BigData / Apache StreamPark Interview questions
What role do flame graphs play in StreamPark's job monitoring?
Flame graphs give a visual answer to "which code is actually eating CPU" for a running job's operator, without attaching an external profiler.
The capability itself is Flink's own, native since Flink 1.13 (rest.flamegraph.enabled): stack traces are sampled repeatedly for an operator, and rendered as a graph where a call's bar width reflects how often it showed up in the samples. StreamPark Console surfaces this directly, so instead of navigating Flink's own JobManager UI, you can pull up a running application's flame graph from the same screen you used to start and monitor it.
It's most useful when a job is visibly backpressured or CPU-bound and you need to know whether the bottleneck is business logic, serialization, or I/O — the flame graph's dominant call stack usually points straight at the answer.
More Related questions...