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Stephen Carman commented on SPARK-10057: ---------------------------------------- Hi, I think I've found a way to reproduce this. I believe it has something to do with the fact that spark overrides the Jul logger in Parquet relation and sets their own SLF4jBridgeHandler. I only get this warning when I try and load something via parquet. I've tested this via local parquet files, parquet files in S3 and also tested a negative case against Json files, both local and in S3 and Text files both local and in S3. In the text and JSON this warning never occurs, but in parquet it always occurs every time no matter where I am loading the data from. {code:java} scala> sc.setLogLevel("WARN") scala> val d = sc.parallelize(Array[Int](1,2,3,4,5)) d: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[0] at parallelize at <console>:21 scala> val ddf = d.toDF() ddf: org.apache.spark.sql.DataFrame = [_1: int] scala> ddf.write.parquet("/home/scarman/data/test.parquet") SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder". SLF4J: Defaulting to no-operation (NOP) logger implementation SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details. {code} This was done on Spark 1.5.2 with Hadoop 2.7.1, whatever the default parquet dependency is. Hopefully this helps, it's not code breaking but it's very annoying. > Faill to load class org.slf4j.impl.StaticLoggerBinder > ----------------------------------------------------- > > Key: SPARK-10057 > URL: https://issues.apache.org/jira/browse/SPARK-10057 > Project: Spark > Issue Type: Bug > Components: Spark Core > Affects Versions: 1.5.0 > Reporter: Davies Liu > > Some loggings are dropped, because it can't load class > "org.slf4j.impl.StaticLoggerBinder" > {code} > SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder". > SLF4J: Defaulting to no-operation (NOP) logger implementation > SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further > details. > {code} -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org