Hi,

OK, could you post the 'Statistics' part of that file?

Regards,
Thomas



On Tue, Jul 9, 2013 at 2:11 PM,
<[email protected]<javascript:_e({}, 'cvml',
'[email protected]');>
> wrote:

> I posted in both to get a wider reach. Would be using only one in the
> future.
>
>  I had stopped both the applications and then applied the Recover tool
> option to generate an SQL file with the same name as the DB. This was done
> when the database file was of large size. One thing noted was that the size
> of the SQL file too was very large close to the .db file.
>
> On Tuesday, July 9, 2013 12:01:13 AM UTC+5:30, Thomas Mueller wrote:
>
>> Hi,
>>
>> You have sent the same question to http://stackoverflow.com/**
>> questions/17488935/continuous-**increase-in-h2-db-size-after-**
>> dropping-and-loading-same-**data-repeatedl<http://stackoverflow.com/questions/17488935/continuous-increase-in-h2-db-size-after-dropping-and-loading-same-data-repeatedl>
>>
>> Please don't use _both_ the Google Group and StackOverflow at the same
>> time for the same question. Use one or the other.
>>
>> Did you run the recover tool _before_ you restored it? To find out what
>> is using the disk space you would need to run it _before_ that (when the
>> database file is large).
>>
>> Regards,
>> Thomas
>>
>>
>>
>> On Mon, Jul 8, 2013 at 8:53 AM, Noel Grandin <[email protected]>wrote:
>>
>>> This is pretty much guaranteed to be because of open transactions.
>>> Unfortunately there is no easy way of finding them, short of monitoring
>>> your own code to check that it is either using AutoCommit or calling
>>> commit()/rollback() timeously.
>>>
>>>
>>> On 2013-07-08 07:31, [email protected] wrote:
>>>
>>> I have an H2 db named temp.h2.db which is accessed by two applications.
>>> The first one accesses it through embedded mode and the second one through
>>> server mode. Through the second application I load data into the database.
>>> But even when I drop the previous values and load the same data repeatedly,
>>> the db size increases. From about 200mb, it increased to about 2Gb. This
>>> happens even when I drop all tables and load a fresh set of data (which is
>>> almost of the same size as the previous set of data). Is this a bug?
>>>
>>>
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