만료된 토큰을 사용하여 작업을 제출하면 만료 상태를 알리는 다른 오류 메시지가 표시됩니다. 지원되는 SDK 버전으로 업그레이드하거나 토큰 없이 작업을 다시 제출하여 새 토큰을 얻을 수 있습니다.
지원되지 않는 SDK를 계속 사용하기 위한 방법으로 토큰을 사용하면 안 됩니다. SDK의 지원되지 않는 날짜가 지나면 모든 토큰이 취소되고 지원되지 않는 SDK 버전을 사용하는 모든 작업이 거부됩니다. 각 SDK의 지원 상태에 대한 자세한 내용은 SDK 버전 지원 상태를 참조하세요.
중단된 작업 재개
스트리밍 작업과 같이 지원되지 않는 SDK를 사용하는 장기 실행 Dataflow 작업도 중단되고 처리량이 크게 줄어듭니다. 이렇게 중단된 작업은 작업 로그에서 다음 오류 메시지를 통해 식별할 수 있습니다.
Python 2.3.0에 지원되지 않는 SDK Apache Beam SDK를 사용하여 서비스에서 워크플로를 자동으로 중단했습니다. 최신 SDK 버전으로 업그레이드하세요. 중단된 작업을 일시적으로 재개하려면 gcloud alpha dataflow jobs resume-unsupported-sdk --token=TOKEN --region=REGION JOB_ID를 사용하세요. 이 토큰으로 재개된 작업은 2020-08-28T11:21:58-07:00에 다시 중단됩니다. 지원되는 SDK 버전 목록은 https://cloud.google.com/dataflow/support#support-status-for-dataflow-sdk-releases를 참조하세요.
오류에서 알 수 있듯이 resume-unsupported-sdk 명령어를 사용하여 중단 문제를 완화할 수 있습니다. 중단된 작업 재개하기는 일시적인 해결책입니다. 대신 향후 지원 중단 작업이 발생하지 않도록 SDK 버전을 업그레이드해야 합니다.
[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["이해하기 어려움","hardToUnderstand","thumb-down"],["잘못된 정보 또는 샘플 코드","incorrectInformationOrSampleCode","thumb-down"],["필요한 정보/샘플이 없음","missingTheInformationSamplesINeed","thumb-down"],["번역 문제","translationIssue","thumb-down"],["기타","otherDown","thumb-down"]],["최종 업데이트: 2025-09-04(UTC)"],[[["\u003cp\u003eSubmitting Dataflow jobs from an unsupported SDK version leads to interruptions and reduced throughput for long-running batch or streaming jobs.\u003c/p\u003e\n"],["\u003cp\u003eUsers can temporarily use a token to resubmit a job with an unsupported SDK, or use a token to resume a disrupted job, although these are not permanent solutions.\u003c/p\u003e\n"],["\u003cp\u003eUpgrading to a supported SDK version is the preferred method to resolve issues caused by unsupported SDKs and avoid future disruptions.\u003c/p\u003e\n"],["\u003cp\u003eTokens for unsupported SDKs expire, and resumed jobs will return to a disrupted state once the temporary token expires.\u003c/p\u003e\n"],["\u003cp\u003eJobs using an unsupported SDK version may be subject to a complete cancellation after the SDK's supported date.\u003c/p\u003e\n"]]],[],null,["# Using an unsupported SDK\n\nSubmitting jobs from an SDK version past its supported date results in interruptions and a reduction in throughput for long-running batch or streaming jobs. To mitigate potential issues, do the following:\n\n- [Upgrade the SDK version](/dataflow/docs/guides/installing-beam-sdk#installing-sdk-releases). (Preferred)\n- [Resubmit the job using a temporary token](#starting_jobs_with_unsupported_sdk_versions).\n- [Resume the disrupted job](#resuming_disrupted_jobs).\n\n| **Note:** All available SDK versions can be found on the [support status page](/dataflow/docs/support/sdk-version-support-status#apache-beam-2.x-sdks).\n\n### Starting jobs with unsupported SDK versions\n\nWhen you submit a Dataflow job from an SDK version past its supported date, you will receive an error message directing you to either [upgrade your SDK version](/dataflow/docs/guides/installing-beam-sdk#installing-sdk-releases) or to use a temporary token when you submit your job.\n\nThe token value in the error message contains the datetime when the token expires as well as the token itself. The expiration date is set for two weeks in the future.\n\nIf you want to use the token, resubmit your job using the `unsupported_sdk_temporary_override_token` experiment flag and token value. \n\n```bash\n--experiments=unsupported_sdk_temporary_override_token=TOKEN\n```\n\nIf you submit a job using the token after it expires, you will receive a different error message informing you of the expired status. You can can either upgrade to a supported SDK version or resubmit your job without the token to get a new token.\n| **Note:** Tokens are applied at the individual job level, so if you have multiple jobs scheduled, each job must use a unique token.\n\nTokens should not be used as a permanent way to keep using an unsupported SDK. At some time after the unsupported date of an SDK, all tokens will be revoked and all jobs using that unsupported SDK version are rejected. For more details on the support status of each SDK, see [SDK version support status](/dataflow/docs/support/sdk-version-support-status).\n\n### Resuming disrupted jobs\n\nLong-running Dataflow jobs that use unsupported SDKs, such as streaming jobs, will also be disrupted and have their throughput significantly reduced. These disrupted jobs can be identified through the following error message in the job logs:\n\u003e The workflow was automatically disrupted by the service because it uses an unsupported SDK Apache Beam SDK for Python 2.3.0. Please upgrade to the latest SDK version. To resume the disrupted job temporarily, please use `gcloud alpha dataflow jobs resume-unsupported-sdk --token=TOKEN --region=REGION JOB_ID`. Note that the resumed job by this token will be disrupted again on 2020-08-28T11:21:58-07:00. For a list of supported SDK versions, see: https://cloud.google.com/dataflow/support#support-status-for-dataflow-sdk-releases.\n\nAs the error suggests, the disruption can be mitigated using the [resume-unsupported-sdk](/sdk/gcloud/reference/alpha/dataflow/jobs/resume-unsupported-sdk) command. Resuming a disrupted job is a temporary solution. Instead, you should [upgrade](/dataflow/docs/guides/installing-beam-sdk#installing-sdk-releases) your SDK version to avoid further deprecation actions in the future.\n| **Note:** Previously resumed jobs will return to the disrupted state once the temporary token expires. Any future disruptions can be resumed in the same way; however, jobs running on unsupported SDK versions could be automatically cancelled at some time after the unsupported date."]]
