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From Barak Gitsis <bar...@similarweb.com>
Subject Re: About memory leak in spark 1.4.1
Date Sun, 02 Aug 2015 13:55:03 GMT
spark uses a lot more than heap memory, it is the expected behavior.
in 1.4 off-heap memory usage is supposed to grow in comparison to 1.3

Better use as little memory as you can for heap, and since you are not
utilizing it already, it is safe for you to reduce it.
memoryFraction helps you optimize heap usage for your data/application
profile while keeping it tight.






On Sun, Aug 2, 2015 at 12:54 PM Sea <261810726@qq.com> wrote:

> spark.storage.memoryFraction is in heap memory, but my situation is that
> the memory is more than heap memory !
>
> Anyone else use spark 1.4.1 in production?
>
>
> ------------------ 原始邮件 ------------------
> *发件人:* "Ted Yu";<yuzhihong@gmail.com>;
> *发送时间:* 2015年8月2日(星期天) 下午5:45
> *收件人:* "Sea"<261810726@qq.com>;
> *抄送:* "Barak Gitsis"<barakg@similarweb.com>; "user@spark.apache.org"<
> user@spark.apache.org>; "rxin"<rxin@databricks.com>; "joshrosen"<
> joshrosen@databricks.com>; "davies"<davies@databricks.com>;
> *主题:* Re: About memory leak in spark 1.4.1
>
> http://spark.apache.org/docs/latest/tuning.html does mention spark.storage.memoryFraction
> in two places.
> One is under Cache Size Tuning section.
>
> FYI
>
> On Sun, Aug 2, 2015 at 2:16 AM, Sea <261810726@qq.com> wrote:
>
>> Hi, Barak
>>     It is ok with spark 1.3.0, the problem is with spark 1.4.1.
>>     I don't think spark.storage.memoryFraction will make any sense,
>> because it is still in heap memory.
>>
>>
>> ------------------ 原始邮件 ------------------
>> *发件人:* "Barak Gitsis";<barakg@similarweb.com>;
>> *发送时间:* 2015年8月2日(星期天) 下午4:11
>> *收件人:* "Sea"<261810726@qq.com>; "user"<user@spark.apache.org>;
>> *抄送:* "rxin"<rxin@databricks.com>; "joshrosen"<joshrosen@databricks.com>;
>> "davies"<davies@databricks.com>;
>> *主题:* Re: About memory leak in spark 1.4.1
>>
>> Hi,
>> reducing spark.storage.memoryFraction did the trick for me. Heap doesn't
>> get filled because it is reserved..
>> My reasoning is:
>> I give executor all the memory i can give it, so that makes it a boundary
>> .
>> From here i try to make the best use of memory I can.
>> storage.memoryFraction is in a sense user data space.  The rest can be used
>> by the system.
>> If you don't have so much data that you MUST store in memory for
>> performance, better give spark more space..
>> ended up setting it to 0.3
>>
>> All that said, it is on spark 1.3 on cluster
>>
>> hope that helps
>>
>> On Sat, Aug 1, 2015 at 5:43 PM Sea <261810726@qq.com> wrote:
>>
>>> Hi, all
>>> I upgrage spark to 1.4.1, many applications failed... I find the heap
>>> memory is not full , but the process of CoarseGrainedExecutorBackend will
>>> take more memory than I expect, and it will increase as time goes on,
>>> finally more than max limited of the server, the worker will die.....
>>>
>>> Any can help?
>>>
>>> Mode:standalone
>>>
>>> spark.executor.memory 50g
>>>
>>> 25583 xiaoju    20   0 75.5g  55g  28m S 1729.3 88.1   2172:52 java
>>>
>>> 55g more than 50g I apply
>>>
>>> --
>> *-Barak*
>>
>
> --
*-Barak*

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