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https://issues.apache.org/jira/browse/FLINK-5815?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15885749#comment-15885749
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ASF GitHub Bot commented on FLINK-5815:
---------------------------------------
Github user tillrohrmann commented on a diff in the pull request:
https://github.com/apache/flink/pull/3388#discussion_r103197726
--- Diff:
flink-yarn/src/main/java/org/apache/flink/yarn/AbstractYarnClusterDescriptor.java
---
@@ -131,6 +134,8 @@
/** Lazily initialized list of files to ship */
protected List<File> shipFiles = new LinkedList<>();
+ private List<URI> archives = new LinkedList<>();
--- End diff --
`LinkedLists` are not so fast. Better to use an `ArrayList` and initialize
it with an initial capacity.
> Add resource files configuration for Yarn Mode
> ----------------------------------------------
>
> Key: FLINK-5815
> URL: https://issues.apache.org/jira/browse/FLINK-5815
> Project: Flink
> Issue Type: Improvement
> Components: Client, YARN
> Affects Versions: 1.3.0
> Reporter: Wenlong Lyu
> Assignee: Wenlong Lyu
>
> Currently in flink, when we want to setup a resource file to distributed
> cache, we need to make the file accessible remotely by a url, which is often
> difficult to maintain a service like that. What's more, when we want do add
> some extra jar files to job classpath, we need to copy the jar files to blob
> server when submitting the jobgraph. In yarn, especially in flip-6, the blob
> server is not running yet when we try to start a flink job.
> Yarn has a efficient distributed cache implementation for application running
> on it, what's more we can be easily share the files stored in hdfs in
> different application by distributed cache without extra IO operations.
> I suggest to introduce -yfiles, -ylibjars -yarchives options to FlinkYarnCLI
> to enable yarn user setup their job resource files by yarn distributed cache.
> The options is compatible with what is used in mapreduce, which make it easy
> to use for yarn user who generally has experience on using mapreduce.
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