1Z0-829 Working with Streams and Lambda Expressions Practice Question
A developer implements a reduction using reduce() to concatenate strings from a stream. The code: Optional<String> result = stream.reduce((s1, s2) -> s1.concat(s2)); The operation works but the developer is concerned about performance with large streams. Which change would most likely improve performance?
⚠ Common exam trap
A common mix-up: candidates assume `reduce()` with an identity or parallel streams will fix performance, but the core issue is the immutable nature of `String` concatenation, which `collect()` with a mutable container like `StringBuffer` or `StringBuilder` resolves.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use StringBuffer with collect() instead.
`StringBuffer` is mutable and thread-safe, making it efficient for accumulating strings in a parallel or sequential stream via `collect()`. The `reduce()` operation with `concat()` creates a new `String` object for each pair, leading to O(n) string copying and quadratic time complexity. Using `collect()` with `StringBuffer` avoids this overhead by reusing a mutable buffer.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use StringBuffer with collect() instead.
Why this is correct
StringBuilder (or StringBuffer) as a mutable reduction with collect() reduces intermediate allocations.
- ✗
Use a sequential stream.
Why it's wrong here
Sequential vs parallel does not address the string concatenation overhead.
- ✗
Use parallelStream with reduce.
Why it's wrong here
Parallel reduce may add threading overhead and still produce many intermediate strings.
- ✗
Use reduce with identity "".
Why it's wrong here
Even with identity, reduce still creates many intermediate String objects.
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