Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/19246#discussion_r139874732
--- Diff: python/pyspark/sql/types.py ---
@@ -410,6 +410,24 @@ def __init__(self, name, dataType, nullable=True,
metadata=None):
self.dataType = dataType
self.nullable = nullable
self.metadata = metadata or {}
+ self.needConversion = dataType.needConversion
+ self.toInternal = dataType.toInternal
+ self.fromInternal = dataType.fromInternal
+
+ def __getstate__(self):
+ """Return state values to be pickled."""
+ return (self.name, self.dataType, self.nullable, self.metadata)
+
+ def __setstate__(self, state):
+ """Restore state from the unpickled state values."""
+ name, dataType, nullable, metadata = state
+ self.name = name
+ self.dataType = dataType
+ self.nullable = nullable
+ self.metadata = metadata
+ self.needConversion = dataType.needConversion
--- End diff --
At the current master,
https://github.com/apache/spark/commit/718bbc939037929ef5b8f4b4fe10aadfbab4408e
**Before**
```
./build/mvn -DskipTests -Psparkr -Phive -Phive-thriftserver clean package
find . -name "*.pyc" -exec rm -f {} \;
sync && sudo purge
./bin/pyspark --conf spark.python.profile=true
```
```python
df = spark.range(10000000).selectExpr("id as id0", "id as id1", "id as
id2", "id as id3", "id as id4", "id as id5", "id as id6", "id as id7", "id as
id8", "id as id9", "struct(id) as s").cache()
df.count()
df.rdd.map(lambda x: x).count()
sc.show_profiles()
```
```
============================================================
Profile of RDD<id=13>
============================================================
220158736 function calls (210148475 primitive calls) in 379.599
seconds
Ordered by: internal time, cumulative time
ncalls tottime percall cumtime percall filename:lineno(function)
30000000/20000000 88.015 0.000 263.471 0.000
types.py:623(fromInternal)
20000000 83.744 0.000 130.714 0.000 types.py:1421(_create_row)
683 62.466 0.091 358.079 0.524 {cPickle.loads}
20000000 21.786 0.000 285.257 0.000 types.py:1418(<lambda>)
10000000 18.998 0.000 18.998 0.000 {zip}
20000000 16.783 0.000 32.260 0.000 types.py:1469(__new__)
30045761 16.197 0.000 16.197 0.000 {isinstance}
20000000 15.477 0.000 15.477 0.000 {built-in method __new__ of
type object at 0x10db7b428}
20000000 14.710 0.000 14.710 0.000 types.py:1553(__setattr__)
10000008 14.361 0.000 377.376 0.000 rdd.py:1040(<genexpr>)
20000000 9.984 0.000 9.984 0.000
types.py:1417(_create_row_inbound_converter)
10000000 9.579 0.000 19.590 0.000 types.py:440(fromInternal)
...
```
**After**
```
curl -O
https://patch-diff.githubusercontent.com/raw/apache/spark/pull/19246.patch
git apply 19246.patch
git diff
./build/mvn -DskipTests -Psparkr -Phive -Phive-thriftserver clean package
find . -name "*.pyc" -exec rm -f {} \;
sync && sudo purge
./bin/pyspark --conf spark.python.profile=true
```
```python
df = spark.range(10000000).selectExpr("id as id0", "id as id1", "id as
id2", "id as id3", "id as id4", "id as id5", "id as id6", "id as id7", "id as
id8", "id as id9", "struct(id) as s").cache()
df.count()
df.rdd.map(lambda x: x).count()
sc.show_profiles()
```
```
============================================================
Profile of RDD<id=13>
============================================================
210149857 function calls (200139596 primitive calls) in 385.988
seconds
Ordered by: internal time, cumulative time
ncalls tottime percall cumtime percall filename:lineno(function)
30000000/20000000 92.012 0.000 265.554 0.000
types.py:632(fromInternal)
20000000 87.470 0.000 137.298 0.000 types.py:1430(_create_row)
683 65.402 0.096 364.590 0.534 {cPickle.loads}
20000000 22.989 0.000 288.543 0.000 types.py:1427(<lambda>)
10000000 19.146 0.000 19.146 0.000 {zip}
20000000 17.881 0.000 33.933 0.000 types.py:1478(__new__)
30045761 17.121 0.000 17.121 0.000 {isinstance}
20000000 16.052 0.000 16.052 0.000 {built-in method __new__ of
type object at 0x10153d428}
20000000 15.894 0.000 15.894 0.000 types.py:1562(__setattr__)
10000008 14.938 0.000 383.739 0.000 rdd.py:1040(<genexpr>)
20000000 10.214 0.000 10.214 0.000
types.py:1426(_create_row_inbound_converter)
16 2.248 0.140 385.986 24.124 {sum}
1374 2.228 0.002 2.228 0.002 {method 'read' of 'file'
objects}
```
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