How can I resolve the Kubernetes client closed warning and hanging executor in Spark 3.1.2?

Based on the Kubernetes documentation, there isn’t any guidance or recommendation that covers the Spark-specific issue (SPARK-33349) or mentions a workaround using Kubernetes settings. The Kubernetes docs focus on ensuring proper cluster component compatibility (for example, keeping kubelet versions properly aligned with the control plane) and on troubleshooting issues around pod deletion and admission webhooks—not on client issues coming from Spark’s integration.

For your specific questions:

1. Which version specifically fixes the issue?
   The Kubernetes documentation does not provide details about the Spark upgrade that addresses SPARK-33349. The fix for this issue is managed within the Apache Spark project. To determine exactly which Spark version addresses the issue, please refer to the Apache Spark release notes or the issue tracker where SPARK-33349 is documented.

2. Is there any workaround with settings to solve this issue without upgrading?
   There is no information in the Kubernetes docs suggesting a workaround—via configuration or otherwise—to mitigate this Spark client issue. The documented best practices in Kubernetes relate to ensuring that components such as the kubelet and admission webhooks are properly configured and do not interfere with cluster operations. In your case, as the warning and subsequent hang stem from the internal behavior of the Spark executor interacting with the Kubernetes client, the solution would need to come from within Spark (or a Spark configuration setting) rather than from cluster-level settings.

For further details, consider reviewing the Apache Spark JIRA issue SPARK-33349 and the associated release notes. Additionally, if upgrading Spark is challenging, you might want to seek guidance from the Spark community on any community-supported workarounds.

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