High Rate insertion with MySQL and InnodbPeter Zaitsev
I again work with the system which needs high insertion rate for data which generally fits in memory. Last time I worked with similar system it used MyISAM and the system was built using multiple tables. Using multiple key caches was the good solution at that time and we could get over 200K of inserts/sec.
This time I worked with Innodb tables… it was a different system with different table structure, not to mention different hardware so It can’t be compared directly, still it is nice to see you can get the numbers as high with Innodb too.
I will spare you all experiments we went through and just share final numbers. On 8 core Opteron Box we were able to achieve 275K inserts/sec at which time we started to see load to get IO bound because of log writes and flushing dirty buffers. I’m confident you can get to 400K+ inserts/sec on faster hardware and disks (say better RAID or Flash) which is a very cool number. Of course, mind you this is in memory insertion in the simple table and table with long rows and bunch of indexes will see lower numbers.
So what’s the deal ? First MySQL 5.5 (frankly I did not try Percona Server 5.1 in this case) With MySQL 5.1 and Innodb Plugin we could see 40%+ CPU wasted on mutex spinlocks (per oprofile), which went down to about 15% in MySQL 5.5.8 with 8 concurrent threads. This both shows there is a substantial gains as well as room for more performance optimizations. Dmitri has good suggestions on tuning MySQL 5.5 and this is what I used for start. Using multiple buffer pools with innodb_buffer_pool_instances=8 was very important.
Second thing – Partitioning. Unfortunately MySQL 5.5 leaves the huge bottleneck for write workloads in place – there is per index rw lock, so only one thread can insert index entry at the time, which can be significant bottleneck. We got 2x+ better performance by hash partitioning table by one of the columns and I would expect gains can be higher with more cores. PARTITION BY HASH(col) PARTITIONS 8 is what we used. This looks like a good workaround but remember partitioning can impact performance of your select queries dramatically.
The inserts in this case of course are bulk inserts… using single value inserts you would get much lower numbers. In fact we used load data infile which is one of the ways to get a great performance (the competing way is to have prepared bulk insert statements).
We need to try new Percona Server 5.5 on our Cisco box to see if we can get to 500K inserts/sec – this can be a nice round number 🙂