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Finding your MySQL High-Availability solution – The questions
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MySQL-Memcached or NOSQL Tokyo Tyrant - part 3
This is part 3 of our series. In part 1 we talked about boosting performance with memcached on top of MySQL, in Part 2 we talked about running 100% outside the data with memcached, and now in Part 3 we are going to look at a possible solution to free you from the database. The solution I am going to discuss here is Tokyo Cabinet and Tyrant. I am not going to give you a primer or Tutorial on
Managing Slave Lag with MySQL Replication
The question I often get is how far MySQL may fall behind and how to keep replication from lagging. The lag you will see will vary a lot from application to the application and from load to load. Plus what is the most important within same application the lag will likely have spikes – most of applications would have typical lag within few milliseconds while there will be rare cases when replicatio
MySQL Master-Master replication manager released
The MySQL Master-Master replication (often in active-passive mode) is popular pattern used by many companies using MySQL for scale out. Most of the companies would have some internal scripts to handle things as automatic fallback and slave cloning but no Open Source solution was made available. Few months ago we were asked to implement such solution for one of the customers and they kindly agreed
PBXT benchmarks
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To UUID or not to UUID ?
Brian recently posted an article comparing UUID and auto_increment primary keys, basically advertising to use UUID instead of primary keys. I wanted to clarify this a bit as I’ve seen it being problems in so many cases. First lets look at the benchmark – we do not have full schema specified in the article itself so it results are not absolutely clear but we already can have certain conclusions. Da
Is it query which needs to be optimized ?
Last few days I had a lot of a lot of questions at MySQL Performance Forum as well as from our customers regarding query optimization… which had one thing in common – It is not query which needed to be optimized. Way too frequently people design schema first and then think how the queries they are looking to be answered can be expressed using that schema… which just does not work as a lot of rows
System size and Performance Optimization
Performance optimization is never ending story, you can virtually always find something else to optimize but while on generic system, not tuned by expert you often can get significant performance increase in the matter of hours further performance improvements become more and more time consuming and expensive and gains smaller. This observation does not only apply to MySQL but to systems running o
Using index for ORDER BY vs restricting number of rows.
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Getting use of Slave in MySQL Replication
MySQL Replication is asynchronous which causes problems if you would like to use MySQL Slave as it can contain stale data. It is true delay is often insignificant but in times of heavy load or in case you was running some heavy queries on the master which not take time to replicate to the slave replication lag can be significant. Also even very small lag can cause the problems – for example you’ve
Opening Tables scalability
I was restarting MySQL on box with 50.000 of Innodb tables and again it took couple of hours to reach decent performance because of “Opening Tables” stage was taking long. Part of the problem is Innodb is updating stats on each table open which is possibly expensive operation, but really it is only great test case for general MySQL problem. During warmup process I noticed I get very low CPU usage
MySQL Performance Blog � Cache Performance Comparison
Jay Pipes continues cache experiements and has compared performance of MySQL Query Cache and File Cache. Jay uses Apache Benchmark to compare full full stack, cached or not which is realistic but could draw missleading picture as contribution of different components may be different depending on your unique applications. For example for application containing a lot of clode but having only couple
Database problems in MySQL/PHP Applications
Article about database design problems is being discussed by Kristian. Both article itself and responce cause mixed feellings so I decided it is worth commenting: 1. Using mysql_* functions directly This is probably bad but I do not like solutions proposed by original article ether. PEAR is slow as well as other complex conectors. I have not yet tested PDO but would not expect it to beat MySQLi in
MySQL Crash Recovery
MySQL is known for its stability but as any other application it has bugs so it may crash sometime. Also operation system may be flawed, hardware has problems or simply power can go down which all mean similar things – MySQL Shutdown is unexpected and there could be various inconsistences. And this is not only problem as we’ll see. MySQL has angel process mysqld_safe which will restart MySQL Serve
Why MySQL Could Be Slow With Large Tables
If you’ve been reading enough database-related forums, mailing lists, or blogs you have probably heard complains about MySQL being unable to handle more than 1,000,000 (or select any other number) rows by some of the users. On the other hand, it is well known with customers like Google, Yahoo, LiveJournal, and Technorati, MySQL has installations with many billions of rows and delivers great perfor
MySQL Performance Blog InnoDB memory usage
There are many questions how InnoDB allocates memory. I’ll try to give some explanation about the memory allocation at startup. Some important constants: NBLOCKS=count of block in innodb_buffer_pool = innodb_buffer_pool_size / 16384 OS_THREADS= if (innodb_buffer_pool_size >= 1000Mb) = 50000 else if (innodb_buffer_pool_size >= 8Mb) = 10000 else = 1000 (it’s true for *nixes, for Windows there is a b
Group commit and XA
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Merge Tables Gotcha
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