Intersection and union of ArrayLists in Java

Improving performance and clarity with streams and sets

Harnessing Java's Stream API

Java 8's Stream API offers a handy toolset to manage collection operations. For intersection, merging filter with collect results in nifty code:

List<Integer> intersection = list1.stream()
                                  .filter(list2::contains) //Secret handshakes are all the rage
                                  .collect(Collectors.toList());


For union, combining Stream.concat followed by distinct() ensures uniqueness:

List<Integer> union = Stream.concat(list1.stream(), list2.stream()) //One big pool party
                            .distinct() //But no clones allowed
                            .collect(Collectors.toList());


Sets for tumbling run-time

Facing massive datasets, a HashSet bumps up performance thanks to constant-time complexity for add and contains procedures.

// Fast track intersection with Set
Set<Integer> set1 = new HashSet<>(list1);
set1.retainAll(new HashSet<>(list2)); //Only the worthy may remain!

// Speedy union with Set
Set<Integer> set2 = new HashSet<>(list1);
set2.addAll(list2); //Everyone is invited!


Best Practice: Always run test drives with your dataset, as performance tends to fluctuate based on data size and operations recurrence.

Advanced collections for specialized needs

If your lists are required to be sorted or to maintain order, resort to using a TreeSet over a HashSet, as it preserves elements in an ordered and unique fashion:

TreeSet<Integer> sortedUnion = new TreeSet<>(list1);
sortedUnion.addAll(list2); //A place for everything and everything in its place


From the Guava Orchard: Guava library introduces Sets.union() and Sets.intersection() returning a Sets.SetView allowing chain operations that can be converted back to a list if required.

Aim for performance cutoffs and data integrity

While leveraging the aforesaid techniques, always aim to keep the original lists intact and evade unnecessary side influences. Make sure to profile methods for performance impacts specifically when scalability becomes a factor.

Opting between alternatives

TreeSet vs HashSet: The showmatch

Use TreeSet when it's paramount to maintain a sorted order. If order doesn't concern, and you're focused on performance, give HashSet a whirl.

Selecting the suitable data structure

A LinkedList might outrun ArrayList for bulky lists that continually insert and delete elements. Conversely, ArrayList outmatches for indexed access.

Deciding between Lists and Sets

Optimize based on your need: ordered elements (List) or unique, unordered collection (Set). Pick your data structure aligned with operations (.removeAll, .addAll) sticking to "and" & "or" filters.

Leveraging algorithms

Complex operations

Guava's Sets render potent utilities for set algebra, analogous to difference, symmetricDifference, and combinations. Reap such libraries to potentially pare down custom code.

Space-time complexity considerations

Always take into account space complexity when opting for HashSet or TreeSet. They might ensure time efficiency but at the expense of extra memory overhead.

Customizing sort with Comparators

When using TreeSet, you can implement a custom comparator to dictate the order of elements. This inches a layer of customization for unique sorting requirements.