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Posted to issues@spark.apache.org by "Weichen Xu (Jira)" <ji...@apache.org> on 2020/05/11 09:38:00 UTC
[jira] [Updated] (SPARK-31676) QuantileDiscretizer raise error
parameter splits given invalid value (splits array includes -0.0 and 0.0)
[ https://issues.apache.org/jira/browse/SPARK-31676?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Weichen Xu updated SPARK-31676:
-------------------------------
Description:
Reproduce code
{code}
import scala.util.Random
val rng = new Random(3)
val a1 = Array.tabulate(200)(_=>rng.nextDouble * 2.0 - 1.0) ++ Array.fill(20)(0.0) ++ Array.fill(20)(-0.0)
import spark.implicits._
val df1 = sc.parallelize(a1, 2).toDF("id")
import org.apache.spark.ml.feature.QuantileDiscretizer
val qd = new QuantileDiscretizer().setInputCol("id").setOutputCol("out").setNumBuckets(200).setRelativeError(0.0)
val model = qd.fit(df1)
{code}
Raise error like:
at org.apache.spark.ml.param.Param.validate(params.scala:76)
at org.apache.spark.ml.param.ParamPair.<init>(params.scala:634)
at org.apache.spark.ml.param.Param.$minus$greater(params.scala:85)
at org.apache.spark.ml.param.Params.set(params.scala:713)
at org.apache.spark.ml.param.Params.set$(params.scala:712)
at org.apache.spark.ml.PipelineStage.set(Pipeline.scala:41)
at org.apache.spark.ml.feature.Bucketizer.setSplits(Bucketizer.scala:77)
at org.apache.spark.ml.feature.QuantileDiscretizer.fit(QuantileDiscretizer.scala:231)
... 49 elided
java.lang.IllegalArgumentException: quantileDiscretizer_479bb5a3ca99 parameter splits given invalid value [-Infinity,-0.9986765732730827,..., -0.0, 0.0, ..., 0.9907184077958491,Infinity]
0.0 > -0.0 is False, which break the paremater validation check.
was:
Reproduce code
{code: scala}
import scala.util.Random
val rng = new Random(3)
val a1 = Array.tabulate(200)(_=>rng.nextDouble * 2.0 - 1.0) ++ Array.fill(20)(0.0) ++ Array.fill(20)(-0.0)
import spark.implicits._
val df1 = sc.parallelize(a1, 2).toDF("id")
import org.apache.spark.ml.feature.QuantileDiscretizer
val qd = new QuantileDiscretizer().setInputCol("id").setOutputCol("out").setNumBuckets(200).setRelativeError(0.0)
val model = qd.fit(df1)
{code}
Raise error like:
at org.apache.spark.ml.param.Param.validate(params.scala:76)
at org.apache.spark.ml.param.ParamPair.<init>(params.scala:634)
at org.apache.spark.ml.param.Param.$minus$greater(params.scala:85)
at org.apache.spark.ml.param.Params.set(params.scala:713)
at org.apache.spark.ml.param.Params.set$(params.scala:712)
at org.apache.spark.ml.PipelineStage.set(Pipeline.scala:41)
at org.apache.spark.ml.feature.Bucketizer.setSplits(Bucketizer.scala:77)
at org.apache.spark.ml.feature.QuantileDiscretizer.fit(QuantileDiscretizer.scala:231)
... 49 elided
java.lang.IllegalArgumentException: quantileDiscretizer_479bb5a3ca99 parameter splits given invalid value [-Infinity,-0.9986765732730827,..., -0.0, 0.0, ..., 0.9907184077958491,Infinity]
0.0 > -0.0 is False, which break the paremater validation check.
> QuantileDiscretizer raise error parameter splits given invalid value (splits array includes -0.0 and 0.0)
> ---------------------------------------------------------------------------------------------------------
>
> Key: SPARK-31676
> URL: https://issues.apache.org/jira/browse/SPARK-31676
> Project: Spark
> Issue Type: Bug
> Components: ML
> Affects Versions: 2.4.5, 3.0.0
> Reporter: Weichen Xu
> Priority: Major
>
> Reproduce code
> {code}
> import scala.util.Random
> val rng = new Random(3)
> val a1 = Array.tabulate(200)(_=>rng.nextDouble * 2.0 - 1.0) ++ Array.fill(20)(0.0) ++ Array.fill(20)(-0.0)
> import spark.implicits._
> val df1 = sc.parallelize(a1, 2).toDF("id")
> import org.apache.spark.ml.feature.QuantileDiscretizer
> val qd = new QuantileDiscretizer().setInputCol("id").setOutputCol("out").setNumBuckets(200).setRelativeError(0.0)
> val model = qd.fit(df1)
> {code}
> Raise error like:
> at org.apache.spark.ml.param.Param.validate(params.scala:76)
> at org.apache.spark.ml.param.ParamPair.<init>(params.scala:634)
> at org.apache.spark.ml.param.Param.$minus$greater(params.scala:85)
> at org.apache.spark.ml.param.Params.set(params.scala:713)
> at org.apache.spark.ml.param.Params.set$(params.scala:712)
> at org.apache.spark.ml.PipelineStage.set(Pipeline.scala:41)
> at org.apache.spark.ml.feature.Bucketizer.setSplits(Bucketizer.scala:77)
> at org.apache.spark.ml.feature.QuantileDiscretizer.fit(QuantileDiscretizer.scala:231)
> ... 49 elided
> java.lang.IllegalArgumentException: quantileDiscretizer_479bb5a3ca99 parameter splits given invalid value [-Infinity,-0.9986765732730827,..., -0.0, 0.0, ..., 0.9907184077958491,Infinity]
> 0.0 > -0.0 is False, which break the paremater validation check.
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