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1 | =head1 NAME |
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2 | |
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3 | DBIx::Class::Manual::Cookbook - Miscellaneous recipes |
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4 | |
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5 | =head1 RECIPES |
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6 | |
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7 | =head2 Searching |
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8 | |
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9 | =head3 Paged results |
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10 | |
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11 | When you expect a large number of results, you can ask L<DBIx::Class> for a |
12 | paged resultset, which will fetch only a small number of records at a time: |
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13 | |
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14 | my $rs = $schema->resultset('Artist')->search( |
15 | {}, |
16 | { |
17 | page => 1, # page to return (defaults to 1) |
18 | rows => 10, # number of results per page |
19 | }, |
20 | ); |
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21 | |
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22 | return $rs->all(); # all records for page 1 |
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23 | |
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24 | The C<page> attribute does not have to be specified in your search: |
25 | |
26 | my $rs = $schema->resultset('Artist')->search( |
27 | {}, |
28 | { |
29 | rows => 10, |
30 | } |
31 | ); |
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32 | |
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33 | return $rs->page(1); # DBIx::Class::ResultSet containing first 10 records |
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34 | |
35 | In either of the above cases, you can return a L<Data::Page> object for the |
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36 | resultset (suitable for use in e.g. a template) using the C<pager> method: |
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37 | |
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38 | return $rs->pager(); |
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39 | |
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40 | =head3 Complex WHERE clauses |
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41 | |
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42 | Sometimes you need to formulate a query using specific operators: |
43 | |
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44 | my @albums = $schema->resultset('Album')->search({ |
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45 | artist => { 'like', '%Lamb%' }, |
46 | title => { 'like', '%Fear of Fours%' }, |
47 | }); |
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48 | |
49 | This results in something like the following C<WHERE> clause: |
50 | |
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51 | WHERE artist LIKE '%Lamb%' AND title LIKE '%Fear of Fours%' |
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52 | |
53 | Other queries might require slightly more complex logic: |
54 | |
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55 | my @albums = $schema->resultset('Album')->search({ |
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56 | -or => [ |
57 | -and => [ |
58 | artist => { 'like', '%Smashing Pumpkins%' }, |
59 | title => 'Siamese Dream', |
60 | ], |
61 | artist => 'Starchildren', |
62 | ], |
63 | }); |
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64 | |
65 | This results in the following C<WHERE> clause: |
66 | |
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67 | WHERE ( artist LIKE '%Smashing Pumpkins%' AND title = 'Siamese Dream' ) |
68 | OR artist = 'Starchildren' |
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69 | |
70 | For more information on generating complex queries, see |
71 | L<SQL::Abstract/WHERE CLAUSES>. |
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72 | |
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73 | =head3 Using specific columns |
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74 | |
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75 | When you only want selected columns from a table, you can use C<cols> to |
76 | specify which ones you need: |
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77 | |
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78 | my $rs = $schema->resultset('Artist')->search( |
79 | {}, |
80 | { |
81 | cols => [qw/ name /] |
82 | } |
83 | ); |
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84 | |
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85 | # Equivalent SQL: |
86 | # SELECT artist.name FROM artist |
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87 | |
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88 | =head3 Using database functions or stored procedures |
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89 | |
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90 | The combination of C<select> and C<as> can be used to return the result of a |
91 | database function or stored procedure as a column value. You use C<select> to |
92 | specify the source for your column value (e.g. a column name, function, or |
93 | stored procedure name). You then use C<as> to set the column name you will use |
94 | to access the returned value: |
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95 | |
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96 | my $rs = $schema->resultset('Artist')->search( |
97 | {}, |
98 | { |
99 | select => [ 'name', { LENGTH => 'name' } ], |
100 | as => [qw/ name name_length /], |
101 | } |
102 | ); |
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103 | |
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104 | # Equivalent SQL: |
105 | # SELECT name name, LENGTH( name ) name_length |
106 | # FROM artist |
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107 | |
108 | If your alias exists as a column in your base class (i.e. it was added with |
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109 | C<add_columns>), you just access it as normal. Our C<Artist> class has a C<name> |
110 | column, so we just use the C<name> accessor: |
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111 | |
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112 | my $artist = $rs->first(); |
113 | my $name = $artist->name(); |
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114 | |
115 | If on the other hand the alias does not correspond to an existing column, you |
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116 | can get the value using the C<get_column> accessor: |
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117 | |
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118 | my $name_length = $artist->get_column('name_length'); |
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119 | |
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120 | If you don't like using C<get_column>, you can always create an accessor for |
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121 | any of your aliases using either of these: |
122 | |
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123 | # Define accessor manually: |
124 | sub name_length { shift->get_column('name_length'); } |
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125 | |
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126 | # Or use DBIx::Class::AccessorGroup: |
127 | __PACKAGE__->mk_group_accessors('column' => 'name_length'); |
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128 | |
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129 | =head3 SELECT DISTINCT with multiple columns |
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130 | |
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131 | my $rs = $schema->resultset('Foo')->search( |
132 | {}, |
133 | { |
134 | select => [ |
135 | { distinct => [ $source->columns ] } |
136 | ], |
137 | as => [ $source->columns ] |
138 | } |
139 | ); |
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140 | |
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141 | =head3 SELECT COUNT(DISTINCT colname) |
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142 | |
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143 | my $rs = $schema->resultset('Foo')->search( |
144 | {}, |
145 | { |
146 | select => [ |
147 | { count => { distinct => 'colname' } } |
148 | ], |
149 | as => [ 'count' ] |
150 | } |
151 | ); |
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152 | |
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153 | =head3 Grouping results |
154 | |
155 | L<DBIx::Class> supports C<GROUP BY> as follows: |
156 | |
157 | my $rs = $schema->resultset('Artist')->search( |
158 | {}, |
159 | { |
160 | join => [qw/ cds /], |
161 | select => [ 'name', { count => 'cds.cdid' } ], |
162 | as => [qw/ name cd_count /], |
163 | group_by => [qw/ name /] |
164 | } |
165 | ); |
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166 | |
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167 | # Equivalent SQL: |
168 | # SELECT name, COUNT( cds.cdid ) FROM artist me |
169 | # LEFT JOIN cd cds ON ( cds.artist = me.artistid ) |
170 | # GROUP BY name |
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171 | |
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172 | =head2 Using joins and prefetch |
173 | |
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174 | You can use the C<join> attribute to allow searching on, or sorting your |
175 | results by, one or more columns in a related table. To return all CDs matching |
176 | a particular artist name: |
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177 | |
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178 | my $rs = $schema->resultset('CD')->search( |
179 | { |
180 | 'artist.name' => 'Bob Marley' |
181 | }, |
182 | { |
183 | join => [qw/artist/], # join the artist table |
184 | } |
185 | ); |
186 | |
187 | # Equivalent SQL: |
188 | # SELECT cd.* FROM cd |
189 | # JOIN artist ON cd.artist = artist.id |
190 | # WHERE artist.name = 'Bob Marley' |
191 | |
192 | If required, you can now sort on any column in the related tables by including |
193 | it in your C<order_by> attribute: |
194 | |
195 | my $rs = $schema->resultset('CD')->search( |
196 | { |
197 | 'artist.name' => 'Bob Marley' |
198 | }, |
199 | { |
200 | join => [qw/ artist /], |
201 | order_by => [qw/ artist.name /] |
202 | } |
203 | }; |
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204 | |
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205 | # Equivalent SQL: |
206 | # SELECT cd.* FROM cd |
207 | # JOIN artist ON cd.artist = artist.id |
208 | # WHERE artist.name = 'Bob Marley' |
209 | # ORDER BY artist.name |
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210 | |
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211 | Note that the C<join> attribute should only be used when you need to search or |
212 | sort using columns in a related table. Joining related tables when you only |
213 | need columns from the main table will make performance worse! |
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214 | |
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215 | Now let's say you want to display a list of CDs, each with the name of the |
216 | artist. The following will work fine: |
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217 | |
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218 | while (my $cd = $rs->next) { |
219 | print "CD: " . $cd->title . ", Artist: " . $cd->artist->name; |
220 | } |
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221 | |
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222 | There is a problem however. We have searched both the C<cd> and C<artist> tables |
223 | in our main query, but we have only returned data from the C<cd> table. To get |
224 | the artist name for any of the CD objects returned, L<DBIx::Class> will go back |
225 | to the database: |
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226 | |
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227 | SELECT artist.* FROM artist WHERE artist.id = ? |
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228 | |
229 | A statement like the one above will run for each and every CD returned by our |
230 | main query. Five CDs, five extra queries. A hundred CDs, one hundred extra |
231 | queries! |
232 | |
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233 | Thankfully, L<DBIx::Class> has a C<prefetch> attribute to solve this problem. |
234 | This allows you to fetch results from a related table as well as the main table |
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235 | for your class: |
236 | |
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237 | my $rs = $schema->resultset('CD')->search( |
238 | { |
239 | 'artist.name' => 'Bob Marley' |
240 | }, |
241 | { |
242 | join => [qw/ artist /], |
243 | order_by => [qw/ artist.name /], |
244 | prefetch => [qw/ artist /] # return artist data too! |
245 | } |
246 | ); |
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247 | |
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248 | # Equivalent SQL (note SELECT from both "cd" and "artist"): |
249 | # SELECT cd.*, artist.* FROM cd |
250 | # JOIN artist ON cd.artist = artist.id |
251 | # WHERE artist.name = 'Bob Marley' |
252 | # ORDER BY artist.name |
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253 | |
254 | The code to print the CD list remains the same: |
255 | |
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256 | while (my $cd = $rs->next) { |
257 | print "CD: " . $cd->title . ", Artist: " . $cd->artist->name; |
258 | } |
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259 | |
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260 | L<DBIx::Class> has now prefetched all matching data from the C<artist> table, |
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261 | so no additional SQL statements are executed. You now have a much more |
262 | efficient query. |
263 | |
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264 | Note that as of L<DBIx::Class> 0.04, C<prefetch> cannot be used with |
265 | C<has_many> relationships. You will get an error along the lines of "No |
266 | accessor for prefetched ..." if you try. |
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267 | |
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268 | Also note that C<prefetch> should only be used when you know you will |
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269 | definitely use data from a related table. Pre-fetching related tables when you |
270 | only need columns from the main table will make performance worse! |
271 | |
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272 | =head3 Multi-step joins |
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273 | |
274 | Sometimes you want to join more than one relationship deep. In this example, |
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275 | we want to find all C<Artist> objects who have C<CD>s whose C<LinerNotes> |
276 | contain a specific string: |
277 | |
278 | # Relationships defined elsewhere: |
279 | # Artist->has_many('cds' => 'CD', 'artist'); |
280 | # CD->has_one('liner_notes' => 'LinerNotes', 'cd'); |
281 | |
282 | my $rs = $schema->resultset('Artist')->search( |
283 | { |
284 | 'liner_notes.notes' => { 'like', '%some text%' }, |
285 | }, |
286 | { |
287 | join => { |
288 | 'cds' => 'liner_notes' |
289 | } |
290 | } |
291 | ); |
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292 | |
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293 | # Equivalent SQL: |
294 | # SELECT artist.* FROM artist |
295 | # JOIN ( cd ON artist.id = cd.artist ) |
296 | # JOIN ( liner_notes ON cd.id = liner_notes.cd ) |
297 | # WHERE liner_notes.notes LIKE '%some text%' |
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298 | |
299 | Joins can be nested to an arbitrary level. So if we decide later that we |
300 | want to reduce the number of Artists returned based on who wrote the liner |
301 | notes: |
302 | |
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303 | # Relationship defined elsewhere: |
304 | # LinerNotes->belongs_to('author' => 'Person'); |
305 | |
306 | my $rs = $schema->resultset('Artist')->search( |
307 | { |
308 | 'liner_notes.notes' => { 'like', '%some text%' }, |
309 | 'author.name' => 'A. Writer' |
310 | }, |
311 | { |
312 | join => { |
313 | 'cds' => { |
314 | 'liner_notes' => 'author' |
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315 | } |
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316 | } |
317 | } |
318 | ); |
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319 | |
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320 | # Equivalent SQL: |
321 | # SELECT artist.* FROM artist |
322 | # JOIN ( cd ON artist.id = cd.artist ) |
323 | # JOIN ( liner_notes ON cd.id = liner_notes.cd ) |
324 | # JOIN ( author ON author.id = liner_notes.author ) |
325 | # WHERE liner_notes.notes LIKE '%some text%' |
326 | # AND author.name = 'A. Writer' |
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327 | |
328 | =head2 Transactions |
329 | |
330 | As of version 0.04001, there is improved transaction support in |
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331 | L<DBIx::Class::Storage::DBI>. Here is an example of the recommended |
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332 | way to use it: |
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333 | |
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334 | my $genus = Genus->find(12); |
335 | eval { |
336 | MyDB->txn_begin; |
337 | $genus->add_to_species({ name => 'troglodyte' }); |
338 | $genus->wings(2); |
339 | $genus->update; |
340 | cromulate($genus); # Can have a nested transation |
341 | MyDB->txn_commit; |
342 | }; |
343 | if ($@) { |
344 | # Rollback might fail, too |
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345 | eval { |
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346 | MyDB->txn_rollback |
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347 | }; |
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348 | } |
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349 | |
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350 | Currently, a nested commit will do nothing and a nested rollback will |
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351 | die. The code at each level must be sure to call rollback in the case |
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352 | of an error, to ensure that the rollback will propagate to the top |
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353 | level and be issued. Support for savepoints and for true nested |
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354 | transactions (for databases that support them) will hopefully be added |
355 | in the future. |
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356 | |
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357 | =head2 Many-to-many relationships |
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358 | |
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359 | This is straightforward using L<DBIx::Class::Relationship::ManyToMany>: |
360 | |
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361 | package My::DB; |
362 | # ... set up connection ... |
363 | |
364 | package My::User; |
365 | use base 'My::DB'; |
366 | __PACKAGE__->table('user'); |
367 | __PACKAGE__->add_columns(qw/id name/); |
368 | __PACKAGE__->set_primary_key('id'); |
369 | __PACKAGE__->has_many('user_address' => 'My::UserAddress', 'user'); |
370 | __PACKAGE__->many_to_many('addresses' => 'user_address', 'address'); |
371 | |
372 | package My::UserAddress; |
373 | use base 'My::DB'; |
374 | __PACKAGE__->table('user_address'); |
375 | __PACKAGE__->add_columns(qw/user address/); |
376 | __PACKAGE__->set_primary_key(qw/user address/); |
377 | __PACKAGE__->belongs_to('user' => 'My::User'); |
378 | __PACKAGE__->belongs_to('address' => 'My::Address'); |
379 | |
380 | package My::Address; |
381 | use base 'My::DB'; |
382 | __PACKAGE__->table('address'); |
383 | __PACKAGE__->add_columns(qw/id street town area_code country/); |
384 | __PACKAGE__->set_primary_key('id'); |
385 | __PACKAGE__->has_many('user_address' => 'My::UserAddress', 'address'); |
386 | __PACKAGE__->many_to_many('users' => 'user_address', 'user'); |
387 | |
388 | $rs = $user->addresses(); # get all addresses for a user |
389 | $rs = $address->users(); # get all users for an address |
390 | |
391 | =head2 Setting default values for a row |
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392 | |
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393 | It's as simple as overriding the C<new> method. Note the use of |
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394 | C<next::method>. |
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395 | |
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396 | sub new { |
397 | my ( $class, $attrs ) = @_; |
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398 | |
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399 | $attrs->{foo} = 'bar' unless defined $attrs->{foo}; |
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400 | |
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401 | $class->next::method($attrs); |
402 | } |
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403 | |
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404 | =head2 Stringification |
405 | |
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406 | Employ the standard stringification technique by using the C<overload> |
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407 | module. Replace C<foo> with the column/method of your choice. |
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408 | |
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409 | use overload '""' => 'foo', fallback => 1; |
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410 | |
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411 | =head2 Disconnecting cleanly |
412 | |
413 | If you find yourself quitting an app with Control-C a lot during |
414 | development, you might like to put the following signal handler in |
415 | your main database class to make sure it disconnects cleanly: |
416 | |
417 | $SIG{INT} = sub { |
418 | __PACKAGE__->storage->dbh->disconnect; |
419 | }; |
420 | |
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421 | =head2 Schema import/export |
422 | |
423 | This functionality requires you to have L<SQL::Translator> (also known as |
424 | "SQL Fairy") installed. |
425 | |
426 | To create a DBIx::Class schema from an existing database: |
427 | |
428 | sqlt --from DBI |
429 | --to DBIx::Class::File |
430 | --prefix "MySchema" > MySchema.pm |
431 | |
432 | To create a MySQL database from an existing L<DBIx::Class> schema, convert the |
433 | schema to MySQL's dialect of SQL: |
434 | |
435 | sqlt --from DBIx::Class --to MySQL --DBIx::Class "MySchema.pm" > Schema1.sql |
436 | |
437 | And import using the mysql client: |
438 | |
439 | mysql -h "host" -D "database" -u "user" -p < Schema1.sql |
440 | |
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441 | =head2 Easy migration from class-based to schema-based setup |
442 | |
443 | You want to start using the schema-based approach to L<DBIx::Class> |
444 | (see L<SchemaIntro.pod>), but have an established class-based setup with lots |
445 | of existing classes that you don't want to move by hand. Try this nifty script |
446 | instead: |
447 | |
448 | use MyDB; |
449 | use SQL::Translator; |
450 | |
451 | my $schema = MyDB->schema_instance; |
452 | |
453 | my $translator = SQL::Translator->new( |
454 | debug => $debug || 0, |
455 | trace => $trace || 0, |
456 | no_comments => $no_comments || 0, |
457 | show_warnings => $show_warnings || 0, |
458 | add_drop_table => $add_drop_table || 0, |
459 | validate => $validate || 0, |
460 | parser_args => { |
461 | 'DBIx::Schema' => $schema, |
462 | } |
463 | producer_args => { |
464 | 'prefix' => 'My::Schema', |
465 | } |
466 | ); |
467 | |
468 | $translator->parser('DBIx::Class'); |
469 | $translator->producer('DBIx::Class::File'); |
470 | |
471 | my $output = $translator->translate(@args) or die |
472 | "Error: " . $translator->error; |
473 | |
474 | print $output; |
475 | |
476 | You could use L<Module::Find> to search for all subclasses in the MyDB::* |
477 | namespace, which is currently left as an excercise for the reader. |
478 | |
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479 | =head2 Schema versioning |
480 | |
481 | The following example shows simplistically how you might use DBIx::Class to |
482 | deploy versioned schemas to your customers. The basic process is as follows: |
483 | |
484 | 1) Create a DBIx::Class schema |
485 | 2) Save the schema |
486 | 3) Deploy to customers |
487 | 4) Modify schema to change functionality |
488 | 5) Deploy update to customers |
489 | |
490 | =head3 Create a DBIx::Class schema |
491 | |
492 | This can either be done manually, or generated from an existing database as |
493 | described under C<Schema import/export>. |
494 | |
495 | =head3 Save the schema |
496 | |
497 | Use C<sqlt> to transform your schema into an SQL script suitable for your |
498 | customer's database. E.g. for MySQL: |
499 | |
500 | sqlt --from DBIx::Class |
501 | --to MySQL |
502 | --DBIx::Class "MySchema.pm" > Schema1.mysql.sql |
503 | |
504 | If you need to target databases from multiple vendors, just generate an SQL |
505 | script suitable for each. To support PostgreSQL too: |
506 | |
507 | sqlt --from DBIx::Class |
508 | --to PostgreSQL |
509 | --DBIx::Class "MySchema.pm" > Schema1.pgsql.sql |
510 | |
511 | =head3 Deploy to customers |
512 | |
513 | There are several ways you could deploy your schema. These are probably |
514 | beyond the scope of this recipe, but might include: |
515 | |
516 | 1) Require customer to apply manually using their RDBMS. |
517 | 2) Package along with your app, making database dump/schema update/tests |
518 | all part of your install. |
519 | |
520 | =head3 Modify the schema to change functionality |
521 | |
522 | As your application evolves, it may be necessary to modify your schema to |
523 | change functionality. Once the changes are made to your schema in DBIx::Class, |
524 | export the modified schema as before, taking care not to overwrite the original: |
525 | |
526 | sqlt --from DBIx::Class |
527 | --to MySQL |
528 | --DBIx::Class "Anything.pm" > Schema2.mysql.sql |
529 | |
530 | Next, use sqlt-diff to create an SQL script that will update the customer's |
531 | database schema: |
532 | |
533 | sqlt-diff --to MySQL Schema1=MySQL Schema2=MySQL > SchemaUpdate.mysql.sql |
534 | |
535 | =head3 Deploy update to customers |
536 | |
537 | The schema update can be deployed to customers using the same method as before. |
538 | |
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539 | =cut |