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fix: Spark Materialization Engine Cannot Infer Schema by jfw-ppi · Pull Request #5806 · feast-dev/feast · GitHub
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fix: Spark Materialization Engine Cannot Infer Schema #5806

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ntkathole merged 2 commits into from
Jan 2, 2026
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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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fix: build Spark DataFrame from Arrow with schema and empty handling(#… 
…5594)

Signed-off-by: Jacob Weinhold <29459386+jfw-ppi@users.noreply.github.com>
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@jfw-ppi @ntkathole
jfw-ppi authored and ntkathole committed Jan 2, 2026
commit 611ead0e6f5d525f58a89fb5ab9c370c462ed8f8
12 changes: 10 additions & 2 deletions 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 +81,15 @@ 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 All @@ -94,7 +103,6 @@ def execute(self, context: ExecutionContext) -> DAGValue:
},
)


class SparkAggregationNode(DAGNode):
def __init__(
self,
Expand Down