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Posted to issues@flink.apache.org by "YufeiLiu (Jira)" <ji...@apache.org> on 2020/02/14 16:27:00 UTC
[jira] [Updated] (FLINK-15959) Add min/max number of slots
configuration to limit total number of slots
[ https://issues.apache.org/jira/browse/FLINK-15959?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
YufeiLiu updated FLINK-15959:
-----------------------------
Description:
Flink removed `-n` option after FLIP-6, change to ResourceManager start a new worker when required. But I think maintain a certain amount of slots is necessary. These workers will start immediately when ResourceManager starts and would not release even if all slots are free.
Here are some resons:
# Users actually know how many resources are needed when run a single job, initialize all workers when cluster starts can speed up startup process.
# Job schedule in topology order, next operator won't schedule until prior execution slot allocated. The TaskExecutors will start in several batchs in some cases, it might slow down the startup speed.
# Flink support [FLINK-12122|https://issues.apache.org/jira/browse/FLINK-12122] [Spread out tasks evenly across all available registered TaskManagers], but it will only effect if all TMs are registered. Start all TMs at begining can slove this problem.
*suggestion:*
Add config "taskmanager.minimum.numberOfTotalSlots" and "taskmanager.maximum.numberOfTotalSlots", start plenty number of workers to satisfy minimum slots when ResourceManager accept leadership(subtract recovered workers).
Don't comlete slot request until minimum number of slots are registered, and throw exeception when exceed maximum.
was:
Flink removed `-n` option after FLIP-6, change to ResourceManager start a new worker when required. But I think maintain a TaskExecutor number option is necessary. These workers will start immediately when ResourceManager starts and would not release even if all slots are free.
Here are some resons:
# Users actually know how many resources are needed when run a single job, initialize all workers when cluster starts can speed up startup process.
# Job schedule in topology order, next operator won't schedule until prior execution slot allocated. The TaskExecutors will start in several batchs in some cases, it might slow down the startup speed.
# Flink support [FLINK-12122|https://issues.apache.org/jira/browse/FLINK-12122] [Spread out tasks evenly across all available registered TaskManagers], but it will only effect if all TMs are registered. Start all TMs at begining can slove this problem.
*suggestion:*
I only changed YarnResourceManager, start all container in `initialize` stage, and don't comlete slot request until minimum number of slots are registered.
Summary: Add min/max number of slots configuration to limit total number of slots (was: Add TaskExecutor number option in FlinkYarnSessionCli)
> Add min/max number of slots configuration to limit total number of slots
> ------------------------------------------------------------------------
>
> Key: FLINK-15959
> URL: https://issues.apache.org/jira/browse/FLINK-15959
> Project: Flink
> Issue Type: New Feature
> Components: Runtime / Coordination
> Affects Versions: 1.11.0
> Reporter: YufeiLiu
> Priority: Major
>
> Flink removed `-n` option after FLIP-6, change to ResourceManager start a new worker when required. But I think maintain a certain amount of slots is necessary. These workers will start immediately when ResourceManager starts and would not release even if all slots are free.
> Here are some resons:
> # Users actually know how many resources are needed when run a single job, initialize all workers when cluster starts can speed up startup process.
> # Job schedule in topology order, next operator won't schedule until prior execution slot allocated. The TaskExecutors will start in several batchs in some cases, it might slow down the startup speed.
> # Flink support [FLINK-12122|https://issues.apache.org/jira/browse/FLINK-12122] [Spread out tasks evenly across all available registered TaskManagers], but it will only effect if all TMs are registered. Start all TMs at begining can slove this problem.
> *suggestion:*
> Add config "taskmanager.minimum.numberOfTotalSlots" and "taskmanager.maximum.numberOfTotalSlots", start plenty number of workers to satisfy minimum slots when ResourceManager accept leadership(subtract recovered workers).
> Don't comlete slot request until minimum number of slots are registered, and throw exeception when exceed maximum.
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