[GitHub] spark pull request #19746: [SPARK-22346][ML] VectorSizeHint Transformer for ...

[MrBago <gi...@git.apache.org>]

Github user MrBago commented on a diff in the pull request:

    https://github.com/apache/spark/pull/19746#discussion_r154815581
  
    --- Diff: mllib/src/test/scala/org/apache/spark/ml/feature/VectorSizeHintSuite.scala ---
    @@ -0,0 +1,173 @@
    +/*
    + * 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.
    + */
    +
    +package org.apache.spark.ml.feature
    +
    +import org.apache.spark.{SparkException, SparkFunSuite}
    +import org.apache.spark.ml.attribute.AttributeGroup
    +import org.apache.spark.ml.linalg.{Vector, Vectors}
    +import org.apache.spark.ml.util.DefaultReadWriteTest
    +import org.apache.spark.mllib.util.MLlibTestSparkContext
    +import org.apache.spark.sql.Row
    +import org.apache.spark.sql.execution.streaming.MemoryStream
    +import org.apache.spark.sql.streaming.StreamTest
    +
    +class VectorSizeHintSuite
    +  extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest {
    +
    +  import testImplicits._
    +
    +  test("Test Param Validators") {
    +    intercept[IllegalArgumentException] (new VectorSizeHint().setHandleInvalid("invalidValue"))
    +    intercept[IllegalArgumentException] (new VectorSizeHint().setSize(-3))
    +  }
    +
    +  test("Adding size to column of vectors.") {
    +
    +    val size = 3
    +    val vectorColName = "vector"
    +    val denseVector = Vectors.dense(1, 2, 3)
    +    val sparseVector = Vectors.sparse(size, Array(), Array())
    +
    +    val data = Seq(denseVector, denseVector, sparseVector).map(Tuple1.apply)
    +    val dataFrame = data.toDF(vectorColName)
    +    assert(
    +      AttributeGroup.fromStructField(dataFrame.schema(vectorColName)).size == -1,
    +      "Transformer did not add expected size data.")
    +
    +    for (handleInvalid <- VectorSizeHint.supportedHandleInvalids) {
    +      val transformer = new VectorSizeHint()
    +        .setInputCol(vectorColName)
    +        .setSize(size)
    +        .setHandleInvalid(handleInvalid)
    +      val withSize = transformer.transform(dataFrame)
    +      assert(
    +        AttributeGroup.fromStructField(withSize.schema(vectorColName)).size == size,
    +        "Transformer did not add expected size data.")
    +      withSize.collect
    +    }
    +  }
    +
    +  test("Size hint preserves attributes.") {
    +
    +    val size = 3
    +    val vectorColName = "vector"
    +    val data = Seq((1, 2, 3), (2, 3, 3))
    +    val dataFrame = data.toDF("x", "y", "z")
    +
    +    val assembler = new VectorAssembler()
    +      .setInputCols(Array("x", "y", "z"))
    +      .setOutputCol(vectorColName)
    +    val dataFrameWithMetadata = assembler.transform(dataFrame)
    +    val group = AttributeGroup.fromStructField(dataFrameWithMetadata.schema(vectorColName))
    +
    +    for (handleInvalid <- VectorSizeHint.supportedHandleInvalids) {
    +      val transformer = new VectorSizeHint()
    +        .setInputCol(vectorColName)
    +        .setSize(size)
    +        .setHandleInvalid(handleInvalid)
    +      val withSize = transformer.transform(dataFrameWithMetadata)
    +
    +      val newGroup = AttributeGroup.fromStructField(withSize.schema(vectorColName))
    +      assert(newGroup.size === size, "Transformer did not add expected size data.")
    +      assert(
    +        newGroup.attributes.get.deep === group.attributes.get.deep,
    +        "SizeHintTransformer did not preserve attributes.")
    +      withSize.collect
    +    }
    +  }
    +
    +  test("Size miss-match between current and target size raises an error.") {
    +    val size = 4
    +    val vectorColName = "vector"
    +    val data = Seq((1, 2, 3), (2, 3, 3))
    +    val dataFrame = data.toDF("x", "y", "z")
    +
    +    val assembler = new VectorAssembler()
    +      .setInputCols(Array("x", "y", "z"))
    +      .setOutputCol(vectorColName)
    +    val dataFrameWithMetadata = assembler.transform(dataFrame)
    +
    +    for (handleInvalid <- VectorSizeHint.supportedHandleInvalids) {
    +      val transformer = new VectorSizeHint()
    +        .setInputCol(vectorColName)
    +        .setSize(size)
    +        .setHandleInvalid(handleInvalid)
    +      intercept[SparkException](transformer.transform(dataFrameWithMetadata))
    +    }
    +  }
    +
    +  test("Handle invalid does the right thing.") {
    +
    +    val vector = Vectors.dense(1, 2, 3)
    +    val short = Vectors.dense(2)
    +    val dataWithNull = Seq(vector, null).map(Tuple1.apply).toDF("vector")
    +    val dataWithShort = Seq(vector, short).map(Tuple1.apply).toDF("vector")
    +
    +    val sizeHint = new VectorSizeHint()
    +      .setInputCol("vector")
    +      .setHandleInvalid("error")
    +      .setSize(3)
    +
    +    intercept[SparkException](sizeHint.transform(dataWithNull).collect)
    +    intercept[SparkException](sizeHint.transform(dataWithShort).collect)
    +
    +    sizeHint.setHandleInvalid("skip")
    +    assert(sizeHint.transform(dataWithNull).count() === 1)
    +    assert(sizeHint.transform(dataWithShort).count() === 1)
    +  }
    +
    +  test("read/write") {
    +    val sizeHint = new VectorSizeHint()
    +      .setInputCol("myInputCol")
    +      .setSize(11)
    +      .setHandleInvalid("skip")
    +    testDefaultReadWrite(sizeHint)
    +  }
    +}
    +
    +class VectorSizeHintStreamingSuite extends StreamTest {
    +
    +  import testImplicits._
    +
    +  test("Test assemble vectors with size hint in steaming.") {
    +    val a = Vectors.dense(0, 1, 2)
    +    val b = Vectors.sparse(4, Array(0, 3), Array(3, 6))
    +
    +    val stream = MemoryStream[(Vector, Vector)]
    +    val streamingDF = stream.toDS.toDF("a", "b")
    +    val sizeHintA = new VectorSizeHint()
    +      .setSize(3)
    +      .setInputCol("a")
    +    val sizeHintB = new VectorSizeHint()
    +      .setSize(4)
    +      .setInputCol("b")
    +    val vectorAssembler = new VectorAssembler()
    +      .setInputCols(Array("a", "b"))
    +      .setOutputCol("assembled")
    +    val output = Seq(sizeHintA, sizeHintB, vectorAssembler).foldLeft(streamingDF) {
    +      case (data, transform) => transform.transform(data)
    +    }.select("assembled")
    +
    +    val expected = Vectors.dense(0, 1, 2, 3, 0, 0, 6)
    +
    +    testStream (output) (
    +      AddData(stream, (a, b), (a, b)),
    +      CheckAnswerRows(Seq(Row(expected), Row(expected)), false, false)
    --- End diff --
    
    The reason I didn't use `CheckAnswer` is because there isn't an implicit encoder in `testImplicits` that handles `Vector`. I tried `CheckAnswer[Vector](expected, expected)` but that doesn't work either :(. Is there an encoder that works for Vectors?


---

---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For additional commands, e-mail: reviews-help@spark.apache.org