Cannot use spark_event_logs_s3_uri in PySparkProcessor job

sagemaker-core/src/sagemaker/core/spark/processing.py の PySparkProcessor イベントログ用の ProcessingOutput 構築部分から始めます。有効な spark_event_logs_s3_uri を使って失敗を再現し、現在の ProcessingOutput インターフェースを確認します。Spark イベントログを設定した状態で PySparkProcessor ジョブが正常に開始すれば完了です。

PySDK Version

• PySDK V2 (2.x)
• PySDK V3 (3.x)

Describe the bug

Similar to #6252 - PySparkProcessor run no longer handles spark_event_logs_s3_uri due to changes in the ProcessingOutput interface - e.g. regression introduced in 3203e49

To reproduce

Provide any (valid) S3 URI for the spark log location.

Expected behavior

Successfully starts the job.

Screenshots or logs

ValidationError: 4 validation errors for ProcessingOutput
output_name
  Field required [type=missing, input_value={'source': '/opt/ml/proce...oad_mode': 'Continuous'}, input_type=dict]
    For further information visit https://errors.pydantic.dev/2.13/v/missing
source
  Extra inputs are not permitted [type=extra_forbidden, input_value='/opt/ml/processing/spark-events/', input_type=str]
    For further information visit https://errors.pydantic.dev/2.13/v/extra_forbidden
destination
  Extra inputs are not permitted [type=extra_forbidden, input_value='s3://...', input_type=str]
    For further information visit https://errors.pydantic.dev/2.13/v/extra_forbidden
s3_upload_mode
  Extra inputs are not permitted [type=extra_forbidden, input_value='Continuous', input_type=str]
    For further information visit https://errors.pydantic.dev/2.13/v/extra_forbidden

The cause of the error is here:

            output = ProcessingOutput(
                source=_SparkProcessorBase._spark_event_log_default_local_path,
                destination=spark_event_logs_s3_uri,
                s3_upload_mode="Continuous",
            )

System information

• AWS SageMaker Studio 4.4.3
• sagemaker-core: 2.20
• Python 3.12.14
• uname: Linux default 6.12.103-127.188.amzn2023.x86_64 SMP PREEMPT_DYNAMIC Tue Aug 25 15:42:53 UTC 2026 x86_64 x86_64 x86_64 GNU/Linux