It turns out the hadoop-default.xml packaged in my custom
hadoop-0.19.0-core.jar has set the "io.file.buffer.size" to 131072 (128KB),
which means DfsBroker has to open a 128KB buffer for every open file. The
official hadoop-0.19.0-core.jar sets this value to 4096, which is more
reasonable for applications like Hypertable.
Donald


On Fri, Feb 20, 2009 at 11:55 AM, Liu Kejia (Donald)
<[email protected]>wrote:

> Caching might not work very well because keys are randomly generated,
> resulting in bad locality...
> Even it's Java, hundreds of kilobytes per file object is still very big.
> I'll profile HdfsBroker to see what exactly is using so much memory, and
> post the results later.
>
> Donald
>
>
> On Fri, Feb 20, 2009 at 11:20 AM, Doug Judd <[email protected]> wrote:
>
>> Hi Donald,
>>
>> Interesting.  One possibility would be to have an open CellStore cache.
>> Frequently accessed CellStores would remain open, while seldom used ones get
>> closed.  The effectiveness of this solution would depend on the workload.
>> Do you think this might work for your use case?
>>
>> - Doug
>>
>>
>> On Thu, Feb 19, 2009 at 7:09 PM, donald <[email protected]> wrote:
>>
>>>
>>> Hi all,
>>>
>>> I recently run into the problem that HdfsBroker throws out of memory
>>> exception, because too many CellStore files in HDFS are kept open - I
>>> have over 600 ranges per range server, with a maximum of 10 cell
>>> stores per range, that'll be 6,000 open files at the same time, making
>>> HdfsBroker to take gigabytes of memory.
>>>
>>> If we open the CellStore file on demand, i.e. when a scanner is
>>> created on it, this problem is gone. However random-read performance
>>> may drop due to the the overhead of opening a file in HDFS. Any better
>>> solution?
>>>
>>> Donald
>>>
>>>
>>
>> >>
>>
>

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