this last bench was Inserting 500000 t1 records and 3000000 t2 records

> MySQLDB... 
> ~7573 i/s 0:06:36.124 (396124 ms)
> Close  0:00:00.001 (1 ms)
> HSQLDB... 
> ~4853 i/s 0:10:18.080 (618080 ms)
> Close  0:00:00.005 (5 ms)
> H2DB... 
> ~1874 i/s 0:26:40.641 (1600641 ms)
> Close  0:00:08.438 (8438 ms)
>
>
> Le lundi 12 août 2013 12:52:18 UTC+2, Noel Grandin a écrit :
>>
>>  
>> On 2013-08-12 06:12, Pierre wrote:
>>  
>> Thanks Thomas but the profiler doesn't showed something interesting. 
>> Anyway, the issue is related to H2, it doesn't supports massive inserts. 
>> When the table size > 3 millions rows, it begins to be very slow. Adding 
>> LOG=0;UNDO_LOG=0;NOLOCK/WHATEVER optmisation just delay the ineluctable 
>> slow insertions, it optimize a lot but only if < 3 millions rows.
>>
>> I know that because I created a bench and just looks at the numbers : 
>>  
>>
>> Two things are at work here:
>>
>> (1) MySQL and HSQLDB cheat a little by not performing fsync() as often as 
>> they should, so they are trading off increased risk of losing data against 
>> better speed
>>
>> (2) When you create an FK constraint, we create an index on the column to 
>> speed up the foreign key checking, which it looks like MySQL and HSQLDB do 
>> not do. This costs us in the insert benchmark because we have to update an 
>> extra on-disk datastructure.
>>
>> When I take those two factors out, the numbers start looking roughly 
>> comparable.
>>
>> One thing you might want to do when trying to run large volumes of data 
>> through H2 is to bump up our cache size using something like:
>> ";CACHE_SIZE=65536" in the URL.
>>
>> Our default cache setting is a little conservative for larger deployments.
>>
>>
>>
>> 

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