Hi VIn, See benchmarks at http://www.h2database.com/html/performance.html to get an idea of maximum statement/seconds ratio, and http://www.h2database.com/html/performance.html#database_performance_tuning.
See fast import advices at http://www.h2database.com/html/performance.html#fast_import. To get an idea of the upper limit for this operation use an in-memory database with the other advices. These URLs can be (in general) a good start point to experimentation: |jdbc:h2:~/test;LOG=0;CACHE_SIZE=512000;LOCK_MODE=0;MULTI_THREADED=1;||DB_CLOSE_DELAY=10| | ||jdbc:h2:||split:nioMapped:test||;LOG=0;CACHE_SIZE=512000;LOCK_MODE=0;MULTI_THREADED=1||;DB_CLOSE_DELAY=10||||;CACHE_TYPE=TQ||| | jdbc:h2:mem:test;LOG=0;CACHE_SIZE=256000;LOCK_MODE=0;MULTI_THREADED=1||;DB_CLOSE_DELAY=10||||;CACHE_TYPE=TQ| ||You need to use proper JVM's start parameters (like -Xmx ). | |Please note that |CREATE TABLE(...) ... AS SELECT ...| is faster than |CREATE TABLE(...); INSERT INTO ... SELECT ...|. Import a CSV file is an operation that don't benefit too much of multi-tasking by nature, so I don't think MULTI_THREADED=1 has much impact. regards, Dario El 14/04/11 03:31, Vin escribió: > I did run those tests on a desktop (2.3 GHz Quad core, 2 GB RAM, 300 > GB HDD @7200). > I got a 70s reading for 2 M records, so I guess it was the hardware. > > On Apr 12, 7:29 pm, Dario Fassi <[email protected]> wrote: >> Let me say that with the mentioned hardware you are getting very good >> numbers: >> 2M records parsed and updated on DB in 176 secs. ~ 11364 tps >> 10M records in 60 secs. ~ 167000 tps !!! >> With witch technology are you getting 167000 tps on a laptop ?? >> >> El 11/04/11 15:05, Vin escribi : >>> For loading 2 M rows into the database - it takes around 176 seconds. >>> (Laptop Specs - 1.6 GHz Intel Pentium M, 2 GB RAM, 80 GB HDD @5400) > -- You received this message because you are subscribed to the Google Groups "H2 Database" group. To post to this group, send email to [email protected]. To unsubscribe from this group, send email to [email protected]. For more options, visit this group at http://groups.google.com/group/h2-database?hl=en.
