Advanced queries in Dart
Joins
Drift supports sql joins to write queries that operate on more than one table. To use that feature, start a select regular select statement with select(table)
and then add a list of joins using .join()
. For inner and left outer joins, a ON
expression needs to be specified. Here's an example using the tables defined in the example.
// we define a data class to contain both a todo entry and the associated category
class EntryWithCategory {
EntryWithCategory(this.entry, this.category);
final TodoEntry entry;
final Category category;
}
// in the database class, we can then load the category for each entry
Stream<List<EntryWithCategory>> entriesWithCategory() {
final query = select(todos).join([
leftOuterJoin(categories, categories.id.equalsExp(todos.category)),
]);
// see next section on how to parse the result
}
Parsing results
Calling get()
or watch
on a select statement with join returns a Future
or Stream
of List<TypedResult>
, respectively. Each TypedResult
represents a row from which data can be read. It contains a rawData
getter to obtain the raw columns. But more importantly, the readTable
method can be used to read a data class from a table.
In the example query above, we can read the todo entry and the category from each row like this:
return query.watch().map((rows) {
return rows.map((row) {
return EntryWithCategory(
row.readTable(todos),
row.readTableOrNull(categories),
);
}).toList();
});
Note: readTable
will throw an ArgumentError
when a table is not present in the row. For instance, todo entries might not be in any category. To account for that, we use row.readTableOrNull
to load categories.
Custom columns
Select statements aren't limited to columns from tables. You can also include more complex expressions in the query. For each row in the result, those expressions will be evaluated by the database engine.
class EntryWithImportance {
final TodoEntry entry;
final bool important;
EntryWithImportance(this.entry, this.important);
}
Future<List<EntryWithImportance>> loadEntries() {
// assume that an entry is important if it has the string "important" somewhere in its content
final isImportant = todos.content.like('%important%');
return select(todos).addColumns([isImportant]).map((row) {
final entry = row.readTable(todos);
final entryIsImportant = row.read(isImportant);
return EntryWithImportance(entry, entryIsImportant);
}).get();
}
Note that the like
check is not performed in Dart - it's sent to the underlying database engine which can efficiently compute it for all rows.
Aliases
Sometimes, a query references a table more than once. Consider the following example to store saved routes for a navigation system:
class GeoPoints extends Table {
IntColumn get id => integer().autoIncrement()();
TextColumn get name => text()();
TextColumn get latitude => text()();
TextColumn get longitude => text()();
}
class Routes extends Table {
IntColumn get id => integer().autoIncrement()();
TextColumn get name => text()();
// contains the id for the start and destination geopoint.
IntColumn get start => integer()();
IntColumn get destination => integer()();
}
Now, let's say we wanted to also load the start and destination GeoPoint
object for each route. We'd have to use a join on the geo-points
table twice: For the start and destination point. To express that in a query, aliases can be used:
class RouteWithPoints {
final Route route;
final GeoPoint start;
final GeoPoint destination;
RouteWithPoints({this.route, this.start, this.destination});
}
// inside the database class:
Future<List<RouteWithPoints>> loadRoutes() async {
// create aliases for the geoPoints table so that we can reference it twice
final start = alias(geoPoints, 's');
final destination = alias(geoPoints, 'd');
final rows = await select(routes).join([
innerJoin(start, start.id.equalsExp(routes.start)),
innerJoin(destination, destination.id.equalsExp(routes.destination)),
]).get();
return rows.map((resultRow) {
return RouteWithPoints(
route: resultRow.readTable(routes),
start: resultRow.readTable(start),
destination: resultRow.readTable(destination),
);
}).toList();
}
The generated statement then looks like this:
SELECT
routes.id, routes.name, routes.start, routes.destination,
s.id, s.name, s.latitude, s.longitude,
d.id, d.name, d.latitude, d.longitude
FROM routes
INNER JOIN geo_points s ON s.id = routes.start
INNER JOIN geo_points d ON d.id = routes.destination
ORDER BY
and WHERE
on joins
Similar to queries on a single table, orderBy
and where
can be used on joins too. The initial example from above is expanded to only include todo entries with a specified filter and to order results based on the category's id:
Stream<List<EntryWithCategory>> entriesWithCategory(String entryFilter) {
final query = select(todos).join([
leftOuterJoin(categories, categories.id.equalsExp(todos.category)),
]);
query.where(todos.content.like(entryFilter));
query.orderBy([OrderingTerm.asc(categories.id)]);
// ...
}
As a join can have more than one table, all tables in where
and orderBy
have to be specified directly (unlike the callback on single-table queries that gets called with the right table by default).
Group by
Sometimes, you need to run queries that aggregate data, meaning that data you're interested in comes from multiple rows. Common questions include
- how many todo entries are in each category?
- how many entries did a user complete each month?
- what's the average length of a todo entry?
What these queries have in common is that data from multiple rows needs to be combined into a single row. In sql, this can be achieved with "aggregate functions", for which drift has builtin support.
Additional info: A good tutorial for group by in sql is available here.
To write a query that answers the first question for us, we can use the count
function. We're going to select all categories and join each todo entry for each category. What's special is that we set useColumns: false
on the join. We do that because we're not interested in the columns of the todo item. We only care about how many there are. By default, drift would attempt to read each todo item when it appears in a join.
Future<void> countTodosInCategories() async {
final amountOfTodos = todos.id.count();
final query = select(categories).join([
innerJoin(
todos,
todos.category.equalsExp(categories.id),
useColumns: false,
)
]);
query
..addColumns([amountOfTodos])
..groupBy([categories.id]);
final result = await query.get();
for (final row in result) {
print('there are ${row.read(amountOfTodos)} entries in'
'${row.readTable(categories)}');
}
}
To find the average length of a todo entry, we use avg
. In this case, we don't even have to use a join
since all the data comes from a single table (todos). That's a problem though - in the join, we used useColumns: false
because we weren't interested in the columns of each todo item. Here we don't care about an individual item either, but there's no join where we could set that flag. Drift provides a special method for this case - instead of using select
, we use selectOnly
. The "only" means that drift will only report columns we added via "addColumns". In a regular select, all columns from the table would be selected, which is what you'd usually need.
Stream<double> averageItemLength() {
final avgLength = todos.content.length.avg();
final query = selectOnly(todos)..addColumns([avgLength]);
return query.map((row) => row.read(avgLength)!).watchSingle();
}