viirya commented on a change in pull request #20146: [SPARK-11215][ML] Add
multiple columns support to StringIndexer
URL: https://github.com/apache/spark/pull/20146#discussion_r244529348
##########
File path: mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala
##########
@@ -421,3 +603,49 @@ object IndexToString extends
DefaultParamsReadable[IndexToString] {
@Since("1.6.0")
override def load(path: String): IndexToString = super.load(path)
}
+
+/**
+ * A SQL `Aggregator` used by `StringIndexer` to count labels in string
columns during fitting.
+ */
+private class StringIndexerAggregator(numColumns: Int, inputColTypes:
Seq[DataType])
+ extends Aggregator[Row, Array[OpenHashMap[String, Long]],
Array[OpenHashMap[String, Long]]] {
+
+ override def zero: Array[OpenHashMap[String, Long]] =
+ Array.fill(numColumns)(new OpenHashMap[String, Long]())
+
+ def reduce(
+ array: Array[OpenHashMap[String, Long]],
+ row: Row): Array[OpenHashMap[String, Long]] = {
+ for (i <- 0 until numColumns) {
+ val stringValue = row.getString(i)
+ // We don't count for null and NaN values.
Review comment:
You're right and doing the filter after the string conversion is unreliable
after rethinking. I changed it now so NaNs are replaced with null before
aggregation. The aggregator can skip null so I think it should be better.
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