mirror of
https://github.com/GreptimeTeam/greptimedb.git
synced 2026-10-25 05:12:27 +00:00
131 lines
7.3 KiB
Python
131 lines
7.3 KiB
Python
# Copyright 2023 Greptime Team
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
"""Focused unit tests for BSS scale experiment parsing and accounting."""
|
|
|
|
import importlib.util
|
|
import sys
|
|
import unittest
|
|
from types import SimpleNamespace
|
|
from pathlib import Path
|
|
from unittest.mock import patch
|
|
|
|
|
|
SCRIPT = Path(__file__).resolve().parents[2] / ".github/scripts/bss-scale-experiment.py"
|
|
SPEC = importlib.util.spec_from_file_location("bss_scale_experiment_under_test", SCRIPT)
|
|
assert SPEC is not None and SPEC.loader is not None
|
|
experiment = importlib.util.module_from_spec(SPEC)
|
|
sys.modules[SPEC.name] = experiment
|
|
SPEC.loader.exec_module(experiment)
|
|
|
|
|
|
class BssScaleExperimentTest(unittest.TestCase):
|
|
def test_scaled_case_and_orders(self) -> None:
|
|
case = experiment.scaled_case(experiment.SOURCE_CASE.read_text(encoding="utf-8"), 50)
|
|
self.assertIn("samples_per_series = 216000", case)
|
|
self.assertIn("timeout_seconds = 3600", case)
|
|
self.assertIn("visibility_timeout_seconds = 600", case)
|
|
self.assertIn("iterations = 1", case)
|
|
self.assertIn("2024-05-30 00:00:00", case)
|
|
self.assertEqual(case.count("trigger_file_num'='10000'"), 2)
|
|
self.assertEqual(experiment.expected_rows(10), 43_200_000)
|
|
self.assertEqual(experiment.paired_orders(), [("base", "candidate"), ("candidate", "base"), ("base", "candidate")])
|
|
|
|
def test_response_rows_accepts_greptime_records_and_format_json_data(self) -> None:
|
|
records = {"code": 0, "output": [{"records": {"schema": [], "rows": [["2024-01-01 00:00:00", "1.0"], ["2024-01-01 01:00:00", 2]]}}]}
|
|
self.assertEqual(len(experiment.response_rows(records, 2)), 2)
|
|
self.assertEqual(experiment.response_rows({"code": "success", "data": [{"sum": 1.0}]}, 1), [{"sum": 1.0}])
|
|
|
|
def test_real_format_json_hourly_dict_order_and_epoch_millis(self) -> None:
|
|
rows = [{"sum(sst_float_bss.greptime_value)": 3.5, "time_window": 1_704_067_200_000},
|
|
{"sum(sst_float_bss.greptime_value)": 4.5, "time_window": 1_704_070_800_000}]
|
|
self.assertEqual(experiment.response_rows({"data": rows}, 2), rows)
|
|
rows[0]["sum(sst_float_bss.greptime_value)"] = None
|
|
with self.assertRaisesRegex(RuntimeError, "finite, non-boolean numeric sum"):
|
|
experiment.response_rows({"data": rows}, 2)
|
|
|
|
def test_response_rows_rejects_null_sum_despite_numeric_timestamp(self) -> None:
|
|
with self.assertRaisesRegex(RuntimeError, "finite, non-boolean numeric sum"):
|
|
experiment.response_rows({"data": [[1_704_067_200_000, None]]}, 1)
|
|
|
|
def test_response_rows_rejects_wrapper_null_and_error_with_output(self) -> None:
|
|
with self.assertRaisesRegex(RuntimeError, "finite, non-boolean numeric sum"):
|
|
experiment.response_rows({"output": [{"records": {"rows": [["time", None]]}}]}, 1)
|
|
with self.assertRaisesRegex(RuntimeError, "exactly one"):
|
|
experiment.response_rows({"output": [{"records": {"rows": [[1]]}}, {"records": {"rows": [[2]]}}]}, 2)
|
|
self.assertTrue(experiment.response_has_error({"code": 42, "output": [{"records": {"rows": [[1]]}}]}))
|
|
|
|
def test_reader_iteration_parser_requires_full_exact_coverage(self) -> None:
|
|
stdout = "\x1b[32mIteration 1: 42 rows in 1ms\x1b[0m\n[iter 2] 42 rows in 2ms\n"
|
|
self.assertEqual(experiment.parse_iterations(stdout, 42, 2), [1.0, 2.0])
|
|
self.assertIsNone(experiment.parse_average(stdout))
|
|
with self.assertRaisesRegex(RuntimeError, "partial"):
|
|
experiment.parse_iterations("Iteration 1: 41 rows in 1ms", 42, 1)
|
|
with self.assertRaisesRegex(RuntimeError, "do not equal"):
|
|
experiment.parse_iterations("Iteration 1: 42 rows in 1ms", 42, 2)
|
|
|
|
def test_footer_accepts_six_ssts_with_4_32m_rows(self) -> None:
|
|
files = [
|
|
{"relative_path": f"{index}.parquet", "num_rows": 720_000,
|
|
"columns": [{"column_path": "greptime_value", "encodings": ["BYTE_STREAM_SPLIT"]}]}
|
|
for index in range(6)
|
|
]
|
|
report = {"targets": [{"name": "candidate", "storage_inspection": {"summary": {
|
|
"summary": {"total_rows": 4_320_000, "file_count": 6}, "files": files}},
|
|
"read_bench": {"parquetbench": [{"command": ["parquetbench"]}], "scanbench": []}}]}
|
|
_, summary = experiment.footer_and_templates(report, "candidate", 4_320_000)
|
|
self.assertEqual(summary, {"file_count": 6, "total_rows": 4_320_000})
|
|
|
|
def test_footer_rejects_partially_bss_value_column(self) -> None:
|
|
files = [
|
|
{"relative_path": "bss.parquet", "num_rows": 2_160_000,
|
|
"columns": [{"column_path": "greptime_value", "encodings": ["BYTE_STREAM_SPLIT"]}]},
|
|
{"relative_path": "plain.parquet", "num_rows": 2_160_000,
|
|
"columns": [{"column_path": "greptime_value", "encodings": ["PLAIN"]}]},
|
|
]
|
|
report = {"targets": [{"name": "candidate", "storage_inspection": {"summary": {
|
|
"summary": {"total_rows": 4_320_000, "file_count": 2}, "files": files}},
|
|
"read_bench": {"parquetbench": [{"command": ["parquetbench"]}], "scanbench": []}}]}
|
|
with self.assertRaisesRegex(RuntimeError, "not BSS"):
|
|
experiment.footer_and_templates(report, "candidate", 4_320_000)
|
|
|
|
def test_aggregate_runs_uses_measured_average(self) -> None:
|
|
totals = experiment.aggregate_runs([{"kind": "scanbench", "native_average_ms": 0.0, "measured": {
|
|
"rows_per_iteration": 10, "wall_seconds": 2.0, "cpu_seconds": 0.5,
|
|
"average_ms_from_iterations": 3.5,
|
|
}}])
|
|
self.assertEqual(totals["scanbench"]["native_average_ms_sum"], 3.5)
|
|
|
|
def test_sql_round_uses_input_row_denominator_for_all_samples(self) -> None:
|
|
target = SimpleNamespace(name="candidate", http_port=4000)
|
|
post_result = {"response": {"data": [{"sum": 1.0}]}}
|
|
with (patch.object(experiment, "post_sql", return_value=post_result),
|
|
patch.object(experiment, "target_cpu_seconds", side_effect=[10.0, 40.0]),
|
|
patch.object(experiment.time, "perf_counter", side_effect=[1.0, 3.0])):
|
|
result = experiment.sql_round(target, {}, [("sum", "SELECT sum(value)", 1)], 100)
|
|
measurement = result["measurements"][0]
|
|
self.assertEqual(len(measurement["samples"]), 15)
|
|
self.assertEqual(measurement["block_wall_seconds"], 2.0)
|
|
self.assertEqual(measurement["cpu_ns_per_input_row"], 20_000_000.0)
|
|
|
|
def test_cpu_denominator_and_proc_parser(self) -> None:
|
|
self.assertEqual(experiment.row_denominator(4_320_000, 15), 64_800_000)
|
|
fields = ["R"] + ["0"] * 10 + ["300", "200"]
|
|
self.assertEqual(experiment.parse_proc_cpu_seconds("123 (worker) " + " ".join(fields), 100), 5.0)
|
|
self.assertEqual(experiment.command_with_iterations(["x", "--iterations", "1"], 7)[-1], "7")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|