-
Notifications
You must be signed in to change notification settings - Fork 1.3k
Expand file tree
/
Copy pathtest_nodes.py
More file actions
425 lines (368 loc) · 13.8 KB
/
test_nodes.py
File metadata and controls
425 lines (368 loc) · 13.8 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
import os
from datetime import datetime, timedelta
from unittest.mock import patch
import pandas as pd
import pytest
import ray
from feast.aggregation import Aggregation
from feast.infra.compute_engines.dag.context import ColumnInfo
from feast.infra.compute_engines.dag.model import DAGFormat
from feast.infra.compute_engines.dag.node import DAGNode
from feast.infra.compute_engines.dag.value import DAGValue
from feast.infra.compute_engines.ray.config import RayComputeEngineConfig
from feast.infra.compute_engines.ray.nodes import (
RayAggregationNode,
RayDedupNode,
RayFilterNode,
RayJoinNode,
RayReadNode,
RayTransformationNode,
)
from feast.infra.ray_initializer import (
RayConfigManager,
RayExecutionMode,
ensure_ray_initialized,
get_ray_wrapper,
)
class DummyInputNode(DAGNode):
def __init__(self, name, output):
super().__init__(name)
self._output = output
def execute(self, context):
return self._output
class DummyFeatureView:
name = "dummy"
online = False
offline = False
class DummySource:
pass
class DummyRetrievalJob:
def __init__(self, ray_dataset):
self._ray_dataset = ray_dataset
def to_ray_dataset(self):
return self._ray_dataset
@pytest.fixture(scope="session")
def ray_session():
"""Initialize Ray session for testing."""
if not ray.is_initialized():
ray.init(num_cpus=2, ignore_reinit_error=True, include_dashboard=False)
yield ray
ray.shutdown()
@pytest.fixture
def ray_config():
"""Create Ray compute engine configuration for testing."""
return RayComputeEngineConfig(
type="ray.engine",
max_workers=2,
enable_optimization=True,
broadcast_join_threshold_mb=50,
target_partition_size_mb=32,
)
@pytest.fixture
def mock_context():
class DummyOfflineStore:
def offline_write_batch(self, *args, **kwargs):
pass
class DummyContext:
def __init__(self):
self.registry = None
self.store = None
self.project = "test_project"
self.entity_data = None
self.config = None
self.node_outputs = {}
self.offline_store = DummyOfflineStore()
return DummyContext()
@pytest.fixture
def sample_data():
"""Create sample data for testing."""
return pd.DataFrame(
[
{
"driver_id": 1001,
"event_timestamp": datetime.now() - timedelta(hours=1),
"created": datetime.now() - timedelta(hours=2),
"conv_rate": 0.8,
"acc_rate": 0.5,
"avg_daily_trips": 15,
},
{
"driver_id": 1002,
"event_timestamp": datetime.now() - timedelta(hours=2),
"created": datetime.now() - timedelta(hours=3),
"conv_rate": 0.7,
"acc_rate": 0.4,
"avg_daily_trips": 12,
},
{
"driver_id": 1001,
"event_timestamp": datetime.now() - timedelta(hours=3),
"created": datetime.now() - timedelta(hours=4),
"conv_rate": 0.75,
"acc_rate": 0.9,
"avg_daily_trips": 14,
},
]
)
@pytest.fixture
def column_info():
"""Create a sample ColumnInfo for testing Ray nodes."""
return ColumnInfo(
join_keys=["driver_id"],
feature_cols=["conv_rate", "acc_rate", "avg_daily_trips"],
ts_col="event_timestamp",
created_ts_col="created",
field_mapping=None,
)
def test_ray_read_node(ray_session, ray_config, mock_context, sample_data, column_info):
"""Test RayReadNode functionality."""
ray_dataset = ray.data.from_pandas(sample_data)
mock_source = DummySource()
node = RayReadNode(
name="read",
source=mock_source,
column_info=column_info,
config=ray_config,
)
mock_context.registry = None
mock_context.store = None
mock_context.offline_store = None
mock_retrieval_job = DummyRetrievalJob(ray_dataset)
import feast.infra.compute_engines.ray.nodes as ray_nodes
ray_nodes.create_offline_store_retrieval_job = lambda **kwargs: mock_retrieval_job
result = node.execute(mock_context)
assert isinstance(result, DAGValue)
assert result.format == DAGFormat.RAY
result_df = result.data.to_pandas()
assert len(result_df) == 3
assert "driver_id" in result_df.columns
assert "conv_rate" in result_df.columns
def test_ray_aggregation_node(
ray_session, ray_config, mock_context, sample_data, column_info
):
"""Test RayAggregationNode functionality."""
ray_dataset = ray.data.from_pandas(sample_data)
input_value = DAGValue(data=ray_dataset, format=DAGFormat.RAY)
dummy_node = DummyInputNode("input_node", input_value)
node = RayAggregationNode(
name="aggregation",
aggregations=[
Aggregation(column="conv_rate", function="sum"),
Aggregation(column="acc_rate", function="avg"),
],
group_by_keys=["driver_id"],
timestamp_col="event_timestamp",
config=ray_config,
)
node.add_input(dummy_node)
mock_context.node_outputs = {"input_node": input_value}
result = node.execute(mock_context)
assert isinstance(result, DAGValue)
assert result.format == DAGFormat.RAY
result_df = result.data.to_pandas()
assert len(result_df) == 2
assert "driver_id" in result_df.columns
assert "sum_conv_rate" in result_df.columns
assert "avg_acc_rate" in result_df.columns
def test_ray_join_node(ray_session, ray_config, mock_context, sample_data, column_info):
"""Test RayJoinNode functionality."""
entity_data = pd.DataFrame(
[
{"driver_id": 1001, "event_timestamp": datetime.now()},
{"driver_id": 1002, "event_timestamp": datetime.now()},
]
)
feature_dataset = ray.data.from_pandas(sample_data)
feature_value = DAGValue(data=feature_dataset, format=DAGFormat.RAY)
dummy_node = DummyInputNode("feature_node", feature_value)
node = RayJoinNode(
name="join",
column_info=column_info,
config=ray_config,
)
node.add_input(dummy_node)
mock_context.node_outputs = {"feature_node": feature_value}
mock_context.entity_df = entity_data
result = node.execute(mock_context)
assert isinstance(result, DAGValue)
assert result.format == DAGFormat.RAY
result_df = result.data.to_pandas()
assert len(result_df) >= 2
assert "driver_id" in result_df.columns
def test_ray_transformation_node(
ray_session, ray_config, mock_context, sample_data, column_info
):
"""Test RayTransformationNode functionality."""
ray_dataset = ray.data.from_pandas(sample_data)
def transform_feature(df: pd.DataFrame) -> pd.DataFrame:
df["conv_rate_doubled"] = df["conv_rate"] * 2
return df
input_value = DAGValue(data=ray_dataset, format=DAGFormat.RAY)
dummy_node = DummyInputNode("input_node", input_value)
node = RayTransformationNode(
name="transformation",
transformation=transform_feature,
config=ray_config,
)
node.add_input(dummy_node)
mock_context.node_outputs = {"input_node": input_value}
result = node.execute(mock_context)
assert isinstance(result, DAGValue)
assert result.format == DAGFormat.RAY
result_df = result.data.to_pandas()
assert len(result_df) == 3
assert "conv_rate_doubled" in result_df.columns
assert (
result_df["conv_rate_doubled"].iloc[0] == sample_data["conv_rate"].iloc[0] * 2
)
def test_ray_filter_node(
ray_session, ray_config, mock_context, sample_data, column_info
):
"""Test RayFilterNode functionality."""
ray_dataset = ray.data.from_pandas(sample_data)
input_value = DAGValue(data=ray_dataset, format=DAGFormat.RAY)
dummy_node = DummyInputNode("input_node", input_value)
node = RayFilterNode(
name="filter",
column_info=column_info,
config=ray_config,
ttl=timedelta(hours=2),
filter_condition=None,
)
node.add_input(dummy_node)
mock_context.node_outputs = {"input_node": input_value}
result = node.execute(mock_context)
assert isinstance(result, DAGValue)
assert result.format == DAGFormat.RAY
result_df = result.data.to_pandas()
assert len(result_df) <= 3
assert "event_timestamp" in result_df.columns
def test_ray_dedup_node(
ray_session, ray_config, mock_context, sample_data, column_info
):
"""Test RayDedupNode functionality."""
duplicated_data = pd.concat([sample_data, sample_data.iloc[:1]], ignore_index=True)
ray_dataset = ray.data.from_pandas(duplicated_data)
input_value = DAGValue(data=ray_dataset, format=DAGFormat.RAY)
dummy_node = DummyInputNode("input_node", input_value)
node = RayDedupNode(
name="dedup",
column_info=column_info,
config=ray_config,
)
node.add_input(dummy_node)
mock_context.node_outputs = {"input_node": input_value}
result = node.execute(mock_context)
assert isinstance(result, DAGValue)
assert result.format == DAGFormat.RAY
result_df = result.data.to_pandas()
assert len(result_df) == 2 # Should remove the duplicate row
assert "driver_id" in result_df.columns
def test_ray_config_validation():
"""Test Ray configuration validation."""
# Test valid configuration
config = RayComputeEngineConfig(
type="ray.engine",
max_workers=4,
enable_optimization=True,
broadcast_join_threshold_mb=100,
target_partition_size_mb=64,
window_size_for_joins="30min",
)
assert config.type == "ray.engine"
assert config.max_workers == 4
assert config.window_size_timedelta == timedelta(minutes=30)
# Test window size parsing
config_hours = RayComputeEngineConfig(window_size_for_joins="2H")
assert config_hours.window_size_timedelta == timedelta(hours=2)
config_seconds = RayComputeEngineConfig(window_size_for_joins="30s")
assert config_seconds.window_size_timedelta == timedelta(seconds=30)
# Test invalid window size defaults to 1 hour
config_invalid = RayComputeEngineConfig(window_size_for_joins="invalid")
assert config_invalid.window_size_timedelta == timedelta(hours=1)
def test_ray_initialization_and_kuberay_modes():
"""
Comprehensive test for Ray initialization modes and KubeRay configuration.
Tests: Mode detection (LOCAL/REMOTE/KUBERAY), config parsing, defaults,
environment variables, mode precedence, and Ray wrapper instantiation.
"""
# Test LOCAL mode (default)
config_local = RayComputeEngineConfig()
assert (
RayConfigManager(config_local).determine_execution_mode()
== RayExecutionMode.LOCAL
)
# Test REMOTE mode
config_remote = RayComputeEngineConfig(ray_address="ray://localhost:10001")
manager_remote = RayConfigManager(config_remote)
assert manager_remote.determine_execution_mode() == RayExecutionMode.REMOTE
# Test execution mode caching
assert manager_remote.determine_execution_mode() == RayExecutionMode.REMOTE
# Test KUBERAY mode with full config
config_kuberay = RayComputeEngineConfig(
use_kuberay=True,
kuberay_conf={
"cluster_name": "feast-cluster",
"namespace": "feast-system",
"auth_token": "test-token",
"auth_server": "https://api.example.com",
"skip_tls": True,
},
)
manager_kuberay = RayConfigManager(config_kuberay)
assert manager_kuberay.determine_execution_mode() == RayExecutionMode.KUBERAY
kuberay_config = manager_kuberay.get_kuberay_config()
assert kuberay_config["cluster_name"] == "feast-cluster"
assert kuberay_config["namespace"] == "feast-system"
assert kuberay_config["auth_token"] == "test-token"
assert kuberay_config["skip_tls"] is True
# Test KubeRay defaults
config_defaults = RayComputeEngineConfig(
use_kuberay=True, kuberay_conf={"cluster_name": "test-cluster"}
)
defaults_config = RayConfigManager(config_defaults).get_kuberay_config()
assert defaults_config["namespace"] == "default"
assert defaults_config["skip_tls"] is False
# Test mode precedence - KUBERAY overrides REMOTE
config_precedence = RayComputeEngineConfig(
ray_address="ray://localhost:10001",
use_kuberay=True,
kuberay_conf={"cluster_name": "test-cluster"},
)
assert (
RayConfigManager(config_precedence).determine_execution_mode()
== RayExecutionMode.KUBERAY
)
# Test environment variable support
with patch.dict(
os.environ,
{
"FEAST_RAY_CLUSTER_NAME": "env-cluster",
"FEAST_RAY_NAMESPACE": "env-namespace",
"FEAST_RAY_AUTH_TOKEN": "env-token",
},
):
env_config = RayConfigManager(
RayComputeEngineConfig(use_kuberay=True, kuberay_conf={})
).get_kuberay_config()
assert env_config["cluster_name"] == "env-cluster"
assert env_config["namespace"] == "env-namespace"
assert env_config["auth_token"] == "env-token"
# Test Ray wrapper instantiation
from feast.infra.ray_initializer import StandardRayWrapper
wrapper = get_ray_wrapper()
assert isinstance(wrapper, StandardRayWrapper)
config_custom = RayComputeEngineConfig(
enable_ray_logging=True,
max_workers=4,
broadcast_join_threshold_mb=200,
ray_conf={"num_cpus": 4},
)
assert config_custom.enable_ray_logging is True
assert config_custom.max_workers == 4
assert config_custom.broadcast_join_threshold_mb == 200
assert config_custom.ray_conf["num_cpus"] == 4
with patch("feast.infra.ray_initializer.ray") as mock_ray:
mock_ray.is_initialized.return_value = True
ensure_ray_initialized(config_local)
mock_ray.init.assert_not_called()