[jira] [Created] (SPARK-29756) CountVectorizer forget to unpersist intermediate rdd

["zhengruifeng (Jira)" <ji...@apache.org>]

zhengruifeng created SPARK-29756:
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             Summary: 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


{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_5edcfe4828c2scala> sc.getPersistentRDDs
res0: scala.collection.Map[Int,org.apache.spark.rdd.RDD[_]] = Map(9 -> MapPartitionsRDD[9] at map at CountVectorizer.scala:223)
 {code}



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