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feat: CLI interface for validation of logged features #2718

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merged 9 commits into from
May 20, 2022
Merged

feat: CLI interface for validation of logged features #2718

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06262b1
store validation reference in registry
pyalex May 18, 2022
0e29fa3
CLI test
pyalex May 19, 2022
ff9eb50
clean function before pickle
pyalex May 19, 2022
8e7da91
ignore "too complex" lint rule
pyalex May 19, 2022
cf622ea
lazy import & correct feature status in logs
pyalex May 19, 2022
d049a61
pygments dependency
pyalex May 19, 2022
acbfe84
ttl for regular feature views
pyalex May 19, 2022
301f61e
some apidocs
pyalex May 20, 2022
14ad6cd
address comments
pyalex May 20, 2022
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lazy import & correct feature status in logs 
Signed-off-by: Oleksii Moskalenko <moskalenko.alexey@gmail.com>
  • Loading branch information
@pyalex
pyalex committed May 19, 2022
commit cf622ea5852965a4054a0af3cf1d625e596af048
7 changes: 6 additions & 1 deletion sdk/python/feast/saved_dataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,6 @@
from google.protobuf.json_format import MessageToJson

from feast.data_source import DataSource
from feast.dqm.profilers.ge_profiler import GEProfile, GEProfiler
from feast.dqm.profilers.profiler import Profile, Profiler
from feast.protos.feast.core.SavedDataset_pb2 import SavedDataset as SavedDatasetProto
from feast.protos.feast.core.SavedDataset_pb2 import SavedDatasetMeta, SavedDatasetSpec
Expand Down Expand Up @@ -252,12 +251,16 @@ def profile(self) -> Profile:
def from_proto(cls, proto: ValidationReferenceProto) -> "ValidationReference":
profiler_attr = proto.WhichOneof("profiler")
if profiler_attr == "ge_profiler":
from feast.dqm.profilers.ge_profiler import GEProfiler

profiler = GEProfiler.from_proto(proto.ge_profiler)
else:
raise RuntimeError("Unrecognized profiler")

profile_attr = proto.WhichOneof("cached_profile")
if profile_attr == "ge_profile":
from feast.dqm.profilers.ge_profiler import GEProfile

profile = GEProfile.from_proto(proto.ge_profile)
elif not profile_attr:
profile = None
Expand All @@ -274,6 +277,8 @@ def from_proto(cls, proto: ValidationReferenceProto) -> "ValidationReference":
return ref

def to_proto(self) -> ValidationReferenceProto:
from feast.dqm.profilers.ge_profiler import GEProfile, GEProfiler

proto = ValidationReferenceProto(
name=self.name,
reference_dataset_name=self.dataset_name,
Expand Down
3 changes: 2 additions & 1 deletion sdk/python/tests/integration/e2e/test_validation.py
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Expand Up @@ -16,6 +16,7 @@
LoggingConfig,
)
from feast.protos.feast.serving.ServingService_pb2 import FieldStatus
from feast.utils import make_tzaware
from feast.wait import wait_retry_backoff
from tests.integration.feature_repos.repo_configuration import (
construct_universal_feature_views,
Expand Down Expand Up @@ -334,7 +335,7 @@ def test_e2e_validation_via_cli(environment, universal_data_sources):
"current_balance": [0],
"avg_passenger_count": [0],
"lifetime_trip_count": [0],
"event_timestamp": [datetime.datetime.utcnow()],
"event_timestamp": [make_tzaware(datetime.datetime.utcnow())],
}
)
invalid_logs = prepare_logs(invalid_data, feature_service, store)
Expand Down
25 changes: 16 additions & 9 deletions sdk/python/tests/utils/logged_features.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,7 @@
from feast.errors import FeatureViewNotFoundException
from feast.feature_logging import LOG_DATE_FIELD, LOG_TIMESTAMP_FIELD, REQUEST_ID_FIELD
from feast.protos.feast.serving.ServingService_pb2 import FieldStatus
from feast.utils import make_tzaware


def prepare_logs(
Expand All @@ -28,21 +29,27 @@ def prepare_logs(
logs_df[LOG_DATE_FIELD] = logs_df[LOG_TIMESTAMP_FIELD].dt.date

for projection in feature_service.feature_view_projections:
feature_view = store.get_feature_view(projection.name)
for feature in projection.features:
source_field = (
feature.name
if feature.name in source_df.columns
else f"{projection.name_to_use()}__{feature.name}"
)
logs_df[f"{projection.name_to_use()}__{feature.name}"] = source_df[
source_field
]
logs_df[
f"{projection.name_to_use()}__{feature.name}__timestamp"
] = source_df["event_timestamp"].dt.floor("s")
logs_df[
f"{projection.name_to_use()}__{feature.name}__status"
] = FieldStatus.PRESENT
destination_field = f"{projection.name_to_use()}__{feature.name}"
logs_df[destination_field] = source_df[source_field]
logs_df[f"{destination_field}__timestamp"] = source_df[
"event_timestamp"
].dt.floor("s")
logs_df[f"{destination_field}__status"] = FieldStatus.PRESENT
if feature_view.ttl:
logs_df[f"{destination_field}__status"] = logs_df[
f"{destination_field}__status"
].mask(
source_df["event_timestamp"]
< (make_tzaware(datetime.datetime.utcnow()) - feature_view.ttl),
FieldStatus.OUTSIDE_MAX_AGE,
)

try:
view = store.get_feature_view(projection.name)
Expand Down