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');
# ->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, ie. 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 thatdeploy
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) count_subq:
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 (EXPERIMENTAL)
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 => {
'=' => $cdrs->search(
{ artist_id => { '=' => \'me.artist_id' } },
{ alias => 'inner' }
)->get_column('year')->max_rs->as_query,
},
});
That creates the following SQL:
SELECT me.cdid, me.artist, me.title, me.year, me.genreid, me.single_track
FROM cd me
WHERE year = (
SELECT MAX(inner.year)
FROM cd inner
WHERE artist_id = me.artist_id
)
EXPERIMENTAL
Please note that subqueries are considered an experimental feature.
Predefined searches
You can write your own DBIx::Class::ResultSet class by inheriting from it and defining often used searches as methods:
package My::DBIC::ResultSet::CD;
use strict;
use warnings;
use base 'DBIx::Class::ResultSet';
sub search_cds_ordered {
my ($self) = @_;
return $self->search(
{},
{ order_by => 'name DESC' },
);
}
1;
To use your resultset, first tell DBIx::Class to create an instance of it 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.
If you do not have quoting on, simply include the function in your search specification as you would any column:
$rs->search({ 'YEAR(date_of_birth)' => 1979 });
With quoting on, or for a more portable solution, use literal SQL values with placeholders:
$rs->search(\[ 'YEAR(date_of_birth) = ?', [ plain_value => 1979 ] ]);
# Equivalent SQL:
# SELECT * FROM employee WHERE YEAR(date_of_birth) = ?
$rs->search({
name => 'Bob',
-nest => \[ '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 otherwise it's essentially a dummy string currently (use plain_value
as a habit). It is used by DBIx::Class to handle special column types.
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 seperate 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 relationships
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
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;
};
my $rs;
eval {
$rs = $schema->txn_do($coderef1);
};
if ($@) { # Transaction failed
die "the sky is falling!" #
if ($@ =~ /Rollback failed/); # Rollback failed
deal_with_failed_transaction();
}
Nested transactions will work as expected. That is, only the outermost transaction will actually issue a commit to the $dbh, and a rollback at any level of any transaction will cause the entire nested transaction to fail.
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
# commited into the database if the eval block succeeds.
eval {
$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.
eval {
$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 $@
$thing->update({force_fail=>'foo'});
# SQL: UPDATE thing SET force_fail = 'foo'
# WHERE ( id = 42 );
}
});
};
if ($@) {
# 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: $@";
}
# There was no error, so save all changes since the last
# savepoint.
# SQL: RELEASE SAVEPOINT savepoint_0;
}
});
};
if ($@) {
# There was an error while handling the $job. Rollback all changes
# since the transaction started, including the already commited
# ('released') savepoints. There will be neither a new $job nor any
# $thing entry in the database.
# SQL: ROLLBACK;
print "ERROR: $@\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 eval
-block around txn_do
fails, a rollback is issued. If the eval
succeeds, the transaction is committed (or the savepoint released).
While you can get more fine-grained controll using svp_begin
, svp_release
and svp_rollback
, it is strongly recommended to use txn_do
with coderefs.
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 make_schema_at method:
perl -MDBIx::Class::Schema::Loader=make_schema_at,dump_to_dir:./lib \
-e 'make_schema_at("My::Schema", { debug => 1 }, [ "dbi:Pg:dbname=foo","postgres" ])'
This will create a tree of files rooted at ./lib/My/Schema/
containing source definitions for all the tables found 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_tables => 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:
Create a DBIx::Class schema
Save the schema
Deploy to customers
Modify schema to change functionality
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:
Require customer to apply manually using their RDBMS.
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 trys 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.
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;
}
Setting limit dialect for SQL::Abstract::Limit
In some cases, SQL::Abstract::Limit cannot determine the dialect of the remote SQL server by looking at the database handle. This is a common problem when using the DBD::JDBC, since the DBD-driver only know that in has a Java-driver available, not which JDBC driver the Java component has loaded. This specifically sets the limit_dialect to Microsoft SQL-server (See more names in SQL::Abstract::Limit -documentation.
__PACKAGE__->storage->sql_maker->limit_dialect('mssql');
The JDBC bridge is one way of getting access to a MSSQL server from a platform that Microsoft doesn't deliver native client libraries for. (e.g. Linux)
The limit dialect can also be set at connect time by specifying a limit_dialect
key in the final hash as shown above.
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 (eg. \%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]
.
BOOTSTRAPPING/MIGRATING
Easy migration from class-based to schema-based setup
You want to start using the schema-based approach to DBIx::Class (see SchemaIntro.pod), but have an established class-based setup with lots of existing classes that you don't want to move by hand. Try this nifty script instead:
use MyDB;
use SQL::Translator;
my $schema = MyDB->schema_instance;
my $translator = SQL::Translator->new(
debug => $debug || 0,
trace => $trace || 0,
no_comments => $no_comments || 0,
show_warnings => $show_warnings || 0,
add_drop_table => $add_drop_table || 0,
validate => $validate || 0,
parser_args => {
'DBIx::Schema' => $schema,
},
producer_args => {
'prefix' => 'My::Schema',
},
);
$translator->parser('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 overriding store_column
:
sub store_column {
my ( $self, $name, $value ) = @_;
if ($name eq 'number') {
$self->squared($value * $value);
}
$self->next::method($name, $value);
}
Note that the hard work is done by the call to next::method
, which redispatches your call to store_column in the superclass(es).
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);
$self->cds->new({})->fill_from_artist($self)->insert;
return $self;
}
where fill_from_artist
is a method you specify in CD
which sets values in CD
based on the data in the Artist
object you pass in.
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.
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 },
});