使用 Snowpark Scala 时分析查询和排除故障¶
本主题提供了一些有关在使用 Snowpark 库时分析查询和故障排除的指引。
在 Snowpark 中查看查询的执行计划¶
To inspect the evaluation plan of a DataFrame, call the explain method of the DataFrame. This prints the SQL statements
used to evaluate the DataFrame. If there is only one SQL statement, the method also prints the logical plan for the statement.
After the execution of a DataFrame has been triggered, you can check on the progress of the query in the Query History page in Snowsight.
In the Query Tag column, you can find the name of the function and the line number in your code that triggered this query.
故障排除
更改日志记录设置
By default, the Snowpark library logs INFO level messages to stdout. To change the logging settings, create a
simplelogger.properties file, and configure the logger properties in that file. For example, to set the log level to
DEBUG:
Put this file in your classpath. If you are using a Maven directory layout, put the file in the src/main/resources/
directory.
java.lang. OutOfMemoryError 异常¶
If a java.lang.OutOfMemoryError exception is thrown, increase the maximum heap size for the JVM.
If you are using the Scala REPL and you need to increase the maximum heap size, edit the run.sh shell script (provided in
the archive file) and add the -J-Xmxmaximum_size flag to the scala command. The following example increases
the maximum heap size to 4 GB:
