shahid created SPARK-24489:
------------------------------
Summary: No check for invalid input type of weight data in
ml.PowerIterationClustering
Key: SPARK-24489
URL: https://issues.apache.org/jira/browse/SPARK-24489
Project: Spark
Issue Type: Bug
Components: ML
Affects Versions: 2.4.0
Reporter: shahid
Fix For: 2.4.0
The test case will result the following failure. currently in ml.PIC, there is
no check for the data type of weight column. We should check for the valid data
type of the weight.
{code:java}
test("invalid input types for weight") {
val invalidWeightData = spark.createDataFrame(Seq(
(0L, 1L, "a"),
(2L, 3L, "b")
)).toDF("src", "dst", "weight")
val pic = new PowerIterationClustering()
.setWeightCol("weight")
val result = pic.assignClusters(invalidWeightData)
}
{code}
{code:java}
Job aborted due to stage failure: Task 0 in stage 8077.0 failed 1 times, most
recent failure: Lost task 0.0 in stage 8077.0 (TID 882, localhost, executor
driver): scala.MatchError: [0,1,null] (of class
org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema)
at
org.apache.spark.ml.clustering.PowerIterationClustering$$anonfun$3.apply(PowerIterationClustering.scala:178)
at
org.apache.spark.ml.clustering.PowerIterationClustering$$anonfun$3.apply(PowerIterationClustering.scala:178)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at org.apache.spark.graphx.EdgeRDD$$anonfun$1.apply(EdgeRDD.scala:107)
at org.apache.spark.graphx.EdgeRDD$$anonfun$1.apply(EdgeRDD.scala:105)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndex$1$$anonfun$apply$26.apply(RDD.scala:847)
{code}
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