[ https://issues.apache.org/jira/browse/FLINK-35823?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Rui Fan closed FLINK-35823. --------------------------- Resolution: Fixed It's duplicated with https://issues.apache.org/jira/browse/FLINK-35814, so close this. > Introduce parameters to control the upper limit of rescale to avoid unlimited > expansion due to server-side bottlenecks or data skew. > ------------------------------------------------------------------------------------------------------------------------------------ > > Key: FLINK-35823 > URL: https://issues.apache.org/jira/browse/FLINK-35823 > Project: Flink > Issue Type: Improvement > Components: Autoscaler > Reporter: yuanfenghu > Priority: Major > Fix For: 2.0.0 > > > 1. If a Flink application writes data to other external storage systems, such > as HDFS, Kafka, etc., when the external server becomes the bottleneck of the > entire task, such as the throughput of HDFS decreases, the writing IO time > will increase, and the corresponding Flink The metric busy will also > increase. At this time, the autoscaler will determine that the parallelism > needs to be increased to increase the write rate. However, in the above case, > due to the bottleneck of the external server, this will not work. This will > cause the next determination cycle to continue to increase the parallelism > until parallelism = max-parallelism. > 2. If some tasks have data skew, it will also cause the same problem. > > Therefore, we should introduce a new parameter judgment. If the degree of > parallelism continues to increase, the throughput will basically remain the > same. There is no need to expand anymore. > -- This message was sent by Atlassian Jira (v8.20.10#820010)