What are data aggregation pipelines?

Data aggregation pipelines are a series of operations applied to a stream of data to transform, filter, and aggregate it in different ways. These pipelines are composed of multiple stages, each stage contributing to the overall transformation of the data. Some common stages include mapping, filtering, sorting, and reducing.

Building an aggregation pipeline

To demonstrate the implementation of data aggregation pipelines, let’s consider an example where we have a list of employees with their salaries, and we want to calculate the average salary of all employees.

First, we need to create a stream from the list of employees:

List<Employee> employees = // initialize the list of employees
Stream<Employee> employeeStream = employees.stream();

Next, we can apply various operations to the stream to transform and aggregate the data. In this case, we will use the mapToDouble operation to extract the salaries of all employees, and then use the average operation to calculate the average:

OptionalDouble averageSalary = employeeStream
    .mapToDouble(Employee::getSalary)
    .average();

Note that the average operation returns an OptionalDouble to handle the case when the stream is empty.

Finally, we can retrieve the calculated average salary using the orElse method:

double average = averageSalary.orElse(0.0);
System.out.println("Average salary: " + average);

Chaining multiple operations

One of the strengths of the Streams API is that we can chain multiple operations together to form a pipeline. Let’s extend our example to also calculate the maximum salary of all employees:

double maxSalary = employeeStream
    .mapToDouble(Employee::getSalary)
    .max()
    .orElse(0.0);
System.out.println("Maximum salary: " + maxSalary);

By chaining multiple operations, we can efficiently perform multiple aggregations or transformations in a single pass over the data.

Conclusion

The Java Streams API provides a powerful and concise way to implement data aggregation pipelines in your applications. By leveraging the various operations available, you can easily process and manipulate data in a declarative and efficient manner. Whether you need to aggregate, filter, or transform data, the Streams API has you covered.

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