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Optimize UDF logs #370

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merged 5 commits into from
May 6, 2024
Merged

Optimize UDF logs #370

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1e4fa44
remove Pipeline object from preprocess logs
Apr 26, 2024
e6f15b2
add artifact version in logs for postprocess
Apr 30, 2024
8688bf9
use logger object in trainer UDF for compute method
May 2, 2024
1d5d035
check for NoneType logger object
May 2, 2024
31d7897
log for ack_insuff_data and add unit test
May 6, 2024
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1 change: 1 addition & 0 deletions numalogic/udfs/postprocess.py
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Original file line number Diff line number Diff line change
Expand Up @@ -207,6 +207,7 @@ def exec(self, keys: list[str], datum: Datum) -> Messages:
y_features=y_features,
y_unified=y_unified,
a_features=a_features.tolist(),
artifact_versions=payload.artifact_versions,
execution_time_secs=round(time.perf_counter() - _start_time, 4),
)

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1 change: 0 additions & 1 deletion numalogic/udfs/preprocess.py
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Expand Up @@ -179,7 +179,6 @@ def exec(self, keys: list[str], datum: Datum) -> Messages:
_increment_counter(SOURCE_COUNTER, labels=("config", *_metric_label_values))
preproc_clf = self._load_model_from_config(_conf.numalogic_conf.preprocess)
payload = replace(payload, status=Status.ARTIFACT_FOUND)
logger = logger.bind(model_from_config=preproc_clf)
try:
x_scaled = self.compute(model=preproc_clf, input_=payload.get_data())

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2 changes: 1 addition & 1 deletion numalogic/udfs/tools.py
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Expand Up @@ -295,7 +295,7 @@ def ack_insufficient_data(self, key: KEYS, uuid: str, train_records: int) -> boo
key=key,
)
return False
_struct_log.debug("Acknowledging insufficient data for the key", uuid, key)
_struct_log.debug("Acknowledging insufficient data for the key", uuid=uuid, key=key)
return True

def ack_read(
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5 changes: 4 additions & 1 deletion numalogic/udfs/trainer/_base.py
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Expand Up @@ -79,6 +79,7 @@ def compute(
trainer_transform: Optional[artifact_t] = None,
threshold_clf: Optional[artifact_t] = None,
numalogic_cfg: Optional[NumalogicConf] = None,
logger=None,
) -> dict[str, KeyedArtifact]:
"""
Train the model on the given input data.
Expand Down Expand Up @@ -128,7 +129,8 @@ def compute(

if threshold_clf:
threshold_clf.fit(train_reconerr)
_struct_log.debug("Fit data using threshold model")
if logger:
logger.debug("Fit data using threshold model")
dict_artifacts["threshold_clf"] = KeyedArtifact(
dkeys=[numalogic_cfg.threshold.name],
artifact=threshold_clf,
Expand Down Expand Up @@ -255,6 +257,7 @@ def exec(self, keys: list[str], datum: Datum) -> Messages:
trainer_transform=trainer_transform,
threshold_clf=thresh_clf,
numalogic_cfg=_conf.numalogic_conf,
logger=logger,
)
# Save artifacts

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9 changes: 9 additions & 0 deletions tests/udfs/test_trainer.py
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Expand Up @@ -425,6 +425,15 @@ def test_TrainMsgDeduplicator_exception_1(self):
train_dedup.ack_insufficient_data([*self.keys, "pipeline1"], "some-uuid", train_records=180)
self.assertLogs("RedisError")

@patch("redis.Redis.hset", Mock(side_effect=mock_druid_fetch_data()))
def test_TrainMsgDeduplicator_insufficent_data(self):
with self.assertLogs(level="DEBUG") as log:
train_dedup = TrainMsgDeduplicator(REDIS_CLIENT)
train_dedup.ack_insufficient_data(
[*self.keys, "pipeline1"], "some-uuid", train_records=180
)
self.assertLogs("Acknowledging insufficient data for the key", log.output[-1])

@patch("redis.Redis.hgetall", Mock(side_effect=RedisError))
def test_TrainMsgDeduplicator_exception_2(self):
train_dedup = TrainMsgDeduplicator(REDIS_CLIENT)
Expand Down
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