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Posted to issues@spark.apache.org by "Pat McDonough (JIRA)" <ji...@apache.org> on 2014/04/02 07:53:15 UTC
[jira] [Updated] (SPARK-1392) Local spark-shell Runs Out of Memory
With Default Settings
[ https://issues.apache.org/jira/browse/SPARK-1392?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Pat McDonough updated SPARK-1392:
---------------------------------
Description:
Using the spark-0.9.0 Hadoop2 binary from the project download page, running the spark-shell locally in out of the box configuration, and attempting to cache all the attached data, spark OOMs with: {{java.lang.OutOfMemoryError: GC overhead limit exceeded}}
{code}
val explore = sc.textFile("/Users/pat/Projects/training-materials/Data/wiki_links")
explore.cache
explore.count
{code}
You can work around the issue by either decreasing {{spark.storage.memoryFraction}} or increasing {{SPARK_MEM}}
was:
When running the spark-shell locally in out of the box configuration, and attempting to cache all the attached data, spark OOMs with: {{java.lang.OutOfMemoryError: GC overhead limit exceeded}}
{code}
val explore = sc.textFile("/Users/pat/Projects/training-materials/Data/wiki_links")
explore.cache
explore.count
{code}
You can work around the issue by either decreasing {{spark.storage.memoryFraction}} or increasing {{SPARK_MEM}}
> Local spark-shell Runs Out of Memory With Default Settings
> ----------------------------------------------------------
>
> Key: SPARK-1392
> URL: https://issues.apache.org/jira/browse/SPARK-1392
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 0.9.0
> Environment: OS X 10.9.2, Java 1.7.0_51, Scala 2.10.3
> Reporter: Pat McDonough
>
> Using the spark-0.9.0 Hadoop2 binary from the project download page, running the spark-shell locally in out of the box configuration, and attempting to cache all the attached data, spark OOMs with: {{java.lang.OutOfMemoryError: GC overhead limit exceeded}}
> {code}
> val explore = sc.textFile("/Users/pat/Projects/training-materials/Data/wiki_links")
> explore.cache
> explore.count
> {code}
> You can work around the issue by either decreasing {{spark.storage.memoryFraction}} or increasing {{SPARK_MEM}}
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