[
https://issues.apache.org/jira/browse/SPARK-21723?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Jan Vršovský updated SPARK-21723:
---------------------------------
Description:
Writing a dataset to LibSVM format raises an exception
{{java.util.NoSuchElementException: key not found: numFeatures}}
Happens only when the dataset was NOT read from a LibSVM format before (because
otherwise numFeatures is in its metadata). Steps to reproduce:
{code}
import org.apache.spark.ml.linalg.Vectors
val rawData = Seq((1.0, Vectors.sparse(3, Seq((0, 2.0), (1, 3.0)))),
(4.0, Vectors.sparse(3, Seq((0, 5.0), (2, 6.0)))))
val dfTemp = spark.sparkContext.parallelize(rawData).toDF("label", "features")
dfTemp.coalesce(1).write.format("libsvm").save("...filename...")
{code}
PR with a fix and unit test is ready - see
[https://github.com/apache/spark/pull/18872].
was:
Writing a dataset to LibSVM format raises an exception
{{java.util.NoSuchElementException: key not found: numFeatures}}
Happens only when the dataset was NOT read from a LibSVM format before (because
otherwise numFeatures is in its metadata). Steps to reproduce:
{code:scala}
import org.apache.spark.ml.linalg.Vectors
val rawData = Seq((1.0, Vectors.sparse(3, Seq((0, 2.0), (1, 3.0)))),
(4.0, Vectors.sparse(3, Seq((0, 5.0), (2, 6.0)))))
val dfTemp = spark.sparkContext.parallelize(rawData).toDF("label", "features")
dfTemp.coalesce(1).write.format("libsvm").save("...filename...")
{code}
PR with a fix and unit test is ready - see
[https://github.com/apache/spark/pull/18872].
> Can't write LibSVM - key not found: numFeatures
> -----------------------------------------------
>
> Key: SPARK-21723
> URL: https://issues.apache.org/jira/browse/SPARK-21723
> Project: Spark
> Issue Type: Bug
> Components: Input/Output, ML
> Affects Versions: 2.2.0, 2.3.0
> Reporter: Jan Vršovský
>
> Writing a dataset to LibSVM format raises an exception
> {{java.util.NoSuchElementException: key not found: numFeatures}}
> Happens only when the dataset was NOT read from a LibSVM format before
> (because otherwise numFeatures is in its metadata). Steps to reproduce:
> {code}
> import org.apache.spark.ml.linalg.Vectors
> val rawData = Seq((1.0, Vectors.sparse(3, Seq((0, 2.0), (1, 3.0)))),
> (4.0, Vectors.sparse(3, Seq((0, 5.0), (2, 6.0)))))
> val dfTemp = spark.sparkContext.parallelize(rawData).toDF("label", "features")
> dfTemp.coalesce(1).write.format("libsvm").save("...filename...")
> {code}
> PR with a fix and unit test is ready - see
> [https://github.com/apache/spark/pull/18872].
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