November 24, 2014

Benchmarking Percona Server TokuDB vs InnoDB

After compiling Percona Server with TokuDB, of course I wanted to compare InnoDB performance vs TokuDB. I have a particular workload I’m interested in testing – it is an insert-intensive workload (which is TokuDB’s strong suit) with some roll-up aggregation, which should produce updates in-place (I will use INSERT .. ON DUPLICATE KEY UPDATE statements […]

Knowing what pt-online-schema-change will do

pt-online-schema-change is simple to use, but internally it is complex.  Baron’s webinar about pt-online-schema-change hinted at several of the tool’s complexities.  Consequently, users often want to know before making changes what pt-online-schema-change will do when it runs.  The tool has two options to help answer this question: –dry-run and –print. When ran with –dry-run and –print, pt-online-schema-change changes nothing […]

Statement based replication with Stored Functions, Triggers and Events

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 […]

Distributed Set Processing with Shard-Query

Can Shard-Query scale to 20 nodes? Peter asked this question in comments to to my previous Shard-Query benchmark. Actually he asked if it could scale to 50, but testing 20 was all I could due to to EC2 and time limits. I think the results at 20 nodes are very useful to understand the performance: […]

Flexviews – part 3 – improving query performance using materialized views

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 […]

How innodb_open_files affects performance

Recently I looked at table_cache sizing which showed larger table cache does not always provides the best performance. So I decided to look at yet another similar variable – innodb_open_files which defines how many files Innodb will keep open while working in innodb_file_per_table mode. Unlike MyISAM Innodb does not have to keep open file descriptor […]

Drilling down to the source of the problem

I had an interesting tuning case few days ago. The system serving high traffic using Innodb tables would be stalling every so often causing even very simple queries both reads and writes taking long time to complete, with progress almost paused (dropping from thousands to tens of queries per second). On the surface the problem […]

Choosing innodb_buffer_pool_size

My last post about Innodb Performance Optimization got a lot of comments choosing proper innodb_buffer_pool_size and indeed I oversimplified things a bit too much, so let me write a bit better description. Innodb Buffer Pool is by far the most important option for Innodb Performance and it must be set correctly. I’ve seen a lot […]


Many people asked me to publish a walk through SHOW INNODB STATUS output, showing what you can learn from SHOW INNODB STATUS output and how to use this info to improve MySQL Performance. To start with basics SHOW INNODB STATUS is command which prints out a lot of internal Innodb performance counters, statistics, information about […]