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https://issues.apache.org/jira/browse/FLINK-2954?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Jian Jiang updated FLINK-2954:
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Description:
There are programs that rely on custom environment variables. In hadoop
mapreduce job we can use -Dmapreduce.map.env and - Dmapreduce.reduce.env to do
pass them. Similarly in Spark
we can use --conf 'spark.executor.XXX=value for XXX'. There is no such feature
yet in Flink.
This has given Flink a serious disadvantage when customers need such feature.
was:
There are programs that relies on custom environment variables. In hadoop
mapreduce job we can use -Dmapreduce.map.env and - Dmapreduce.reduce.env to do
pass them. Similarly in Spark
we can use --conf 'spark.executor.XXX=value for XXX'. There is no such feature
yet in Flink.
This has given Flink a serious disadvantage when customers need such feature.
> Not able to pass custom environment variables in cluster to processes that
> spawning TaskManager
> -----------------------------------------------------------------------------------------------
>
> Key: FLINK-2954
> URL: https://issues.apache.org/jira/browse/FLINK-2954
> Project: Flink
> Issue Type: Bug
> Components: Command-line client, Distributed Runtime
> Reporter: Jian Jiang
> Priority: Critical
>
> There are programs that rely on custom environment variables. In hadoop
> mapreduce job we can use -Dmapreduce.map.env and - Dmapreduce.reduce.env to
> do pass them. Similarly in Spark
> we can use --conf 'spark.executor.XXX=value for XXX'. There is no such
> feature yet in Flink.
> This has given Flink a serious disadvantage when customers need such feature.
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