http://apache-carbondata-dev-mailing-list-archive.168.s1.nabble.com/Logging-problem-tp13170p13265.html
> Hi Rana
>
> Your this query is in Spark-shell ?
> Please try the below script:
>
> import org.apache.log4j.Logger
> import org.apache.log4j.Level
> Logger.getLogger("org").setLevel(Level.OFF)
> Logger.getLogger("akka").setLevel(Level.OFF)
>
>
> Regards
> Liang
>
> Rana Faisal Munir wrote
> > Hi,
> >
> > Today, I was running a filter query ("SELECT * FROM widetable WHERE
> > col_long_0 = 0") on a wide table with 1187 columns and Spark started
> > printing the below output. It spills alot of log which I want to turn
> > off. There is any option to turn it off. I have tried both option
> > (ERROR,INFO) in log4j.properties file. It did not work for me.
> >
> > Thank you
> >
> > Regards
> > Faisal
> >
> >
> > 17/05/24 12:39:41 INFO CarbonLateDecodeRule: main Starting to optimize
> > plan
> > 17/05/24 12:39:41 INFO CarbonLateDecodeRule: main Skip CarbonOptimizer
> > 17/05/24 12:39:42 INFO deprecation: mapred.job.id is deprecated.
> > Instead, use mapreduce.job.id
> > 17/05/24 12:39:42 INFO deprecation: mapred.tip.id is deprecated.
> > Instead, use mapreduce.task.id
> > 17/05/24 12:39:42 INFO deprecation: mapred.task.id is deprecated.
> > Instead, use mapreduce.task.attempt.id
> > 17/05/24 12:39:42 INFO deprecation: mapred.task.is.map is deprecated.
> > Instead, use mapreduce.task.ismap
> > 17/05/24 12:39:42 INFO deprecation: mapred.task.partition is deprecated.
> > Instead, use mapreduce.task.partition
> > 17/05/24 12:39:42 INFO FileOutputCommitter: File Output Committer
> > Algorithm version is 1
> > 17/05/24 12:39:42 INFO SQLHadoopMapReduceCommitProtocol: Using output
> > committer class org.apache.hadoop.mapreduce.
> lib.output.FileOutputCommitter
> > 17/05/24 12:39:44 ERROR CodeGenerator: failed to compile:
> > org.codehaus.janino.JaninoRuntimeException: Code of method
> > "processNext()V" of class
> > "org.apache.spark.sql.catalyst.expressions.GeneratedClass$
> GeneratedIterator"
> > grows beyond 64 KB
> > /* 001 */ public Object generate(Object[] references) {
> > /* 002 */ return new GeneratedIterator(references);
> > /* 003 */ }
> > /* 004 */
> > /* 005 */ final class GeneratedIterator extends
> > org.apache.spark.sql.execution.BufferedRowIterator {
> > /* 006 */ private Object[] references;
> > /* 007 */ private scala.collection.Iterator[] inputs;
> > /* 008 */ private scala.collection.Iterator scan_input;
> > /* 009 */ private org.apache.spark.sql.execution.metric.SQLMetric
> > scan_numOutputRows;
> > /* 010 */ private org.apache.spark.sql.execution.metric.SQLMetric
> > scan_scanTime;
> > /* 011 */ private long scan_scanTime1;
> > /* 012 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnarBatch scan_batch;
> > /* 013 */ private int scan_batchIdx;
> > /* 014 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance0;
> > /* 015 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance1;
> > /* 016 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance2;
> > /* 017 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance3;
> > /* 018 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance4;
> > /* 019 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance5;
> > /* 020 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance6;
> > /* 021 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance7;
> > /* 022 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance8;
> > /* 023 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance9;
> > /* 024 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance10;
> > /* 025 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance11;
> > /* 026 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance12;
> > /* 027 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance13;
> > /* 028 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance14;
> > /* 029 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance15;
> > /* 030 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance16;
> > /* 031 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance17;
> > /* 032 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance18;
> > /* 033 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance19;
> > /* 034 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance20;
> > /* 035 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance21;
> > /* 036 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance22;
> > /* 037 */ private
> > org.apache.spark.sql.execution.vectorized.ColumnVector
> scan_colInstance23;
>
>
>
>
>
> --
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> tp13170p13219.html
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