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Hive >> mail # user >> The dreaded Heap Space Issue on a Transform


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Re: The dreaded Heap Space Issue on a Transform
We didn't ask yet, but to be sure, are all the slave nodes configured the
same, both in terms of hardware and other apps running, if any, running on
them?

On Wed, Jan 30, 2013 at 10:14 AM, Richard Nadeau <[EMAIL PROTECTED]>wrote:

> What do you have set in core-site.XML for io.sort.mb, io.sort.factor, and
> io.file.buffer.size? You should be able to adjust these and get past the
> heap issue. Be careful about how much ram you ave though, and don't st them
> too high.
>
> Rick
> On Jan 30, 2013 8:55 AM, "John Omernik" <[EMAIL PROTECTED]> wrote:
>
>> So it's filling up on the emitting stage, so I need to look at the task
>> logs and or my script that's printing to stdout as the likely culprits I am
>> guessing.
>>
>>
>>
>> On Wed, Jan 30, 2013 at 9:11 AM, Philip Tromans <
>> [EMAIL PROTECTED]> wrote:
>>
>>> That particular OutOfMemoryError is happening on one of your hadoop
>>> nodes. It's the heap within the process forked by the hadoop tasktracker, I
>>> think.
>>>
>>> Phil.
>>>
>>>
>>> On 30 January 2013 14:28, John Omernik <[EMAIL PROTECTED]> wrote:
>>>
>>>> So just a follow-up. I am less looking for specific troubleshooting on
>>>> how to fix my problem, and more looking for a general understanding of heap
>>>> space usage with Hive.  When I get an error like this, is it heap space on
>>>> a node, or heap space on my hive server?  Is it the heap space of the
>>>> tasktracker? Heap of the job kicked off on the node?  Which heap is being
>>>> affected? If it's not clear in my output, where can I better understand
>>>> this? I am sorely out of my league here when it comes to understanding the
>>>> JVM interactions of Hive and Hadoop, i.e. where hive is run, vs where task
>>>> trackers are run etc.
>>>>
>>>> Thanks is advance!
>>>>
>>>>
>>>>
>>>> On Tue, Jan 29, 2013 at 7:43 AM, John Omernik <[EMAIL PROTECTED]> wrote:
>>>>
>>>>> I am running a transform script that parses through a bunch of binary
>>>>> data. In 99% of the cases it runs, it runs fine, but on certain files I get
>>>>> a failure (as seen below).  Funny thing is, I can run a job with "only" the
>>>>> problem source file, and it will work fine, but when as a group of files, I
>>>>> get these warnings.  I guess what I am asking here is this: Where is the
>>>>> heap error? Is this occurring on the nodes themselves or, since this is
>>>>> where the script is emitting records (and potentially large ones at that)
>>>>> and in this case my hive server running the job may be memory light, could
>>>>> the issue actually be due to heap on the hive server itself?   My setup is
>>>>> 1 Hive node (that is woefully underpowered, under memoried, and under disk
>>>>> I/Oed) and 4 beefy hadoop nodes.  I guess, my question is the heap issue on
>>>>> the sender or the receiver :)
>>>>>
>>>>>
>>>>>
>>>>>
>>>>> 13-01-29 08:20:24,107 INFO org.apache.hadoop.hive.ql.io.CodecPool: Got
>>>>> brand-new compressor
>>>>> 2013-01-29 08:20:24,107 INFO
>>>>> org.apache.hadoop.hive.ql.exec.SelectOperator: 12 forwarding 1 rows
>>>>> 2013-01-29 08:20:24,410 INFO
>>>>> org.apache.hadoop.hive.ql.exec.ScriptOperator: 3 forwarding 10 rows
>>>>> 2013-01-29 08:20:24,410 INFO
>>>>> org.apache.hadoop.hive.ql.exec.SelectOperator: 4 forwarding 10 rows
>>>>> 2013-01-29 08:20:24,411 INFO
>>>>> org.apache.hadoop.hive.ql.exec.SelectOperator: 5 forwarding 10 rows
>>>>> 2013-01-29 08:20:24,411 INFO
>>>>> org.apache.hadoop.hive.ql.exec.SelectOperator: 6 forwarding 10 rows
>>>>> 2013-01-29 08:20:24,411 INFO
>>>>> org.apache.hadoop.hive.ql.exec.FilterOperator: 8 forwarding 10 rows
>>>>> 2013-01-29 08:20:24,411 INFO
>>>>> org.apache.hadoop.hive.ql.exec.SelectOperator: 9 forwarding 10 rows
>>>>> 2013-01-29 08:20:24,411 INFO
>>>>> org.apache.hadoop.hive.ql.exec.SelectOperator: 10 forwarding 10 rows
>>>>> 2013-01-29 08:20:24,412 INFO
>>>>> org.apache.hadoop.hive.ql.exec.SelectOperator: 12 forwarding 10 rows
>>>>> 2013-01-29 08:20:27,170 INFO
>>>>> org.apache.hadoop.hive.ql.exec.ScriptOperator: 3 forwarding 100 rows
*Dean Wampler, Ph.D.*
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