Setting default log level to "WARN". To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
时间: 2023-09-09 16:08:19 浏览: 403
这个是 Spark 在启动时的日志输出,告诉我们当前的默认日志级别为 WARN,如果需要调整日志级别,可以使用 `sc.setLogLevel(newLevel)` 函数来设置。例如,如果需要将日志级别改为 INFO,可以使用以下代码:
```python
sc.setLogLevel("INFO")
```
需要注意的是,这个日志级别设置只会影响当前 SparkContext 对象的日志级别,如果存在多个 SparkContext 对象,则需要为每个 SparkContext 对象单独设置日志级别。另外,如果使用了 SparkR,需要使用 `setLogLevel(newLevel)` 函数来设置日志级别。
相关问题
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Thank you for the information. This command is used to set the logging level for Spark applications in Scala, Java, and Python. The logging level determines the amount of information that is written to the log files during the Spark application's execution.
The available logging levels are (in ascending order of verbosity): ALL, DEBUG, ERROR, FATAL, INFO, OFF, TRACE, and WARN.
To set the logging level to a specific value, you can use the sc.setLogLevel() method in Scala or Java, or the setLogLevel() function in SparkR. For example, to set the logging level to WARN, you would use:
```
sc.setLogLevel("WARN")
```
This will ensure that only warning messages and above are written to the log files during the Spark application's execution.
using spark's default log4j profile: org/apache/spark/log4j-defaults.properties setting default log level to "warn". to adjust logging level use sc.setloglevel(newlevel). for sparkr, use setloglevel(newlevel).
Spark使用默认的log4j配置文件org/apache/spark/log4j-defaults.properties,将默认的日志级别设置为“warn”。如果需要调整日志级别,请使用sc.setloglevel(newlevel)(对于SparkR,请使用setloglevel(newlevel))。
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