May 21, 2013

Benchmarking Percona Server TokuDB vs InnoDB

May 7, 2013 By 29 Comments

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 [...]

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More on MySQL transaction descriptors optimization

April 26, 2013 By Leave a Comment

Since my first post on MySQL transaction descriptors optimization introduced in Percona Server 5.5.30-30.2 and a followup by Dimitri Kravchuk, we have received a large number of questions on why the benchmark results in both posts look rather different. We were curious as well, so we tried to answer that question by retrying benchmarks on [...]

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MySQL 5.6 – InnoDB Memcached Plugin as a caching layer

March 29, 2013 By 10 Comments

A common practice to offload traffic from MySQL 5.6 is to use a caching layer to store expensive result sets or objects.  Some typical use cases include: Complicated query result set (search results, recent users, recent posts, etc) Full page output (relatively static pages) Full objects (user or cart object built from several queries) Infrequently [...]

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MySQL 5.6.10 Optimizer Limitations: Index Condition Pushdown

March 14, 2013 By 2 Comments

While preparing the webinar I will deliver this Friday, I ran into a quite interesting (although not very impacting) optimizer issue: a “SELECT *” taking half the time to execute than the same “SELECT one_indexed_column” query in MySQL 5.6.10. This turned into a really nice exercise for checking the performance and inner workings of one [...]

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MySQL 5.6 vs MySQL 5.5 and the Star Schema Benchmark

March 11, 2013 By 7 Comments

So far most of the benchmarks posted about MySQL 5.6 use the sysbench OLTP workload.  I wanted to test a set of queries which, unlike sysbench, utilize joins.  I also wanted an easily reproducible set of data which is more rich than the simple sysbench table.  The Star Schema Benchmark (SSB) seems ideal for this. [...]

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MySQL performance: Impact of memory allocators (Part 2)

March 8, 2013 By 12 Comments

Last time I wrote about memory allocators and how they can affect MySQL performance in general. This time I would like to explore this topic from a bit different angle: What impact does the number of processor cores have on different memory allocators and what difference we will see in MySQL performance in this scenario? [...]

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Accessing Percona XtraDB Cluster nodes in parallel from PHP using MySQL asynchronous queries

March 6, 2013 By 2 Comments

This post is followup to Peter’s recent post, “Investigating MySQL Replication Latency in Percona XtraDB Cluster,” in which a question was raised as to whether we can measure latency to all nodes at the same time. It is an interesting question: If we have N nodes, can we send queries to nodes to be executed in [...]

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InnoDB Full-text Search in MySQL 5.6: Part 2, The Queries!

March 4, 2013 By 7 Comments

This is part 2 in a 3 part series. In part 1, we took a quick look at some initial configuration of InnoDB full-text search and discovered a little bit of quirky behavior; here, we are going to run some queries and compare the result sets. Our hope is that the one of two things [...]

Filed Under: Insight for DBAs, Insight for Developers, MySQL Tagged With: , , , , ,

Investigating MySQL Replication Latency in Percona XtraDB Cluster

March 3, 2013 By 13 Comments

I was curious to check how Percona XtraDB Cluster behaves when it comes to MySQL replication latency — or better yet, call it data propagation latency. It was interesting to see whenever I can get stale data reads from other cluster nodes after write performed to some specific node. To test it I wrote quite a [...]

Filed Under: Benchmarks, Insight for DBAs, MySQL, XtraDB Cluster Tagged With: , ,

MySQL optimizer: ANALYZE TABLE and Waiting for table flush

February 27, 2013 By 3 Comments

The MySQL optimizer makes the decision of what execution plan to use based on the information provided by the storage engines. That information is not accurate in some engines like InnoDB and they are based in statistics calculations therefore sometimes some tune is needed. In InnoDB these statistics are calculated automatically, check the following blog [...]

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