Provided by: libdbix-class-perl_0.08250-2_all 
NAME
DBIx::Class::Manual::Cookbook - Miscellaneous 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 defined 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
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:
• 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;
• 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 = $cd_rs->search ({}, { order_by => 'rating', rows => 1 })->single;
Arbitrary SQL through a custom ResultSource
Sometimes you have to run arbitrary SQL because your query is too complex (e.g. it
contains Unions, Sub-Selects, Stored Procedures, etc.) or has to be optimized for your
database in a special way, but you still want to get the results as a
DBIx::Class::ResultSet.
This is accomplished by defining a ResultSource::View for your query, almost like you
would define a regular ResultSource.
package My::Schema::Result::UserFriendsComplex;
use strict;
use warnings;
use base qw/DBIx::Class::Core/;
__PACKAGE__->table_class('DBIx::Class::ResultSource::View');
# For the time being this is necessary even for virtual views
__PACKAGE__->table($view_name);
#
# ->add_columns, etc.
#
# do not attempt to deploy() this view
__PACKAGE__->result_source_instance->is_virtual(1);
__PACKAGE__->result_source_instance->view_definition(q[
SELECT u.* FROM user u
INNER JOIN user_friends f ON u.id = f.user_id
WHERE f.friend_user_id = ?
UNION
SELECT u.* FROM user u
INNER JOIN user_friends f ON u.id = f.friend_user_id
WHERE f.user_id = ?
]);
Next, you can execute your complex query using bind parameters like this:
my $friends = $schema->resultset( 'UserFriendsComplex' )->search( {},
{
bind => [ 12345, 12345 ]
}
);
... and you'll get back a perfect DBIx::Class::ResultSet (except, of course, that you
cannot modify the rows it contains, e.g. cannot call "update", "delete", ... on it).
Note that you cannot have bind parameters unless is_virtual is set to true.
• NOTE
If you're using the old deprecated "$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(
undef,
{
columns => [qw/ name /]
}
);
# Equivalent SQL:
# SELECT artist.name 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 has absolutely nothing to do 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.name, 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.name, 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.name, me.rank
# FROM artist me
# GROUP BY artist_id, name, rank
SELECT COUNT(DISTINCT colname)
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:
# SELECT COUNT( * ) FROM (SELECT me.name FROM artist me GROUP BY me.name) me:
Grouping results
DBIx::Class supports "GROUP BY" as follows:
my $rs = $schema->resultset('Artist')->search(
{},
{
join => [qw/ cds /],
select => [ 'name', { count => 'cds.id' } ],
as => [qw/ name cd_count /],
group_by => [qw/ name /]
}
);
# Equivalent SQL:
# SELECT name, COUNT( cd.id ) FROM artist
# LEFT JOIN cd ON artist.id = 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
").
Subqueries
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.
NOTE: You have to explicitly use '=' when doing an equality comparison. The following
will not work:
my $rs = $schema->resultset('CD')->search({
artist_id => $inside_rs->get_column('id')->as_query, # does NOT work
});
Support
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 => {
'=' => $cdrs->search(
{ artist_id => { -ident => 'me.artist_id' } },
{ alias => 'sub_query' }
)->get_column('year')->max_rs->as_query,
},
});
That creates the following SQL:
SELECT me.cdid, me.artist, me.title, me.year, me.genreid, me.single_track
FROM cd me
WHERE year = (
SELECT MAX(sub_query.year)
FROM cd sub_query
WHERE artist_id = me.artist_id
)
Predefined searches
You can define frequently used searches as methods by subclassing DBIx::Class::ResultSet:
package My::DBIC::ResultSet::CD;
use strict;
use warnings;
use base 'DBIx::Class::ResultSet';
sub search_cds_ordered {
my ($self) = @_;
return $self->search(
{},
{ order_by => 'name DESC' },
);
}
1;
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';
__PACKAGE__->table('cd');
# tell DBIC to use the custom ResultSet class
__PACKAGE__->resultset_class('My::DBIC::ResultSet::CD');
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:
$rs->search(
\[ '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 "Schema.pm":
__PACKAGE__->default_resultset_attributes({ software_limit => 1 });
WARNING: 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!
JOINS AND PREFETCHING
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(
{
'artists.name' => 'Bob Marley'
},
{
join => 'artists', # join the artist table
}
);
# Equivalent SQL:
# SELECT cd.* FROM cd
# JOIN artist ON cd.artist = artist.id
# WHERE artist.name = '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(
{
'artists.name' => 'Bob Marley'
},
{
join => 'artists',
order_by => [qw/ artists.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(
{
'artists.name' => 'Bob Marley'
},
{
join => 'artists',
order_by => [qw/ artists.name /],
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 = 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.
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(
{
'artist.name' => 'Bob Marley'
'liner_notes.notes' => { 'like', '%some text%' },
},
{
join => [qw/ artist liner_notes /],
order_by => [qw/ artist.name /],
}
);
# Equivalent SQL:
# SELECT cd.*, artist.*, liner_notes.* FROM cd
# JOIN artist ON cd.artist = artist.id
# JOIN liner_notes ON cd.id = liner_notes.cd
# WHERE artist.name = 'Bob Marley' AND liner_notes.notes LIKE '%some text%'
# ORDER BY artist.name
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 "CD"s 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 artist.id = cd.artist
# LEFT 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
# LEFT JOIN cd ON artist.id = cd.artist
# LEFT JOIN liner_notes ON cd.id = liner_notes.cd
# LEFT JOIN author ON author.id = liner_notes.author
# WHERE liner_notes.notes LIKE '%some text%'
# AND author.name = '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'
},
'concerts'
],
}
);
# Equivalent SQL:
# SELECT artist.* FROM artist
# LEFT JOIN cd ON artist.id = cd.artist
# LEFT JOIN liner_notes ON cd.id = liner_notes.cd
# LEFT JOIN concert ON artist.id = 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 tag.cd = cd.id
# JOIN artist ON cd.artist = artist.id
Now accessing our "cd" and "artist" relationships does not need additional SQL statements:
my $tag = $rs->first;
print $tag->cd->artist->name;
ROW-LEVEL OPERATIONS
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.
Stringification
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) {
$obj->insert;
# 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.
Schema definition
package My::App::Schema;
use base 'DBIx::Class::Schema';
# load subclassed classes from My::App::Schema::Result/ResultSet
__PACKAGE__->load_namespaces;
# load classes from shared model
load_classes({
'My::Shared::Model::Result' => [qw/
Foo
Bar
/]});
1;
Result-Subclass definition
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
__PACKAGE__->table('baz');
sub additional_method {
return "I'm an additional method only needed by this app";
}
1;
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 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:
Schema Definition
package My::Schema;
use base qw/DBIx::Class::Schema/;
__PACKAGE__->load_namespaces;
1;
Proxy-Class definitions
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__->table('users');
__PACKAGE__->add_columns(qw/user_id email password
firstname lastname active
admin/);
__PACKAGE__->set_primary_key('user_id');
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 ;
}
1;
package My::Schema::Result::User::Admin;
use strict;
use warnings;
use base qw/My::Schema::Result::User/;
# This line is important
__PACKAGE__->table('users');
sub hello
{
print "I am an admin.\n";
return;
}
sub do_admin_stuff
{
print "I am doing admin stuff\n";
return ;
}
1;
Test File test.pl
use warnings;
use strict;
use My::Schema;
my $user_data = { email => 'someguy@place.com',
password => 'pass1',
admin => 0 };
my $admin_data = { email => 'someadmin@adminplace.com',
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');
$rs->result_class('DBIx::Class::ResultClass::HashRefInflator');
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).
RESULTSET OPERATIONS
Getting Schema from a ResultSet
To get the DBIx::Class::Schema object from a ResultSet, do the following:
$rs->result_source->schema
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:
SELECT AVERAGE(Cost) FROM Items me
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;
$new_rs->set_cache(\@uploadable_groups);
return $new_rs;
USING RELATIONSHIPS
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 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__->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 'DBIx::Class::Core';
__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 'DBIx::Class::Core';
__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
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 MyDatabase::Main::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__->set_primary_key('artist_id');
__PACKAGE__->has_many('cds' => 'MyDatabase::Main::Cd');
1;
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 MyDatabase::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};
$inner->(@_);
if ( $postfix ) {
$self->append_db_name($postfix);
}
};
sub append_db_name {
my ( $self, $postfix ) = @_;
my @sources_with_db
= grep
{ $_->name =~ /^\w+\./mx }
map
{ $self->source($_) }
$self->sources;
foreach my $source (@sources_with_db) {
my $name = $source->name;
$name =~ s{^(\w+)\.}{${1}${postfix}\.}mx;
$source->name($name);
}
}
1;
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
= MyDatabase::Schema->connect(
$dsn,
$user,
$pass,
{
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
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 {
$genus->extinct(1);
$genus->update;
};
my $coderef1 = sub {
$genus->add_to_species({ name => 'troglodyte' });
$genus->wings(2);
$genus->update;
$schema->txn_do($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
deal_with_failed_transaction();
};
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 $@
$thing->update({force_fail=>'foo'});
# 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.
# SQL: ROLLBACK;
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".
SQL
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'],
'0.1',
'./dbscriptdir/'
);
By default this will create schema files in the current directory, for MySQL, SQLite and
PostgreSQL, using the $VERSION from your Schema.pm.
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'],
'0.2',
'/dbscriptdir/',
'0.1'
);
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: <http://troels.arvin.dk/db/rdbms/#other-dummy_table>.
Note: If you're using Oracles dual table don't ever 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';
__PACKAGE__->table("Dual");
__PACKAGE__->add_columns(
"dummy",
{ 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";
}
# Can't locate object method "now" via package "MyAppDB::Dual" at headshot.pl 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
$rs->result_class('DBIx::Class::ResultClass::HashRefInflator');
while ( my $dual = $rs->next ) {
print $dual->{now}."\n";
}
Here are some example "select" conditions to illustrate the different syntax you could use
for doing stuff like "oracles.heavily(nested(functions_can('take', 'lots'), OF), 'args')"
# get a sequence value
select => [ 'A_SEQ.nextval' ],
# get create table sql
select => [ { 'dbms_metadata.get_ddl' => [ "'TABLE'", "'ARTIST'" ]} ],
# get a random num between 0 and 100
select => [ { "trunc" => [ { "dbms_random.value" => [0,100] } ]} ],
# what year is it?
select => [ { 'extract' => [ \'year from sysdate' ] } ],
# do some math
select => [ {'round' => [{'cos' => [ \'180 * 3.14159265359/180' ]}]}],
# which day of the week were you born on?
select => [{'to_char' => [{'to_date' => [ "'25-DEC-1980'", "'dd-mon-yyyy'" ]}, "'day'"]}],
# select 16 rows from dual
select => [ "'hello'" ],
as => [ 'world' ],
group_by => [ 'cube( 1, 2, 3, 4 )' ],
Adding Indexes And Functions To Your SQL
Often you will want indexes on columns on your table to speed up searching. To do this,
create a method called "sqlt_deploy_hook" in the relevant source class (refer to the
advanced callback system if you wish to share a hook between multiple sources):
package My::Schema::Result::Artist;
__PACKAGE__->table('artist');
__PACKAGE__->add_columns(id => { ... }, name => { ... })
sub sqlt_deploy_hook {
my ($self, $sqlt_table) = @_;
$sqlt_table->add_index(name => 'idx_name', fields => ['name']);
}
1;
Sometimes you might want to change the index depending on the type of the database for
which SQL is being generated:
my ($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) = @_;
$sqlt_schema->drop_table('table_name');
}
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
Create a DBIx::Class schema
This can either be done manually, or generated from an existing database as described
under "Creating Schemas From An Existing Database"
Save the schema
Call "create_ddl_dir" in DBIx::Class::Schema as above under "Creating DDL 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 and the conversion scripts as in "Creating DDL SQL".
Deploy update to customers
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/[ ]/] );
$schema->storage->sql_maker->name_sep('.');
The first sets the quote characters. Either a pair of matching brackets, or a """ or "'":
$schema->storage->sql_maker->quote_char('"');
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(
'dbi:mysql:my_db',
'db_user',
'db_password',
{
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/[ ]/ ]);
$rv->storage->sql_maker->name_sep('.');
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:
$resultset->create({
numbers => [1, 2, 3]
});
$row->update(
{
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 "OR"ed), but you can use the following syntax to force passing them as bind values:
$resultset->search(
{
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 => [
$dtf->format_datetime($dt_start),
$dtf->format_datetime($dt_end),
],
}
},
);
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" in DBIx::Class::ResultSet,
whereas create, find, "update" in DBIx::Class::Row (but not "update" in
DBIx::Class::ResultSet) are all 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 will occur.
The Catalyst Wiki Unicode page at
<http://wiki.catalystframework.org/wiki/tutorialsandhowtos/using_unicode> has additional
information on the use of Unicode with Catalyst and DBIx::Class.
The following databases do correctly handle unicode data:-
MySQL
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.
Oracle
Information about Oracle support for unicode can be found in "Unicode" in DBD::Oracle.
PostgreSQL
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
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} );
BOOTSTRAPPING/MIGRATING
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',
},
);
$translator->parser('SQL::Translator::Parser::DBIx::Class');
$translator->producer('SQL::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 exercise for the reader.
OVERLOADING METHODS
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 );
}
$self->$orig(@_);
};
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 "CD"s. 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->next::method(@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->next::method(@args);
$self->create_related ('cds', \%initial_cd_data );
$guard->commit;
return $self
}
Wrapping/overloading a column accessor
Problem:
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.
Solution:
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, we'll let the original accessor
# deal with it.
return $self->_description(@_) if @_;
# Fetch the column value.
my $description = $self->_description;
# If there's something in the description field, then just return that.
return $description if defined $description && length $descripton;
# Otherwise, generate a description.
return $self->generate_description;
}
DEBUGGING AND PROFILING
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.
Profiling
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;
}
1;
You can then install that class as the debugging object:
__PACKAGE__->storage->debugobj(new My::Profiler());
__PACKAGE__->storage->debug(1);
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.
IMPROVING PERFORMANCE
• Install Class::XSAccessor to speed up Class::Accessor::Grouped.
• On Perl 5.8 install Class::C3::XS.
• prefetch relationships, where possible. See "Using joins and prefetch".
• 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.
• When selecting many rows, if you don't need full-blown DBIx::Class::Row objects,
consider using DBIx::Class::ResultClass::HashRefInflator.
• See also "STARTUP SPEED" and "MEMORY USAGE" in this document.
STARTUP SPEED
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 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/;
__PACKAGE__->load_components(qw/InflateColumn::DateTime/);
If this preamble is moved into a common base class:-
package MyDBICbase;
use base qw/DBIx::Class::Core/;
__PACKAGE__->load_components(qw/InflateColumn::DateTime/);
1;
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
__PACKAGE__->load_classes();
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.
MEMORY USAGE
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 },
});