DBIx::Class::Manual::CUseroContributed Perl DoDBIx::Class::Manual::Cookbook(3)NAMEDBIx::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');
# ->table, ->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 => {
'=' => $cdrs->search(
{ artist_id => { '=' => { -ident => 'me.artist_id' } } },
{ alias => 'inner' }
)->get_column('year')->max_rs->as_query,
},
});
That creates the following SQL:
SELECT me.cdid, me.artist, me.title, me.year, me.genreid, me.single_track
FROM cd me
WHERE year = (
SELECT MAX(inner.year)
FROM cd inner
WHERE artist_id = me.artist_id
)
Predefined searches
You can define frequently used searches as methods by subclassing
DBIx::Class::ResultSet:
package My::DBIC::ResultSet::CD;
use strict;
use warnings;
use base 'DBIx::Class::ResultSet';
sub search_cds_ordered {
my ($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) = ?', [ plain_value => 1979 ] ]);
# Equivalent SQL:
# SELECT * FROM employee WHERE YEAR(date_of_birth) = ?
$rs->search({ -and => [
name => 'Bob',
\[ 'YEAR(date_of_birth) = ?', [ plain_value => 1979 ] ],
]});
# Equivalent SQL:
# SELECT * FROM employee WHERE name = ? AND YEAR(date_of_birth) = ?
Note: the "plain_value" string in the "[ plain_value => 1979 ]" part
should be either the same as the name of the column (do this if the
type of the return value of the function is the same as the type of the
column) or in the case of a function it's currently treated as a dummy
string (it is a good idea to use "plain_value" or something similar to
convey intent). The value is currently only significant when handling
special column types (BLOBs, arrays, etc.), but this may change in the
future.
See also "Literal SQL with placeholders and bind values (subqueries)"
in SQL::Abstract.
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'
# 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 row object's Schema
It is possible to get a Schema object from a row 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 row 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) row 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 overridding 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 = $_;
}
if ($caught) {
# 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
<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 $new;
}
For more information about "next::method", look in the Class::C3
documentation. See also DBIx::Class::Manual::Component for more ways to
write your own base classes to do this.
People looking for ways to do "triggers" with DBIx::Class are probably
just looking for this.
Changing one field whenever another changes
For example, say that you have three columns, "id", "number", and
"squared". You would like to make changes to "number" and have
"squared" be automagically set to the value of "number" squared. You
can accomplish this by wrapping the "number" accessor with
Class::Method::Modifiers:
around number => sub {
my ($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 DBIx::Class::Row 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 },
});
perl v5.14.2 2012-01-22 DBIx::Class::Manual::Cookbook(3)