There are times where you need to know exactly how much memory the mysqld server (or any other program) is using, where (i.e. for what function) it was allocated, how it got there (a backtrace, please!), and at what point in time the allocation happened. For example; you may have noticed a sharp memory increase [...]
Minimizing Downtime from Lengthy AWS Outages
October 24, 2012 By 6 Comments
Well, it happened again… Another lengthy EBS outage in the US-East region impacted several sites across the net. While failures like this are rare, they can be quite costly and translate into headaches for the operations team when impact production systems for any length of time. At Percona, we routinely help clients architect and deploy [...]
SQL Injection Questions Followup
July 26, 2012 By 2 Comments
I presented a webinar today about SQL Injection, to try to clear up some of the misconceptions that many other blogs and articles have about this security risk. You can register for the webinar even now that I’ve presented it, and you’ll be emailed a link to the recording, which will be available soon. During [...]
How FLUSH TABLES WITH READ LOCK works with Innodb Tables
March 23, 2012 By 20 Comments
Many backup tools including Percona Xtrabackup, MyLVMBackup and others use FLUSH TABLES WITH READ LOCK to temporary make MySQL read only. In many cases the period for which server has to be made read only is very short, just few seconds, yet the impact of FLUSH TABLES WITH READ LOCK can be quite large because [...]
Statement based replication with Stored Functions, Triggers and Events
December 16, 2011 By 4 Comments
Statement based replication writes the queries that modify data in the Binary Log to replicate them on the slave or to use it as a PITR recovery. Here we will see what is the behavior of the MySQL when it needs to log “not usual” queries like Events, Functions, Stored Procedures, Local Variables, etc. We’ll [...]
MySQL versions shootout
October 10, 2011 By 6 Comments
As part of work on “High Performance MySQL, 3rd edition”, Baron asked me to compare different MySQL version in some simple benchmark, but on decent hardware. So why not.
Flexviews – part 3 – improving query performance using materialized views
April 4, 2011 By 20 Comments
Combating “data drift” In my first post in this series, I described materialized views (MVs). An MV is essentially a cached result set at one point in time. The contents of the MV will become incorrect (out of sync) when the underlying data changes. This loss of synchronization is sometimes called drift. This is conceptually [...]
Is VoltDB really as scalable as they claim?
February 28, 2011 By 3 Comments
Before I begin, a disclaimer. VoltDB is not a customer, and did not pay Percona or me to investigate VoltDB’s scalability or publish this blog post. More disclaimers at the end. Short version: VoltDB is very scalable; it should scale to 120 partitions, 39 servers, and 1.6 million complex transactions per second at over 300 [...]
Star Schema Bechmark: InfoBright, InfiniDB and LucidDB
January 7, 2010 By 48 Comments
In my previous rounds with DataWarehouse oriented engines I used single table without joins, and with small (as for DW) datasize (see http://www.mysqlperformanceblog.com/2009/10/02/analyzing-air-traffic-performance-with-infobright-and-monetdb/, http://www.mysqlperformanceblog.com/2009/10/26/air-traffic-queries-in-luciddb/, http://www.mysqlperformanceblog.com/2009/11/02/air-traffic-queries-in-infinidb-early-alpha/). Addressing these issues, I took Star Schema Benchmark, which is TPC-H modification, and tried run queries against InfoBright, InfiniDB, LucidDB and MonetDB. I did not get results for MonetDB, will [...]
Analyzing air traffic performance with InfoBright and MonetDB
October 2, 2009 By 50 Comments
Accidentally me and Baron played with InfoBright (see http://www.mysqlperformanceblog.com/2009/09/29/quick-comparison-of-myisam-infobright-and-monetdb/) this week. And following Baron’s example I also run the same load against MonetDB. Reading comments to Baron’s post I tied to load the same data to LucidDB, but I was not successful in this. I tried to analyze a bigger dataset and I took public [...]
