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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2018/04/02 04:09:00 UTC
[jira] [Commented] (SPARK-23841) NodeIdCache should unpersist the
last cached nodeIdsForInstances
[ https://issues.apache.org/jira/browse/SPARK-23841?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16421919#comment-16421919 ]
Apache Spark commented on SPARK-23841:
--------------------------------------
User 'zhengruifeng' has created a pull request for this issue:
https://github.com/apache/spark/pull/20956
> NodeIdCache should unpersist the last cached nodeIdsForInstances
> ----------------------------------------------------------------
>
> Key: SPARK-23841
> URL: https://issues.apache.org/jira/browse/SPARK-23841
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 2.4.0
> Reporter: zhengruifeng
> Priority: Minor
>
> {{{{NodeIdCache}}}} forget to unpersist the last cached intermediate dataset:
>
> {code:java}
> scala> import org.apache.spark.ml.classification._
> import org.apache.spark.ml.classification._
> scala> val df = spark.read.format("libsvm").load("/Users/zrf/Dev/OpenSource/spark/data/mllib/sample_libsvm_data.txt")
> 2018-04-02 11:48:25 WARN LibSVMFileFormat:66 - 'numFeatures' option not specified, determining the number of features by going though the input. If you know the number in advance, please specify it via 'numFeatures' option to avoid the extra scan.
> 2018-04-02 11:48:31 WARN ObjectStore:568 - Failed to get database global_temp, returning NoSuchObjectException
> df: org.apache.spark.sql.DataFrame = [label: double, features: vector]
> scala> val rf = new RandomForestClassifier().setCacheNodeIds(true)
> rf: org.apache.spark.ml.classification.RandomForestClassifier = rfc_aab2b672546b
> scala> val rfm = rf.fit(df)
> rfm: org.apache.spark.ml.classification.RandomForestClassificationModel = RandomForestClassificationModel (uid=rfc_aab2b672546b) with 20 trees
> scala> sc.getPersistentRDDs
> res0: scala.collection.Map[Int,org.apache.spark.rdd.RDD[_]] = Map(56 -> MapPartitionsRDD[56] at map at NodeIdCache.scala:102){code}
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