[jira] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: (was: Apache Spark) > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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] [Assigned] (SPARK-19189) Optimize CartesianRDD to avoid parent RDD partition re-computation and re-serialization
[ https://issues.apache.org/jira/browse/SPARK-19189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-19189: Assignee: Apache Spark > Optimize CartesianRDD to avoid parent RDD partition re-computation and > re-serialization > --- > > Key: SPARK-19189 > URL: https://issues.apache.org/jira/browse/SPARK-19189 > Project: Spark > Issue Type: Improvement > Components: Spark Core >Affects Versions: 2.1.0 >Reporter: Weichen Xu >Assignee: Apache Spark >Priority: Minor > Original Estimate: 24h > Remaining Estimate: 24h > > Current CartesianRDD implementation, suppose RDDA cartisian RDDB, generating > RDDC, > each RDDA partition will be reading by multiple RDDC partition, and RDDB has > similar problem. > This will cause, when RDDC partition computing, each partition's data in RDDA > or RDDB will be repeatedly serialized (then transfer through network), if > RDDA or RDDB haven't been persist, it will cause RDD recomputation repeatedly. -- 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
