Implementation
Implement the Parallel Stats project with parallel streams to calculate summary statistics.
Implementation is a free Java Academy lesson on CoddyKit. This is lesson 2 of 3. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Java Academy learning path, and your progress syncs across the web and the CoddyKit app. The Java Academy course includes 3 lessons in total.
Intro
Time to implement Parallel Stats: use parallel streams to calculate sum, average, min, and max.
Code: sum
Use mapToInt().sum() on a parallel stream to calculate totals.
import java.util.*;public class Main {
public static void main(String[] args) {
List<Integer> nums = Arrays.asList(1,2,3,4,5,6,7,8,9,10);
int sum = nums.parallelStream().mapToInt(n -> n).sum();
System.out.println("Sum = " + sum);
}
}
Code: average
average() computes mean value across parallel data.
import java.util.*;public class Main {
public static void main(String[] args) {
List<Integer> nums = Arrays.asList(10,20,30,40,50);
double avg = nums.parallelStream().mapToInt(n -> n).average().orElse(0);
System.out.println("Average = " + avg);
}
}
Code: summaryStatistics
summaryStatistics() provides all key statistics in one step.
import java.util.*;import java.util.stream.*;public class Main {
public static void main(String[] args) {
List<Integer> nums = Arrays.asList(3,7,2,9,5);
IntSummaryStatistics stats = nums.parallelStream().mapToInt(n -> n).summaryStatistics();
System.out.println("Count = " + stats.getCount());
System.out.println("Sum = " + stats.getSum());
System.out.println("Min = " + stats.getMin());
System.out.println("Average = " + stats.getAverage());
System.out.println("Max = " + stats.getMax());
}
}
Empty lists
Guard against empty lists: average().orElse(0) avoids errors when no elements exist.
Performance
Parallel speedup appears only with large datasets. For small lists, sequential may be faster.
Implementation check
Quick check: Which method can summarize statistics from an IntStream directly?
Recap
Recap: Implemented stats with parallel streams using sum, average, and summaryStatistics().
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Frequently Asked Questions
Is the “Implementation” lesson free?
Yes — the full text of “Implementation” is free to read here on the web. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Java Academy course, upgrade to CoddyKit PRO. The Java Academy course includes 3 lessons in total.
What will I learn in “Implementation”?
Implement the Parallel Stats project with parallel streams to calculate summary statistics. You practise Java Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start Java Academy?
No prior experience is required. Java Academy on CoddyKit is structured for beginners through advanced learners, so you can start here or from the beginning and move at your own pace. This is lesson 2 of 3.
How long does the “Implementation” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this Java Academy lesson?
Yes. Every Java Academy lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
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