You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "zhengruifeng (JIRA)" <ji...@apache.org> on 2018/01/16 06:11:00 UTC
[jira] [Updated] (SPARK-23085) API parity for
mllib.linalg.Vectors.sparse
[ https://issues.apache.org/jira/browse/SPARK-23085?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
zhengruifeng updated SPARK-23085:
---------------------------------
Description:
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}
was:
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}
> 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
> Priority: Minor
>
> 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}
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org