[GitHub] [spark] BryanCutler commented on a diff in pull request #36683: [SPARK-39301][SQL][PYTHON] Leverage LocalRelation and respect Arrow batch size in createDataFrame with Arrow optimization

[GitBox <gi...@apache.org>]

BryanCutler commented on code in PR #36683:
URL: https://github.com/apache/spark/pull/36683#discussion_r889416243


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python/pyspark/sql/pandas/conversion.py:
##########
@@ -596,7 +596,7 @@ def _create_from_pandas_with_arrow(
             ]
 
         # Slice the DataFrame to be batched
-        step = -(-len(pdf) // self.sparkContext.defaultParallelism)  # round int up
+        step = self._jconf.arrowMaxRecordsPerBatch()

Review Comment:
   I thought this was to control how many partitions were in the rdd?  Each partition could have multiple batches, and probably should be capped at `arrowMaxRecordsPerBatch`, but since it was coming from a local Pandas DataFrame already in memory, that didn't seem to be a big deal.



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sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala:
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@@ -2575,6 +2575,18 @@ object SQLConf {
       .booleanConf
       .createWithDefault(false)
 
+  val ARROW_LOCAL_RELATION_THRESHOLD =
+    buildConf("spark.sql.execution.arrow.localRelationThreshold")
+      .doc(
+        "When converting Arrow batches to Spark DataFrame, local collections are used in the " +
+          "driver side if the byte size of Arrow batches is smaller than this threshold. " +
+          "Otherwise, the Arrow batches are sent and deserialized to Spark internal rows " +
+          "in the executors.")
+      .version("3.4.0")
+      .bytesConf(ByteUnit.BYTE)
+      .checkValue(_ >= 0, "This value must be equal to or greater than 0.")
+      .createWithDefaultString("48MB")

Review Comment:
   Is this the max size of each batch or all batches together?



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