Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/20285#discussion_r162223973
--- Diff:
examples/src/main/scala/org/apache/spark/examples/ml/VectorSizeHintExample.scala
---
@@ -0,0 +1,63 @@
+/*
+ * 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.
+ */
+
+// scalastyle:off println
+package org.apache.spark.examples.ml
+
+// $example on$
+import org.apache.spark.ml.feature.{VectorAssembler, VectorSizeHint}
+import org.apache.spark.ml.linalg.Vectors
+// $example off$
+import org.apache.spark.sql.SparkSession
+
+object VectorSizeHintExample {
+ def main(args: Array[String]): Unit = {
+ val spark = SparkSession
+ .builder
+ .appName("VectorSizeHintExample")
+ .getOrCreate()
+
+ // $example on$
+ val dataset = spark.createDataFrame(
+ Seq(
+ (0, 18, 1.0, Vectors.dense(0.0, 10.0, 0.5), 1.0),
+ (0, 18, 1.0, Vectors.dense(0.0, 10.0), 0.0))
+ ).toDF("id", "hour", "mobile", "userFeatures", "clicked")
+
+ val sizeHint = new VectorSizeHint()
+ .setInputCol("userFeatures")
+ .setHandleInvalid("skip")
+ .setSize(3)
+
+ val datasetWithSize = sizeHint.transform(dataset)
+ println("Rows where 'userFeatures' is not the right size are filtered
out")
+ datasetWithSize.show(false)
+
+ val assembler = new VectorAssembler()
+ .setInputCols(Array("hour", "mobile", "userFeatures"))
+ .setOutputCol("features")
+
+ // This dataframe can be used by used by downstream transformers as
before
--- End diff --
ditto.
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