Claude
b3564737f7
yarn_client.py no longer invokes the 'yarn' binary via subprocess; it uses
httpx against /ws/v1/cluster/apps/* endpoints. This means the runtime image
no longer needs the Hadoop client installation — the only YARN-side
dependency left in the container is the config dir consumed by
spark-submit itself.
New model field:
- Job.yarn_rm_url: str | None
- PendingSubmission.yarn_rm_url: str | None (snapshotted at prepare)
prepare_submit_job snapshots Connection.yarn_rm_url into the pending
record (consistent with the existing master/deploy_mode/spark_conf
snapshot pattern); confirm_submit_job copies it onto the Job so
status/logs/kill can use it without re-looking-up the connection.
Resolution order for the RM URL at runtime:
1. Job.yarn_rm_url (preferred — survives connection edits/deletes)
2. Connection.yarn_rm_url fallback (if a future tool is added that
doesn't go through a Job)
3. YARN_RESOURCE_MANAGER_URL env var
Errors:
- YarnConfigError (HTTP 4xx semantics) when URL is missing/malformed
- YarnError for HTTP 4xx/5xx from the RM, network failures, missing
state field, or unparseable log responses
10 new tests in test_yarn_client.py cover the REST surface:
success, 404, 5xx, missing state field, env-var fallback, malformed
URL, log 404 with log-aggregation hint, kill PUT body shape, and
httpx connection-error wrapping.
133 lines
4.5 KiB
Python
133 lines
4.5 KiB
Python
# coding=utf-8
|
|
from unittest.mock import patch
|
|
|
|
import httpx
|
|
import pytest
|
|
|
|
from spark_executor.core.yarn_client import (
|
|
YarnConfigError,
|
|
YarnError,
|
|
get_application_logs,
|
|
get_application_status,
|
|
kill_application,
|
|
)
|
|
|
|
|
|
RM = "http://rm:8088"
|
|
|
|
|
|
def _resp(status: int, *, json_data=None, text: str | None = None) -> httpx.Response:
|
|
if json_data is not None:
|
|
return httpx.Response(status, json=json_data)
|
|
return httpx.Response(status, text=text or "")
|
|
|
|
|
|
# --- get_application_status ---
|
|
|
|
def test_status_parses_app_state():
|
|
fake = _resp(200, json_data={"app": {"id": "application_1", "state": "RUNNING"}})
|
|
with patch("spark_executor.core.yarn_client.httpx.request", return_value=fake) as m:
|
|
state, raw = get_application_status("application_1", RM)
|
|
assert state == "RUNNING"
|
|
assert "RUNNING" in raw
|
|
args = m.call_args.args
|
|
assert args == ("GET", f"{RM}/ws/v1/cluster/apps/application_1")
|
|
|
|
|
|
def test_status_raises_on_404():
|
|
with patch("spark_executor.core.yarn_client.httpx.request", return_value=_resp(404)):
|
|
with pytest.raises(YarnError, match="not found"):
|
|
get_application_status("application_x", RM)
|
|
|
|
|
|
def test_status_raises_on_5xx():
|
|
with patch(
|
|
"spark_executor.core.yarn_client.httpx.request",
|
|
return_value=_resp(503, text="upstream down"),
|
|
):
|
|
with pytest.raises(YarnError, match="503"):
|
|
get_application_status("application_1", RM)
|
|
|
|
|
|
def test_status_raises_when_state_field_missing():
|
|
fake = _resp(200, json_data={"app": {"id": "application_1"}})
|
|
with patch("spark_executor.core.yarn_client.httpx.request", return_value=fake):
|
|
with pytest.raises(YarnError, match="Could not parse YARN state"):
|
|
get_application_status("application_1", RM)
|
|
|
|
|
|
def test_status_requires_rm_url():
|
|
with patch.dict("os.environ", {}, clear=True):
|
|
with pytest.raises(YarnConfigError):
|
|
get_application_status("application_1", None)
|
|
|
|
|
|
def test_status_falls_back_to_env_var():
|
|
fake = _resp(200, json_data={"app": {"state": "FINISHED"}})
|
|
with patch.dict("os.environ", {"YARN_RESOURCE_MANAGER_URL": "http://env-rm:8088"}, clear=False):
|
|
with patch("spark_executor.core.yarn_client.httpx.request", return_value=fake) as m:
|
|
state, _ = get_application_status("application_1", None)
|
|
assert state == "FINISHED"
|
|
assert "env-rm:8088" in m.call_args.args[1]
|
|
|
|
|
|
def test_status_rejects_non_http_url():
|
|
with pytest.raises(YarnConfigError, match="must start with"):
|
|
get_application_status("application_1", "rm:8088")
|
|
|
|
|
|
# --- get_application_logs ---
|
|
|
|
def test_logs_returns_text():
|
|
fake = _resp(200, text="log line 1\nlog line 2\n")
|
|
with patch("spark_executor.core.yarn_client.httpx.request", return_value=fake) as m:
|
|
out = get_application_logs("application_1", RM)
|
|
assert out == "log line 1\nlog line 2\n"
|
|
assert m.call_args.args == ("GET", f"{RM}/ws/v1/cluster/apps/application_1/aggregated-logs")
|
|
|
|
|
|
def test_logs_raises_on_404_with_explanation():
|
|
with patch("spark_executor.core.yarn_client.httpx.request", return_value=_resp(404)):
|
|
with pytest.raises(YarnError, match="log-aggregation-enable"):
|
|
get_application_logs("application_1", RM)
|
|
|
|
|
|
def test_logs_raises_on_5xx():
|
|
with patch(
|
|
"spark_executor.core.yarn_client.httpx.request",
|
|
return_value=_resp(500, text="boom"),
|
|
):
|
|
with pytest.raises(YarnError):
|
|
get_application_logs("application_1", RM)
|
|
|
|
|
|
# --- kill_application ---
|
|
|
|
def test_kill_sends_put_with_killed_state():
|
|
fake = _resp(200, json_data={"app": {"state": "KILLED"}})
|
|
with patch("spark_executor.core.yarn_client.httpx.request", return_value=fake) as m:
|
|
kill_application("application_1", RM)
|
|
args = m.call_args.args
|
|
assert args == ("PUT", f"{RM}/ws/v1/cluster/apps/application_1/state")
|
|
assert m.call_args.kwargs["json"] == {"state": "KILLED"}
|
|
|
|
|
|
def test_kill_raises_on_5xx():
|
|
with patch(
|
|
"spark_executor.core.yarn_client.httpx.request",
|
|
return_value=_resp(403, text="forbidden"),
|
|
):
|
|
with pytest.raises(YarnError, match="403"):
|
|
kill_application("application_1", RM)
|
|
|
|
|
|
# --- connection errors ---
|
|
|
|
def test_status_wraps_httpx_errors_as_yarn_error():
|
|
with patch(
|
|
"spark_executor.core.yarn_client.httpx.request",
|
|
side_effect=httpx.ConnectError("connection refused"),
|
|
):
|
|
with pytest.raises(YarnError, match="connection failed"):
|
|
get_application_status("application_1", RM)
|