Github user wangmiao1981 commented on the issue:
https://github.com/apache/spark/pull/14433
@felixcheung I checked which object calls the log and print message
accordingly.
./bin/sparkR
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[Previously saved workspace restored]
Launching java with spark-submit command
/Users/mwang/spark_ws_0904/bin/spark-submit "sparkr-shell"
/var/folders/s_/83b0sgvj2kl2kwq4stvft_pm0000gn/T//Rtmpi4dP8y/backend_portb9fa113abad2
Using Spark's default log4j profile:
org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use setLogLevel(newLevel).
./bin/spark-shell
Using Spark's default log4j profile:
org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel).
./bin/pyspark
Python 2.7.11 |Anaconda 2.4.0 (x86_64)| (default, Dec 6 2015, 18:57:58)
[GCC 4.2.1 (Apple Inc. build 5577)] on darwin
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Using Spark's default log4j profile:
org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel).
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