Three behavioural improvements driven by the sub-agent end-to-end test
findings, plus scheduler tweaks to prevent the post-deploy contention
burst we measured.
CATALOG (catalog-side bugs the test agents tripped on):
- new entity_type field per remote row (BASE TABLE / VIEW /
MATERIALIZED VIEW). For views, rows + size_bytes return null
instead of the misleading 0 that __TABLES__ reports.
- where_examples now validates against the table's actual schema
(cached known_columns from refresh). The pre-fix behavior
blindly advertised `country_code = 'CZ'` on tables with no
country_code column — the sub-agent tests reliably hit this on
unit_economics.
- new known_columns + entity_type columns on bq_metadata_cache;
populated by bq_metadata_refresh.refresh_one from the same
fetch_bq_columns_full call (no extra BQ roundtrip) plus a
cheap INFORMATION_SCHEMA.TABLES lookup for table_type.
QUERY COST-GUARD:
- remote_scan_too_large suggestion now names views explicitly:
`Target(s) <ids> are VIEW or MATERIALIZED VIEW. BigQuery does
not push LIMIT into the view body — SELECT * FROM <view>
LIMIT 1 still runs the full underlying scan.` Programmatic
consumers get a new view_targets field on the error detail.
SCHEDULER HYGIENE (the post-deploy 1-minute window where
concurrent parquet downloads dropped to ~1 MB/s):
- SCHEDULER_STARTUP_GRACE_SECONDS (default 60) holds the first
tick so the burst doesn't overlap cache_warmup writes.
- SCHEDULER_BQ_METADATA_INITIAL_OFFSET_MAX_SECONDS (default 900)
randomises bq-metadata-refresh's first-fire offset.
TESTS:
- test_bq_metadata_cache_repo: entity_type + known_columns round-trip
- test_v2_catalog_remote_metadata: where_examples validation, views
return null rows/size_bytes, cold rows have empty examples
- test_api_query_guardrail: VIEW-aware suggestion text + view_targets
- test_connectors_bigquery_metadata: entity_type lookup mock + new
fields in TableMetadata expectations
- test_scheduler_sidecar: grace + jitter env-var resolution
157 lines
6.5 KiB
Python
157 lines
6.5 KiB
Python
"""Unit tests for the env-driven JOBS builder in services.scheduler."""
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import pytest
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def test_build_jobs_uses_documented_defaults(monkeypatch):
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"""No env overrides → default cadences."""
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for v in (
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"SCHEDULER_DATA_REFRESH_INTERVAL",
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"SCHEDULER_HEALTH_CHECK_INTERVAL",
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"SCHEDULER_TICK_SECONDS",
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"SCHEDULER_SCRIPT_RUN_INTERVAL",
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):
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monkeypatch.delenv(v, raising=False)
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from services.scheduler.__main__ import build_jobs, resolved_tick_seconds
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jobs = {name: schedule for name, schedule, *_ in build_jobs()}
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assert jobs["data-refresh"] == "every 15m"
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assert jobs["health-check"] == "every 5m"
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assert jobs["script-runner"] == "every 1m"
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assert jobs["marketplaces"] == "daily 03:00"
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assert jobs["bq-metadata-refresh"] == "every 4h"
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assert resolved_tick_seconds() == 30
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def test_build_jobs_honors_bq_metadata_env_override(monkeypatch):
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monkeypatch.setenv("SCHEDULER_BQ_METADATA_REFRESH_INTERVAL", "7200") # 2h
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from services.scheduler.__main__ import build_jobs
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jobs = {name: schedule for name, schedule, *_ in build_jobs()}
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assert jobs["bq-metadata-refresh"] == "every 2h"
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def test_resolved_startup_grace_default(monkeypatch):
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monkeypatch.delenv("SCHEDULER_STARTUP_GRACE_SECONDS", raising=False)
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from services.scheduler.__main__ import resolved_startup_grace_seconds
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assert resolved_startup_grace_seconds() == 60
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def test_resolved_startup_grace_zero_is_valid(monkeypatch):
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"""0 means "disable" — useful for unit tests / fast dev iterations."""
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monkeypatch.setenv("SCHEDULER_STARTUP_GRACE_SECONDS", "0")
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from services.scheduler.__main__ import resolved_startup_grace_seconds
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assert resolved_startup_grace_seconds() == 0
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def test_resolved_startup_grace_rejects_negative(monkeypatch):
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monkeypatch.setenv("SCHEDULER_STARTUP_GRACE_SECONDS", "-1")
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from services.scheduler.__main__ import resolved_startup_grace_seconds
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with pytest.raises(ValueError):
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resolved_startup_grace_seconds()
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def test_resolved_startup_grace_rejects_empty(monkeypatch):
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"""Empty string is operator typo, not 'use default' — fail fast."""
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monkeypatch.setenv("SCHEDULER_STARTUP_GRACE_SECONDS", "")
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from services.scheduler.__main__ import resolved_startup_grace_seconds
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with pytest.raises(ValueError):
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resolved_startup_grace_seconds()
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def test_bq_metadata_initial_offset_within_cap(monkeypatch):
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"""Default cap is 900s. With a fixed RNG, the offset is deterministic
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and bounded."""
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monkeypatch.delenv("SCHEDULER_BQ_METADATA_INITIAL_OFFSET_MAX_SECONDS", raising=False)
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import random
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from services.scheduler.__main__ import resolved_bq_metadata_initial_offset_seconds
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rng = random.Random(42) # deterministic
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val = resolved_bq_metadata_initial_offset_seconds(rng=rng)
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assert 0 <= val <= 900
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def test_bq_metadata_initial_offset_zero_cap_returns_zero(monkeypatch):
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"""Operator opt-out: setting cap to 0 disables the jitter."""
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monkeypatch.setenv("SCHEDULER_BQ_METADATA_INITIAL_OFFSET_MAX_SECONDS", "0")
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from services.scheduler.__main__ import resolved_bq_metadata_initial_offset_seconds
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assert resolved_bq_metadata_initial_offset_seconds() == 0
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def test_bq_metadata_initial_offset_honors_custom_cap(monkeypatch):
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monkeypatch.setenv("SCHEDULER_BQ_METADATA_INITIAL_OFFSET_MAX_SECONDS", "60")
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import random
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from services.scheduler.__main__ import resolved_bq_metadata_initial_offset_seconds
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# Loop a few times since RNG could legitimately return 60.
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for seed in range(20):
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val = resolved_bq_metadata_initial_offset_seconds(rng=random.Random(seed))
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assert 0 <= val <= 60
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def test_build_jobs_honors_env_overrides(monkeypatch):
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monkeypatch.setenv("SCHEDULER_DATA_REFRESH_INTERVAL", "1800") # 30m
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monkeypatch.setenv("SCHEDULER_HEALTH_CHECK_INTERVAL", "60") # 1m
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monkeypatch.setenv("SCHEDULER_SCRIPT_RUN_INTERVAL", "120") # 2m
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monkeypatch.setenv("SCHEDULER_TICK_SECONDS", "10")
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from services.scheduler.__main__ import build_jobs, resolved_tick_seconds
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jobs = {name: schedule for name, schedule, *_ in build_jobs()}
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assert jobs["data-refresh"] == "every 30m"
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assert jobs["health-check"] == "every 1m"
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assert jobs["script-runner"] == "every 2m"
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assert resolved_tick_seconds() == 10
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@pytest.mark.parametrize("var", [
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"SCHEDULER_DATA_REFRESH_INTERVAL",
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"SCHEDULER_HEALTH_CHECK_INTERVAL",
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"SCHEDULER_TICK_SECONDS",
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"SCHEDULER_SCRIPT_RUN_INTERVAL",
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])
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@pytest.mark.parametrize("bad", ["0", "-5", "abc", ""])
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def test_build_jobs_rejects_invalid_env(monkeypatch, var, bad):
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monkeypatch.setenv(var, bad)
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from services.scheduler.__main__ import build_jobs
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with pytest.raises(ValueError):
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build_jobs()
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def test_build_jobs_rejects_tick_larger_than_smallest_interval(monkeypatch):
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"""Tick must be <= the smallest job interval, otherwise jobs would
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consistently miss their cadence by up to one tick."""
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monkeypatch.setenv("SCHEDULER_HEALTH_CHECK_INTERVAL", "60")
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monkeypatch.setenv("SCHEDULER_TICK_SECONDS", "120")
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from services.scheduler.__main__ import build_jobs
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with pytest.raises(ValueError, match="tick"):
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build_jobs()
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def test_build_jobs_includes_run_due_endpoint():
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"""The script-runner job must POST to /api/scripts/run-due."""
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from services.scheduler.__main__ import build_jobs
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target = next(j for j in build_jobs() if j[0] == "script-runner")
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name, schedule, endpoint, method, _timeout = target
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assert endpoint == "/api/scripts/run-due"
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assert method == "POST"
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@pytest.mark.parametrize("seconds,expected", [
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# Exact multiples of 60 → unchanged.
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(60, "every 1m"),
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(120, "every 2m"),
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(900, "every 15m"),
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# Exact multiples of 3600 → hour form.
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(3600, "every 1h"),
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(7200, "every 2h"),
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# Non-multiples of 60 must round UP (ceiling), so the job never fires
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# MORE often than the operator configured. Devin BUG_0001 on 1af2081.
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(90, "every 2m"), # 90s asked → 120s scheduled, NOT 60s
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(150, "every 3m"),
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(61, "every 2m"),
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(3601, "every 61m"),
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# Sub-minute clamps to 1m (schedule grammar minute-grained).
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(30, "every 1m"),
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(1, "every 1m"),
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])
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def test_seconds_to_schedule_rounds_up_not_down(seconds, expected):
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from services.scheduler.__main__ import _seconds_to_schedule
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assert _seconds_to_schedule(seconds) == expected, (
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f"_seconds_to_schedule({seconds}) must round UP — flooring would "
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f"make jobs fire more often than the operator configured."
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)
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