Querying

Morphia offers a fluent API with which to build up a query and map the results back to instances of your entity classes. It attempts to provide as much type safety and validation as possible. To this end, Morphia offers the Query<T> class which can be parameterized to the type of your entity.

Creating a Query

The Datastore is the key class when using Morphia. Virtually all operations begin with the Datastore. To create the Query, we invoke the following code:

Query<Product> query = datastore.createQuery(Product.class);

createQuery() returns an instance of Query with which we can build a query.

filter()

The first method of interest is filter(). This method takes two values: a condition string and a value. The value parameter is, of course, the value to use when applying the condition clause. The condition parameter is a bit more complicated. At its simplest, the condition is just a field name. In this case, the condition is assumed to be an equality check. There is a slightly more complicated variant, however.

The condition value can also contain an operator. For example, to compare a numeric field against a value, you might write something like this:

query.filter("price >=", 1000);

In this case, we’re instructing Morphia to add a filter using $gte. This would result in a query that looks like this:

{ price: { $gte: 1000 } }

The list of supported filter operations can be found in the FilterOperator class.

Operator Alias
$center
$centerSphere
$box
$eq =, ==
$ne !=, <>
$gt >
$gte >=
$lt <
$lte <=
$exists exists
$type type
$not
$mod mod
$size size
$in in
$nin nin
$all all
$elemMatch elem, elemMatch
$where
$near near
$nearSphere
$within (deprecated replaced by $geoWithin) within
$geoNear geoNear
$geoWithin geoWithin
$geoIntersects geoIntersects

Each filter operator can either be referenced by its MongoDB “dollar operator” or by the aliases listed afterward. For example, with the equal operator, you can use the canonical $eq operator as you would when building a query in the shell or you could opt to use either the = or == aliases which might feel a little more natural to use than the dollar operators.

field()

For those who would prefer more compile time validation of their queries, there is field(). This method takes only the field name and returns an instance of a class providing methods with which to define your filters. This approach is slightly more verbose but can be validated by the compiler to a much greater degree than filter() can be. To perform the same query as above, you’d write this:

query.field("price").greaterThanOrEq(1000);

This results in the exact same query as the filter() version but has the advantage that any typo in the operation name (method in this case) would easily be caught by an IDE or compiler. Which version you use is largely a question of preference.

Note

Regardless of the approach used, the field name given can be either the Java field name or the document field name as defined by the @Property annotation on the field. Morphia will normalize the name and validate the name such that a query with a bad field name will result in an error.

Complex Queries

Of course, queries are usually more complex than single field comparisons. Morphia offers both and() and or() to build up more complex queries. An and query might look something like this:

q.and(
    q.criteria("width").equal(10),
    q.criteria("height").equal(1)
);

An or clause looks exactly the same except for using or() instead of and(), of course. For these clauses we use the criteria() method instead of field() but it is used in much the same fashion. and() and or() take a varargs parameter of type Criteria so you can include as many filters as necessary. If all you need is an and clause, you don’t need an explicit call to and():

datastore.createQuery(UserLocation.class)
    .field("x").lessThan(5)
    .field("y").greaterThan(4)
    .field("z").greaterThan(10);

This generates an implicit and across the field comparisons.

Text Searching

Morphia also supports MongoDB’s text search capabilities. In order to execute a text search against a collection, the collection must have a text index defined first. Using Morphia that definition would look like this:

@Indexes(@Index(fields = @Field(value = "$**", type = IndexType.TEXT)))
public static class Greeting {
    @Id
    private ObjectId id;
    private String value;
    private String language;
    
    ...
}

The $** value tells MongoDB to create a text index on all the text fields in a document. A more targeted index can be created, if desired, by explicitly listing which fields to index. Once the index is defined, we can start querying against it like this test does:

morphia.map(Greeting.class);
datastore.ensureIndexes();

datastore.save(new Greeting("good morning", "english"));
datastore.save(new Greeting("good afternoon", "english"));
datastore.save(new Greeting("good night", "english"));
datastore.save(new Greeting("good riddance", "english"));

datastore.save(new Greeting("guten Morgen", "german"));
datastore.save(new Greeting("guten Tag", "german"));
datastore.save(new Greeting("guten Nacht", "german"));

List<Greeting> good = datastore.createQuery(Greeting.class)
                             .search("good")
                             .order("_id")
                             .asList();
Assert.assertEquals(4, good.size());

As you can see here, we create Greeting objects for multiple languages. In our test query, we’re looking for occurrences of the word “good” in any document. We created four such documents and our query returns exactly those four.

Other Query Options

There is more to querying than simply filtering against different document values. Listed below are some of the options for modifying the query results in different ways.

Projections

Projections allow you to return only a subset of the fields in a document. This is useful when you need to only return a smaller view of a larger object. Borrowing from the unit tests, this is an example of this feature in action:

ContainsRenamedFields user = new ContainsRenamedFields("Frank", "Zappa");
getDs().save(user);

ContainsRenamedFields found = getDs()
    .find(ContainsRenamedFields.class)
    .retrievedFields(true, "first_name").get();
Assert.assertNotNull(found.firstName);
Assert.assertNull(found.lastName);

found = getDs()
    .find(ContainsRenamedFields.class)
    .retrievedFields(true, "firstName").get();
Assert.assertNotNull(found.firstName);
Assert.assertNull(found.lastName);

As you can see here, we’re saving this entity with a first and last name but our query only returns the first name (and the _id value) in the returned instance of our type. It’s also worth noting that this project works with both the mapped document field name "first_name" and the Java field name "firstName".

The boolean value passed in to the first parameter instructs Morphia to either include (true) or exclude (false) the fields listed. The second parameter is a varargs String parameter defining which fields are to be either included or excluded in the query results. It is not currently possible to list both inclusions and exclusions in one query.

important

While projections can be a nice performance win in some cases, it’s important to note that this object can not be safely saved back to MongoDB. Any fields in the existing document in the database that are missing from the entity will be removed if this entity is saved. For example, in the example above if found is saved back to MongoDB, the last_name field that currently exists in the database for this entity will be removed.

Limiting and Skipping

Pagination of query results is often done as a combination of skips and limits. Morphia offers Query.limit(int) and Query.offset(int) for these cases. An example of these methods in action would look like this:

datastore.createQuery(Person.class)
    .offset(1)
    .limit(10)
    .asList()

This query will skip the first element and take up to the next 10 items found by the query. There’s a caveat to using skip/limit for pagination, however. See the skip documentation for more detail.

Ordering

Ordering the results of a query is done via Query.order(String) . The javadoc has complete examples but this String consists of a list of comma delimited fields to order by. To reverse the sort order for a particular field simply prefix that field with a -. For example, to sort by age (youngest to oldest) and then income (highest to lowest), you would use this:

query.order("age,-income");

Tailable Cursors

If you have a capped collection it’s possible to “tail” a query so that when new documents are added to the collection that match your query, they’ll be returned by the tailable cursor. An example of this feature in action can be found in the unit tests in the testTailableCursors() test:

getMorphia().map(CappedPic.class);
getDs().ensureCaps();                                                          // #1
final Query<CappedPic> query = getDs().createQuery(CappedPic.class);
final List<CappedPic> found = new ArrayList<CappedPic>();

final Iterator<CappedPic> tail = query.tail();
while(found.size() < 10) {
    found.add(tail.next());                                                    // #2
}

There are two things to note about this code sample:

  1. This tells Morphia to make sure that any entity configured to use a capped collection has its collection created correctly. If the collection already exists and is not capped, you will have to manually update your collection to be a capped collection.
  2. Since this Iterator is backed by a tailable cursor, hasNext() and next() will block until a new item is found. In this version of the unit test, we tail the cursor waiting to pull out objects until we have 10 of them and then proceed with the rest of the application.