计划执行与检查节点
executing-plans
按既定实施计划完成工作,保持过程检查和反馈。
batch-and-cli【效率与协作】Use hailtop.batch DAGs and packaged hailctl commands for Hail Batch, cloud configuration, authentication, cluster helpers, and file description workflows.
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Use this sub-skill when the task mentions Hail Batch, hailtop.batch, Batch, LocalBackend, ServiceBackend, new_job, resource files, Docker/resource settings, hailctl batch, hailctl config, hailctl auth, hailctl dataproc, hailctl hdinsight, hailctl describe, billing projects, requester-pays, regions, or remote_tmpdir.
references/batch-workflows.md for Python hailtop.batch DAG construction, local/service backend choice, dependencies, input/output files, resource groups, Docker images, resource requests, and scatter/gather planning.references/cloud-and-cli.md for packaged hailctl command families, Batch service configuration, auth, Dataproc, HDInsight, describe, and cloud side-effect boundaries.references/troubleshooting.md for LocalBackend/Docker/tmp failures, ServiceBackend auth/billing/remote tmpdir errors, requester-pays access, command interpolation mistakes, and cloud skip conditions.scripts/batch_local_smoke.py --help first; use scripts/batch_local_smoke.py --dry-run for a no-execution template or scripts/batch_local_smoke.py --run for a local-only smoke when hailtop.batch is importable.hl.init, hl.init_batch, Spark/local setup, package import failures, or generated runtime asset issues, route to ../setup-and-backends/SKILL.md unless the task is specifically about hailtop.batch DAG execution.../tables-and-expressions/SKILL.md or ../genomics-analysis/SKILL.md; use this sub-skill only to package those scripts as Batch jobs.VariantDataset or GVCF combiner workflows, route data-processing logic to ../variant-datasets/SKILL.md; keep this sub-skill focused on orchestration.hailctl commands visible in installed help.hailtop.batch.Batch, LocalBackend, ServiceBackend, Batch.new_job, Batch.new_python_job, Batch.read_input, Batch.read_input_group, Batch.write_output, Job.depends_on, BashJob.command, BashJob.declare_resource_group, BashJob.image, Job.cpu, Job.memory, Job.storage, and Job.regions.Batch(name=None, backend=None, attributes=None, requester_pays_project=None, default_image=None, default_memory=None, default_cpu=None, default_storage=None, default_regions=None, default_timeout=None, default_shell=None, default_python_image=None, default_spot=None, project=None, cancel_after_n_failures=None).LocalBackend(tmp_dir='/tmp/', gsa_key_file=None, extra_docker_run_flags=None) and ServiceBackend(*args, billing_project=None, bucket=None, remote_tmpdir=None, google_project=None, token=None, regions=None, gcs_requester_pays_configuration=None, gcs_bucket_allow_list=None).hailctl --help, hailctl auth --help, hailctl batch --help, hailctl config --help, hailctl dataproc --help, hailctl describe --help, hailctl hdinsight --help, and python -m hailtop.hailctl --help.LocalBackend for examples, smoke tests, and DAG debugging; it avoids Batch Service credentials and cloud billing.ServiceBackend, hailctl batch submit, hailctl batch init, hailctl dataproc start, hailctl dataproc stop, hailctl dataproc modify, hailctl hdinsight start, and hailctl hdinsight stop as cloud-mutating or billing-impacting.backend.close() or the async close pattern used by the surrounding application.