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ray-project--ray/python/ray/dashboard/modules/data/tests/test_data_head.py
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2026-07-13 13:17:40 +08:00

142 lines
4.0 KiB
Python

import os
import sys
import pytest
import requests
import ray
from ray.job_submission import JobSubmissionClient
from ray.tests.conftest import * # noqa
# For local testing on a Macbook, set `export TEST_ON_DARWIN=1`.
TEST_ON_DARWIN = os.environ.get("TEST_ON_DARWIN", "0") == "1"
DATA_HEAD_URLS = {"GET": "http://localhost:8265/api/data/datasets/{job_id}"}
DATA_SCHEMA = [
"state",
"progress",
"total",
"total_rows",
"ray_data_output_rows",
"ray_data_spilled_bytes",
"ray_data_current_bytes",
"ray_data_cpu_usage_cores",
"ray_data_gpu_usage_cores",
]
RESPONSE_SCHEMA = [
"dataset",
"job_id",
"start_time",
"end_time",
"operators",
] + DATA_SCHEMA
OPERATOR_SCHEMA = [
"name",
"operator",
"queued_blocks",
] + DATA_SCHEMA
@pytest.mark.skipif(
sys.platform == "darwin" and not TEST_ON_DARWIN, reason="Flaky on OSX."
)
def test_unique_operator_id(ray_start_regular_shared):
# This regression test addresses a bug caused by using a non-unique operator ID
# format. Specifically, the third operator's name is limit11 with the ID limit112,
# while the thirteenth operator's name is limit1 with the same ID limit112, leading
# to a collision.
ds = ray.data.range(100, override_num_blocks=20).limit(11) # 3 operators
for i in range(11): # 11 more operators
ds = ds.limit(1)
ds._set_name("unique_operator_id_test")
ds.materialize()
client = JobSubmissionClient()
jobs = client.list_jobs()
assert len(jobs) == 1, jobs
job_id = jobs[0].job_id
data = requests.get(DATA_HEAD_URLS["GET"].format(job_id=job_id)).json()
datasets = [
dataset
for dataset in data["datasets"]
if dataset["dataset"].startswith("unique_operator_id_test")
]
assert len(datasets) == 1
dataset = datasets[0]
operators = dataset["operators"]
assert len(operators) == 3 # Should be 3 because of limiter operator fusion.
@pytest.mark.skipif(
sys.platform == "darwin" and not TEST_ON_DARWIN, reason="Flaky on OSX."
)
def test_get_datasets(ray_start_regular_shared):
ds = ray.data.range(100, override_num_blocks=20).map_batches(lambda x: x)
ds.set_name("data_head_test")
ds.materialize()
client = JobSubmissionClient()
jobs = client.list_jobs()
assert len(jobs) == 1, jobs
job_id = jobs[0].job_id
data = requests.get(DATA_HEAD_URLS["GET"].format(job_id=job_id)).json()
datasets = [
dataset
for dataset in data["datasets"]
if dataset["dataset"].startswith("data_head_test")
]
assert len(datasets) == 1
assert sorted(datasets[0].keys()) == sorted(RESPONSE_SCHEMA)
dataset = datasets[0]
assert dataset["dataset"].startswith("data_head_test")
assert dataset["job_id"] == job_id
assert dataset["state"] == "FINISHED"
assert dataset["end_time"] is not None
operators = dataset["operators"]
assert len(operators) == 2
op0 = operators[0]
op1 = operators[1]
assert sorted(op0.keys()) == sorted(OPERATOR_SCHEMA)
assert sorted(op1.keys()) == sorted(OPERATOR_SCHEMA)
assert {
"operator": "Input_0",
"name": "Input",
"state": "FINISHED",
"progress": 20,
"total": 20,
}.items() <= op0.items()
assert {
"operator": "ReadRange->MapBatches(<lambda>)_1",
"name": "ReadRange->MapBatches(<lambda>)",
"state": "FINISHED",
"progress": 20,
"total": 20,
}.items() <= op1.items()
ds._set_name("another_data_head_test")
ds.map_batches(lambda x: x).materialize()
data = requests.get(DATA_HEAD_URLS["GET"].format(job_id=job_id)).json()
dataset = [
dataset
for dataset in data["datasets"]
if dataset["dataset"].startswith("another_data_head_test")
][0]
assert dataset["dataset"].startswith("another_data_head_test")
assert dataset["job_id"] == job_id
assert dataset["state"] == "FINISHED"
assert dataset["end_time"] is not None
if __name__ == "__main__":
sys.exit(pytest.main(["-vv", __file__]))