Hi,
What are "the spark driver and executor threads information" and "spark
application logging"?
Spark uses log4j so set up logging levels appropriately and you should be
done.
Pozdrawiam,
Jacek Laskowski
https://about.me/JacekLaskowski
The Internals of Spark SQL https://bit.ly/spark-sql-i
Hello,
How can we dump the spark driver and executor threads information in spark
application logging.?
PS: submitting spark job using spark submit
Regards
Rohit
I’ve gotten a little further along. It now submits the job via Yarn, but now
the jobs exit immediately with the following error:
Exception in thread "main" java.lang.NoClassDefFoundError:
org/apache/spark/Logging
at java.lang.ClassLoader.defineClass1(Native Method)
; .appName("DecisionTreeExample")
> .getOrCreate();
>
> Running this in the eclipse debugger, execution fails in getOrCreate()
> with this exception
>
> Exception in thread "main" java.lang.NoClassDefFoundE
g.NoClassDefFoundError:
org/apache/spark/Logging
at java.lang.ClassLoader.defineClass1(Native Method)
at java.lang.ClassLoader.defineClass(ClassLoader.java:800)
at
java.security.SecureClassLoader.defineClass(SecureClassLoader.java:142)
at java.net.URLClassLoader.
One can specify "-Dlog4j.configuration=" or
"-Dlog4j.configuration=".
Is there any preference to using one over other?
All the spark documentation talks about using "log4j.properties" only (
http://spark.apache.org/docs/latest/configuration.html#configuring-logging).
So is only "log4j.properties"
s. Is it
feasible?
I am using org.apache.log4j.Logger.
Regards,
Sam
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Hi,
http://stackoverflow.com/questions/29208844/apache-spark-logging-within-scala
What is the best way to capture spark logs without getting task not
serialzible error ?
The above link has various workarounds.
Also is there a way to dynamically set the log level when the application
is running
Hi,
I am using spark 1.1.0 and setting below properties while creating spark
context.
*spark.executor.logs.rolling.maxRetainedFiles = 10*
*spark.executor.logs.rolling.size.maxBytes = 104857600*
*spark.executor.logs.rolling.strategy = size*
Even though I am setting to rollover after 100 MB, the
)
> at
> taoensso.timbre$wrap_appender_juxt$fn__3244$fn__3248.invoke(timbre.clj:297)
> at
> taoensso.timbre$wrap_appender_juxt$fn__3229$fn__3231.invoke(timbre.clj:319)
> at taoensso.timbre$send_to_appenders_BANG_.doInvoke(timbre.clj:398)
> at clojure.lang.RestFn.invoke(RestFn.java:866)
&g
eption_calculation.clj:207)
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-
eadlock
> between spark logging thread and wildfly logging thread.
>
> Can I control the spark logging in the driver application? How can I turn
> it off in the driver application? How can I control the level of spark logs
> in the driver application?
>
> 2014-11-27 14:39:26,7
between spark logging thread and wildfly logging thread.
Can I control the spark logging in the driver application? How can I turn
it off in the driver application? How can I control the level of spark logs
in the driver application?
2014-11-27 14:39:26,719 INFO [akka.event.slf4j.Slf4jLogger
actice.
Anyone else have ideas? thoughts?
> From: kudryavtsev.konstan...@gmail.com
> Subject: Spark logging strategy on YARN
> Date: Thu, 3 Jul 2014 22:26:48 +0300
> To: user@spark.apache.org
>
> Hi all,
>
> Could you please share your the best practices on writing logs in Spark?
Hi all,
Could you please share your the best practices on writing logs in Spark? I’m
running it on YARN, so when I check logs I’m bit confused…
Currently, I’m writing System.err.println to put a message in log and access it
via YARN history server. But, I don’t like this way… I’d like to use
l
Hello Spark fans,
I am unable to figure out how Spark figures out which logger to use. I know
that Spark decides upon this at the time of initialization of the Spark
Context. From Spark documentation it is clear that Spark uses log4j, and
not slf4j, but I have been able to successfully get spark t
We need a centralized spark logging solution. Ideally, it should:
* Allow any Spark process to log at multiple levels (info, warn,
debug) using a single line, similar to log4j
* All logs should go to a central location - so, to read the logs, we
don't need to check each worker by i
t;
>
>
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> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>
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SUREN HIRAMAN, VP TECHNOLOGY
Velos
Accelerating Machine Learning
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You can import org.apache.spark.Logging, and use logInfo, logWarning etc.
Besides viewing them from the Web console, the location of the logs can be
found under $SPARK_HOME/logs, on both the driver and executor machines. (If
you are on YARN, these logs are located elsewhere, however.)
2014-06-10
How can I write to Spark's logs from my client code?
What are the options to view those logs?
Besides the Web console, is there a way to read and grep the file?
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