Claude
70400d3ed1
`get_job_status` returns YARN state + the raw response blob, so the terminal fields (finalStatus, diagnostics, trackingUrl, startedTime, finishedTime) are buried inside `raw` and not surfaced in a structured form. Add a new tool that parses them. `get_job_result(job_id)` reuses `yarn_client.get_application_status` and extracts: - finalStatus (SUCCEEDED / FAILED / KILLED / UNDEFINED) - diagnostics (YARN final message) - tracking_url (Spark Web UI) - started_time / finished_time (epoch ms) All five fields are optional: running jobs have no `finishedTime`, and older YARN versions (CDH 5 / H2) may omit some fields. Missing fields stay None — never raise. Coexistence with `get_job_status` is intentional: the latter is for polling the running YARN state, the former is the terminal view. Tests: 4 cases — happy path, running job (no finishedTime), bare-minimum raw (all optionals None), unknown job_id raises KeyError. uv run pytest -> 171 passed.
37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
# coding=utf-8
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"""
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@Time :2026/6/26
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@Author :tao.chen
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"""
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import json
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from common.logging import logger
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from spark_executor.core.job_store import JobStore
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from spark_executor.core.yarn_client import get_application_status
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from spark_executor.models import JobResult
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store = JobStore()
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def get_job_result(job_id: str) -> JobResult:
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logger.debug(f"get_job_result enter job_id={job_id}")
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job = store.get(job_id)
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if job is None:
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raise KeyError(f"Unknown job_id: {job_id}")
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state, raw = get_application_status(job.application_id, job.yarn_rm_url)
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app = json.loads(raw).get("app", {})
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result = JobResult(
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application_id=job.application_id,
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state=state,
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final_status=app.get("finalStatus"),
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diagnostics=app.get("diagnostics"),
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tracking_url=app.get("trackingUrl"),
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started_time=app.get("startedTime"),
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finished_time=app.get("finishedTime"),
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)
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logger.info(
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f"get_job_result ok job_id={job_id} application_id={job.application_id} "
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f"state={state} final_status={result.final_status}"
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)
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return result
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