Parallel streams can help for CPU-bound work on large collections when each element is independent and the work is heavy enough to amortize overhead. Pitfalls: they use `ForkJoinPool.commonPool` by default, they can be slower for small tasks, they are bad for blocking I/O, and side effects/shared mutable state can cause race conditions.
Advanced answer
Deep dive
Expanding on the short answer — what usually matters in practice:
Explain the "why", not just the "what" (intuition + consequences).
Trade-offs: what you gain/lose (time, memory, complexity, risk).
Edge cases: empty inputs, large inputs, invalid inputs, concurrency.
Examples
A tiny example (an explanation template):
// Example: discuss trade-offs for "parallel-streams:-when-can-they-help-and-what-ar"
function explain() {
// Start from the core idea:
// Parallel streams can help for CPU-bound work on large collections when each element is ind
}
Common pitfalls
Too generic: no concrete trade-offs or examples.
Mixing average-case and worst-case (e.g., complexity).