[jira] [Updated] (SPARK-17020) Materialization of RDD via DataFrame.rdd forces a poor re-distribution of data
[ https://issues.apache.org/jira/browse/SPARK-17020?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Hyukjin Kwon updated SPARK-17020: - Labels: bulk-closed (was: ) > Materialization of RDD via DataFrame.rdd forces a poor re-distribution of data > -- > > Key: SPARK-17020 > URL: https://issues.apache.org/jira/browse/SPARK-17020 > Project: Spark > Issue Type: Bug > Components: Spark Core, SQL >Affects Versions: 1.6.1, 1.6.2, 2.0.0 >Reporter: Roi Reshef >Priority: Major > Labels: bulk-closed > Attachments: dataframe_cache.PNG, rdd_cache.PNG > > > Calling DataFrame's lazy val .rdd results with a new RDD with a poor > distribution of partitions across the cluster. Moreover, any attempt to > repartition this RDD further will fail. > Attached are a screenshot of the original DataFrame on cache and the > resulting RDD on cache. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-17020) Materialization of RDD via DataFrame.rdd forces a poor re-distribution of data
[ https://issues.apache.org/jira/browse/SPARK-17020?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Sean Owen updated SPARK-17020: -- Priority: Major (was: Critical) > Materialization of RDD via DataFrame.rdd forces a poor re-distribution of data > -- > > Key: SPARK-17020 > URL: https://issues.apache.org/jira/browse/SPARK-17020 > Project: Spark > Issue Type: Bug > Components: Spark Core, SQL >Affects Versions: 1.6.1, 1.6.2, 2.0.0 >Reporter: Roi Reshef > Attachments: dataframe_cache.PNG, rdd_cache.PNG > > > Calling DataFrame's lazy val .rdd results with a new RDD with a poor > distribution of partitions across the cluster. Moreover, any attempt to > repartition this RDD further will fail. > Attached are a screenshot of the original DataFrame on cache and the > resulting RDD on cache. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-17020) Materialization of RDD via DataFrame.rdd forces a poor re-distribution of data
[ https://issues.apache.org/jira/browse/SPARK-17020?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Roi Reshef updated SPARK-17020: --- Affects Version/s: 2.0.0 > Materialization of RDD via DataFrame.rdd forces a poor re-distribution of data > -- > > Key: SPARK-17020 > URL: https://issues.apache.org/jira/browse/SPARK-17020 > Project: Spark > Issue Type: Bug > Components: Spark Core, SQL >Affects Versions: 1.6.1, 1.6.2, 2.0.0 >Reporter: Roi Reshef >Priority: Critical > Attachments: dataframe_cache.PNG, rdd_cache.PNG > > > Calling DataFrame's lazy val .rdd results with a new RDD with a poor > distribution of partitions across the cluster. Moreover, any attempt to > repartition this RDD further will fail. > Attached are a screenshot of the original DataFrame on cache and the > resulting RDD on cache. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-17020) Materialization of RDD via DataFrame.rdd forces a poor re-distribution of data
[ https://issues.apache.org/jira/browse/SPARK-17020?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Roi Reshef updated SPARK-17020: --- Attachment: rdd_cache.PNG dataframe_cache.PNG > Materialization of RDD via DataFrame.rdd forces a poor re-distribution of data > -- > > Key: SPARK-17020 > URL: https://issues.apache.org/jira/browse/SPARK-17020 > Project: Spark > Issue Type: Bug > Components: Spark Core, SQL >Affects Versions: 1.6.1, 1.6.2 >Reporter: Roi Reshef >Priority: Critical > Attachments: dataframe_cache.PNG, rdd_cache.PNG > > > Calling DataFrame's lazy val .rdd results with a new RDD with a poor > distribution of partitions across the cluster. Moreover, any attempt to > repartition this RDD further will fail. > Attached are a screenshot of the original DataFrame on cache and the > resulting RDD on cache. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
