How to surpress “Code Generated” and “Cleaned Accumulator” messages in Spark












1















I wrote a spark job. The job ran fine without any problems. However when I look at my error log file, I see so many messages of type



[error] 18/11/25 17:28:14 INFO CodeGenerator: Code 

generated in 16.947005 ms


and 



[error] 18/11/25 17:28:15 INFO ContextCleaner: Cleaned

accumulator 239819


and 



[error] 18/11/25 17:28:06 INFO BlockManagerInfo: Removed 

broadcast_13354_piece0 on 192.168.2.101:43753 in memory 

(size: 20.5 KB, free: 6.2 GB)


Is there any way to suppress these messages. they are just bloating up my log file.



Not sure why spark is reporting these as error. when they look like some kind of debug messages.






scala apache-spark







share|improve this question





























    1















    I wrote a spark job. The job ran fine without any problems. However when I look at my error log file, I see so many messages of type



    [error] 18/11/25 17:28:14 INFO CodeGenerator: Code 
    
generated in 16.947005 ms


    and 



    [error] 18/11/25 17:28:15 INFO ContextCleaner: Cleaned
    
accumulator 239819


    and 



    [error] 18/11/25 17:28:06 INFO BlockManagerInfo: Removed 
    
broadcast_13354_piece0 on 192.168.2.101:43753 in memory 
    
(size: 20.5 KB, free: 6.2 GB)


    Is there any way to suppress these messages. they are just bloating up my log file.



    Not sure why spark is reporting these as error. when they look like some kind of debug messages.






    scala apache-spark







    share|improve this question



























      1












      1








      1


      1






      I wrote a spark job. The job ran fine without any problems. However when I look at my error log file, I see so many messages of type



      [error] 18/11/25 17:28:14 INFO CodeGenerator: Code 
      
generated in 16.947005 ms


      and 



      [error] 18/11/25 17:28:15 INFO ContextCleaner: Cleaned
      
accumulator 239819


      and 



      [error] 18/11/25 17:28:06 INFO BlockManagerInfo: Removed 
      
broadcast_13354_piece0 on 192.168.2.101:43753 in memory 
      
(size: 20.5 KB, free: 6.2 GB)


      Is there any way to suppress these messages. they are just bloating up my log file.



      Not sure why spark is reporting these as error. when they look like some kind of debug messages.






      scala apache-spark







      share|improve this question
















      I wrote a spark job. The job ran fine without any problems. However when I look at my error log file, I see so many messages of type



      [error] 18/11/25 17:28:14 INFO CodeGenerator: Code 
      
generated in 16.947005 ms


      and 



      [error] 18/11/25 17:28:15 INFO ContextCleaner: Cleaned
      
accumulator 239819


      and 



      [error] 18/11/25 17:28:06 INFO BlockManagerInfo: Removed 
      
broadcast_13354_piece0 on 192.168.2.101:43753 in memory 
      
(size: 20.5 KB, free: 6.2 GB)


      Is there any way to suppress these messages. they are just bloating up my log file.



      Not sure why spark is reporting these as error. when they look like some kind of debug messages.






      scala apache-spark




      scala apache-spark






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Nov 26 '18 at 3:39







      Knows Not Much

















      asked Nov 26 '18 at 3:33









      Knows Not MuchKnows Not Much

      10.6k28100203




      10.6k28100203
























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          when you are creating the object of SparkContext, use the following code with it to set the log level according to the requirement:



          sparkContext.setLogLevel("WARN")


          The above line will set the log level for Spark to WARN and you will not get any INFO or DEBUG level logs.






          share|improve this answer























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            4














            when you are creating the object of SparkContext, use the following code with it to set the log level according to the requirement:



            sparkContext.setLogLevel("WARN")


            The above line will set the log level for Spark to WARN and you will not get any INFO or DEBUG level logs.






            share|improve this answer




























              4














              when you are creating the object of SparkContext, use the following code with it to set the log level according to the requirement:



              sparkContext.setLogLevel("WARN")


              The above line will set the log level for Spark to WARN and you will not get any INFO or DEBUG level logs.






              share|improve this answer


























                4












                4








                4







                when you are creating the object of SparkContext, use the following code with it to set the log level according to the requirement:



                sparkContext.setLogLevel("WARN")


                The above line will set the log level for Spark to WARN and you will not get any INFO or DEBUG level logs.






                share|improve this answer













                when you are creating the object of SparkContext, use the following code with it to set the log level according to the requirement:



                sparkContext.setLogLevel("WARN")


                The above line will set the log level for Spark to WARN and you will not get any INFO or DEBUG level logs.







                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered Nov 26 '18 at 4:33









                anuj saxenaanuj saxena

                24917




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