[
https://issues.apache.org/jira/browse/SPARK-23085?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sean Owen resolved SPARK-23085.
-------------------------------
Resolution: Fixed
Fix Version/s: 2.4.0
Issue resolved by pull request 20275
[https://github.com/apache/spark/pull/20275]
> API parity for mllib.linalg.Vectors.sparse
> -------------------------------------------
>
> Key: SPARK-23085
> URL: https://issues.apache.org/jira/browse/SPARK-23085
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 2.4.0
> Reporter: zhengruifeng
> Assignee: zhengruifeng
> Priority: Minor
> Fix For: 2.4.0
>
>
> Both {{ML.Vectors#sparse(size: {color:#cc7832}Int, {color}indices:
> Array[{color:#cc7832}Int{color}]{color:#cc7832}, {color}values:
> Array[{color:#cc7832}Double{color}]}} and {{ML.Vectors#sparse(size:
> {color:#cc7832}Int, {color}elements:
> {color:#4e807d}Seq{color}[({color:#cc7832}Int, Double{color})])}} support
> zero-length vectors.
> In old MLLib,
> {{MLLib.Vectors.sparse(size: {color:#cc7832}Int, {color}indices:
> Array[{color:#cc7832}Int{color}]{color:#cc7832}, {color}values:
> Array[{color:#cc7832}Double{color}])}} also supports it.
> However,
> {{ML.Vectors#sparse(size: {color:#cc7832}Int, {color}elements:
> {color:#4e807d}Seq{color}[({color:#cc7832}Int, Double{color})])}} require a
> positve length.
>
> {code:java}
> scala> org.apache.spark.ml.linalg.Vectors.sparse(0, Array.empty[Int],
> Array.empty[Double])
> res15: org.apache.spark.ml.linalg.Vector = (0,[],[])
> scala> org.apache.spark.ml.linalg.Vectors.sparse(0, Array.empty[(Int,
> Double)])
> res16: org.apache.spark.ml.linalg.Vector = (0,[],[])
> scala> org.apache.spark.mllib.linalg.Vectors.sparse(0, Array.empty[Int],
> Array.empty[Double])
> res17: org.apache.spark.mllib.linalg.Vector = (0,[],[])
> scala> org.apache.spark.mllib.linalg.Vectors.sparse(0, Array.empty[(Int,
> Double)])
> java.lang.IllegalArgumentException: requirement failed: The size of the
> requested sparse vector must be greater than 0.
> at scala.Predef$.require(Predef.scala:224)
> at org.apache.spark.mllib.linalg.Vectors$.sparse(Vectors.scala:315)
> ... 50 elided
>
> {code}
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