Streaming Backpressure¶
Streaming backpressure is the runtime response when a downstream operator cannot drain records as quickly as upstream operators produce them.
flowchart LR
J[Junior: lag and growing buffers] --> M[Middle: bounded channels]
M --> S[Senior: propagation and checkpoint impact] --> P[Professional: runtime internals]
flowchart RL
K[Kafka source] --> M[Map]
M --> W[Window]
W --> S[Sink]
S -.slow.-> W
W -.backpressure.-> M
M -.pause reads.-> K
Choose a level¶
| Level | Guide | You are done when |
|---|---|---|
| Junior | When the sink slows | You can distinguish lag, buffering, and backpressure. |
| Middle | Bounded operator channels | You can trace pressure through a Flink-style graph. |
| Senior | Failure and tuning | You can diagnose skew, checkpoint delay, and source throttling. |
| Professional | Runtime flow control | You can compare Flink, Reactive Streams, and Spark behavior. |
Practice rule¶
Locate the first saturated downstream operator before scaling the source. More input parallelism usually makes an uncorrected downstream bottleneck worse.