Which are the most relevant parameters I should look into (to keep as much as possible in memory, improve index maintanance performance, etc.)? This did not seem to help anything. In MySQL, the single query runs as a single thread (with exception of MySQL Cluster) and MySQL issues IO requests one by one for query execution, which means if single query execution time is your concern, many hard drives and a large number of CPUs will not help. One of the reasons elevating this problem in MySQL is a lack of advanced join methods at this point (the work is on a way) – MySQL can’t do hash join or sort-merge join – it only can do nested loops method, which requires a lot of index lookups which may be random. Would be a great help to readers. The reason I’m asking is that I’ll be inserting loads of data at the same time, and the insert has to be relatively quick. Soon after the innoDB-buffer gets depleted, they drop down to roughly 5K/sec. If you started from in-memory data size and expect gradual performance decrease as the database size grows, you may be surprised by a severe drop in performance. I didn’t said I wanted to combine indexes, I was talking about a combined index. Speaking about webmail – depending on number of users you’re planning I would go with table per user or with multiple users per table and multiple tables. Might be for some reason ALTER TABLE was doing index rebuild by keycache in your tests, this would explain it. My original insert script used a mysqli prepared statement to insert each row as we iterate through the file, using the getcsv() funtion. Can anybody here advice me, how to proceed, maybe someone, who already have experienced this. A word about partitions: INSERT-statements in MySQL do not support pruning, so all your partitions will be scanned on each statement for unique index matching. – may i remove old_passwords=1 & big-tables? For in-memory workload indexes, access might be faster even if 50% of rows are accessed, while for disk IO bound access we might be better off doing a full table scan even if only a few percent or rows are accessed. I’m not worried if I only have a few in there. Although the selects now take 25% more time to perform, it’s still around 1 second, so it seams quite acceptable to me, since there are more than 100 million records in the table, and if it means that the inserts are faster. Basically: we’ve moved to PostgreSQL, which is a real database and with version 8.x is fantastic with speed as well. This query takes about 45 minutes to execute (DELETE FROM Data WHERE Cat=’1021′ AND LastModified, I am having a problem when I try to “prune” old data. You need a lot of work on your technical writing skills. OK, good to know. [mysqld] innodb_buffer_pool_size = 2G innodb_log_buffer_size=5m innodb_flush_log_at_trx_commit=2 innodb_lock_wait_timeout=120 datadir=/var/lib/mysql socket=/var/lib/mysql/mysql.sock user=mysql init_connect=’SET collation_connection = utf8_general_ci; SET NAMES utf8;’ default-character-set=utf8 character-set-server=utf8 collation-server=utf8_general_ci [client] default-character-set=utf8 set-variable = max_allowed_packet=32M [mysqld_safe] log-error=/var/log/mysqld.log pid-file=/var/run/mysqld/mysqld.pid. As I mentioned sometime if you want to have quick build of unique/primary key you need to do ugly hack – create table without the index, load data, replace the .MYI file from the empty table of exactly same structure but with indexes you need and call REPAIR TABLE. Due to the usage of subqueries, I think this may be the main cause of the slowness. 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