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[SPARK-54577][PYTHON] Optimize Py4J calls in schema inference #53300

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[SPARK-54577][PYTHON] Optimize Py4J calls in schema inference #53300

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46 changes: 37 additions & 9 deletions python/pyspark/sql/session.py
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Original file line number Diff line number Diff line change
Expand Up @@ -64,7 +64,6 @@
)
from pyspark.errors.exceptions.captured import install_exception_handler
from pyspark.sql.utils import (
is_timestamp_ntz_preferred,
to_str,
try_remote_session_classmethod,
remote_only,
Expand Down Expand Up @@ -1050,10 +1049,25 @@ def _inferSchemaFromList(
errorClass="CANNOT_INFER_EMPTY_SCHEMA",
messageParameters={},
)
infer_dict_as_struct = self._jconf.inferDictAsStruct()
infer_array_from_first_element = self._jconf.legacyInferArrayTypeFromFirstElement()
infer_map_from_first_pair = self._jconf.legacyInferMapStructTypeFromFirstItem()
prefer_timestamp_ntz = is_timestamp_ntz_preferred()

(
timestampType,
inferDictAsStruct,
legacyInferArrayTypeFromFirstElement,
legacyInferMapStructTypeFromFirstItem,
) = self._jconf.getConfs(
[
"spark.sql.timestampType",
"spark.sql.pyspark.inferNestedDictAsStruct.enabled",
"spark.sql.pyspark.legacy.inferArrayTypeFromFirstElement.enabled",
"spark.sql.pyspark.legacy.inferMapTypeFromFirstPair.enabled",
]
)
prefer_timestamp_ntz = timestampType == "TIMESTAMP_NTZ"
infer_dict_as_struct = inferDictAsStruct == "true"
infer_array_from_first_element = legacyInferArrayTypeFromFirstElement == "true"
infer_map_from_first_pair = legacyInferMapStructTypeFromFirstItem == "true"

schema = reduce(
_merge_type,
(
Expand Down Expand Up @@ -1103,10 +1117,24 @@ def _inferSchema(
messageParameters={},
)

infer_dict_as_struct = self._jconf.inferDictAsStruct()
infer_array_from_first_element = self._jconf.legacyInferArrayTypeFromFirstElement()
infer_map_from_first_pair = self._jconf.legacyInferMapStructTypeFromFirstItem()
prefer_timestamp_ntz = is_timestamp_ntz_preferred()
(
timestampType,
inferDictAsStruct,
legacyInferArrayTypeFromFirstElement,
legacyInferMapStructTypeFromFirstItem,
) = self._jconf.getConfs(
[
"spark.sql.timestampType",
"spark.sql.pyspark.inferNestedDictAsStruct.enabled",
"spark.sql.pyspark.legacy.inferArrayTypeFromFirstElement.enabled",
"spark.sql.pyspark.legacy.inferMapTypeFromFirstPair.enabled",
]
)
prefer_timestamp_ntz = timestampType == "TIMESTAMP_NTZ"
infer_dict_as_struct = inferDictAsStruct == "true"
infer_array_from_first_element = legacyInferArrayTypeFromFirstElement == "true"
infer_map_from_first_pair = legacyInferMapStructTypeFromFirstItem == "true"

if samplingRatio is None:
schema = _infer_schema(
first,
Expand Down