Doctrine sql not null

Create a free Team What is Teams? Collectives on Stack Overflow. Learn more. Ask Question. Asked 10 years, 4 months ago. Active 1 month ago. Viewed 64k times. Geoffrey Hale 8, 5 5 gold badges 36 36 silver badges 42 42 bronze badges. There are three cases:. In this case, the result will be an array of arrays. In the example above, each element of the result array would be an array of the scalar name and address values.

Here, the result will again be an array of arrays, with each element being an array made up of a User object and the scalar value p. You cannot select other entities unless you also select the root of the selection which is the first entity in FROM. Fetch Joins : In addition to the uses of regular joins: Used to fetch related entities and include them in the hydrated result of a query.

There is no special DQL keyword that distinguishes a regular join from a fetch join. A join be it an inner or outer join becomes a fetch join as soon as fields of the joined entity appear in the SELECT part of the DQL query outside of an aggregate function. Otherwise its a regular join.

When Doctrine hydrates a query with fetch-join it returns the class in the FROM clause on the root level of the result array. In the previous example an array of User instances is returned and the address of each user is fetched and hydrated into the User address variable.

If you access the address Doctrine does not need to lazy load the association with another query. Doctrine allows you to walk all the associations between all the objects in your domain model. Objects that were not already loaded from the database are replaced with lazy load proxy instances. Non-loaded Collections are also replaced by lazy-load instances that fetch all the contained objects upon first access.

However relying on the lazy-load mechanism leads to many small queries executed against the database, which can significantly affect the performance of your application. DQL supports both named and positional parameters, however in contrast to many SQL dialects positional parameters are specified with numbers, for example?

Named parameters are specified with :name1, :name2 and so on. This section contains a large set of DQL queries and some explanations of what is happening. The actual result also depends on the hydration mode. Joins between entities without associations are available, where you can generate an arbitrary join with the following syntax:.

With an arbitrary join the result differs from the joins using a mapped property. The result of an arbitrary join is an one dimensional array with a mix of the entity from the SELECT and the joined entity fitting to the filtering of the query. In case of the example with User and Banlist , it can look like this:. In this form of join, the Banlist entities found by the filtering in the WITH part are not fetched by an accessor method on User , but are already part of the result.

In case the accessor method for Banlists is invoked on a User instance, it loads all the related Banlist objects corresponding to this User. This change of behaviour needs to be considered when the DQL is switched to an arbitrary join. By default when you run a DQL query in Doctrine and select only a subset of the fields for a given entity, you do not receive objects back.

Instead, you receive only arrays as a flat rectangular result set, similar to how you would if you were just using SQL directly and joining some data. By default a result is incremented by numerical keys starting with 0.

However with INDEX BY you can specify any other column to be the key of your result, it really only makes sense with primary or unique fields though:. You can also index by a to-one association, which will use the id of the associated entity the join column as the key in the result set:.

Entities that are already loaded into the persistence context will NOT be synced with the updated database state. It is recommended to call EntityManager clear and retrieve new instances of any affected entity.

Therefore, some limitations apply:. This, however, is costly performance-wise: It means collections and related entities are fetched into memory even if they are marked as lazy.

Pulling object graphs into memory on cascade can cause considerable performance overhead, especially when the cascaded collections are large. Make sure to weigh the benefits and downsides. It is possible to wrap both fields and identification values into aggregation and DQL functions. Numerical fields can be part of computations using mathematical operations. DQL offers a wide-range of additional expressions that are known from SQL, here is a list of all the supported constructs:.

So i didn't go further down that road. Net, you cannot assign a null value to an int or any other struct. The problem is that doctrine's DQL is a statically typed language that comes with a certain amount of complexity in its internals. We thought about allowing upcasting a couple of times, but the effort to get that working is simply not worth it, and people would simply abuse the syntax doing very dangerous things.

As stated on DDC, it is also indeed not possible to understand which class the property belongs to without incurring in nasty problems such as multiple subclasses defining same properties with different column names. That couples your DQL with all involved subclasses. Now we can take this even further and give a valid e-mail address format but an invalid domain name:. Now the above code will still fail because the domain somefakedomainiknowdoesntexist.

The not blank validator is similar to the not null validator except that it will fail on empty strings or strings with white space. Now if we try and save a User record with a username that is a single blank white space, validation will fail:. Now if we try and save a User with a username that has a space in it, the validation will fail:. The past validator checks if the given value is a valid date in the past. In this example we'll have a User model with a birthday column and we want to validate that the date is in the past.

The future validator is the opposite of the past validator and checks if the given value is a valid date in the future. Now if we try and set an appointment date that is not in the future we will get a validation error.

The min length does exactly what it says. It checks that the value string length is greater than the specified minimum length. In this example we will have a User model with a password column where we want to make sure the length of the password is at least 5 characters long.

Now if we try and save a User with a password that is shorter than 5 characters, the validation will fail. Now if you try and save a User with an invalid country code the validation will fail. Now if you try and save a User with an age that is less than 10 or greater than , the validation will fail.

You can use the range validator to validate max and min values by omitting either one of the 0 or 1 keys of the range array. Below is an example:. The above would make it so that age has a max of