Relations & Hints

We have already seen how to use hints to inject values into resulting objects. Lets analyze this topic more and see how to deal with the one-to-one and one-to-many relations efficiently.
Problem
Here is the real-life problem. Lets say that we have a list of some telecommunication centers in database. Each center has one or more associated prefixes. Also, each center belongs to one country (i.e. region). We need to fetch all telecom data, as they do not change during the application runtime.
Model
Model is no-brainer.
    @DbTable
    public class Telecom extends Entity {
        @DbId
        private long telecomId;
        @DbColumn
        private String name;
        @DbColumn
        private long countryId;
        ...
    }
    @DbTable
    public class TelecomPrefix extends Entity {
        @DbId
        protected long prefix;
        @DbColumn
        protected long telecomId;
        ...
    }
    @DbTable
    public class Country extends Entity {
        @DbId
        long countryId;
        @DbColumn
        String name;
        ...
    }
The rest of fields just hold various entity data. All methods are POJO setters and getters. Model objects, for now, are independent.
Note that each model object extends Entity class. This is not mandatory, but is considered as a good practice. Entity class usually contains implementation of hashCode() and equals() methods, based on the primary key of the class. Again, this is also not mandatory and some would consider the whole instance state then just primary keys. This is fine; using just primary keys is somewhat more pragmatic - and faster - if code is written with having that in mind.
Lazy approach
Lazy approach is fetching data without joins, firing several database queries. In our example we would need to execute the following queries:
fetch all Telecoms.
For each Telecom, fetch list of its TelecomPrefix
For each Telecom, fetch the belonging Country.
There is nothing special to mention here, each query and DbOom usage is simple.
Entity relationships
Up to now, there was no dependencies between entities. Obviously, it make sense to have list of TelecomPrefixes inside of Telecom, as well as the single Country. Therefore, we can write something like this:
    @DbTable
    public class Telecom extends Entity {
        ...
        protected TelecomPrefix[] prefixes;
        protected Country country;
        // get/set methods for above fields
        ...
    }
Instead of an array of TelecomPrefixes, we could use any Collection. {: .attn}
In the lazy approach, the whole wiring would be done manually, by developer. Once when he get list of TelecomPrefix entities for some Telecom he would need to manually convert it to an array and set it to target.
Join
This is nice case when we can use a join of three tables to fetch all data in one call. So the code may look like this:
    DbOomQuery q = query(sql(
            "select $C{t.*}, $C{tp.*}, $C{c.*} " +
            "from $T{Telecom t} join $T{TelecomPrefix tp} using ($.telecomId) " +
            "join $T{Country c} using ($.countryId)"));
​
    telecoms = q.list(Telecom.class, TelecomPrefix.class, Country.class);
Here we create join of three tables. Each result set row is mapped to an object array with three elements: telecom, telecom prefix and country. And finally, each such object array is stored in resulting list.
On the first sight, there are no improvements here: for each row, we still need to manually wire results.
Hints
Hints to the rescue! As we explained, hints defines how to wire objects within the single row. We want to use hints to inject e.g. Country instance into the Telecom instance, in the single row. Here is how to do so:
    DbOomQuery q = query(sql(
            "select $C{t.*}, $C{t.prefixes:tp.*}, $C{t.country:c.*} " +
            "from $T{Telecom t} join $T{TelecomPrefix tp} using ($.telecomId) " +
            "join $T{Country c} using ($.countryId)"));
​
    telecoms = q.list(Telecom.class, TelecomPrefix.class, Country.class);
The change is small, yet powerful! With hints we instruct to append all TelecomPrefix into the Telecom.prefixes property, as well to inject Country into the Telecom.country! Resulting list elements would have just one element, a Telecom, since all other mapped elements are injected into this instance.
While this perfectly works with one-to-one relationships, like with Country; there is a failure with one-to-many relationships, like with TelecomPrefix. This is because for the each row of result set, DbOom will create a new instance of Telecome. Hence, if a telecom contain two prefixes, it will be listed twice and each time telecom will link just one, different, telecom prefix!
Cache entities
Fortunately, the problem is easy to solve: by enabling caching on query level (i.e. on result-set level). So this code:
    DbOomQuery q = query(sql(
            "select $C{t.*}, $C{t.prefixes:tp.*}, $C{t.country:c.*} " +
            "from $T{Telecom t} join $T{TelecomPrefix tp} using ($.telecomId) " +
            "join $T{Country c} using ($.countryId)"));
​
    q.cacheEntities(true);
    telecoms = q.list(Telecom.class, TelecomPrefix.class, Country.class);
DbOoom now caches all entities during the execution of a query and re-uses existing instances if already exist! In our case this means that instead of creating several instances of Telecom for each its prefix, there will be just one instance, with many prefixes injected into it.
Using query cache increases memory usage. {: .attn}
There is just one thing to be aware of - the resulting list will still contain duplicated records (hey, it's the same with Hibernate:) The trivial way to fix this is to use a Set instead of List\:
    DbOomQuery q = query(sql(
            "select $C{t.*}, $C{t.prefixes:tp.*}, $C{t.country:c.*} " +
            "from $T{Telecom t} join $T{TelecomPrefix tp} using ($.telecomId) " +
            "join $T{Country c} using ($.countryId)"));
​
    q.cacheEntities(true);
    telecoms = q.listSet(Telecom.class, TelecomPrefix.class, Country.class);
What we have now is the set of unique entities, properly injected with related content.
EntityAware mode
But using Set is not always an option. Can we have a List, but without duplicate entries? Sure! DbOomQuery supports so called "entity mode". It goes one step further from cacheEntities, so enabling the entity mode will also enable cached entities.
In entity aware mode, not only that objects are cached, but also they are compared to the previous result! The very same example from above:
    DbOomQuery q = query(sql(
            "select $C{t.*}, $C{t.prefixes:tp.*}, $C{t.country:c.*} " +
            "from $T{Telecom t} join $T{TelecomPrefix tp} using ($.telecomId) " +
            "join $T{Country c} using ($.countryId)"));
​
    q.entityAwareMode(true);
    telecoms = q.list(Telecom.class, TelecomPrefix.class, Country.class);
will now return List without the duplicates! Just a nice object tree, ready to be used :)
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Problem
Model
Lazy approach
Entity relationships
Join
Hints
Cache entities
EntityAware mode