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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( |
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15 | undef, |
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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( |
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27 | undef, |
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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( |
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79 | undef, |
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80 | { |
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81 | columns => [qw/ name /] |
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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( |
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97 | undef, |
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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( |
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132 | undef, |
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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( |
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144 | undef, |
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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( |
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158 | undef, |
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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. |
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234 | This allows you to fetch results from related tables in advance: |
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235 | |
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236 | my $rs = $schema->resultset('CD')->search( |
237 | { |
238 | 'artist.name' => 'Bob Marley' |
239 | }, |
240 | { |
241 | join => [qw/ artist /], |
242 | order_by => [qw/ artist.name /], |
243 | prefetch => [qw/ artist /] # return artist data too! |
244 | } |
245 | ); |
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246 | |
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247 | # Equivalent SQL (note SELECT from both "cd" and "artist"): |
248 | # SELECT cd.*, artist.* FROM cd |
249 | # JOIN artist ON cd.artist = artist.id |
250 | # WHERE artist.name = 'Bob Marley' |
251 | # ORDER BY artist.name |
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252 | |
253 | The code to print the CD list remains the same: |
254 | |
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255 | while (my $cd = $rs->next) { |
256 | print "CD: " . $cd->title . ", Artist: " . $cd->artist->name; |
257 | } |
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258 | |
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259 | L<DBIx::Class> has now prefetched all matching data from the C<artist> table, |
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260 | so no additional SQL statements are executed. You now have a much more |
261 | efficient query. |
262 | |
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263 | Note that as of L<DBIx::Class> 0.04, C<prefetch> cannot be used with |
264 | C<has_many> relationships. You will get an error along the lines of "No |
265 | accessor for prefetched ..." if you try. |
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266 | |
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267 | Also note that C<prefetch> should only be used when you know you will |
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268 | definitely use data from a related table. Pre-fetching related tables when you |
269 | only need columns from the main table will make performance worse! |
270 | |
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271 | =head3 Multi-step joins |
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272 | |
273 | Sometimes you want to join more than one relationship deep. In this example, |
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274 | we want to find all C<Artist> objects who have C<CD>s whose C<LinerNotes> |
275 | contain a specific string: |
276 | |
277 | # Relationships defined elsewhere: |
278 | # Artist->has_many('cds' => 'CD', 'artist'); |
279 | # CD->has_one('liner_notes' => 'LinerNotes', 'cd'); |
280 | |
281 | my $rs = $schema->resultset('Artist')->search( |
282 | { |
283 | 'liner_notes.notes' => { 'like', '%some text%' }, |
284 | }, |
285 | { |
286 | join => { |
287 | 'cds' => 'liner_notes' |
288 | } |
289 | } |
290 | ); |
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291 | |
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292 | # Equivalent SQL: |
293 | # SELECT artist.* FROM artist |
294 | # JOIN ( cd ON artist.id = cd.artist ) |
295 | # JOIN ( liner_notes ON cd.id = liner_notes.cd ) |
296 | # WHERE liner_notes.notes LIKE '%some text%' |
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297 | |
298 | Joins can be nested to an arbitrary level. So if we decide later that we |
299 | want to reduce the number of Artists returned based on who wrote the liner |
300 | notes: |
301 | |
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302 | # Relationship defined elsewhere: |
303 | # LinerNotes->belongs_to('author' => 'Person'); |
304 | |
305 | my $rs = $schema->resultset('Artist')->search( |
306 | { |
307 | 'liner_notes.notes' => { 'like', '%some text%' }, |
308 | 'author.name' => 'A. Writer' |
309 | }, |
310 | { |
311 | join => { |
312 | 'cds' => { |
313 | 'liner_notes' => 'author' |
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314 | } |
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315 | } |
316 | } |
317 | ); |
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318 | |
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319 | # Equivalent SQL: |
320 | # SELECT artist.* FROM artist |
321 | # JOIN ( cd ON artist.id = cd.artist ) |
322 | # JOIN ( liner_notes ON cd.id = liner_notes.cd ) |
323 | # JOIN ( author ON author.id = liner_notes.author ) |
324 | # WHERE liner_notes.notes LIKE '%some text%' |
325 | # AND author.name = 'A. Writer' |
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326 | |
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327 | =head2 Multi-step prefetch |
328 | |
329 | From 0.04999_05 onwards, C<prefetch> can be nested more than one relationship |
330 | deep using the same syntax as a multi-step join: |
331 | |
332 | my $rs = $schema->resultset('Tag')->search( |
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333 | undef, |
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334 | { |
335 | prefetch => { |
336 | cd => 'artist' |
337 | } |
338 | } |
339 | ); |
340 | |
341 | # Equivalent SQL: |
342 | # SELECT tag.*, cd.*, artist.* FROM tag |
343 | # JOIN cd ON tag.cd = cd.cdid |
344 | # JOIN artist ON cd.artist = artist.artistid |
345 | |
346 | Now accessing our C<cd> and C<artist> relationships does not need additional |
347 | SQL statements: |
348 | |
349 | my $tag = $rs->first; |
350 | print $tag->cd->artist->name; |
351 | |
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352 | =head2 Transactions |
353 | |
354 | As of version 0.04001, there is improved transaction support in |
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355 | L<DBIx::Class::Storage::DBI> and L<DBIx::Class::Schema>. Here is an |
356 | example of the recommended way to use it: |
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357 | |
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358 | my $genus = $schema->resultset('Genus')->find(12); |
359 | |
360 | my $coderef1 = sub { |
361 | my ($schema, $genus, $code) = @_; |
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362 | $genus->add_to_species({ name => 'troglodyte' }); |
363 | $genus->wings(2); |
364 | $genus->update; |
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365 | $schema->txn_do($code, $genus); # Can have a nested transation |
366 | return $genus->species; |
367 | }; |
368 | |
369 | my $coderef2 = sub { |
370 | my ($genus) = @_; |
371 | $genus->extinct(1); |
372 | $genus->update; |
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373 | }; |
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374 | |
375 | my $rs; |
376 | eval { |
377 | $rs = $schema->txn_do($coderef1, $schema, $genus, $coderef2); |
378 | }; |
379 | |
380 | if ($@) { # Transaction failed |
381 | die "the sky is falling!" # |
382 | if ($@ =~ /Rollback failed/); # Rollback failed |
383 | |
384 | deal_with_failed_transaction(); |
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385 | } |
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386 | |
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387 | Nested transactions will work as expected. That is, only the outermost |
388 | transaction will actually issue a commit to the $dbh, and a rollback |
389 | at any level of any transaction will cause the entire nested |
390 | transaction to fail. Support for savepoints and for true nested |
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391 | transactions (for databases that support them) will hopefully be added |
392 | in the future. |
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393 | |
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394 | =head2 Many-to-many relationships |
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395 | |
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396 | This is straightforward using L<DBIx::Class::Relationship::ManyToMany>: |
397 | |
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398 | package My::DB; |
399 | # ... set up connection ... |
400 | |
401 | package My::User; |
402 | use base 'My::DB'; |
403 | __PACKAGE__->table('user'); |
404 | __PACKAGE__->add_columns(qw/id name/); |
405 | __PACKAGE__->set_primary_key('id'); |
406 | __PACKAGE__->has_many('user_address' => 'My::UserAddress', 'user'); |
407 | __PACKAGE__->many_to_many('addresses' => 'user_address', 'address'); |
408 | |
409 | package My::UserAddress; |
410 | use base 'My::DB'; |
411 | __PACKAGE__->table('user_address'); |
412 | __PACKAGE__->add_columns(qw/user address/); |
413 | __PACKAGE__->set_primary_key(qw/user address/); |
414 | __PACKAGE__->belongs_to('user' => 'My::User'); |
415 | __PACKAGE__->belongs_to('address' => 'My::Address'); |
416 | |
417 | package My::Address; |
418 | use base 'My::DB'; |
419 | __PACKAGE__->table('address'); |
420 | __PACKAGE__->add_columns(qw/id street town area_code country/); |
421 | __PACKAGE__->set_primary_key('id'); |
422 | __PACKAGE__->has_many('user_address' => 'My::UserAddress', 'address'); |
423 | __PACKAGE__->many_to_many('users' => 'user_address', 'user'); |
424 | |
425 | $rs = $user->addresses(); # get all addresses for a user |
426 | $rs = $address->users(); # get all users for an address |
427 | |
428 | =head2 Setting default values for a row |
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429 | |
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430 | It's as simple as overriding the C<new> method. Note the use of |
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431 | C<next::method>. |
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432 | |
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433 | sub new { |
434 | my ( $class, $attrs ) = @_; |
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435 | |
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436 | $attrs->{foo} = 'bar' unless defined $attrs->{foo}; |
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437 | |
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438 | $class->next::method($attrs); |
439 | } |
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440 | |
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441 | =head2 Stringification |
442 | |
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443 | Employ the standard stringification technique by using the C<overload> |
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444 | module. Replace C<foo> with the column/method of your choice. |
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445 | |
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446 | use overload '""' => 'foo', fallback => 1; |
25af00d7 |
447 | |
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448 | =head2 Disconnecting cleanly |
449 | |
450 | If you find yourself quitting an app with Control-C a lot during |
451 | development, you might like to put the following signal handler in |
452 | your main database class to make sure it disconnects cleanly: |
453 | |
454 | $SIG{INT} = sub { |
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455 | __PACKAGE__->storage->disconnect; |
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456 | }; |
457 | |
362500af |
458 | =head2 Schema import/export |
459 | |
460 | This functionality requires you to have L<SQL::Translator> (also known as |
461 | "SQL Fairy") installed. |
462 | |
463 | To create a DBIx::Class schema from an existing database: |
464 | |
465 | sqlt --from DBI |
466 | --to DBIx::Class::File |
467 | --prefix "MySchema" > MySchema.pm |
468 | |
469 | To create a MySQL database from an existing L<DBIx::Class> schema, convert the |
470 | schema to MySQL's dialect of SQL: |
471 | |
472 | sqlt --from DBIx::Class --to MySQL --DBIx::Class "MySchema.pm" > Schema1.sql |
473 | |
474 | And import using the mysql client: |
475 | |
476 | mysql -h "host" -D "database" -u "user" -p < Schema1.sql |
477 | |
b0a20454 |
478 | =head2 Easy migration from class-based to schema-based setup |
479 | |
480 | You want to start using the schema-based approach to L<DBIx::Class> |
481 | (see L<SchemaIntro.pod>), but have an established class-based setup with lots |
482 | of existing classes that you don't want to move by hand. Try this nifty script |
483 | instead: |
484 | |
485 | use MyDB; |
486 | use SQL::Translator; |
487 | |
488 | my $schema = MyDB->schema_instance; |
489 | |
490 | my $translator = SQL::Translator->new( |
491 | debug => $debug || 0, |
492 | trace => $trace || 0, |
493 | no_comments => $no_comments || 0, |
494 | show_warnings => $show_warnings || 0, |
495 | add_drop_table => $add_drop_table || 0, |
496 | validate => $validate || 0, |
497 | parser_args => { |
498 | 'DBIx::Schema' => $schema, |
c5f36986 |
499 | }, |
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500 | producer_args => { |
501 | 'prefix' => 'My::Schema', |
c5f36986 |
502 | }, |
b0a20454 |
503 | ); |
504 | |
505 | $translator->parser('DBIx::Class'); |
506 | $translator->producer('DBIx::Class::File'); |
507 | |
508 | my $output = $translator->translate(@args) or die |
509 | "Error: " . $translator->error; |
510 | |
511 | print $output; |
512 | |
513 | You could use L<Module::Find> to search for all subclasses in the MyDB::* |
514 | namespace, which is currently left as an excercise for the reader. |
515 | |
362500af |
516 | =head2 Schema versioning |
517 | |
518 | The following example shows simplistically how you might use DBIx::Class to |
519 | deploy versioned schemas to your customers. The basic process is as follows: |
520 | |
da4779ad |
521 | =over 4 |
522 | |
523 | =item 1. |
524 | |
525 | Create a DBIx::Class schema |
526 | |
527 | =item 2. |
528 | |
529 | Save the schema |
530 | |
531 | =item 3. |
532 | |
533 | Deploy to customers |
534 | |
535 | =item 4. |
536 | |
537 | Modify schema to change functionality |
538 | |
539 | =item 5. |
540 | |
541 | Deploy update to customers |
542 | |
543 | =back |
362500af |
544 | |
545 | =head3 Create a DBIx::Class schema |
546 | |
547 | This can either be done manually, or generated from an existing database as |
548 | described under C<Schema import/export>. |
549 | |
550 | =head3 Save the schema |
551 | |
552 | Use C<sqlt> to transform your schema into an SQL script suitable for your |
553 | customer's database. E.g. for MySQL: |
554 | |
555 | sqlt --from DBIx::Class |
556 | --to MySQL |
557 | --DBIx::Class "MySchema.pm" > Schema1.mysql.sql |
558 | |
559 | If you need to target databases from multiple vendors, just generate an SQL |
560 | script suitable for each. To support PostgreSQL too: |
561 | |
562 | sqlt --from DBIx::Class |
563 | --to PostgreSQL |
564 | --DBIx::Class "MySchema.pm" > Schema1.pgsql.sql |
565 | |
566 | =head3 Deploy to customers |
567 | |
568 | There are several ways you could deploy your schema. These are probably |
569 | beyond the scope of this recipe, but might include: |
570 | |
da4779ad |
571 | =over 4 |
572 | |
573 | =item 1. |
574 | |
575 | Require customer to apply manually using their RDBMS. |
576 | |
577 | =item 2. |
578 | |
579 | Package along with your app, making database dump/schema update/tests |
362500af |
580 | all part of your install. |
581 | |
da4779ad |
582 | =back |
583 | |
362500af |
584 | =head3 Modify the schema to change functionality |
585 | |
586 | As your application evolves, it may be necessary to modify your schema to |
587 | change functionality. Once the changes are made to your schema in DBIx::Class, |
588 | export the modified schema as before, taking care not to overwrite the original: |
589 | |
590 | sqlt --from DBIx::Class |
591 | --to MySQL |
592 | --DBIx::Class "Anything.pm" > Schema2.mysql.sql |
593 | |
594 | Next, use sqlt-diff to create an SQL script that will update the customer's |
595 | database schema: |
596 | |
597 | sqlt-diff --to MySQL Schema1=MySQL Schema2=MySQL > SchemaUpdate.mysql.sql |
598 | |
599 | =head3 Deploy update to customers |
600 | |
601 | The schema update can be deployed to customers using the same method as before. |
602 | |
7be93b07 |
603 | =head2 Setting limit dialect for SQL::Abstract::Limit |
604 | |
605 | In some cases, SQL::Abstract::Limit cannot determine the dialect of the remote |
606 | SQL-server by looking at the database-handle. This is a common problem when |
607 | using the DBD::JDBC, since the DBD-driver only know that in has a Java-driver |
608 | available, not which JDBC-driver the Java component has loaded. |
609 | This specifically sets the limit_dialect to Microsoft SQL-server (Se more names |
610 | in SQL::Abstract::Limit -documentation. |
611 | |
612 | __PACKAGE__->storage->sql_maker->limit_dialect('mssql'); |
613 | |
614 | The JDBC-bridge is one way of getting access to a MSSQL-server from a platform |
615 | that Microsoft doesn't deliver native client libraries for. (e.g. Linux) |
616 | |
2437a1e3 |
617 | =head2 Setting quotes for the generated SQL. |
618 | |
619 | If the database contains columnames with spaces and/or reserved words, the |
620 | SQL-query needs to be quoted. This is done using: |
621 | |
622 | __PACKAGE__->storage->sql_maker->quote_char([ qw/[ ]/] ); |
623 | __PACKAGE__->storage->sql_maker->name_sep('.'); |
624 | |
625 | The first sets the quotesymbols. If the quote i "symmetric" as " or ' |
626 | |
627 | __PACKAGE__->storage->sql_maker->quote_char('"'); |
628 | |
629 | is enough. If the left qoute differs form the right quote, the first |
630 | notation should be used. name_sep needs to be set to allow the |
631 | SQL generator to put the quotes the correct place. |
632 | |
40dbc108 |
633 | =cut |