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[SPARK-27870][PYTHON][FOLLOW-UP] Rename spark.sql.pandas.udf.buffer.size to spark.sql.execution.pandas.udf.buffer.size #27450

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[SPARK-27870][PYTHON][FOLLOW-UP] Rename spark.sql.pandas.udf.buffer.size to spark.sql.execution.pandas.udf.buffer.size #27450

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2 changes: 1 addition & 1 deletion python/pyspark/sql/tests/test_pandas_udf_scalar.py
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Original file line number Diff line number Diff line change
Expand Up @@ -868,7 +868,7 @@ def test_close(batch_iter):

with QuietTest(self.sc):
with self.sql_conf({"spark.sql.execution.arrow.maxRecordsPerBatch": 1,
"spark.sql.pandas.udf.buffer.size": 4}):
"spark.sql.execution.pandas.udf.buffer.size": 4}):
self.spark.range(10).repartition(1) \
.select(test_close(col("id"))).limit(2).collect()
# wait here because python udf worker will take some time to detect
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2 changes: 1 addition & 1 deletion sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
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Expand Up @@ -1600,7 +1600,7 @@ object SQLConf {
.createWithDefault(10000)

val PANDAS_UDF_BUFFER_SIZE =
buildConf("spark.sql.pandas.udf.buffer.size")
buildConf("spark.sql.execution.pandas.udf.buffer.size")
.doc(
s"Same as ${BUFFER_SIZE} but only applies to Pandas UDF executions. If it is not set, " +
s"the fallback is ${BUFFER_SIZE}. Note that Pandas execution requires more than 4 bytes. " +
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