Zhu Zhu created FLINK-10945:
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Summary: Avoid resource deadlocks for finite stream jobs when
resources are limited
Key: FLINK-10945
URL: https://issues.apache.org/jira/browse/FLINK-10945
Project: Flink
Issue Type: Improvement
Components: Distributed Coordination
Affects Versions: 1.7.1
Reporter: Zhu Zhu
Currently *resource deadlocks* can happen to finite stream jobs(or batch jobs)
when resources are limited. In 2 cases as below:
# Task Y is a pipelined downstream task of task X. When X takes all
resources(slots), Y cannot acquire slots to start, thus the back pressure will
block X to finish
# Task Y is a upstream task of task X. When X takes all resources(slots) and Y
cannot start, X cannot finish as some of its inputs are not finished
We can avoid case 1 by setting all edges to be BLOCKING to avoid pipeline back
pressure. However, case 2 cannot be avoided as X(downstream task) will be
launched when any of its input result is ready.
To be detailed, say task X has BLOCKING upstream task Y and Z, X can be
launched when Z finishes, though task Y is not launched yet. This pre-launch
behaviour can be beneficial when there are plenty of resources, thus X can
process data from Z earlier before Y finishes its data processing. However,
resource deadlocks may happen when the resources are limited, e.g. in small
sessions.
I’d propose introducing a constraint named as *InputDependencyConstraint* to
control the scheduling of vertices. It has 2 values:
# *ANY*. The vertex can be scheduled when any of its inputs is consumable.
# *ALL*. The vertex can be scheduled when all of its inputs are consumable.
Here one input corresponds to an *IntermediateResult*. The constraint can be
configured for *certain vertex or job-wide*. Making the constraint default as
*ANY* job-wide will keep the job scheduling behaves in the same way as current
version.
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