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Accumulo, mail # user - tservers running out of heap space


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Re: tservers running out of heap space
Anthony Fox 2012-11-29, 19:09
We're not on 1.4 yet, unfortunately.  Are there any config params I can
tweak to manipulate the compressor pool?
On Thu, Nov 29, 2012 at 1:49 PM, Keith Turner <[EMAIL PROTECTED]> wrote:

>
>
> On Thu, Nov 29, 2012 at 12:20 PM, Anthony Fox <[EMAIL PROTECTED]>wrote:
>
>> Compacting down to a single file is not feasible - there's about 70G in
>> 255 tablets across 15 tablet servers.  Is there another way to tune the
>> compressor pool or another mechanism to verify that this is the issue?
>
>
> I suppose another way to test this would be to run a lot of concurrent
> scans, but not enough to kill the tserver.  Then get a heap dump of the
> tserver and see if it contains a lot of 128k or 256k (can not remember
> exact size) byte arrays that are referenced by the compressor pool.
>
>
>>
>>
>> On Thu, Nov 29, 2012 at 12:09 PM, Keith Turner <[EMAIL PROTECTED]> wrote:
>>
>>>
>>>
>>> On Thu, Nov 29, 2012 at 11:14 AM, Anthony Fox <[EMAIL PROTECTED]>wrote:
>>>
>>>> I am experiencing some issues running multiple parallel scans against
>>>> Accumulo.  Running single scans works just fine but when I ramp up the
>>>> number of simultaneous clients, my tablet servers die due to running out of
>>>> heap space.  I've tried raising max heap to 4G which should be more than
>>>> enough but I still see this error.  I've tried with
>>>> table.cache.block.enable=false
>>>> table.cache.index.enable=false, and table.scan.cache.enable=false and
>>>> all combinations of caching enabled as well.
>>>>
>>>> My scans involve a custom intersecting iterator that maintains no more
>>>> state than the top key and value.  The scans also do a bit of aggregation
>>>> on column qualifiers but the result is small and the number of returned
>>>> entries is only in the dozens.  The size of each returned value is only
>>>> around 500 bytes.
>>>>
>>>> Any ideas why this may be happening or where to look for further info?
>>>>
>>>
>>> One know issues is hadoops compressor pool.  If you have a tablet with 8
>>> files and you query 10 terms, you will allocate 80 decompressors.   Each
>>> decompressor uses 128K.   If you have 10 concurrent queries, 10 terms, and
>>> 10 files then you will allocate 1000 decompressors.    These decompressors
>>> come from a pool that never shrinks.  So if you allocate 1000 at the same
>>> time, they will stay around.
>>>
>>> Try compacting your table down to one file and rerun your query just to
>>> see if that helps.   If it does, then thats an important clue.
>>>
>>>
>>>
>>>>
>>>> Thanks,
>>>> Anthony
>>>>
>>>
>>>
>>
>