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 2019/11/08 10:33:00 UTC
[jira] [Assigned] (SPARK-29756) CountVectorizer forget to unpersist
intermediate rdd
[ https://issues.apache.org/jira/browse/SPARK-29756?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
zhengruifeng reassigned SPARK-29756:
------------------------------------
Assignee: zhengruifeng
> CountVectorizer forget to unpersist intermediate rdd
> ----------------------------------------------------
>
> Key: SPARK-29756
> URL: https://issues.apache.org/jira/browse/SPARK-29756
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 3.0.0
> Reporter: zhengruifeng
> Assignee: zhengruifeng
> Priority: Trivial
>
> {code:java}
> scala> val df = spark.createDataFrame(Seq(
> | (0, Array("a", "b", "c")),
> | (1, Array("a", "b", "b", "c", "a"))
> | )).toDF("id", "words")
> df: org.apache.spark.sql.DataFrame = [id: int, words: array<string>]scala>
> import org.apache.spark.ml.feature._
> import org.apache.spark.ml.feature._
> scala> val cvModel: CountVectorizerModel = new CountVectorizer().setInputCol("words").setOutputCol("features").setVocabSize(3).setMinDF(2).fit(df)
> cvModel: org.apache.spark.ml.feature.CountVectorizerModel = cntVec_5edcfe4828c2
> scala> sc.getPersistentRDDs
> res0: scala.collection.Map[Int,org.apache.spark.rdd.RDD[_]] = Map(9 -> MapPartitionsRDD[9] at map at CountVectorizer.scala:223)
> {code}
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org