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Posted to reviews@spark.apache.org by "viirya (via GitHub)" <gi...@apache.org> on 2026/03/31 21:48:05 UTC
[PR] [SPARK-xxxxx][SQL] Skip ColumnarToRow for Arrow-backed input to Python UDFs [spark]
viirya opened a new pull request, #55120:
URL: https://github.com/apache/spark/pull/55120
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Re: [PR] [SPARK-56350][SQL] Skip ColumnarToRow for Arrow-backed input to Python UDFs [spark]
Posted by "viirya (via GitHub)" <gi...@apache.org>.
viirya commented on code in PR #55120:
URL: https://github.com/apache/spark/pull/55120#discussion_r3053688706
##########
python/pyspark/sql/tests/pandas/bench_arrow_columnar_udf.py:
##########
@@ -0,0 +1,178 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""
+Benchmark: Arrow columnar vs row-based input for scalar Arrow Python UDFs.
+
+Compares end-to-end execution time of applying a scalar pandas_udf to data
+from two sources:
+
+1. ArrowBackedDataSourceV2 -- produces ColumnarBatch with ArrowColumnVector.
+ ArrowEvalPythonExec extracts Arrow FieldVectors directly via the columnar
+ path (no ColumnarToRow conversion).
+
+2. spark.range() -- produces row-based data.
+ ArrowEvalPythonExec uses the standard path: InternalRow -> ArrowWriter.
+
+The UDF does minimal computation (addition) so the benchmark isolates
+the data transfer overhead between JVM and Python.
+
+Usage:
+ cd $SPARK_HOME
+ python python/pyspark/sql/tests/pandas/bench_arrow_columnar_udf.py \
+ [--rows N] [--iterations N] [--partitions N]
Review Comment:
| Scenario | Rows | String Length | UDF | Sink | Arrow Columnar (ms) | Row-based (ms) | Speedup |
|---|---|---|---|---|---|---|---|
| string concat | 2M | 200 chars | `name + data` | noop | 2086 | 2401 | **1.15x** |
| string identity | 1M | 1000 chars | `return data` | noop | 4506 | 4839 | **1.07x** |
| string identity | 2M | 200 chars | `return data` | noop | 2118 | 2324 | **1.10x** |
| string identity | 10M | 100 chars | `return data` | noop | 6067 | 7124 | **1.17x** |
| string identity | 20M | 100 chars | `return data` | noop | 11917 | 14106 | **1.18x** |
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Re: [PR] [SPARK-56350][SQL] Skip ColumnarToRow for Arrow-backed input to Python UDFs [spark]
Posted by "viirya (via GitHub)" <gi...@apache.org>.
viirya commented on code in PR #55120:
URL: https://github.com/apache/spark/pull/55120#discussion_r3053688706
##########
python/pyspark/sql/tests/pandas/bench_arrow_columnar_udf.py:
##########
@@ -0,0 +1,178 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""
+Benchmark: Arrow columnar vs row-based input for scalar Arrow Python UDFs.
+
+Compares end-to-end execution time of applying a scalar pandas_udf to data
+from two sources:
+
+1. ArrowBackedDataSourceV2 -- produces ColumnarBatch with ArrowColumnVector.
+ ArrowEvalPythonExec extracts Arrow FieldVectors directly via the columnar
+ path (no ColumnarToRow conversion).
+
+2. spark.range() -- produces row-based data.
+ ArrowEvalPythonExec uses the standard path: InternalRow -> ArrowWriter.
+
+The UDF does minimal computation (addition) so the benchmark isolates
+the data transfer overhead between JVM and Python.
+
+Usage:
+ cd $SPARK_HOME
+ python python/pyspark/sql/tests/pandas/bench_arrow_columnar_udf.py \
+ [--rows N] [--iterations N] [--partitions N]
Review Comment:
| Scenario | Rows | String Length | UDF | Sink | Arrow Columnar (ms) | Row-based (ms) | Speedup |
|---|---|---|---|---|---|---|---|
| string concat | 2M | 200 chars | `name + data` | noop | 2086 | 2401 | **1.15x** |
| string identity | 2M | 200 chars | `return data` | noop | 2118 | 2324 | **1.10x** |
| string identity | 1M | 1000 chars | `return data` | noop | 4506 | 4839 | **1.07x** |
| string identity | 10M | 100 chars | `return data` | noop | 6067 | 7124 | **1.17x** |
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Re: [PR] [SPARK-xxxxx][SQL] Skip ColumnarToRow for Arrow-backed input to Python UDFs [spark]
Posted by "viirya (via GitHub)" <gi...@apache.org>.
viirya commented on PR #55120:
URL: https://github.com/apache/spark/pull/55120#issuecomment-4166078763
> Please create and use a JIRA ID in the PR title before converting back from `Draft` status~
Okay. Thank you @dongjoon-hyun
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Re: [PR] [SPARK-56350][SQL] Skip ColumnarToRow for Arrow-backed input to Python UDFs [spark]
Posted by "dongjoon-hyun (via GitHub)" <gi...@apache.org>.
dongjoon-hyun commented on PR #55120:
URL: https://github.com/apache/spark/pull/55120#issuecomment-4209180362
Oh, I didn't notice this is still under developing.
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Re: [PR] [SPARK-56350][SQL] Skip ColumnarToRow for Arrow-backed input to Python UDFs [spark]
Posted by "viirya (via GitHub)" <gi...@apache.org>.
viirya commented on code in PR #55120:
URL: https://github.com/apache/spark/pull/55120#discussion_r3053691822
##########
python/pyspark/sql/tests/pandas/bench_arrow_columnar_udf.py:
##########
@@ -0,0 +1,178 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""
+Benchmark: Arrow columnar vs row-based input for scalar Arrow Python UDFs.
+
+Compares end-to-end execution time of applying a scalar pandas_udf to data
+from two sources:
+
+1. ArrowBackedDataSourceV2 -- produces ColumnarBatch with ArrowColumnVector.
+ ArrowEvalPythonExec extracts Arrow FieldVectors directly via the columnar
+ path (no ColumnarToRow conversion).
+
+2. spark.range() -- produces row-based data.
+ ArrowEvalPythonExec uses the standard path: InternalRow -> ArrowWriter.
+
+The UDF does minimal computation (addition) so the benchmark isolates
+the data transfer overhead between JVM and Python.
+
+Usage:
+ cd $SPARK_HOME
+ python python/pyspark/sql/tests/pandas/bench_arrow_columnar_udf.py \
+ [--rows N] [--iterations N] [--partitions N]
Review Comment:
Arrow columnar path:
```
*(1) Project [id#0, name#1, value#2, data#3, pythonUDF0#6 AS identity_udf(data)#5]
+- ArrowEvalPython [identity_udf(data#3)#4], [pythonUDF0#6], 200
+- BatchScan ArrowBackedTestTable[id#0, name#1, value#2, data#3]
```
Row-based path:
```
*(2) Project [id#14, name#15, value#16, data#17, pythonUDF0#20 AS identity_udf(data)#19]
+- ArrowEvalPython [identity_udf(data#17)#18], [pythonUDF0#20], 200
+- *(1) ColumnarToRow
+- BatchScan ArrowBackedTestTable[id#14, name#15, value#16, data#17]
```
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Re: [PR] [SPARK-56350][SQL] Skip ColumnarToRow for Arrow-backed input to Python UDFs [spark]
Posted by "viirya (via GitHub)" <gi...@apache.org>.
viirya commented on PR #55120:
URL: https://github.com/apache/spark/pull/55120#issuecomment-4215775862
Thank you @dongjoon-hyun. I updated the PR description with the benchmark result table.
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Re: [PR] [SPARK-56350][SQL] Skip ColumnarToRow for Arrow-backed input to Python UDFs [spark]
Posted by "FelixYBW (via GitHub)" <gi...@apache.org>.
FelixYBW commented on PR #55120:
URL: https://github.com/apache/spark/pull/55120#issuecomment-4711880645
FYI, @viirya
https://issues.apache.org/jira/browse/SPARK-57468
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Re: [PR] [SPARK-xxxxx][SQL] Skip ColumnarToRow for Arrow-backed input to Python UDFs [spark]
Posted by "dongjoon-hyun (via GitHub)" <gi...@apache.org>.
dongjoon-hyun commented on PR #55120:
URL: https://github.com/apache/spark/pull/55120#issuecomment-4165927154
Please create and use a JIRA ID in the PR title before converting back from `Draft` status~
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Re: [PR] [SPARK-56350][SQL] Skip ColumnarToRow for Arrow-backed input to Python UDFs [spark]
Posted by "viirya (via GitHub)" <gi...@apache.org>.
viirya commented on PR #55120:
URL: https://github.com/apache/spark/pull/55120#issuecomment-4209245740
> Oh, I didn't notice this is still under developing.
I was unable to run benchmark due to some constraints on local environment. I found a way to overcome it and ran the benchmark. These changes are adjustment to benchmark related stuffs + a new config to control this new behavior. They are just for making the benchmark able to measure the difference correctly.
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Re: [PR] [SPARK-56350][SQL] Skip ColumnarToRow for Arrow-backed input to Python UDFs [spark]
Posted by "dongjoon-hyun (via GitHub)" <gi...@apache.org>.
dongjoon-hyun commented on PR #55120:
URL: https://github.com/apache/spark/pull/55120#issuecomment-4223904508
Thank you, @viirya . Merged to master.
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Re: [PR] [SPARK-56350][SQL] Skip ColumnarToRow for Arrow-backed input to Python UDFs [spark]
Posted by "viirya (via GitHub)" <gi...@apache.org>.
viirya commented on PR #55120:
URL: https://github.com/apache/spark/pull/55120#issuecomment-4225505861
Thank you @dongjoon-hyun
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Re: [PR] [SPARK-xxxxx][SQL] Skip ColumnarToRow for Arrow-backed input to Python UDFs [spark]
Posted by "viirya (via GitHub)" <gi...@apache.org>.
viirya commented on code in PR #55120:
URL: https://github.com/apache/spark/pull/55120#discussion_r3018648091
##########
python/pyspark/sql/tests/pandas/bench_arrow_columnar_udf.py:
##########
@@ -0,0 +1,178 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""
+Benchmark: Arrow columnar vs row-based input for scalar Arrow Python UDFs.
+
+Compares end-to-end execution time of applying a scalar pandas_udf to data
+from two sources:
+
+1. ArrowBackedDataSourceV2 -- produces ColumnarBatch with ArrowColumnVector.
+ ArrowEvalPythonExec extracts Arrow FieldVectors directly via the columnar
+ path (no ColumnarToRow conversion).
+
+2. spark.range() -- produces row-based data.
+ ArrowEvalPythonExec uses the standard path: InternalRow -> ArrowWriter.
+
+The UDF does minimal computation (addition) so the benchmark isolates
+the data transfer overhead between JVM and Python.
+
+Usage:
+ cd $SPARK_HOME
+ python python/pyspark/sql/tests/pandas/bench_arrow_columnar_udf.py \
+ [--rows N] [--iterations N] [--partitions N]
Review Comment:
Due to some constraints on local dev environment for now, I cannot build Spark locally to run this benchmark. I will update the result once the constraints are removed.
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Re: [PR] [SPARK-56350][SQL] Skip ColumnarToRow for Arrow-backed input to Python UDFs [spark]
Posted by "viirya (via GitHub)" <gi...@apache.org>.
viirya commented on code in PR #55120:
URL: https://github.com/apache/spark/pull/55120#discussion_r3053688706
##########
python/pyspark/sql/tests/pandas/bench_arrow_columnar_udf.py:
##########
@@ -0,0 +1,178 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""
+Benchmark: Arrow columnar vs row-based input for scalar Arrow Python UDFs.
+
+Compares end-to-end execution time of applying a scalar pandas_udf to data
+from two sources:
+
+1. ArrowBackedDataSourceV2 -- produces ColumnarBatch with ArrowColumnVector.
+ ArrowEvalPythonExec extracts Arrow FieldVectors directly via the columnar
+ path (no ColumnarToRow conversion).
+
+2. spark.range() -- produces row-based data.
+ ArrowEvalPythonExec uses the standard path: InternalRow -> ArrowWriter.
+
+The UDF does minimal computation (addition) so the benchmark isolates
+the data transfer overhead between JVM and Python.
+
+Usage:
+ cd $SPARK_HOME
+ python python/pyspark/sql/tests/pandas/bench_arrow_columnar_udf.py \
+ [--rows N] [--iterations N] [--partitions N]
Review Comment:
| Scenario | Rows | String Length | UDF | Sink | Arrow Columnar (ms) | Row-based (ms) | Speedup |
|---|---|---|---|---|---|---|---|
| string concat | 2M | 200 chars | `name + data` | noop | 2086 | 2401 | **1.15x** |
| string identity | 2M | 200 chars | `return data` | noop | 2118 | 2324 | **1.10x** |
| string identity | 1M | 1000 chars | `return data` | noop | 4506 | 4839 | **1.07x** |
| string identity | 10M | 100 chars | `return data` | noop | 6067 | 7124 | **1.17x** |
| string identity | 20M | 100 chars | `return data` | noop | 11917 | 14106 | **1.18x** |
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Re: [PR] [SPARK-56350][SQL] Skip ColumnarToRow for Arrow-backed input to Python UDFs [spark]
Posted by "dongjoon-hyun (via GitHub)" <gi...@apache.org>.
dongjoon-hyun closed pull request #55120: [SPARK-56350][SQL] Skip ColumnarToRow for Arrow-backed input to Python UDFs
URL: https://github.com/apache/spark/pull/55120
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Re: [PR] [SPARK-56350][SQL] Skip ColumnarToRow for Arrow-backed input to Python UDFs [spark]
Posted by "viirya (via GitHub)" <gi...@apache.org>.
viirya commented on PR #55120:
URL: https://github.com/apache/spark/pull/55120#issuecomment-4211853276
Restored the CIs broken due to change to ArrowBackedDataSourceV2 used both in benchmark and in test code.
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