"shutdown compact" recovers about 8% of the space.

On Friday, November 1, 2013 10:56:02 AM UTC-7, Thomas Mueller wrote:
>
> Hi,
>
> Did you use the SQL statement SHUTDOWN COMPACT? 
> http://h2database.com/html/grammar.html#shutdown
>
> Regards,
> Thomas
>
>
>
> On Fri, Nov 1, 2013 at 6:54 PM, Brian Craft <[email protected]<javascript:>
> > wrote:
>
>> Just for comparison, I swapped out this table for the leveldb java port. 
>> In that case the 30G of byte arrays becomes 30G + change, which is about 
>> what I would expect for the db overhead. The read performance of leveldb 
>> was not much different than h2 for this data (it's mostly limited by disk 
>> seeks... will do an ssd test next), but the nearly 3X increase in data size 
>> in h2 is problematic for data at this scale.
>>
>>
>> On Friday, October 11, 2013 9:15:48 AM UTC-7, Brian Craft wrote:
>>>
>>> I'm storing a bunch of 400 byte varbinary objects in a table like so:
>>>
>>> CREATE CACHED TABLE PUBLIC.SCORES(
>>>     ID INT DEFAULT (NEXT VALUE FOR PUBLIC.SYSTEM_SEQUENCE_**
>>> 0D2CC30B_0ED7_4EB5_A0D4_**6448B031FC02) NOT NULL NULL_TO_DEFAULT 
>>> SEQUENCE PUBLIC.SYSTEM_SEQUENCE_**0D2CC30B_0ED7_4EB5_A0D4_**6448B031FC02 
>>> SELECTIVITY 100,
>>>     EXPSCORES VARBINARY(400) NOT NULL SELECTIVITY 67
>>> )
>>>
>>> There are 84440461 rows, so a bit over 30G of data. In h2 this becomes 
>>> over 90G on disk. Doing a dump/restore with SCRIPT/RUNSCRIPT, it becomes 
>>> over 100G (I was hoping it would shrink, by reducing fragmentation).
>>>
>>> I did expect some size cost for putting it in a sql database, but this 
>>> is fairly huge. What would be causing this, and are there any settings that 
>>> would affect it?
>>>
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