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fix: Revert mypy config #3952

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Merged
shuchu merged 5 commits into from
Feb 20, 2024
Merged

fix: Revert mypy config #3952

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6e05cf2
fetch_arrow_all returns empty table
bushwhackr Feb 16, 2024
04de64c
fix spark_kafka_processor typing errors
bushwhackr Feb 16, 2024
696d5d6
fix correct return type
bushwhackr Feb 16, 2024
bbcce21
revert _to_arrow_internal
bushwhackr Feb 16, 2024
1aac1e9
revert kafkaStreamProcessor changes, change base type instead
bushwhackr Feb 16, 2024
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fix spark_kafka_processor typing errors 
Signed-off-by: Chester Ong <chester.ong.ch@gmail.com>
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@bushwhackr
bushwhackr committed Feb 16, 2024
commit 04de64ce7033108d33844442c2561400c2b45f06
11 changes: 3 additions & 8 deletions sdk/python/feast/infra/contrib/spark_kafka_processor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,6 @@
from pyspark.sql import DataFrame, SparkSession
from pyspark.sql.avro.functions import from_avro
from pyspark.sql.functions import col, from_json
from pyspark.sql.streaming import StreamingQuery

from feast.data_format import AvroFormat, JsonFormat
from feast.data_source import KafkaSource, PushMode
Expand Down Expand Up @@ -68,13 +67,10 @@ def __init__(
# data_source type has been checked to be an instance of KafkaSource.
self.data_source: KafkaSource = self.data_source # type: ignore

def ingest_stream_feature_view(
self, to: PushMode = PushMode.ONLINE
) -> StreamingQuery:
def ingest_stream_feature_view(self, to: PushMode = PushMode.ONLINE) -> None:
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ingested_stream_df = self._ingest_stream_data()
transformed_df = self._construct_transformation_plan(ingested_stream_df)
online_store_query = self._write_stream_data(transformed_df, to)
return online_store_query
self._write_stream_data(transformed_df, to)

# In the line 64 of __init__(), the "data_source" is assigned a stream_source (and has to be KafkaSource as in line 40).
@no_type_check
Expand Down Expand Up @@ -131,7 +127,7 @@ def _ingest_stream_data(self) -> StreamTable:
def _construct_transformation_plan(self, df: StreamTable) -> StreamTable:
return self.sfv.udf.__call__(df) if self.sfv.udf else df

def _write_stream_data(self, df: StreamTable, to: PushMode) -> StreamingQuery:
def _write_stream_data(self, df: StreamTable, to: PushMode) -> None:
# Validation occurs at the fs.write_to_online_store() phase against the stream feature view schema.
def batch_write(row: DataFrame, batch_id: int):
rows: pd.DataFrame = row.toPandas()
Expand Down Expand Up @@ -170,4 +166,3 @@ def batch_write(row: DataFrame, batch_id: int):
)

query.awaitTermination(timeout=self.query_timeout)
return query