[jira] [Assigned] (SPARK-10985) Avoid passing evicted blocks throughout BlockManager / CacheManager

2016-01-15 Thread Apache Spark (JIRA)

 [ 
https://issues.apache.org/jira/browse/SPARK-10985?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Apache Spark reassigned SPARK-10985:


Assignee: (was: Apache Spark)

> Avoid passing evicted blocks throughout BlockManager / CacheManager
> ---
>
> Key: SPARK-10985
> URL: https://issues.apache.org/jira/browse/SPARK-10985
> Project: Spark
>  Issue Type: Improvement
>  Components: Block Manager, Spark Core
>Reporter: Andrew Or
>Priority: Minor
>
> This is a minor refactoring task.
> Currently when we attempt to put a block in, we get back an array buffer of 
> blocks that are dropped in the process. We do this to propagate these blocks 
> back to our TaskContext, which will add them to its TaskMetrics so we can see 
> them in the SparkUI storage tab properly.
> Now that we have TaskContext.get, we can just use that to propagate this 
> information. This simplifies a lot of the signatures and gets rid of weird 
> return types like the following everywhere:
> {code}
> ArrayBuffer[(BlockId, BlockStatus)]
> {code}



--
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-10985) Avoid passing evicted blocks throughout BlockManager / CacheManager

2016-01-15 Thread Apache Spark (JIRA)

 [ 
https://issues.apache.org/jira/browse/SPARK-10985?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Apache Spark reassigned SPARK-10985:


Assignee: Apache Spark

> Avoid passing evicted blocks throughout BlockManager / CacheManager
> ---
>
> Key: SPARK-10985
> URL: https://issues.apache.org/jira/browse/SPARK-10985
> Project: Spark
>  Issue Type: Improvement
>  Components: Block Manager, Spark Core
>Reporter: Andrew Or
>Assignee: Apache Spark
>Priority: Minor
>
> This is a minor refactoring task.
> Currently when we attempt to put a block in, we get back an array buffer of 
> blocks that are dropped in the process. We do this to propagate these blocks 
> back to our TaskContext, which will add them to its TaskMetrics so we can see 
> them in the SparkUI storage tab properly.
> Now that we have TaskContext.get, we can just use that to propagate this 
> information. This simplifies a lot of the signatures and gets rid of weird 
> return types like the following everywhere:
> {code}
> ArrayBuffer[(BlockId, BlockStatus)]
> {code}



--
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-10985) Avoid passing evicted blocks throughout BlockManager / CacheManager

2015-10-16 Thread Josh Rosen (JIRA)

 [ 
https://issues.apache.org/jira/browse/SPARK-10985?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Josh Rosen reassigned SPARK-10985:
--

Assignee: Josh Rosen

> Avoid passing evicted blocks throughout BlockManager / CacheManager
> ---
>
> Key: SPARK-10985
> URL: https://issues.apache.org/jira/browse/SPARK-10985
> Project: Spark
>  Issue Type: Sub-task
>  Components: Block Manager, Spark Core
>Reporter: Andrew Or
>Assignee: Josh Rosen
>Priority: Minor
>
> This is a minor refactoring task.
> Currently when we attempt to put a block in, we get back an array buffer of 
> blocks that are dropped in the process. We do this to propagate these blocks 
> back to our TaskContext, which will add them to its TaskMetrics so we can see 
> them in the SparkUI storage tab properly.
> Now that we have TaskContext.get, we can just use that to propagate this 
> information. This simplifies a lot of the signatures and gets rid of weird 
> return types like the following everywhere:
> {code}
> ArrayBuffer[(BlockId, BlockStatus)]
> {code}



--
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