Peter said me that previous results http://www.mysqlperformanceblog.com/2008/12/18/xtradb-benchmarks-15x-gain/ are too marketing, and we should show other results also.

Here is the run for CPU Bound,or it would be more correctly to say in-cache benchmark, because there is a lot of CPU remains idle. This run is exactly the same as Disk Bound but with innodb_buffer_pool_size=8G which is more than enough to fit all data in memory.

The XtraDB is showing very modest gain of about 2.5% in this case which can be attributed to measurement error too.

The story becomes more …

I guess it is first reaction on new storage engine - show me benefits. So there is benchmark I made on one our servers. It is Dell 2950 with 8CPU cores and RAID10 on 6 disks with BBU, and 32GB RAM on board with CentOS 5.2 as OS. This is quite typical server we recommend to run MySQL on. What is important I used Noop IO scheduler, instead of default CFQ. Disclaimer: Please note you may not get similar benefits on less powerful servers, as most important fixes in XtraDB are related to multi-core and multi-disks utilization. Also results may be different if load is CPU bound.

I compared MySQL 5.1.30 trees - MySQL 5.1.30 with standard InnoDB, MySQL 5.1.30 with InnoDB-plugin-1.0.2 and MySQL 5.1.30 with XtraDB (all plugins statically compiled in MySQL)

For benchmarks I used scripts that emulate TPCC load and datasize 40W (about 4GB in size), 20 client connections. Please note I used …

As you might have seen MySQL QA Team has published their benchmarks for MySQL 5.0.72 and 5.1.30.

It is interesting to compare with results I posted previously

The quote from the results mentioned above:

"Maybe you’ve seen some claims by others in the MySQL community that MySQL 5.1 runs slower than MySQL 5.0. Maybe you’ve also seen some claims by others in the MySQL community that MySQL 5.1 runs faster than MySQL 5.0.

Guess what? They’re both right. "

But is it really what results are telling us ?

I do not think so. When you're doing benchmarks you should be comparing best performance settings for given application and conditions. For example it is unfair to …

We've recently done benchmarks comparing different MySQL versions in terms of their CPU efficiently in TPC-C like Workload. We did it couple of weeks ago so MySQL 5.0.67, MySQL 5.1.29 and Innodb Plugin 1.0.1 were used which are not very recent, though we do not think results will differ a lot with today versions.

Results are as follows:

The system was 2* Quad Core Xeon E5310, CentOS 5, Data stored on ramfs. We controlled number of cores used with /sys/devices/system/cpu/cpuX/online Maximum performance for each number of cores was taken though it was reached with number of sessions matching number of cores. Just 1 "Data warehourse" was used to keep data small.

As you can see there is some gain for MySQL from read-write lock split patch (found in Percona Builds) though it is not very significant for this workload. To isolate effect of this patch …

Do you know that there are two limits about dirty (modified but not flushed to disk) blocks of InnoDB buffer pool? One is the limit of "amount". The other is the limit of "age".

-- limit of "amount" --

As you know, buffer pool of InnoDB works as write-back cache of its datafiles. If the buffer pool is filled by dirty blocks, InnoDB cannot allocate new blocks without flushing the dirty blocks and the performance would get worse. This is the limit of dirty block "amount". We can avoid this limit by setting 'innodb_max_dirty_pages_pct' smaller or setting the larger buffer pool size. We might be never at a loss about the limit.

The another limit we should understand is limit of dirty block "age".

-- limit of "age" --

As you know again, because InnoDB write the modifies of datafile to transaction log file synchronously, InnoDB is allowed to treat its buffer pool as write-back …

As you likely have seen Sun has posted the new SpecJAppServer Results More information from Tom Daly can be found here These results are quite interesting for me as I worked on some of the previous SpecJAppServer Benchmarks several years ago while being employed by MySQL.

These are great results, plus they can be relevant to a lot of us because commodity x86 based hardware was used for the test. So it is not just about Sun it is about OpenSource hardware on Commodity Hardware.

As usually with results from such benchmarks there is no direct comparison available. The configuration Tom compares results to are not OpenSource and on the hardware of the different class so it is really hard to see what really caused the difference. It would be very interesting to …

This is a fun question I've been wanting to test for some time.  How much overhead does a trivial WHERE clause add to a MySQL query?  To find out, I set my InnoDB buffer pool to 256MB and created a table that's large enough to test, but small enough to fit wholly in memory:

PLAIN TEXT SQL:

1. CREATE TABLE `t` (
2. `a` date NOT NULL
3. ) ENGINE=InnoDB DEFAULT CHARSET=latin1;
4.  
5. INSERT INTO t(a) VALUES(current_date);
6. INSERT INTO t SELECT * FROM t;

I repeated the last statement until it got slow enough that I thought I could do a reasonable test; at this point there were 8388608 rows. I then optimized the table and restarted MySQL. The table ended up at 237MB.

Now let's see how long a table scan with no WHERE clause …

We are going to show the effects of the new patches applied to Percona HighPerf release. As you see from the following graphs, there is significant difference to normal version when the data bigger than buffer pool (right graph shows CPU usage)

The workload emulates TPC-C and has a same characteristic to DBT-2 (it is not DBT-2, but custom scripts, we will publish them eventually). There are no delays between transactions (no thinking time, no keying time), it uses MySQL C API and the server side prepared statement.

The server has 8core CPU and RAID storage (RAID10 / 6 disks). The data population is along to the scale factor 40WH (:=~4GB). It is enough bigger than the data cache of the storage.

main common settings

innodb_buffer_pool_size = 2048M
innodb_thread_concurrency = 0 …

It is that time of the year when many PostgreSQL fans gather in Ottawa, Canada for PGCon 2008 next week. This will be my first visit to PGCon in Ottawa. Earlier this year I had presented two sessions "PostgreSQL and Benchmarks" and "Best Practices of PostgreSQL on Solaris" at PostgreSQL Conference 2008 East in Maryland. Thanks to that visit, this time I might recognize many people by face this time around.

Sun is a Gold Sponsor at PGCon 2008. There will be quite a bit of presence from Sun in PGCon. Josh, Max, Robert, Magne, Zdenek, Jim, Mayuresh et all will be present out there.

Josh Berkus is doing a tutorial on  "GUCs: A Three Hour Tour" on …

Today is the first day at the conference (aside from the tutorials, which were yesterday). Here’s what I went to:

New Subquery Optimizations in 6.0

By Sergey Petrunia. This was a similar session to one I went to last year. MySQL has a few cases where subqueries are badly optimized, and this session went into the details of how this is being addressed in MySQL 6.0. There are several new optimization techniques for all types of subqueries, such as inside-out subqueries, materialization, and converting to joins. The optimizations apply to scalar subqueries and subqueries in the FROM clause. Performance results are very good, depending on which data you choose to illustrate. The overall point is that the worst-case subquery nastiness should be resolved. I’m speaking of WHERE NOT IN(SELECT…) and friends. It remains to be seen how this shakes out as 6.0 matures, and what edge cases will pop up.

The Lost Art Of the Self …