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How To Compare Sets In Java Efficiently

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Comparing sets in Java is a common task, but doing it efficiently is crucial for performance. At compare.edu.vn, we provide clear comparisons and actionable solutions, ensuring you make informed decisions. Discover the optimized methods and data structure comparisons that will significantly improve your set comparison strategy. Explore effective comparison techniques now, from identifying differences to finding common elements.

1. Understanding the Basics of Sets in Java

Before diving into the specifics of How To Compare Sets In Java, it’s essential to understand what sets are and how they function within the Java Collections Framework. A set is an abstract data type that can store certain values, without any particular order, and no repeated values. It models the mathematical set abstraction. The Java Set interface represents a collection that contains no duplicate elements. More formally, sets contain no pair of elements e1 and e2 such that e1.equals(e2), and at most one null element.

1.1. What is a Set?

In Java, a Set is an interface that extends the Collection interface. It is a collection that does not allow duplicate elements. This means that each element in a set must be unique. The Set interface is part of the Java Collections Framework, which provides a unified architecture for representing and manipulating collections. Sets are useful for representing groups of unique items, such as unique IDs, distinct objects, or any scenario where duplicates are not allowed.

1.2. Common Implementations of the Set Interface

Java provides several implementations of the Set interface, each with its own characteristics and performance trade-offs:

  • HashSet: This implementation stores elements in a hash table, offering constant time complexity for basic operations like adding, removing, and checking for the presence of an element, provided the hash function distributes elements properly among the buckets. HashSet does not guarantee the order of elements.
  • LinkedHashSet: This is a subclass of HashSet that maintains the order of elements as they are inserted. It uses a doubly-linked list to preserve insertion order, providing predictable iteration.
  • TreeSet: This implementation stores elements in a sorted order, using a tree structure (specifically, a red-black tree). TreeSet provides logarithmic time complexity for basic operations and requires elements to be comparable, either through implementing the Comparable interface or by providing a Comparator when creating the TreeSet.
  • EnumSet: A specialized set implementation for use with enum types. EnumSet is highly efficient and compact, as it uses a bit vector to represent the set of enum constants. There are two implementations: RegularEnumSet is used when the enum type has 64 or fewer elements, JumboEnumSet is used when there are more than 64.

Each implementation has its own use cases, depending on the specific requirements of your application.

1.3. Key Characteristics of Sets

Sets in Java have several key characteristics that make them useful in various programming scenarios:

  • Uniqueness: Sets do not allow duplicate elements. Adding an element that is already present in the set has no effect.
  • Unordered (in some implementations): HashSet does not maintain the order of elements. Elements are stored based on their hash code, which can change over time. LinkedHashSet maintains insertion order, and TreeSet maintains elements in sorted order.
  • No Indexing: Sets do not provide indexing like lists or arrays. You cannot access elements by their position in the set.
  • Null Elements: Most set implementations allow one null element. TreeSet does not allow null elements because it relies on comparison for sorting, and null cannot be compared.

1.4. Why is Efficient Set Comparison Important?

Efficient set comparison is crucial for performance-sensitive applications. Inefficient set comparison can lead to significant performance bottlenecks, especially when dealing with large datasets. The choice of algorithm and data structure can greatly impact the time complexity and overall performance of the comparison operation. Understanding the trade-offs between different approaches is essential for writing efficient Java code.

2. Common Use Cases for Comparing Sets in Java

Comparing sets in Java is a fundamental operation that arises in various application scenarios. Understanding these common use cases will help you appreciate the importance of efficient set comparison techniques.

2.1. Finding Common Elements Between Two Sets (Intersection)

One of the most common use cases is finding the common elements between two sets, also known as the intersection of the sets. This operation identifies elements that are present in both sets. This is useful in scenarios where you need to find overlapping data.

Example:

Consider two sets, setA and setB, representing the IDs of users who have accessed two different features of an application. Finding the intersection of these sets will give you the IDs of users who have accessed both features.

2.2. Identifying Differences Between Two Sets (Difference)

Another frequent use case is identifying the differences between two sets. This involves finding elements that are present in one set but not in the other. This operation is useful for determining what is unique to each set.

Example:

Suppose you have two sets, setA and setB, representing the products in two different inventory lists. Finding the difference between setA and setB will give you the products that are only in setA and not in setB.

2.3. Checking if Two Sets are Equal

Sometimes, you need to check if two sets are equal, meaning they contain the exact same elements. This is different from checking if they have any elements in common.

Example:

You might have two sets representing the permissions assigned to two different user roles. Checking if these sets are equal will ensure that both roles have the same permissions.

2.4. Determining if One Set is a Subset or Superset of Another

Determining if one set is a subset or superset of another is another important use case. A set setA is a subset of setB if all elements of setA are also present in setB. Conversely, setB is a superset of setA if it contains all elements of setA.

Example:

Consider a set setA representing the required dependencies for a software module and a set setB representing the installed dependencies on a system. Checking if setA is a subset of setB will determine if all required dependencies are installed on the system.

2.5. Data Validation and Deduplication

Sets are often used for data validation and deduplication. Comparing sets can help identify invalid or duplicate data entries.

Example:

Suppose you have a set setA of valid email addresses and you receive a new set setB of email addresses from a form submission. Comparing setB against setA can help you identify any invalid or duplicate email addresses in the new submission.

2.6. Use Case Summary

Use Case Description Example
Finding Common Elements (Intersection) Identifying elements present in both sets. Users who have accessed both Feature A and Feature B.
Identifying Differences (Difference) Finding elements present in one set but not the other. Products present in Inventory List A but not in Inventory List B.
Checking if Two Sets are Equal Verifying if two sets contain the exact same elements. Ensuring two user roles have the same permissions.
Subset/Superset Determination Checking if one set contains all elements of another. Verifying that all required software dependencies are installed.
Data Validation and Deduplication Identifying invalid or duplicate data entries. Detecting invalid or duplicate email addresses in a form submission.

By understanding these common use cases, you can better appreciate the importance of efficient set comparison techniques in Java and how they can be applied in various scenarios.

3. Naive Approach: Nested Loops

The simplest and most intuitive way to compare two sets in Java is by using nested loops. This approach involves iterating through each element of one set and comparing it with every element of the other set. While straightforward to implement, this method is highly inefficient for large sets due to its quadratic time complexity.

3.1. How Nested Loops Work

The nested loop approach works as follows:

  1. Iterate through each element of the first set (setA).
  2. For each element in setA, iterate through each element of the second set (setB).
  3. Compare the current element from setA with the current element from setB.
  4. Perform the desired operation (e.g., check for equality, find common elements) based on the comparison result.

3.2. Java Code Example

Here’s a Java code example demonstrating the nested loop approach for finding the common elements between two sets:

import java.util.HashSet;
import java.util.Set;

public class NestedLoopComparison {

    public static void main(String[] args) {
        Set<Integer> setA = new HashSet<>();
        setA.add(1);
        setA.add(2);
        setA.add(3);
        setA.add(4);
        setA.add(5);

        Set<Integer> setB = new HashSet<>();
        setB.add(3);
        setB.add(5);
        setB.add(6);
        setB.add(7);

        Set<Integer> commonElements = findCommonElements(setA, setB);

        System.out.println("Common elements: " + commonElements);
    }

    public static Set<Integer> findCommonElements(Set<Integer> setA, Set<Integer> setB) {
        Set<Integer> commonElements = new HashSet<>();
        for (Integer elementA : setA) {
            for (Integer elementB : setB) {
                if (elementA.equals(elementB)) {
                    commonElements.add(elementA);
                }
            }
        }
        return commonElements;
    }
}

*3.3. Time Complexity: O(nm)**

The nested loop approach has a time complexity of O(n*m), where n is the size of the first set and m is the size of the second set. This means that the execution time increases quadratically with the size of the sets. For large sets, this can result in significant performance issues.

3.4. Why is it Inefficient?

The nested loop approach is inefficient because it performs a comparison for every possible pair of elements between the two sets. This results in a large number of unnecessary comparisons, especially when the sets are large. The quadratic time complexity makes this approach impractical for real-world applications dealing with large datasets.

3.5. When to Avoid Nested Loops

You should avoid using nested loops for set comparison when:

  • The sets are large, as the quadratic time complexity will lead to performance bottlenecks.
  • Performance is critical, and you need to minimize the execution time of the comparison operation.
  • Alternative approaches with better time complexity are available.

In most practical scenarios, there are more efficient ways to compare sets in Java than using nested loops. These alternatives, such as using the built-in methods provided by the Set interface or leveraging hash-based approaches, offer significantly better performance.

4. Efficient Approach: Using Built-in Set Methods

Java’s Set interface provides built-in methods that can be used to efficiently compare sets. These methods leverage optimized algorithms and data structures, resulting in significantly better performance compared to the naive nested loop approach.

4.1. containsAll() Method

The containsAll() method is used to check if one set contains all the elements of another set. This method is useful for determining if one set is a subset of another.

How it Works:

The containsAll() method iterates through the elements of the specified collection and checks if each element is present in the set. If all elements are present, the method returns true; otherwise, it returns false.

Java Code Example:

import java.util.HashSet;
import java.util.Set;

public class ContainsAllExample {

    public static void main(String[] args) {
        Set<Integer> setA = new HashSet<>();
        setA.add(1);
        setA.add(2);
        setA.add(3);

        Set<Integer> setB = new HashSet<>();
        setB.add(1);
        setB.add(2);

        boolean isSubset = setA.containsAll(setB);

        System.out.println("Is setB a subset of setA? " + isSubset);
    }
}

Time Complexity:

The time complexity of the containsAll() method is O(n), where n is the size of the specified collection (the set being checked for containment).

4.2. retainAll() Method

The retainAll() method is used to find the intersection of two sets. It modifies the set on which it is called to retain only the elements that are also present in the specified collection.

How it Works:

The retainAll() method iterates through the elements of the set and removes any elements that are not present in the specified collection. The set is modified to contain only the common elements.

Java Code Example:

import java.util.HashSet;
import java.util.Set;

public class RetainAllExample {

    public static void main(String[] args) {
        Set<Integer> setA = new HashSet<>();
        setA.add(1);
        setA.add(2);
        setA.add(3);
        setA.add(4);
        setA.add(5);

        Set<Integer> setB = new HashSet<>();
        setB.add(3);
        setB.add(5);
        setB.add(6);
        setB.add(7);

        setA.retainAll(setB);

        System.out.println("Intersection of setA and setB: " + setA);
    }
}

Time Complexity:

The time complexity of the retainAll() method is O(n), where n is the size of the set on which the method is called.

4.3. removeAll() Method

The removeAll() method is used to find the difference between two sets. It modifies the set on which it is called to remove all the elements that are also present in the specified collection.

How it Works:

The removeAll() method iterates through the elements of the specified collection and removes any matching elements from the set. The set is modified to contain only the elements that are not present in the specified collection.

Java Code Example:

import java.util.HashSet;
import java.util.Set;

public class RemoveAllExample {

    public static void main(String[] args) {
        Set<Integer> setA = new HashSet<>();
        setA.add(1);
        setA.add(2);
        setA.add(3);
        setA.add(4);
        setA.add(5);

        Set<Integer> setB = new HashSet<>();
        setB.add(3);
        setB.add(5);
        setB.add(6);
        setB.add(7);

        setA.removeAll(setB);

        System.out.println("Difference between setA and setB: " + setA);
    }
}

Time Complexity:

The time complexity of the removeAll() method is O(n), where n is the size of the specified collection (the collection of elements to be removed).

4.4. equals() Method

The equals() method is used to check if two sets are equal, meaning they contain the exact same elements.

How it Works:

The equals() method first checks if the two sets have the same size. If they do not, the method returns false. Otherwise, it iterates through the elements of one set and checks if each element is present in the other set. If all elements are present, the method returns true; otherwise, it returns false.

Java Code Example:

import java.util.HashSet;
import java.util.Set;

public class EqualsExample {

    public static void main(String[] args) {
        Set<Integer> setA = new HashSet<>();
        setA.add(1);
        setA.add(2);
        setA.add(3);

        Set<Integer> setB = new HashSet<>();
        setB.add(3);
        setB.add(2);
        setB.add(1);

        boolean areEqual = setA.equals(setB);

        System.out.println("Are setA and setB equal? " + areEqual);
    }
}

Time Complexity:

The time complexity of the equals() method is O(n), where n is the size of the sets being compared.

4.5. Performance Benefits

Using the built-in set methods offers significant performance benefits compared to the nested loop approach. These methods leverage optimized algorithms and data structures, resulting in linear time complexity for most operations. This makes them suitable for comparing large sets in real-world applications.

4.6. Best Practices

When using the built-in set methods, consider the following best practices:

  • Choose the appropriate method based on the specific comparison task (e.g., containsAll() for subset checking, retainAll() for intersection, removeAll() for difference, equals() for equality checking).
  • Be aware of the time complexity of each method and choose the most efficient option for your use case.
  • Utilize the HashSet implementation for best performance, as it offers constant time complexity for basic operations.

By following these best practices, you can effectively leverage the built-in set methods to efficiently compare sets in Java.

5. Optimizing Set Comparison with HashSets

When dealing with large sets, optimizing set comparison becomes crucial for maintaining performance. Using HashSet can significantly improve the efficiency of set operations due to its constant-time complexity for basic operations like adding, removing, and checking for the presence of an element.

5.1. Leveraging HashSet for Faster Lookups

HashSet uses a hash table to store elements, which allows for constant-time complexity (O(1)) for add(), remove(), and contains() operations on average. This is a significant advantage over other set implementations like TreeSet, which has logarithmic time complexity (O(log n)) for these operations.

5.2. Creating a HashSet of IDs for Efficient Comparison

To efficiently compare sets, you can create a HashSet of IDs from one set and then iterate through the other set, checking for the presence of each element’s ID in the HashSet. This approach reduces the time complexity from O(n*m) (nested loops) to O(n + m), where n and m are the sizes of the two sets.

Java Code Example:

import java.util.HashSet;
import java.util.Set;

public class HashSetComparison {

    public static void main(String[] args) {
        Set<A> setA = new HashSet<>();
        setA.add(new A(1, "Object 1"));
        setA.add(new A(2, "Object 2"));
        setA.add(new A(3, "Object 3"));

        Set<B> setB = new HashSet<>();
        setB.add(new B(2, "Item 2"));
        setB.add(new B(4, "Item 4"));
        setB.add(new B(5, "Item 5"));

        Set<A> commonElements = findCommonElements(setA, setB);

        System.out.println("Common elements: " + commonElements);
    }

    public static Set<A> findCommonElements(Set<A> setA, Set<B> setB) {
        Set<A> commonElements = new HashSet<>();
        Set<Integer> bIds = new HashSet<>();
        for (B b : setB) {
            bIds.add(b.getId());
        }
        for (A a : setA) {
            if (bIds.contains(a.getId())) {
                commonElements.add(a);
            }
        }
        return commonElements;
    }

    static class A {
        private int id;
        private String name;

        public A(int id, String name) {
            this.id = id;
            this.name = name;
        }

        public int getId() {
            return id;
        }

        @Override
        public String toString() {
            return "A{" +
                    "id=" + id +
                    ", name='" + name + ''' +
                    '}';
        }
    }

    static class B {
        private int id;
        private String description;

        public B(int id, String description) {
            this.id = id;
            this.description = description;
        }

        public int getId() {
            return id;
        }
    }
}

5.3. Step-by-Step Explanation

  1. Create a HashSet called bIds to store the IDs of the elements in setB.
  2. Iterate through setB and add each element’s ID to the bIds set.
  3. Iterate through setA and check if each element’s ID is present in the bIds set using the contains() method.
  4. If the ID is present, add the corresponding element from setA to the commonElements set.

5.4. Time Complexity Analysis

  • Creating the bIds set: O(m), where m is the size of setB.
  • Iterating through setA and checking for the presence of each element’s ID in bIds: O(n), where n is the size of setA.
  • Total time complexity: O(n + m).

5.5. Benefits of Using HashSet

  • Improved Performance: HashSet provides constant-time complexity for basic operations, resulting in faster set comparison.
  • Scalability: This approach is more scalable than nested loops, as the time complexity increases linearly with the size of the sets.
  • Efficiency: By creating a HashSet of IDs, you can avoid unnecessary object comparisons, further improving performance.

5.6. Considerations

  • Memory Usage: Creating a HashSet of IDs requires additional memory. Consider the memory constraints of your application when using this approach.
  • Hash Function: The performance of HashSet depends on the quality of the hash function used by the objects in the set. Ensure that the hash function is well-distributed to avoid collisions.

By leveraging HashSet and creating a set of IDs for efficient comparison, you can significantly improve the performance of set operations in Java, especially when dealing with large datasets.

6. Comparing Sets with Different Object Types

Comparing sets with different object types requires careful consideration of how equality is defined and implemented. When the sets contain objects of different classes, you need to ensure that the comparison logic is well-defined and handles the type differences appropriately.

6.1. Challenges When Comparing Different Types

When comparing sets containing different object types, you may encounter the following challenges:

  • Type Mismatch: Objects of different types may not have a natural or meaningful way to be compared directly.
  • Equality Definition: The definition of equality may vary between different types. You need to ensure that the comparison logic aligns with the desired notion of equality.
  • Type Conversion: You may need to perform type conversions or casting to compare objects of different types, which can introduce complexity and potential errors.

6.2. Implementing a Custom Comparator

One way to compare sets with different object types is by implementing a custom Comparator. A Comparator is an interface that defines a method for comparing two objects. You can create a custom Comparator that handles the type differences and implements the desired comparison logic.

Java Code Example:

import java.util.Comparator;
import java.util.HashSet;
import java.util.Set;

public class CustomComparatorExample {

    public static void main(String[] args) {
        Set<A> setA = new HashSet<>();
        setA.add(new A(1, "Object 1"));
        setA.add(new A(2, "Object 2"));
        setA.add(new A(3, "Object 3"));

        Set<B> setB = new HashSet<>();
        setB.add(new B(2, "Item 2"));
        setB.add(new B(4, "Item 4"));
        setB.add(new B(5, "Item 5"));

        Set<A> commonElements = findCommonElements(setA, setB, new IdBasedComparator());

        System.out.println("Common elements: " + commonElements);
    }

    public static Set<A> findCommonElements(Set<A> setA, Set<B> setB, Comparator<Object> comparator) {
        Set<A> commonElements = new HashSet<>();
        for (A a : setA) {
            for (B b : setB) {
                if (comparator.compare(a, b) == 0) {
                    commonElements.add(a);
                    break;
                }
            }
        }
        return commonElements;
    }

    static class A {
        private int id;
        private String name;

        public A(int id, String name) {
            this.id = id;
            this.name = name;
        }

        public int getId() {
            return id;
        }

        @Override
        public String toString() {
            return "A{" +
                    "id=" + id +
                    ", name='" + name + ''' +
                    '}';
        }
    }

    static class B {
        private int id;
        private String description;

        public B(int id, String description) {
            this.id = id;
            this.description = description;
        }

        public int getId() {
            return id;
        }
    }

    static class IdBasedComparator implements Comparator<Object> {
        @Override
        public int compare(Object o1, Object o2) {
            if (o1 instanceof A && o2 instanceof B) {
                return Integer.compare(((A) o1).getId(), ((B) o2).getId());
            }
            return 0;
        }
    }
}

6.3. Using a Common Interface or Abstract Class

Another approach is to define a common interface or abstract class that both types implement. This allows you to compare the objects based on a shared set of properties or methods.

Java Code Example:

import java.util.HashSet;
import java.util.Set;

public class CommonInterfaceExample {

    public static void main(String[] args) {
        Set<MyInterface> setA = new HashSet<>();
        setA.add(new A(1, "Object 1"));
        setA.add(new A(2, "Object 2"));
        setA.add(new A(3, "Object 3"));

        Set<MyInterface> setB = new HashSet<>();
        setB.add(new B(2, "Item 2"));
        setB.add(new B(4, "Item 4"));
        setB.add(new B(5, "Item 5"));

        Set<MyInterface> commonElements = findCommonElements(setA, setB);

        System.out.println("Common elements: " + commonElements);
    }

    public static Set<MyInterface> findCommonElements(Set<MyInterface> setA, Set<MyInterface> setB) {
        Set<MyInterface> commonElements = new HashSet<>();
        for (MyInterface a : setA) {
            for (MyInterface b : setB) {
                if (a.getId() == b.getId()) {
                    commonElements.add(a);
                    break;
                }
            }
        }
        return commonElements;
    }

    interface MyInterface {
        int getId();
    }

    static class A implements MyInterface {
        private int id;
        private String name;

        public A(int id, String name) {
            this.id = id;
            this.name = name;
        }

        public int getId() {
            return id;
        }

        @Override
        public String toString() {
            return "A{" +
                    "id=" + id +
                    ", name='" + name + ''' +
                    '}';
        }
    }

    static class B implements MyInterface {
        private int id;
        private String description;

        public B(int id, String description) {
            this.id = id;
            this.description = description;
        }

        public int getId() {
            return id;
        }
    }
}

6.4. Using a Conversion Function

Another approach is to define a conversion function that transforms objects of one type into objects of another type. This allows you to compare the objects after they have been converted to the same type.

Java Code Example:

import java.util.HashSet;
import java.util.Set;

public class ConversionFunctionExample {

    public static void main(String[] args) {
        Set<A> setA = new HashSet<>();
        setA.add(new A(1, "Object 1"));
        setA.add(new A(2, "Object 2"));
        setA.add(new A(3, "Object 3"));

        Set<B> setB = new HashSet<>();
        setB.add(new B(2, "Item 2"));
        setB.add(new B(4, "Item 4"));
        setB.add(new B(5, "Item 5"));

        Set<A> commonElements = findCommonElements(setA, setB);

        System.out.println("Common elements: " + commonElements);
    }

    public static Set<A> findCommonElements(Set<A> setA, Set<B> setB) {
        Set<A> commonElements = new HashSet<>();
        Set<Integer> bIds = new HashSet<>();
        for (B b : setB) {
            bIds.add(b.getId());
        }
        for (A a : setA) {
            if (bIds.contains(a.getId())) {
                commonElements.add(a);
            }
        }
        return commonElements;
    }

    static class A {
        private int id;
        private String name;

        public A(int id, String name) {
            this.id = id;
            this.name = name;
        }

        public int getId() {
            return id;
        }

        @Override
        public String toString() {
            return "A{" +
                    "id=" + id +
                    ", name='" + name + ''' +
                    '}';
        }
    }

    static class B {
        private int id;
        private String description;

        public B(int id, String description) {
            this.id = id;
            this.description = description;
        }

        public int getId() {
            return id;
        }
    }
}

6.5. Best Practices

When comparing sets with different object types, consider the following best practices:

  • Define Equality Clearly: Ensure that the notion of equality is well-defined and aligns with the desired comparison logic.
  • Handle Type Differences: Implement appropriate type handling mechanisms, such as custom comparators, common interfaces, or conversion functions.
  • Consider Performance: Choose the most efficient approach based on the size of the sets and the complexity of the comparison logic.
  • Test Thoroughly: Test your comparison logic thoroughly to ensure that it handles different scenarios correctly.

By following these best practices, you can effectively compare sets with different object types in Java and ensure that the comparison logic is accurate, efficient, and maintainable.

7. Parallel Processing for Large Sets

When dealing with extremely large sets, the performance of set comparison can become a bottleneck, even with optimized algorithms and data structures. Parallel processing can be used to distribute the comparison task across multiple threads or processors, significantly reducing the execution time.

7.1. Why Use Parallel Processing?

Parallel processing can provide several benefits when comparing large sets:

  • Reduced Execution Time: By distributing the comparison task across multiple threads or processors, the overall execution time can be significantly reduced.
  • Improved Scalability: Parallel processing can improve the scalability of your application, allowing it to handle larger datasets without performance degradation.
  • Increased Throughput: Parallel processing can increase the throughput of your application, allowing it to process more data in a given amount of time.

7.2. Using Java’s parallelStream() for Parallel Set Operations

Java 8 introduced the parallelStream() method, which allows you to perform operations on collections in parallel. You can use parallelStream() to parallelize set comparison operations, such as finding the intersection or difference between two sets.

Java Code Example:

import java.util.HashSet;
import java.util.Set;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.ConcurrentMap;

public class ParallelStreamExample {

    public static void main(String[] args) {
        Set<Integer> setA = new HashSet<>();
        for (int i = 0; i < 1000000; i++) {
            setA.add(i);
        }

        Set<Integer> setB = new HashSet<>();
        for (int i = 500000; i < 1500000; i++) {
            setB.add(i);
        }

        Set<Integer> commonElements = findCommonElements(setA, setB);

        System.out.println("Number of common elements: " + commonElements.size());
    }

    public static Set<Integer> findCommonElements(Set<Integer> setA, Set<Integer> setB) {
        ConcurrentMap<Integer, Boolean> commonElementsMap = new ConcurrentHashMap<>();
        setA.parallelStream().forEach(elementA -> {
            if (setB.contains(elementA)) {
                commonElementsMap.put(elementA, true);
            }
        });
        return commonElementsMap.keySet();
    }
}

7.3. Using ExecutorService for Fine-Grained Control

For more fine-grained control over parallel processing, you can use Java’s ExecutorService. ExecutorService allows you to manage a pool of threads and submit tasks for execution. You can use ExecutorService to divide the set comparison task into smaller subtasks and execute them in parallel.

Java Code Example:


import java.util.HashSet;
import java.util.Set;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.Future;
import java.util.ArrayList;
import java.util.List;

public class ExecutorServiceExample {

    public static void main(String[] args) throws Exception {
        Set<Integer> setA

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