Erik O'Shaughnessy created SPARK-13776:
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             Summary: Web UI is not available after ./sbin/start-master.sh
                 Key: SPARK-13776
                 URL: https://issues.apache.org/jira/browse/SPARK-13776
             Project: Spark
          Issue Type: Bug
          Components: Web UI
    Affects Versions: 1.6.0
         Environment: Solaris 11.3, Oracle SPARC T-5 8 with 1024 hardware 
threads
            Reporter: Erik O'Shaughnessy


The Sparc Web UI fails to become available after starting a Spark master in 
stand-alone mode:

$ ./sbin/start-master.sh

The log file contains the following:
{quote}
cat spark-hadoop-org.apache.spark.deploy.master.Master-1-t5-8-002.out
Spark Command: /usr/java/bin/java -cp 
/usr/local/spark-1.6.0_nohadoop/conf/:/usr/local/spark-1.6.0_nohadoop/assembly/target/scala-2.10/spark-assembly-1.6.0-hadoop2.2.0.jar:/usr/local/spark-1.6.0_nohadoop/lib_managed/jars/datanucleus-api-jdo-3.2.6.jar:/usr/local/spark-1.6.0_nohadoop/lib_managed/jars/datanucleus-rdbms-3.2.9.jar:/usr/local/spark-1.6.0_nohadoop/lib_managed/jars/datanucleus-core-3.2.10.jar
 -Xms1g -Xmx1g org.apache.spark.deploy.master.Master --ip t5-8-002 --port 7077 
--webui-port 8080
========================================
16/01/27 12:00:42 WARN AbstractConnector: insufficient threads configured for 
SelectChannelConnector@0.0.0.0:8080
16/01/27 12:00:42 WARN AbstractConnector: insufficient threads configured for 
SelectChannelConnector@t5-8-002:6066
{quote}

I did some poking around and it seems that message is coming from Jetty and 
indicates a mismatch between Jetty's default maxThreads configuration and the 
actual number of CPUs available on the hardware (1024). I was not able to find 
a way to successfully change Jetty's configuration at run-time. 

Our work around was to disable CPUs until the WARN messages did not occur in 
the log file, which was when NCPUs = 504. 

I don't know for certain that this is isn't a known problem in Jetty from 
looking at their bug reports, but I wasn't able to locate a Jetty issue that 
described this problem.

While not specifically an Apache Spark problem, I thought documenting it would 
at least be helpful.




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