Using Spark container log rotation - Amazon EMR
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Using Spark container log rotation

With Amazon EMR 6.11.0 and later, you can turn on the Spark container log rotation feature for Amazon EMR on EKS. Instead of generating a single stdout or stderr log file, this feature rotates the file based on your configured rotation size and removes the oldest log files from the container.

Rotating Spark container logs can help you avoid potential issues with a large Spark log files generated for long-running or streaming jobs. For example, you might start a long-running Spark job, and the Spark driver generates a container log file. If the job runs for hours or days and there is limited disk space on the Kubernetes node, the container log file can consume all available disk space. When you turn on Spark container log rotation, you split the log file into multiple files, and remove the oldest files.

To turn on the Spark container log rotation feature, configure the following Spark parameters:

containerLogRotationConfiguration

Include this parameter in monitoringConfiguration to turn on log rotation. It is disabled by default. You must use containerLogRotationConfiguration in addition to s3MonitoringConfiguration.

rotationSize

The rotationSize parameter specifies file size for the log rotation. The range of possible values is from 2KB to 2GB. The numeric unit portion of the rotationSize parameter is passed as an integer. Since decimal values aren't supported, you can specify a rotation size of 1.5GB, for example, with the value 1500MB.

maxFilesToKeep

The maxFilesToKeep parameter specifies the maximum number of files to retain in container after rotation has taken place. The minimum value is 1, and the maximum value is 50.

You can specify these parameters in the monitoringConfiguration section of the StartJobRun API, as the following example shows. In this example, with rotationSize = "10 MB" and maxFilesToKeep = 3, Amazon EMR on EKS rotates your logs at 10 MB, generates a new log file, and then purges the oldest log file once the number of log files reaches 3.

{
  "name": "my-long-running-job", 
  "virtualClusterId": "123456",  
  "executionRoleArn": "iam_role_name_for_job_execution", 
  "releaseLabel": "emr-6.11.0-latest", 
  "jobDriver": {
    "sparkSubmitJobDriver": {
      "entryPoint": "entryPoint_location",
      "entryPointArguments": ["argument1", "argument2", ...],  
       "sparkSubmitParameters": "--class main_class --conf spark.executor.instances=2 --conf spark.executor.memory=2G --conf spark.executor.cores=2 --conf spark.driver.cores=1"
    }
  }, 
  "configurationOverrides": {
    "applicationConfiguration": [
      {
        "classification": "spark-defaults", 
        "properties": {
          "spark.driver.memory":"2G"
         }
      }
    ], 
    "monitoringConfiguration": {
      "persistentAppUI": "ENABLED", 
      "cloudWatchMonitoringConfiguration": {
        "logGroupName": "my_log_group", 
        "logStreamNamePrefix": "log_stream_prefix"
      }, 
      "s3MonitoringConfiguration": {
        "logUri": "s3://my_s3_log_location"
      },
      "containerLogRotationConfiguration": {
        "rotationSize":"10MB",
        "maxFilesToKeep":"3"
      }
    }
  }
}

To start a job run with Spark container log rotation, include a path to the json file that you configured with these parameters in the StartJobRun command.

aws emr-containers start-job-run \
--cli-input-json file://path-to-json-request-file