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必备logging初始配置

import logging import sys logger = logging.getLogger() logger.setLevel(logging.INFO) rf_handler = logging.StreamHandler(sys.stderr) rf_handler.setLevel(logging.DEBUG) rf_handler.setFormatter(logging.Formatter("%(asctime)s - %(name)s - %(levelname)s

logger日志重复打印问题-解决

def getlogger(self): self.logger = logging.getLogger() self.logger.setLevel(logging.DEBUG) rp = strftime('%Y%m%d%H%M', localtime(time())) log_path = os.path.dirname(os.getcwd()) + '/logs/'

logging 模块使用

import logging# 创建一个loggerlogger = logging.getLogger('hadoop')logger.setLevel(logging.DEBUG)# 创建一个handler，用于写入日志文件log_file = 'D:\pythonproj\hadoop_tools\public\ops.log'fh = logging.FileHandler(log_file)fh.setLevel(logging.INFO)# 再创

常用模块1

# # 日志模块# # import logging# # logging.debug('debug') # 10 日志级别# # logging.info('info') # 20# # logging.warning('warn') # 30# # logging.error('error') # 40# # logging.critical('critical') # 50# ''

设置Spark运行程序时不显示log信息

在IDEA中设置不要显示spark的log信息 需要导入的包： import org.apache.log4j.Logger import org.apache.log4j.Level 第一种方式：在main函数中设置 def main(args:Array[String]):Unit={ Logger.getLogger("org").setLevel(Level.OFF) System.setProperty("spark.ui.show