InnoDB has an oft-unused parameter innodb_concurrency_tickets that seems widely misunderstood. From the docs: "The number of threads that can enter InnoDB concurrently is determined by the innodb_thread_concurrency variable. A thread is placed in a queue when it tries to enter InnoDB if the number of threads has already reached the concurrency limit. When a thread is allowed to enter InnoDB, it is given a number of “free tickets” equal to the value of innodb_concurrency_tickets, and the thread can enter and leave InnoDB freely until it has used up its tickets. After that point, the thread again becomes subject to the concurrency check (and possible queuing) the next time it tries to enter InnoDB. The default value is 500..."

What this means from a practical perspective is that each query is allocated 500 tickets when it begins executing. Each time it

There was a discussion on LinkedIn one month ago that caught my eye:

Database search by "within x number of miles" radius?

Anyone out there created a zipcode database and created a "search within x numer of miles" function ?
Thankful for any tips you can throw my way..

J

A few people commented that some solutions wouldn't scale. To understand why these sorts of geographic search queries are problematic in MySQL, it's best to show some execution plans on dummy data:

I recently had the chance to witness the effects of innodb_adaptive_flushing on the performance of InnoDB Plugin 1.0.5 in the wild, which Yasufumi wrote about previously here and here.

The server in question was Solaris 10 with 8 disk RAID10 and 2 32GB SSDs used for ZIL and L2ARC, 72G RAM and 40G buffer pool. We started it up with innodb_adaptive_flushing=OFF and innodb_doublewrite=OFF, then ramped up traffic and everything looked stable ... but I noticed one troubling thing: ~2GB of uncheckpointed data.

mysql> SHOW INNODB STATUS\G
....
Database pages      2318457
Old database pages  855816
Modified db pages   457902
Log flushed up to   10026890404067
Last checkpoint at

There are a few parameters that may be worth looking at when first installing InfiniDB; NumBlocksPct for managing memory, PmMaxMemorySmallSide for optimizing join behaviors, and MaxOutstandingRequests which changes how individual queries share resources.

The NumBlocksPct parameter manages the amount of memory on each server allocated to store data blocks and is expressed as a % of server memory. For example, to allocate 5 GB for the data buffer cache for a server with 8GB memory, set thRead More...

There are a few parameters that may be worth looking at when first installing InfiniDB; NumBlocksPct for managing memory, PmMaxMemorySmallSide for optimizing join behaviors, and MaxOutstandingRequests which changes how individual queries share resources.

The NumBlocksPct parameter manages the amount of memory on each server allocated to store data blocks and is expressed as a % of server memory. For example, to allocate 5 GB for the data buffer cache for a server with 8GB memory, set thRead More...

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 Tyrant and Cabinet, there are plenty of these out there already.  Instead I want to see what sort of performance we can see compared to MySQL and Memcached, and later on other NoSQL solutions.  Tokyo actually allows you to use several types of databases that are supported,

For the my previous post, there was comment to suggest to test db_STRESS benchmark on XtraDB by Dimitri. And I tested and tuned for the benchmark. I will show you the tunings. It should be also tuning procedure for general heavy writing workloads.

At first, <tuning peak performance>. The next, <tuning purge operation> to stabilize performance  and to avoid decreasing performance.

<test condition>

Server:
PowerEdge R900, Four Quad Core E7320 Xeon, 2.13GHz, 32GB Memory, 16X2GB, 667MHz

db_STRESS:
32 sessions, RW=1, dbsize = 1000000, no thinktime

XtraDB: (mysql-5.1.39 + XtraDB-1.0.4-current)
innodb_io_capacity = 4000
innodb_support_xa = false

As you may know, InnoDB has 2 limits for unflushed modified blocks in the buffer pool. The one is from physical size of the buffer pool. And the another one is oldness of the block which is from the capacity of transaction log files.

In the case of heavy updating workload, the modified ages of the many blocks are clustered. And to reduce the maximum of the modified ages InnoDB needs to flush many of the blocks in a short time, if these are not flushed at all. Then the flushing storm affect the performance seriously.

We suggested the "adaptive_checkpoint" option of constant flushing to avoid such a flushing storm. And finally, the newest InnoDB Plugin 1.0.4 has the new similar option "adaptive_flushing" as native.

Let's check the adaptive flushing options at this post.

HOW THEY WORK

<

I will co-present in webinar on Performance Challenges and Solutions for IO Bound Workloads in MySQL. My part of the presentation will be speaking about why switching from CPU bound workload to IO bound is such an important event, how to prepare to it as well as how to keep your application performance good as the data growths.

The Brian's portion of webinar will focus on the Schooner offering as example of flash based appliance - one of solutions I mention in my presentation.

It should be interesting whenever you're interested in Schooner appliance offerings, flash or scaling MySQL in General.

You can follow this url to register.

Entry posted by peter |

Ronald Bradford last week posted about memcached not being multi-threaded on Ubuntu, something he discovered via some small utilities that are bundled with libmemcached, written by Brian Aker.

When I noticed there were no Ubuntu packages for libmemcached (or the CLI tools) I decided to create some.

For your enjoyment: http://ubuntu.cafuego.net/dists/jaunty-cafuego/memcached/ (Source debs are included)

The repository also contains a memcached that has been re-compiled with multithreading enabled.

I wanted to share a little rule of thumb I sometimes use to decide which columns should come first in an index. This is not specific to MySQL, it's generally applicable to any database server with b-tree indexes. And there are a bunch of subtleties, but I will also ignore those for the sake of simplicity.

Let's start with this query, which returns zero rows but does a full table scan. EXPLAIN says there are no possible_keys.

Don't try to figure out the meaning of the query, because that'll