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fix: Spark Materialization Engine Cannot Infer Schema #5806

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Merged
ntkathole merged 2 commits into from
Jan 2, 2026
Merged

fix: Spark Materialization Engine Cannot Infer Schema #5806

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611ead0
fix: build Spark DataFrame from Arrow with schema and empty handling(…
jfw-ppi Jan 1, 2026
237a65d
fix: build Spark DataFrame from Arrow with schema and empty handling(…
jfw-ppi Jan 1, 2026
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10 changes: 9 additions & 1 deletion sdk/python/feast/infra/compute_engines/spark/nodes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,7 @@
import pandas as pd
from pyspark.sql import DataFrame, SparkSession, Window
from pyspark.sql import functions as F
from pyspark.sql.pandas.types import from_arrow_schema

from feast import BatchFeatureView, StreamFeatureView
from feast.aggregation import Aggregation
Expand Down Expand Up @@ -80,7 +81,14 @@ def execute(self, context: ExecutionContext) -> DAGValue:
if isinstance(retrieval_job, SparkRetrievalJob):
spark_df = cast(SparkRetrievalJob, retrieval_job).to_spark_df()
else:
spark_df = self.spark_session.createDataFrame(retrieval_job.to_arrow())
arrow_table = retrieval_job.to_arrow()
if arrow_table.num_rows == 0:
spark_schema = from_arrow_schema(arrow_table.schema)
spark_df = self.spark_session.createDataFrame(
self.spark_session.sparkContext.emptyRDD(), schema=spark_schema
)
else:
spark_df = self.spark_session.createDataFrame(arrow_table.to_pandas())

return DAGValue(
data=spark_df,
Expand Down
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