Quick study sessions to strengthen memory and retain key concepts.
Understanding Thread-Per-Request Bottlenecks?
Thread-per-request can lead to resource exhaustion. In a thread-per-request model, each incoming request spawns a new thread. As…
View Card →Why are functional pipelines valuable in Project Reactor?
They simplify complex transformations. Frame the concept in practical terms so you can explain it during interview discussion.…
View Card →What are the risks of using flatMap in Project Reactor?
It can lead to uncontrolled concurrency. Frame the concept in practical terms so you can explain it during…
View Card →How does a Subscriber work in Reactive Streams?
It consumes data from a Publisher. Frame the concept in practical terms so you can explain it during…
View Card →What happens if you block an asynchronous call?
It negates the benefits of non-blocking architecture. Blocking an asynchronous call forces the thread to wait, nullifying the…
View Card →Compare WebFlux and Virtual Threads in terms of concurrency management?
WebFlux uses non-blocking I/O, while Virtual Threads simplify traditional concurrency. WebFlux is built on non-blocking I/O, leveraging event…
View Card →What is backpressure and how does it function in Reactive Streams?
Backpressure handles data flow control by regulating requests from Subscriber. Backpressure is a mechanism in Reactive Streams that…
View Card →Why is it important to avoid blocking calls on the event loop in Reactive Streams?
Blocking calls can freeze the event loop, stalling processing. In non-blocking architectures like Reactive Streams, the event loop…
View Card →How does the Subscriber interact with the Publisher in Reactive Streams?
The Subscriber requests data and processes it upon receipt. The Subscriber in Reactive Streams is like a listener…
View Card →Why does the Publisher in Reactive Streams matter in practice?
The Publisher emits data to the Subscriber. In Reactive Streams, the Publisher acts as an emitter of data,…
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