Being able to set default job configuration values on the jobtracker
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Key: HADOOP-3287
URL: https://issues.apache.org/jira/browse/HADOOP-3287
Project: Hadoop Core
Issue Type: Bug
Components: conf, mapred
Environment: all
Reporter: Alejandro Abdelnur
Priority: Critical
The jobtracker hadoop-site.xml carries custom configuration for the cluster and
the 'final' flag allows to fix a value ignoring any override by a client when
submitting a job.
There are several properties for which a cluster may want to set some default
values (different from the ones in the hadoop-default.xml), for example:
* enabling/disabling compression
* type of compression, record/block
* number of task retries
* block replication factor
* job priority
* tasks JVM options
The cluster default values should apply to submitted jobs when the job
submitter does not care about those values. When the job submitter cares, it
should include its preferred values. Using the final flag on the jobtracker
hadoop-site.xml will lock the value ignoring the value set in the client
jobconf.
Currently the only way of doing this is to distribute the jobtracker
hadoop-site.xml to all clients and make sure they use it when creating the job
configuration.
There are situations where this is not practical:
* In a shared cluster with several clients submitting jobs. It requires
redistributing the hadoop-site.xml to all clients.
* In a cluster where the jobs are dispatched by a webapp application. It
requires rebundling and redeploying the webapp.
The current behavior happens because the jobconf when serialized, to be sent to
the jobtracker, sends all the values found in the hadoop-default.xml bundled
with the hadoop JAR file. On the jobtracker side, all those values override all
but the 'final' properties of the jobtracker hadoop-site.xml.
According to the javadocs of the Configuration.write(OutpuStream) this should
not happen ' Writes non-default properties in this configuration.'
If taken the javadocs as the proper behavior this is a bug in the current
implementation and it could be easily fixed by avoiding writing default values
on write.
This is a generalization of the problem mentioned in Hadoop-3171.
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