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https://issues.apache.org/jira/browse/SPARK-3731?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Milan Straka updated SPARK-3731:
--------------------------------
    Attachment: worker.log

Sample worker.log showing the problem. For example, consider rdd_1_1. It has 
size 46.3MB. At the beginning, the caching work, but that stops -- the last 
time rdd_1_1 does not fit into cache, the following is reported:
{{14/09/29 21:53:10 WARN CacheManager: Not enough space to cache partition 
rdd_1_1 in memory! Free memory is 148908945 bytes.}}


> RDD caching stops working in pyspark after some time
> ----------------------------------------------------
>
>                 Key: SPARK-3731
>                 URL: https://issues.apache.org/jira/browse/SPARK-3731
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark, Spark Core
>    Affects Versions: 1.1.0
>         Environment: Linux, 32bit, standalone mode
>            Reporter: Milan Straka
>         Attachments: worker.log
>
>
> Consider a file F which when loaded with sc.textFile and cached takes up 
> slightly more than half of free memory for RDD cache.
> When in PySpark the following is executed:
>   1) a = sc.textFile(F)
>   2) a.cache().count()
>   3) b = sc.textFile(F)
>   4) b.cache().count()
> and then the following is repeated (for example 10 times):
>   a) a.unpersist().cache().count()
>   b) b.unpersist().cache().count()
> after some time, there are no RDD cached in memory.
> Also, since that time, no other RDD ever gets cached (the worker always 
> reports something like "WARN CacheManager: Not enough space to cache 
> partition rdd_23_5 in memory! Free memory is 277478190 bytes.", even if 
> rdd_23_5 is ~50MB). The Executors tab of the Application Detail UI shows that 
> all executors have 0MB memory used (which is consistent with the CacheManager 
> warning).
> When doing the same in scala, everything works perfectly.
> I understand that this is a vague description, but I do no know how to 
> describe the problem better.



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