I think you're talking about an insert buffer, not a transaction log, and in that case, no matter how big your insert buffer is, it will eventually saturate and you'll end up hitting the performance cliff of the B-tree. You really need better data structures (like fractal trees or LSM trees) to get past it.
no, i'm talking about transaction log ("redo log" in Oracle parlance). Switching log files causes checkpoint (ie. flush - it is when the index datablocks changed by the inserts you mention will finally hit the disk )
Oh ok, now I see what you're saying, it's still similar to an insert buffer in that case. B-tree behavior is still to blame for this, and if you make your log file bigger it lets you soak up more writes before you need to checkpoint but you'll either have even longer checkpoints eventually, or you'll run out of memory before you have to checkpoint.
We also checkpoint before trimming the log, but our checkpoints are a lot smaller because of write optimization.
yes, that is the point as big flush instead of many small ones would take either the same or, usually, less time than cumulative time of small flushes because of IO ordering and probability of some writes hitting the same data block.
