Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/17233#discussion_r105721463
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala ---
@@ -188,35 +189,45 @@ class StringIndexerModel (
transformSchema(dataset.schema, logging = true)
val filteredLabels = getHandleInvalid match {
- case StringIndexer.KEEP_UNSEEN_LABEL => labels :+ "__unknown"
+ case StringIndexer.KEEP_INVALID => labels :+ "__unknown"
case _ => labels
}
val metadata = NominalAttribute.defaultAttr
.withName($(outputCol)).withValues(filteredLabels).toMetadata()
// If we are skipping invalid records, filter them out.
val (filteredDataset, keepInvalid) = getHandleInvalid match {
- case StringIndexer.SKIP_UNSEEN_LABEL =>
+ case StringIndexer.SKIP_INVALID =>
val filterer = udf { label: String =>
labelToIndex.contains(label)
}
- (dataset.where(filterer(dataset($(inputCol)))), false)
- case _ => (dataset, getHandleInvalid ==
StringIndexer.KEEP_UNSEEN_LABEL)
+
(dataset.na.drop(Array($(inputCol))).where(filterer(dataset($(inputCol)))),
false)
+ case _ => (dataset, getHandleInvalid == StringIndexer.KEEP_INVALID)
}
- val indexer = udf { label: String =>
- if (labelToIndex.contains(label)) {
- labelToIndex(label)
- } else if (keepInvalid) {
- labels.length
+ val indexer = udf { row: Row =>
--- End diff --
No need to use a Row; just take a String:
```
val indexer = udf { label: String =>
if (label == null) {
if (keepInvalid) {
labels.length
} else {
throw new SparkException("StringIndexer encountered NULL value.
To handle or skip " +
"NULLS, try setting StringIndexer.handleInvalid.")
}
} else {
if (labelToIndex.contains(label)) {
labelToIndex(label)
} else if (keepInvalid) {
labels.length
} else {
throw new SparkException(s"Unseen label: $label. To handle
unseen labels, " +
s"set Param handleInvalid to ${StringIndexer.KEEP_INVALID}.")
}
}
}
```
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