Java: Aggregate Data Off-Heap

Creating large aggregations using Java Map, List and Object normally creates a lot of heap memory overhead. This also means that the garbage collector will have to clean up these objects once the aggregation goes out of scope.

Read this short article and discover how we can use Speedment Stream ORM to create off-heap aggregations that can utilize memory more efficiently and with little or no GC impact.

Person

Let's say we have a large number of Person objects that take the following shape:

public class Person {
    private final int age;
    private final short height;
    private final short weight;        
    private final String gender;
    private final double salary;
    ...
    // Getters and setters hidden for brievity
}

For the sake of argument, we also have access to a method called persons() that will create a new Stream with all these Person objects.

Salary Per Age

We want to create the average salary for each age bucket. To represent the results of aggregations, we will be using a data class called AgeSalary, which associates a certain age with an average salary.

public class AgeSalary {
     private int age;
     private double avgSalary;
     ... 
    // Getters and setters hidden for brievity
}

Age grouping for salaries normally entails less than 100 buckets being used, and so, this example is just to show the principle. The more buckets, the more sense it makes to aggregate off-heap.

Solution

Using Speedment Stream ORM, we can derive an off-heap aggregation solution with these three steps:

Create an Aggregator

var aggregator = Aggregator.builderOfType(Person.class, AgeSalary::new)
    .on(Person::age).key(AgeSalary::setAge)
    .on(Person::salary).average(AgeSalary::setAvgSalary)
    .build();

The aggregator can be reused over and over again.

Compute an Aggregation

var aggregation = persons().collect(aggregator.createCollector());

Using the aggregator, we create a standard Java stream Collector that has its internal state completely off-heap.

Use the Aggregation Result

aggregation.streamAndClose()
    .forEach(System.out::println);

Since the Aggregation holds data that is stored off-heap, it may benefit from explicit closing rather than just being potentially cleaned up much later. Closing the Aggregation can be done by calling the close() method, possibly by taking advantage of the AutoCloseable trait, or as in the example above by using streamAndClose(), which returns a stream that will close the Aggregation after stream termination.

Everything in a One-Liner

The code above can be condensed to what is an effective one-liner:

persons().collect(Aggregator.builderOfType(Person.class, AgeSalary::new)
    .on(Person::age).key(AgeSalary::setAge)
    .on(Person::salary).average(AgeSalary::setAvgSalary)
    .build()
    .createCollector()
).streamAndClose()
    .forEach(System.out::println);

There is also support for parallel aggregations. Just add the stream operation Stream::parallel and aggregation is done using the ForkJoin pool.

Resources

Download Speedment here

Read more about off-heap aggregations here