harupy commented on a change in pull request #32245:
URL: https://github.com/apache/spark/pull/32245#discussion_r616310831
##########
File path: python/pyspark/ml/classification.py
##########
@@ -3151,7 +3151,7 @@ def func(predictions):
predArray.append(x)
return Vectors.dense(predArray)
- rawPredictionUDF = udf(func)
+ rawPredictionUDF = udf(func, VectorUDT())
aggregatedDataset = aggregatedDataset.withColumn(
self.getRawPredictionCol(),
rawPredictionUDF(aggregatedDataset[accColName]))
Review comment:
Can we just cast the `accColName` column to `VectorUDT` here instead of
using `udf`?
```suggestion
aggregatedDataset = aggregatedDataset.withColumn(
self.getRawPredictionCol(),
aggregatedDataset[accColName].cast(VectorUDT()))
```
##########
File path: python/pyspark/ml/classification.py
##########
@@ -3151,7 +3151,7 @@ def func(predictions):
predArray.append(x)
return Vectors.dense(predArray)
- rawPredictionUDF = udf(func)
+ rawPredictionUDF = udf(func, VectorUDT())
aggregatedDataset = aggregatedDataset.withColumn(
self.getRawPredictionCol(),
rawPredictionUDF(aggregatedDataset[accColName]))
Review comment:
Can we just cast the `accColName` column to `VectorUDT` here?
```suggestion
aggregatedDataset = aggregatedDataset.withColumn(
self.getRawPredictionCol(),
aggregatedDataset[accColName].cast(VectorUDT()))
```
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