Recently, I found myself needing MariaDB 5.1.60 for Windows for some testing purposes. Therefore, I needed to build it from source. I ended up using what I’d call a “blend” of the commands listed in this “how-to” and the readme file INSTALL-WIN-SOURCE, so I thought I’d post those steps.

1. Download 5.1.60 MariaDB source from here.

2. cd C:\mariadb-5.1

3. win\configure.js

4. cmake .

5. VS: File -> Open -> Solution -> MySql.sln
6. VS: Build -> Build Solution
7. VS: Right-click “PACKAGE” -> Build (in “Solution Explorer” View)

That’s it.

Let’s fire it up:

MariaDB> select version(); …

 
Thanks again to Sheeri Cabral  for having me at the Boston MySQL Meetup on Monday for the talk on “Fractal Tree® Indexes – Theoretical Overview and Customer Use Cases.” The crowd was very interactive, and I appreciated that over 50 people signed up for the event and left some very positive comments and reviews.

In addition, the conversation spilled over late into the night as we made our way over to nearby Mead Hall afterwards for a few drinks, some food, and to continue the discussion.

The presentation is …

I find myself constantly looking up server variables (and manuals and changelogs) for MySQL, MariaDB, and XtraDB, which versions they are in, and so forth. So I finally created a couple pages which contain the links to all of these various bits of information across the various flavors of MySQL.

I’ve been using them every day, so I thought some others might want to bookmark these as well.

I’ve created the following:

o Changelogs
o Documentation
o Server Variables
o InnoDB Plugin Versions

The Changelogs page contains links for MySQL 3.23 up through 5.6, MariaDB 5.1 – 5.3, XtraDB 5.1 – 5.5, Xtrabackup 1.3 – …

FictionPress

Issues addressed:

• Support complex and efficient indexes at 100+ million rows.
• Predicable and consistent performance regardless of data size growth.
• Fast recovery.

Ensuring Predictable Performance at Scale

The Company:  FictionPress operates both FictionPress.com and FanFiction.net and is home to over 6 million works of fiction, with millions of writers/readers participating from around the world in over 30 languages

The Challenge: FictionPress offers a number of interactive features to its large user base. These …

This guide will get you up and running with how to identify the bottleneck queries using the excellent tool pt-query-digest. You will learn how to use and analyze the output returned by pt-query-digest. You will also learn some differences between slow query logging in various MySQL versions. Later on in the post I will also show you how to make use of the extra diagnostic data available with Percona Server.

The post Profiling your slow queries using pt-query-digest and some love from Percona Server appeared first on ovais.tariq.

A customer opened a support issue to ask about some help determining why they were seeing a lot of Lock Wait Timeouts. I asked them to enable the InnoDB Lock Monitor so that I could get a look at what was going on in their transactions and whether there might be some locks held longer than necessary.

The customer sent in a 184MB MySQL error log with 4773836 lines. I started looking through it, but I could tell I was going to need a better way to get a better overview of the file than what I'd be able to piece together trying to poke through it and look for individual lines. I started piping the file through a variety of UNIX tools to narrow down what I was seeing.

I ended up with this mess:

 < mysqld.err grep ACTIVE | cut -d' ' -f 2,4 | sort -rn -k 2 | perl -F, -ane 'print "$F[0] $F[1]" if not $v{$F[0]}; $v{$F[0]} = $F[1];' | head

It's hideous, but it's pretty helpful. Here's the output:

1EC080F1 …

Note: this article was originally published on http://blogs.innodb.com on Dec 23, 2011 by Vasil Dimov.

Continues from Improving InnoDB memory usage.

Here are some numbers from the fixups described in the above article:

The workload consists of 10 partitioned tables, each one containing 1000 partitions. This means 10’000 InnoDB tables. We truncate the tables, then restart mysqld and run:

1. INSERT a single row into each of the 10 tables
2. SELECT * from each table
3. FLUSH TABLES (this causes the tables to be closed and reopened on the next run)
4. wait for 10 seconds

we repeat the above steps 10 …

Once upon a time, it would have been considered madness to even attempt to create 30,000 tables in InnoDB. That time is now a memory. We have customers with a lot more tables than a mere 30,000. There have historically been no tests for anything near this many tables in the MySQL test suite.

So, in fleshing out the test cases for this and innodb_dict_size_limit I was left with the not so awesome task of making the test case run in remotely reasonable time. The test case itself is pretty simple, a simple loop in the not at all exciting mysqltest language that will create 30,000 identical tables, insert a row into each of them and then drop them.

Establishing the ground rules: I do not care about durability. This is a test case, not a production system holding important data which means I can lie, cheat and steal to get …

Note: this article was originally published on http://blogs.innodb.com on Dec 20, 2011 by Vasil Dimov.

Last month we did a few improvements in InnoDB memory usage. We solved a challenging issue about how InnoDB uses memory in certain places of the code.

The symptom of the issue was that under a certain workloads the memory used by InnoDB kept growing infinitely, until OOM killer kicked in. It looked like a memory leak, but Valgrind wasn’t reporting any leaks and the issue was not reproducible on FreeBSD – it only happened on Linux (see Bug#57480). Especially the latest fact lead us to think that there is something in the InnoDB memory usage pattern that reveals a …

Last month we did a few improvements in InnoDB memory usage. We solved a challenging issue about how InnoDB uses memory in certain places of the code.

The symptom of the issue was that under a certain workloads the memory used by InnoDB kept growing infinitely, until OOM killer kicked in. It looked like a memory leak, but Valgrind wasn’t reporting any leaks and the issue was not reproducible on FreeBSD – it only happened on Linux (see Bug#57480). Especially the latest fact lead us to think that there is something in the InnoDB memory usage pattern that reveals a nasty side of the otherwise good-natured Linux’s memory manager.

It turned out to be an interesting …