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https://issues.apache.org/jira/browse/FLINK-13938?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Yang Wang updated FLINK-13938:
------------------------------
Description:
Currently, every time we start a flink cluster, flink lib jars need to be
uploaded to hdfs and then register Yarn local resource so that it could be
downloaded to jobmanager and all taskmanager container. I think we could have
two optimizations.
# Use pre-uploaded flink binary to avoid uploading of flink system jars
# By default, the LocalResourceVisibility is APPLICATION, so they will be
downloaded only once and shared for all taskmanager containers of a same
application in the same node. However, different applications will have to
download all jars every time, including the flink-dist.jar. We could use the
yarn public cache to eliminate the unnecessary jars downloading and make
launching container faster.
How the feature work?
* Add {{yarn.provided.lib.dirs}} to configure pre-uploaded libs, which contain
files that are useful for all the users of the platform(i.e. different
applications).
* When the Flink client wants to ship a local file, it will check the provided
libs first. If the provided libs contains a file with the same name, the local
ship files will be automatically excluded from uploading.
* These provided libs needs to be public readable and will be set with
{{PUBLIC}} visibility for local resources. So they will be cache in the nodes
and shared by different applications.
How to use the pre-upload feature?
1. First, upload the Flink binary to the HDFS directories
2. Use {{yarn.provided.lib.dirs}} to specify the pre-uploaded libs
A final submission command could be issued like following.
{code:java}
./bin/flink run -m yarn-cluster -d \
-yD yarn.provided.lib.dirs=hdfs://myhdfs/flink/lib,hdfs://myhdfs/flink/plugins \
examples/streaming/WindowJoin.jar
{code}
was:
Currently, every time we start a flink cluster, flink lib jars need to be
uploaded to hdfs and then register Yarn local resource so that it could be
downloaded to jobmanager and all taskmanager container. I think we could have
two optimizations.
# Use pre-uploaded flink binary to avoid uploading of flink system jars
# By default, the LocalResourceVisibility is APPLICATION, so they will be
downloaded only once and shared for all taskmanager containers of a same
application in the same node. However, different applications will have to
download all jars every time, including the flink-dist.jar. We could use the
yarn public cache to eliminate the unnecessary jars downloading and make
launching container faster.
Take both FLINK-13938 and FLINK-14964 into account, this whole submission
optimization feature will be done in the following steps.
* Add {{yarn.provided.lib.dirs}} to configure pre-uploaded libs, which contain
files that are useful for all the users of the platform(i.e. different
applications). So it needs to be public readable and will be set with
{{PUBLIC}} visibility for local resources. For the first version, we can have
only the flink-dist, lib/, plugins/ being automatically excluded from uploading
if the {{yarn.pre-uploaded.flink.path}} contains a file with the same name.
This will be done in FLINK-13938.
* Make all the options(including user jar, flink-dist-*.jar, libs, etc.) could
support remote path. This feature allow the Flink client do not need to have a
local user jar and dependencies. Combined with application mode, the
deployer(i.e. Flink job management system) will have better performance. This
will be done in FLINK-14964.
How to use the pre-upload feature?
1. First, upload the Flink binary to the HDFS directories
2. Use {{yarn.provided.lib.dirs}} to specify the pre-uploaded libs
A final submission command could be issued like following.
{code:java}
./bin/flink run -m yarn-cluster -d \
-yD yarn.provided.lib.dirs=hdfs://myhdfs/flink/lib,hdfs://myhdfs/flink/plugins \
examples/streaming/WindowJoin.jar
{code}
> Use pre-uploaded libs to accelerate flink submission
> ----------------------------------------------------
>
> Key: FLINK-13938
> URL: https://issues.apache.org/jira/browse/FLINK-13938
> Project: Flink
> Issue Type: New Feature
> Components: Client / Job Submission, Deployment / YARN
> Reporter: Yang Wang
> Assignee: Yang Wang
> Priority: Major
> Labels: pull-request-available
> Time Spent: 0.5h
> Remaining Estimate: 0h
>
> Currently, every time we start a flink cluster, flink lib jars need to be
> uploaded to hdfs and then register Yarn local resource so that it could be
> downloaded to jobmanager and all taskmanager container. I think we could have
> two optimizations.
> # Use pre-uploaded flink binary to avoid uploading of flink system jars
> # By default, the LocalResourceVisibility is APPLICATION, so they will be
> downloaded only once and shared for all taskmanager containers of a same
> application in the same node. However, different applications will have to
> download all jars every time, including the flink-dist.jar. We could use the
> yarn public cache to eliminate the unnecessary jars downloading and make
> launching container faster.
>
> How the feature work?
> * Add {{yarn.provided.lib.dirs}} to configure pre-uploaded libs, which
> contain files that are useful for all the users of the platform(i.e.
> different applications).
> * When the Flink client wants to ship a local file, it will check the
> provided libs first. If the provided libs contains a file with the same name,
> the local ship files will be automatically excluded from uploading.
> * These provided libs needs to be public readable and will be set with
> {{PUBLIC}} visibility for local resources. So they will be cache in the nodes
> and shared by different applications.
>
> How to use the pre-upload feature?
> 1. First, upload the Flink binary to the HDFS directories
> 2. Use {{yarn.provided.lib.dirs}} to specify the pre-uploaded libs
>
> A final submission command could be issued like following.
> {code:java}
> ./bin/flink run -m yarn-cluster -d \
> -yD
> yarn.provided.lib.dirs=hdfs://myhdfs/flink/lib,hdfs://myhdfs/flink/plugins \
> examples/streaming/WindowJoin.jar
> {code}
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