Zhanghao Chen created FLINK-33123:
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Summary: Wrong dynamic replacement of partitioner from FORWARD to
REBLANCE for autoscaler and adaptive scheduler and
Key: FLINK-33123
URL: https://issues.apache.org/jira/browse/FLINK-33123
Project: Flink
Issue Type: Bug
Components: Autoscaler, Runtime / Coordination
Affects Versions: 1.17.0, 1.18.0
Reporter: Zhanghao Chen
*Background*
https://issues.apache.org/jira/browse/FLINK-30213 reported that the edge is
wrong when the parallelism is changed for a vertex with a FORWARD edge, which
is used by both the autoscaler and adaptive scheduler where one can change the
vertex parallelism dynamically. Fix is applied to dynamically replace
partitioner from FORWARD to REBLANCE on task deployment in {{{}StreamTask{}}}:
{{private static void
replaceForwardPartitionerIfConsumerParallelismDoesNotMatch(}}
{{ Environment environment, NonChainedOutput streamOutput) {}}
{{ Environment environment, NonChainedOutput streamOutput, int
outputIndex) {}}
{{ if (streamOutput.getPartitioner() instanceof ForwardPartitioner}}
{{ && streamOutput.getConsumerParallelism()}}
{{ &&
environment.getWriter(outputIndex).getNumberOfSubpartitions()}}
{{ !=
environment.getTaskInfo().getNumberOfParallelSubtasks()) {}}
{{ LOG.debug(}}
{{ "Replacing forward partitioner with rebalance for {}",}}
{{ environment.getTaskInfo().getTaskNameWithSubtasks());}}
{{ streamOutput.setPartitioner(new RebalancePartitioner<>());}}
{{ }}}
{{ }}}
*Problem*
Unfortunately, the fix is still buggy in two aspects:
# The connections between upstream and downstream tasks are determined by the
distribution type of the partitioner when generating execution graph on the JM
side. When the edge is FORWARD, the distribution type is POINTWISE, and Flink
will try to evenly distribute subpartitions to all downstream tasks. If one
want to change it to REBALANCE, the distribution type has to be changed to
ALL_TO_ALL to make all-to-all connections between upstream and downstream
tasks. However, the fix did not change the distribution type which makes the
network connections be set up in a wrong way.
# The FOWARD partitioner will be replaced if
environment.getWriter(outputIndex).getNumberOfSubpartitions() equals to the
task parallelism. However, the number of subpartitions here equals to the
number of downstream tasks of this particular task, which is also determined by
the distribution type of the partitioner when generating execution graph on the
JM side. When ceil(downstream task parallelism / upstream task parallelism) =
upstream task parallelism, we will have the number of subpartitions = task
parallelism. In fact, for a normal job with a FORWARD edge without any
autoscaling action, you will find that the partitioner is changed to REBALANCE
internally as the number of subpartitions always equals to 1 in this case.
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