[
https://issues.apache.org/jira/browse/SPARK-24213?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
spark_user updated SPARK-24213:
-------------------------------
Summary: Power Iteration Clustering in SparkML throws exception, when the
ID is IntType (was: Power Iteration Clustering in SparkML throws exception,
when the ID in IntType)
> Power Iteration Clustering in SparkML throws exception, when the ID is IntType
> ------------------------------------------------------------------------------
>
> Key: SPARK-24213
> URL: https://issues.apache.org/jira/browse/SPARK-24213
> Project: Spark
> Issue Type: Bug
> Components: ML
> Affects Versions: 2.4.0
> Reporter: spark_user
> Priority: Major
> Fix For: 2.4.0
>
>
> While running the code, PowerIterationClustering in spark ML throws exception.
> {code:scala}
> val data = spark.createDataFrame(Seq(
> (0, Array(1), Array(0.9)),
> (1, Array(2), Array(0.9)),
> (2, Array(3), Array(0.9)),
> (3, Array(4), Array(0.1)),
> (4, Array(5), Array(0.9))
> )).toDF("id", "neighbors", "similarities")
> val result = new PowerIterationClustering()
> .setK(2)
> .setMaxIter(10)
> .setInitMode("random")
> .transform(data)
> .select("id","prediction")
> {code}
> {code:java}
> org.apache.spark.sql.AnalysisException: cannot resolve '`prediction`' given
> input columns: [id, neighbors, similarities];;
> 'Project [id#215, 'prediction]
> +- AnalysisBarrier
> +- Project [id#215, neighbors#216, similarities#217]
> +- Join Inner, (id#215 = id#234)
> :- Project [_1#209 AS id#215, _2#210 AS neighbors#216, _3#211 AS
> similarities#217]
> : +- LocalRelation [_1#209, _2#210, _3#211]
> +- Project [cast(id#230L as int) AS id#234]
> +- LogicalRDD [id#230L, prediction#231], false
> at
> org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
> at
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:88)
> at
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:85)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:289)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:289)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:288)
> {code}
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