Peek
Peek is an operation that observes the next or otherwise accessible element without consuming, removing, or advancing past it.
Kafka Streams in Action, Second Edition
KStream.peek is a Kafka Streams operation that performs a stateless action on each record without changing the record's key or value.
- How it is used
- Provides development-time visibility into records without interrupting a Kafka Streams topology.
- How deep it goes
- Explains callback behavior, unchanged records, chaining, and windowed-result inspection without descending into processor internals.
- Examples
- Uses the Yelling app and windowed aggregation logging to inspect records before transformations and analyze window boundaries.
- What you can do after
- Apply it via Kafka Streams to print, log, or collect records while continuing a KStream chain.
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100 Java Mistakes and How to Avoid Them
A peek operation is a Stream intermediate operation that applies a supplied Consumer to elements as they pass through the pipeline without changing their values.
- How it is used
- Uses a Consumer for observational side effects, chiefly debugging within a Stream pipeline.
- How deep it goes
- Explains side effects, short-circuiting, parallel execution, and optimization limits without descending into Stream implementation internals.
- Examples
- Uses trimming, external collection, filtering, limit(5), count, and separate streams to expose incomplete side effects.
- What you can do after
- Diagnose/debug pipeline traversal with peek and replace fragile side effects using explicit stream operations.
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Grokking Data Structures
A peek operation returns the top element of a stack without removing it or changing the stack's structure.
- How it is used
- Supports inspecting a stack’s next element without removing it or changing its structure.
- How deep it goes
- Explains empty checks, private-attribute access, mutable results, copying, and public accessors, then assigns implementation exercises.
- Examples
- Uses a pile-of-dishes analogy, Python linked-list code, deepcopy, get(i), and exercises comparing linked-list and dynamic-array stacks.
- What you can do after
- Build it from scratch by implementing peek, handling empty stacks, protecting mutable values, and replacing private access with get(i).
Related concepts
- side effectuses · A software side effect is an observable change or interaction caused by an operation beyond producing its direct result, such as modifying state or performing input or output.
- topcontrasts with · The top operation accesses the element currently having the highest priority in a priority queue or heap.
- stackpart of · A stack is a data structure that adds and removes elements at one end, following last-in, first-out order.
- dequeuecontrasts with · Dequeue is a queue operation that removes the next item according to the queue’s ordering policy and typically returns it.
- wait-free synchronizationimplements · A concurrency technique in which every operation completes in a bounded number of steps, regardless of the actions or delays of other threads.
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