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From "Patrick Wendell (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (SPARK-5152) Let metrics.properties file take an hdfs:// path
Date Fri, 09 Jan 2015 06:20:35 GMT

    [ https://issues.apache.org/jira/browse/SPARK-5152?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14270616#comment-14270616
] 

Patrick Wendell edited comment on SPARK-5152 at 1/9/15 6:19 AM:
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Should we be loading the metrics properties on executors in the first place? Maybe that's
the issue. I haven't looked at the code in a while but I'm not sure people use this in a way
where they expect to be able to query executors for metrics.


was (Author: pwendell):
Should we be loading the metrics properties on executors in the first place? Maybe that's
the issue. Since executors are ephemeral you can't query them for any metrics anyways, right?

> Let metrics.properties file take an hdfs:// path
> ------------------------------------------------
>
>                 Key: SPARK-5152
>                 URL: https://issues.apache.org/jira/browse/SPARK-5152
>             Project: Spark
>          Issue Type: Improvement
>          Components: Spark Core
>    Affects Versions: 1.2.0
>            Reporter: Ryan Williams
>
> From my reading of [the code|https://github.com/apache/spark/blob/06dc4b5206a578065ebbb6bb8d54246ca007397f/core/src/main/scala/org/apache/spark/metrics/MetricsConfig.scala#L53],
the {{spark.metrics.conf}} property must be a path that is resolvable on the local filesystem
of each executor.
> Running a Spark job with {{--conf spark.metrics.conf=hdfs://host1.domain.com/path/metrics.properties}}
logs many errors (~1 per executor, presumably?) like:
> {code}
> 15/01/08 13:20:57 ERROR metrics.MetricsConfig: Error loading configure file
> java.io.FileNotFoundException: hdfs:/host1.domain.com/path/metrics.properties (No such
file or directory)
>         at java.io.FileInputStream.open(Native Method)
>         at java.io.FileInputStream.<init>(FileInputStream.java:146)
>         at java.io.FileInputStream.<init>(FileInputStream.java:101)
>         at org.apache.spark.metrics.MetricsConfig.initialize(MetricsConfig.scala:53)
>         at org.apache.spark.metrics.MetricsSystem.<init>(MetricsSystem.scala:92)
>         at org.apache.spark.metrics.MetricsSystem$.createMetricsSystem(MetricsSystem.scala:218)
>         at org.apache.spark.SparkEnv$.create(SparkEnv.scala:329)
>         at org.apache.spark.SparkEnv$.createExecutorEnv(SparkEnv.scala:181)
>         at org.apache.spark.executor.CoarseGrainedExecutorBackend$$anonfun$run$1.apply$mcV$sp(CoarseGrainedExecutorBackend.scala:131)
>         at org.apache.spark.deploy.SparkHadoopUtil$$anon$1.run(SparkHadoopUtil.scala:61)
>         at org.apache.spark.deploy.SparkHadoopUtil$$anon$1.run(SparkHadoopUtil.scala:60)
>         at java.security.AccessController.doPrivileged(Native Method)
>         at javax.security.auth.Subject.doAs(Subject.java:415)
>         at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1548)
>         at org.apache.spark.deploy.SparkHadoopUtil.runAsSparkUser(SparkHadoopUtil.scala:60)
>         at org.apache.spark.executor.CoarseGrainedExecutorBackend$.run(CoarseGrainedExecutorBackend.scala:113)
>         at org.apache.spark.executor.CoarseGrainedExecutorBackend$.main(CoarseGrainedExecutorBackend.scala:163)
>         at org.apache.spark.executor.CoarseGrainedExecutorBackend.main(CoarseGrainedExecutorBackend.scala)
> {code}
> which seems consistent with the idea that it's looking on the local filesystem and not
parsing the "scheme" portion of the URL.
> Letting all executors get their {{metrics.properties}} files from one location on HDFS
would be an improvement, right?



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