Spark应用日志级别设置

一. 日志效率原因

开发时，控制台输出一大堆日志信息，严重影响查看日志效率。

 

从控制台输出日志我们可以看出，应用程序是默认加载Spark-core包下面的log4j-defaults.properties日志文件。查看log4j-defaults.properties文件

 

由上图可知，Spark-core包设置默认的日志级别为info，所以我们才看到一大堆日志信息。

那针对以上问题，在开发过程中我们如何解决？

二. 日志级别解决方法

方式一.局部应用设置

针对SparkContext应用，Spark有专门的api设置日志级别，如下：

上述方法，只针对SparkContext相关的应用，而对Spark Streaming等应用无效果。

方式二.全局应用设置

针对spark所有应用，可以在Java工程目录中新建/src/main/resources目录，把log4j.properties放置该目录。

 

log4j.properties生成：

1. Spark中conf默认配置文件是log4j.properties.template，可以将其改名为log4j.properties;

2. 将Spark-core包中的log4j-default.properties内容复制到log4j.properties文件。

 

#log4j内容如下

    #  
    # Licensed to the Apache Software Foundation (ASF) under one or more  
    # contributor license agreements.  See the NOTICE file distributed with  
    # this work for additional information regarding copyright ownership.  
    # The ASF licenses this file to You under the Apache License, Version 2.0  
    # (the "License"); you may not use this file except in compliance with  
    # the License.  You may obtain a copy of the License at  
    #  
    #    http://www.apache.org/licenses/LICENSE-2.0  
    #  
    # Unless required by applicable law or agreed to in writing, software  
    # distributed under the License is distributed on an "AS IS" BASIS,  
    # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.  
    # See the License for the specific language governing permissions and  
    # limitations under the License.  
    #  
      
    # Set everything to be logged to the console  
    log4j.rootCategory=WARN, console  
    log4j.appender.console=org.apache.log4j.ConsoleAppender  
    log4j.appender.console.target=System.err  
    log4j.appender.console.layout=org.apache.log4j.PatternLayout  
    log4j.appender.console.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss} %p %c{1}: %m%n  
      
    # Settings to quiet third party logs that are too verbose  
    log4j.logger.org.spark-project.jetty=WARN  
    log4j.logger.org.spark-project.jetty.util.component.AbstractLifeCycle=ERROR  
    log4j.logger.org.apache.spark.repl.SparkIMain$exprTyper=INFO  
    log4j.logger.org.apache.spark.repl.SparkILoop$SparkILoopInterpreter=INFO  
    log4j.logger.org.apache.parquet=ERROR  
    log4j.logger.parquet=ERROR  
      
    # SPARK-9183: Settings to avoid annoying messages when looking up nonexistent UDFs in SparkSQL with Hive support  
    log4j.logger.org.apache.hadoop.hive.metastore.RetryingHMSHandler=FATAL  
    log4j.logger.org.apache.hadoop.hive.ql.exec.FunctionRegistry=ERROR  

 

在开发工程中，我们可以设置日志级别为WARN，即：

log4j.rootCategory=WARN, console

三. 日志级别设置效果