db");

  # Start a transaction. Every database change from here on will only be
  # committed into the database if the try block succeeds.
  use Try::Tiny;
  my $exception;
  try {
    $schema->txn_do(sub {
      # SQL: BEGIN WORK;

      my $job = $schema->resultset(Job)->create({ name=> big job });
      # SQL: INSERT INTO job ( name) VALUES ( big job );

      for (1..10) {

        # Start a nested transaction, which in fact sets a savepoint.
        try {
          $schema->txn_do(sub {
            # SQL: SAVEPOINT savepoint_0;

            my $thing = $schema->resultset(Thing)->create({ job=>$job->id });
            # SQL: INSERT INTO thing ( job) VALUES ( 1 );

            if (rand > 0.8) {
              # This will generate an error, thus setting $@

              # SQL: UPDATE thing SET force_fail = foo
              #      WHERE ( id = 42 );
        } catch {
          # SQL: ROLLBACK TO SAVEPOINT savepoint_0;

          # There was an error while creating a $thing. Depending on the error
          # we want to abort the whole transaction, or only rollback the
          # changes related to the creation of this $thing

          # Abort the whole job
          if ($_ =~ /horrible_problem/) {
            print "something horrible happend, aborting job!";
            die $_;                # rethrow error

          # Ignore this $thing, report the error, and continue with the
          # next $thing
          print "Cannot create thing: $_";
        # There was no error, so save all changes since the last
        # savepoint.

        # SQL: RELEASE SAVEPOINT savepoint_0;
  } catch {
    $exception = $_;

  if ($exception) {
    # There was an error while handling the $job. Rollback all changes
    # since the transaction started, including the already committed
    # (released) savepoints. There will be neither a new $job nor any
    # $thing entry in the database.


    print "ERROR: $exception\n";
  else {
    # There was no error while handling the $job. Commit all changes.
    # Only now other connections can see the newly created $job and
    # @things.

    # SQL: COMMIT;

    print "Ok\n";

In this example it might be hard to see where the rollbacks, releases and commits are happening, but it works just the same as for plain txn_do: If the try-block around txn_do fails, a rollback is issued. If the try succeeds, the transaction is committed (or the savepoint released).

While you can get more fine-grained control using svp_begin, svp_release and svp_rollback, it is strongly recommended to use txn_do with coderefs.

    Simple Transactions with DBIx::Class::Storage::TxnScopeGuard

An easy way to use transactions is with DBIx::Class::Storage::TxnScopeGuard. See Automatically creating related objects for an example.

Note that unlike txn_do, TxnScopeGuard will only make sure the connection is alive when issuing the BEGIN statement. It will not (and really can not) retry if the server goes away mid-operations, unlike txn_do.


    Creating Schemas From An Existing Database

DBIx::Class::Schema::Loader will connect to a database and create a DBIx::Class::Schema and associated sources by examining the database.

The recommend way of achieving this is to use the dbicdump utility or the Catalyst helper, as described in Manual::Intro.

Alternatively, use the make_schema_at method:

  perl -MDBIx::Class::Schema::Loader=make_schema_at,dump_to_dir:./lib \
    -e make_schema_at("My::Schema", \
    { db_schema => myschema, components => ["InflateColumn::DateTime"] }, \
    [ "dbi:Pg:dbname=foo", "username", "password" ])

This will create a tree of files rooted at ./lib/My/Schema/ containing source definitions for all the tables found in the myschema schema in the foo database.

    Creating DDL SQL

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

To create a set of database-specific .sql files for the above schema:

 my $schema = My::Schema->connect($dsn);
 $schema->create_ddl_dir([MySQL, SQLite, PostgreSQL],

By default this will create schema files in the current directory, for MySQL, SQLite and PostgreSQL, using the $VERSION from your

To create a new database using the schema:

 my $schema = My::Schema->connect($dsn);
 $schema->deploy({ add_drop_table => 1});

To import created .sql files using the mysql client:

  mysql -h "host" -D "database" -u "user" -p < My_Schema_1.0_MySQL.sql

To create ALTER TABLE conversion scripts to update a database to a newer version of your schema at a later point, first set a new $VERSION in your Schema file, then:

 my $schema = My::Schema->connect($dsn);
 $schema->create_ddl_dir([MySQL, SQLite, PostgreSQL],

This will produce new database-specific .sql files for the new version of the schema, plus scripts to convert from version 0.1 to 0.2. This requires that the files for 0.1 as created above are available in the given directory to diff against.

    Select from dual

Dummy tables are needed by some databases to allow calling functions or expressions that aren’t based on table content, for examples of how this applies to various database types, see: <>.

Note: If you’re using Oracles dual table don’t <B>everB> do anything other than a select, if you CRUD on your dual table you *will* break your database.

Make a table class as you would for any other table

  package MyAppDB::Dual;
  use strict;
  use warnings;
  use base DBIx::Class::Core;
    { data_type => "VARCHAR2", is_nullable => 0, size => 1 },

Once you’ve loaded your table class select from it using select and as instead of columns

  my $rs = $schema->resultset(Dual)->search(undef,
    { select => [ sydate ],
      as     => [ now ]

All you have to do now is be careful how you access your resultset, the below will not work because there is no column called ’now’ in the Dual table class

  while (my $dual = $rs->next) {
    print $dual->now."\n";
  # Cant locate object method "now" via package "MyAppDB::Dual" at line 23.

You could of course use ’dummy’ in as instead of ’now’, or add_columns to your Dual class for whatever you wanted to select from dual, but that’s just silly, instead use get_column

  while (my $dual = $rs->next) {
    print $dual->get_column(now)."\n";

Or use cursor

  my $cursor = $rs->cursor;
  while (my @vals = $cursor->next) {
    print $vals[0]."\n";

In case you’re going to use this trick together with deploy in DBIx::Class::Schema or create_ddl_dir in DBIx::Class::Schema a table called dual will be created in your current schema. This would overlap sys.dual and you could not fetch sysdate or sequence.nextval anymore from dual. To avoid this problem, just tell SQL::Translator to not create table dual:

    my $sqlt_args = {
        add_drop_table => 1,
        parser_args    => { sources => [ grep $_ ne Dual, schema->sources ] },
    $schema->create_ddl_dir( [qw/Oracle/], undef, ./sql, undef, $sqlt_args );

Or use DBIx::Class::ResultClass::HashRefInflator

  while ( my $dual = $rs->next ) {
    print $dual->{now}."\n";

Here are some example select conditions to illustrate the different syntax you could use for doing stuff like oracles.heavily(nested(functions_can(take, lots), OF), args)

  # get a sequence value
  select => [ A_SEQ.nextval ],

  # get create table sql
  select => [ { dbms_metadata.get_ddl => [ "TABLE", "ARTIST" ]} ],

  # get a random num between 0 and 100
  select => [ { "trunc" => [ { "dbms_random.value" => [0,100] } ]} ],

  # what year is it?
  select => [ { extract => [ \year from sysdate ] } ],

  # do some math
  select => [ {round => [{cos => [ \180 * 3.14159265359/180 ]}]}],

  # which day of the week were you born on?
  select => [{to_char => [{to_date => [ "25-DEC-1980", "dd-mon-yyyy" ]}, "day"]}],

  # select 16 rows from dual
  select   => [ "hello" ],
  as       => [ world ],
  group_by => [ cube( 1, 2, 3, 4 ) ],

    Adding Indexes And Functions To Your SQL

Often you will want indexes on columns on your table to speed up searching. To do this, create a method called sqlt_deploy_hook in the relevant source class (refer to the advanced callback system if you wish to share a hook between multiple sources):

 package My::Schema::Result::Artist;

 __PACKAGE__->add_columns(id => { ... }, name => { ... })

 sub sqlt_deploy_hook {
   my ($self, $sqlt_table) = @_;

   $sqlt_table->add_index(name => idx_name, fields => [name]);


Sometimes you might want to change the index depending on the type of the database for which SQL is being generated:

  my ($db_type = $sqlt_table->schema->translator->producer_type)
    =~ s/^SQL::Translator::Producer:://;

You can also add hooks to the schema level to stop certain tables being created:

 package My::Schema;


 sub sqlt_deploy_hook {
   my ($self, $sqlt_schema) = @_;


You could also add views, procedures or triggers to the output using add_view in SQL::Translator::Schema, add_procedure in SQL::Translator::Schema or add_trigger in SQL::Translator::Schema.

    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
<B>Create a DBIx::Class schemaB>

This can either be done manually, or generated from an existing database as described under Creating Schemas From An Existing Database

<B>Save the schemaB>

Call create_ddl_dir in DBIx::Class::Schema as above under Creating DDL SQL.

<B>Deploy to customersB>

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.
<B>Modify the schema to change functionalityB>

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 and the conversion scripts as in Creating DDL SQL.

<B>Deploy update to customersB>

Add the DBIx::Class::Schema::Versioned schema component to your Schema class. This will add a new table to your database called dbix_class_schema_vesion which will keep track of which version is installed and warn if the user tries to run a newer schema version than the database thinks it has.

Alternatively, you can send the conversion SQL scripts to your customers as above.

    Setting quoting for the generated SQL

If the database contains column names with spaces and/or reserved words, they need to be quoted in the SQL queries. This is done using:

 $schema->storage->sql_maker->quote_char([ qw/[ ]/] );

The first sets the quote characters. Either a pair of matching brackets, or a " or :


Check the documentation of your database for the correct quote characters to use. name_sep needs to be set to allow the SQL generator to put the quotes the correct place, and defaults to . if not supplied.

In most cases you should set these as part of the arguments passed to connect in DBIx::Class::Schema:

 my $schema = My::Schema->connect(
    quote_char => ",
    name_sep   => .

In some cases, quoting will be required for all users of a schema. To enforce this, you can also overload the connection method for your schema class:

 sub connection {
     my $self = shift;
     my $rv = $self->next::method( @_ );
     $rv->storage->sql_maker->quote_char([ qw/[ ]/ ]);
     return $rv;

    Working with PostgreSQL array types

You can also assign values to PostgreSQL array columns by passing array references in the \%columns (\%vals) hashref of the create in DBIx::Class::ResultSet and update in DBIx::Class::Row family of methods:

    numbers => [1, 2, 3]

      numbers => [1, 2, 3]
      day => 2008-11-24

In conditions (e.g. \%cond in the search in DBIx::Class::ResultSet family of methods) you cannot directly use array references (since this is interpreted as a list of values to be ORed), but you can use the following syntax to force passing them as bind values:

      numbers => \[ = ?, [numbers => [1, 2, 3]] ]

See array_datatypes in SQL::Abstract and Literal SQL with placeholders and bind values (subqueries) in SQL::Abstract for more explanation. Note that DBIx::Class sets bindtype in SQL::Abstract to columns, so you must pass the bind values (the [1, 2, 3] arrayref in the above example) wrapped in arrayrefs together with the column name, like this: [column_name => value].

    Formatting DateTime objects in queries

To ensure WHERE conditions containing DateTime arguments are properly formatted to be understood by your RDBMS, you must use the DateTime formatter returned by datetime_parser in DBIx::Class::Storage::DBI to format any DateTime objects you pass to search conditions. Any Storage object attached to your Schema provides a correct DateTime formatter, so all you have to do is:

  my $dtf = $schema->storage->datetime_parser;
  my $rs = $schema->resultset(users)->search(
      signup_date => {
        -between => [

Without doing this the query will contain the simple stringification of the DateTime object, which almost never matches the RDBMS expectations.

This kludge is necessary only for conditions passed to search and find in DBIx::Class::ResultSet, whereas create and update in DBIx::Class::Row (but not update in DBIx::Class::ResultSet) are DBIx::Class::InflateColumn-aware and will do the right thing when supplied an inflated DateTime object.

    Using Unicode

When using unicode character data there are two alternatives - either your database supports unicode characters (including setting the utf8 flag on the returned string), or you need to encode/decode data appropriately each time a string field is inserted into or retrieved from the database. It is better to avoid encoding/decoding data and to use your database’s own unicode capabilities if at all possible.

The DBIx::Class::UTF8Columns component handles storing selected unicode columns in a database that does not directly support unicode. If used with a database that does correctly handle unicode then strange and unexpected data corrupt <B>willB> occur.

The Catalyst Wiki Unicode page at <> has additional information on the use of Unicode with Catalyst and DBIx::Class.

The following databases do correctly handle unicode data:-


MySQL supports unicode, and will correctly flag utf8 data from the database if the mysql_enable_utf8 is set in the connect options.

  my $schema = My::Schema->connection(dbi:mysql:dbname=test,
                                      $user, $pass,
                                      { mysql_enable_utf8 => 1} );

When set, a data retrieved from a textual column type (char, varchar, etc) will have the UTF-8 flag turned on if necessary. This enables character semantics on that string. You will also need to ensure that your database / table / column is configured to use UTF8. See Chapter 10 of the mysql manual for details.

See DBD::mysql for further details.


Information about Oracle support for unicode can be found in UNICODE in DBD::Oracle.


PostgreSQL supports unicode if the character set is correctly set at database creation time. Additionally the pg_enable_utf8 should be set to ensure unicode data is correctly marked.

  my $schema = My::Schema->connection(dbi:Pg:dbname=test,
                                      $user, $pass,
                                      { pg_enable_utf8 => 1} );

Further information can be found in DBD::Pg.


SQLite version 3 and above natively use unicode internally. To correctly mark unicode strings taken from the database, the sqlite_unicode flag should be set at connect time (in versions of DBD::SQLite prior to 1.27 this attribute was named unicode).

  my $schema = My::Schema->connection(dbi:SQLite:/tmp/test.db,
                                      , ,
                                      { sqlite_unicode => 1} );


    Easy migration from class-based to schema-based setup

You want to start using the schema-based approach to DBIx::Class (see Setting it up manually in DBIx::Class::Manual::Intro), 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,


  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 exercise for the reader.


DBIx::Class uses the Class::C3 package, which provides for redispatch of method calls, useful for things like default values and triggers. You have to use calls to next::method to overload methods. More information on using Class::C3 with DBIx::Class can be found in DBIx::Class::Manual::Component.

    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};

    my $new = $class->next::method($attrs);

    return $new;

For more information about next::method, look in the Class::C3 documentation. See also DBIx::Class::Manual::Component for more ways to write your own base classes to do this.

People looking for ways to do triggers with DBIx::Class are probably just looking for this.

    Changing one field whenever another changes

For example, say that you have three columns, id, number, and squared. You would like to make changes to number and have squared be automagically set to the value of number squared. You can accomplish this by wrapping the number accessor with the around method modifier, available through either Class::Method::Modifiers, Moose or Moose-like modules):

  around number => sub {
    my ($orig, $self) = (shift, shift);

    if (@_) {
      my $value = $_[0];
      $self->squared( $value * $value );


Note that the hard work is done by the call to $self->$orig, which redispatches your call to store_column in the superclass(es).

Generally, if this is a calculation your database can easily do, try and avoid storing the calculated value, it is safer to calculate when needed, than rely on the data being in sync.

    Automatically creating related objects

You might have a class Artist which has many CDs. Further, you want to create a CD object every time you insert an Artist object. You can accomplish this by overriding insert on your objects:

  sub insert {
    my ( $self, @args ) = @_;
    $self->create_related (cds, \%initial_cd_data );
    return $self;

If you want to wrap the two inserts in a transaction (for consistency, an excellent idea), you can use the awesome DBIx::Class::Storage::TxnScopeGuard:

  sub insert {
    my ( $self, @args ) = @_;

    my $guard = $self->result_source->schema->txn_scope_guard;

    $self->create_related (cds, \%initial_cd_data );


    return $self

    Wrapping/overloading a column accessor


Say you have a table Camera and want to associate a description with each camera. For most cameras, you’ll be able to generate the description from the other columns. However, in a few special cases you may want to associate a custom description with a camera.


In your database schema, define a description field in the Camera table that can contain text and null values.

In DBIC, we’ll overload the column accessor to provide a sane default if no custom description is defined. The accessor will either return or generate the description, depending on whether the field is null or not.

First, in your Camera schema class, define the description field as follows:

  __PACKAGE__->add_columns(description => { accessor => _description });

Next, we’ll define the accessor-wrapper subroutine:

  sub description {
      my $self = shift;

      # If there is an update to the column, well let the original accessor
      # deal with it.
      return $self->_description(@_) if @_;

      # Fetch the column value.
      my $description = $self->_description;

      # If theres something in the description field, then just return that.
      return $description if defined $description && length $descripton;

      # Otherwise, generate a description.
      return $self->generate_description;


    DBIx::Class objects with Data::Dumper

Data::Dumper can be a very useful tool for debugging, but sometimes it can be hard to find the pertinent data in all the data it can generate. Specifically, if one naively tries to use it like so,

  use Data::Dumper;

  my $cd = $schema->resultset(CD)->find(1);
  print Dumper($cd);

several pages worth of data from the CD object’s schema and result source will be dumped to the screen. Since usually one is only interested in a few column values of the object, this is not very helpful.

Luckily, it is possible to modify the data before Data::Dumper outputs it. Simply define a hook that Data::Dumper will call on the object before dumping it. For example,

  package My::DB::CD;

  sub _dumper_hook {
    $_[0] = bless {
      %{ $_[0] },
      result_source => undef,
    }, ref($_[0]);


  use Data::Dumper;

  local $Data::Dumper::Freezer = _dumper_hook;

  my $cd = $schema->resultset(CD)->find(1);
  print Dumper($cd);
         # dumps $cd without its ResultSource

If the structure of your schema is such that there is a common base class for all your table classes, simply put a method similar to _dumper_hook in the base class and set $Data::Dumper::Freezer to its name and Data::Dumper will automagically clean up your data before printing it. See EXAMPLES in Data::Dumper for more information.


When you enable DBIx::Class::Storage’s debugging it prints the SQL executed as well as notifications of query completion and transaction begin/commit. If you’d like to profile the SQL you can subclass the DBIx::Class::Storage::Statistics class and write your own profiling mechanism:

  package My::Profiler;
  use strict;

  use base DBIx::Class::Storage::Statistics;

  use Time::HiRes qw(time);

  my $start;

  sub query_start {
    my $self = shift();
    my $sql = shift();
    my @params = @_;

    $self->print("Executing $sql: ".join(, , @params)."\n");
    $start = time();

  sub query_end {
    my $self = shift();
    my $sql = shift();
    my @params = @_;

    my $elapsed = sprintf("%0.4f", time() - $start);
    $self->print("Execution took $elapsed seconds.\n");
    $start = undef;


You can then install that class as the debugging object:

  __PACKAGE__->storage->debugobj(new My::Profiler());

A more complicated example might involve storing each execution of SQL in an array:

  sub query_end {
    my $self = shift();
    my $sql = shift();
    my @params = @_;

    my $elapsed = time() - $start;
    push(@{ $calls{$sql} }, {
        params => \@params,
        elapsed => $elapsed

You could then create average, high and low execution times for an SQL statement and dig down to see if certain parameters cause aberrant behavior. You might want to check out DBIx::Class::QueryLog as well.


o Install Class::XSAccessor to speed up Class::Accessor::Grouped.
o On Perl 5.8 install Class::C3::XS.
o prefetch relationships, where possible. See Using joins and prefetch.
o Use populate in void context to insert data when you don’t need the resulting result objects, if possible, but see the caveats.

When inserting many rows, for best results, populate a large number of rows at a time, but not so large that the table is locked for an unacceptably long time.

If using create instead, use a transaction and commit every X rows; where X gives you the best performance without locking the table for too long.

o When selecting many rows, if you don’t need full-blown DBIx::Class::Row objects, consider using DBIx::Class::ResultClass::HashRefInflator.
o See also STARTUP SPEED and MEMORY USAGE in this document.


DBIx::Class programs can have a significant startup delay as the ORM loads all the relevant classes. This section examines techniques for reducing the startup delay.

These tips are listed in order of decreasing effectiveness - so the first tip, if applicable, should have the greatest effect on your application.

    Statically Define Your Schema

If you are using DBIx::Class::Schema::Loader to build the classes dynamically based on the database schema then there will be a significant startup delay.

For production use a statically defined schema (which can be generated using DBIx::Class::Schema::Loader to dump the database schema once - see make_schema_at and dump_directory for more details on creating static schemas from a database).

    Move Common Startup into a Base Class

Typically DBIx::Class result classes start off with

    use base qw/DBIx::Class::Core/;

If this preamble is moved into a common base class:-

    package MyDBICbase;

    use base qw/DBIx::Class::Core/;

and each result class then uses this as a base:-

    use base qw/MyDBICbase/;

then the load_components is only performed once, which can result in a considerable startup speedup for schemas with many classes.

    Explicitly List Schema Result Classes

The schema class will normally contain


to load the result classes. This will use Module::Find to find and load the appropriate modules. Explicitly defining the classes you wish to load will remove the overhead of Module::Find and the related directory operations:

    __PACKAGE__->load_classes(qw/ CD Artist Track /);

If you are instead using the load_namespaces syntax to load the appropriate classes there is not a direct alternative avoiding Module::Find.


    Cached statements

DBIx::Class normally caches all statements with prepare_cached(). This is normally a good idea, but if too many statements are cached, the database may use too much memory and may eventually run out and fail entirely. If you suspect this may be the case, you may want to examine DBI’s CachedKids hash:

    # print all currently cached prepared statements
    print for keys %{$schema->storage->dbh->{CachedKids}};
    # get a count of currently cached prepared statements
    my $count = scalar keys %{$schema->storage->dbh->{CachedKids}};

If it’s appropriate, you can simply clear these statements, automatically deallocating them in the database:

    my $kids = $schema->storage->dbh->{CachedKids};
    delete @{$kids}{keys %$kids} if scalar keys %$kids > 100;

But what you probably want is to expire unused statements and not those that are used frequently. You can accomplish this with Tie::Cache or Tie::Cache::LRU:

    use Tie::Cache;
    use DB::Main;
    my $schema = DB::Main->connect($dbi_dsn, $user, $pass, {
        on_connect_do => sub { tie %{shift->_dbh->{CachedKids}}, Tie::Cache, 100 },


Check the list of additional DBIC resources.


This module is free software copyright by the DBIx::Class (DBIC) authors. You can redistribute it and/or modify it under the same terms as the DBIx::Class library.
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