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Ran the pipeline on real Egocentric-10K factory footage, then attacked it: repeat runs, two concurrent processes, a 600s
and a 1190s episode, full 1080p, a bucket-backed root, a mid-run kill, and ...
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[… 8929 characters cut …]
memorysetup-temp-allocator-size-cloud-worker=32768
memorysetup-bucket-allocator-granularity=16
memorysetup-bucket-allocator-bucket-count=8
memorysetup ...
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... . Are there additional K3s-specific prerequisites for this case before moving to v1.33.13+k3s2?
The intention is to stay with official K3s releases and avoid replacing embedded etcd independently, editing datastore
buckets, or using skip-check flags. Thanks for clarifying the supported path.
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... 22:41:01 dataproc_cluster_name: None 22:41:01
gcs_bucket: None 22:41:01 dataproc_batch: None 22:41:01 Registered adapter: bigquery=1.12.1 22:41:05 Connection test:
[OK connection ok]
22:41:05 All checks passed! (datos-gcp) PS D:\datos-gcp\analytics
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... :12 compute_region: None
21:21:12 dataproc_cluster_name: None
21:21:12 gcs_bucket: None
21:21:12 dataproc_batch: None
21:21:12 Registered adapter: bigquery=1.12.1
21:21:16 Connection test: [OK connection ok]
21:21:16 All checks passed!
