In the first part of this article we examined the types of conflicts and their causes. In this part, we will analyse some of the methods available to deal with conflicts.

Pessimistic locking (or: conflicts won't happen)

Applicability: synchronous clusters with 2pc

We've covered this topic in the previous article, but it's worth repeating. If you use a synchronous cluster, you don't have conflicts. For example, MySQL Cluster ensures consistent data with updates coming from different nodes. However, MySQL Cluster is not a replacement for a MySQL server, and it has severe limitations.

Optimistic locking

Applicability: synchronous clusters without 2pc (Galera)

Conflicting transactions proceed on different

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When using the replication slave stream, or mysql command line client and mysqlbinlog output from a binary/relay log, all statements are executed in a single thread as quickly as possible.

I am seeking a tool to simulate the replay of the binary/relay log for a benchmark at a pace that is more representative to original statements. For a simple example, if the Binary Log has 3 transactions in the first second, 2 transactions in the second second, and 5 transactions in the third second, I am wanting to simulate the replay to take roughly 3 seconds, not as fast as possible (which would be sub-second). The tool should try to wait the remainder of a second before processing SQL statements in the incoming stream.

Does anybody know of a tool that currently provides this type of functionality? Any input appreciated before I create my own.

Even when the output of EXPLAIN doesn’t show “using temporary”, a temporary file may still be used in certain cases.

That’s not to say the query needs the temporary file to actually resolve the query (like what you’d see from the need for a derived table). But rather, the temporary file I’m speaking of is due to binary logging.

In particular, you can see this easily if using InnoDB, (most commonly) row-based binary logging, and you issue a large transaction, say a large UPDATE (large meaning something larger than the size of

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I am facing an interesting problem. I need to mark somehow a statement in such a way that the comment is preserved through the binary log.
I don't have control on how the statement is generated or using which client software. For the sake of example, let's say that I need to mark a CREATE PROCEDURE statement in such a way that, if I extract the query from the binary log and apply it to another server, the information is still available.

Background

Normally, I would use a comment. The first thing I would think is
CREATE PROCEDURE p1(i int) select "hello" /* This is my text */
But most client libraries will strip it.
There was



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A few days ago, a friend of mine asked me if I knew of a way of filtering a bunch of binary logs, to extract only statements related to a single table. The task was about filtering a few hundred binary log files.

It's a tricky problem. Even with my experience with regular expressions, I knew that using a script to extract statements related to a single table was going to be a nasty business.
However, I know of an entity that can filter by table name efficiently, and that's the MySQL replication system. So I suggested using replication to a sandbox with a replicate-wild-do-table statement to get the job done.
My friend was skeptical and did not want to go that way. I was busy writing an article for an Italian magazine and did not follow up immediately. But today, with the article safely in the editor's hands, I did a quick test, and guess what? It works!



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Scenario: Master-Master replication
Description: Master A is the active db server whilst Master B is a read only swappable db server hence both are creating binary logs. During backup I run “FLUSH LOGS” in order to have a simpler point in time recovery procedure if that case arises.
Problem: Flush logs is mean mean command :) …. it rotates not only my binary logs but my error log too (since I user error-log=blahblahblah in my my.cnf). Well given I flush logs every night my error log is cycled through every night, but unlike binary logs which have an incrimental number attached to the fine, error logs only have a `-log` attached to the filename and a second “FLUSH LOG” would just clear all error logs permanently. That is really not fun believe me!

So what is the solution?

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Applying binary logs to a MySQL instance is not particularly difficult, using the mysqlbinlog command line utility:

$> mysqlbinlog mysql-bin.000003 > 03.sql
$> mysql < 03.sql

Turning off binary logging for a session is not difficult, from the MySQL commandline, if you authenticate as a user with the SUPER privilege:

mysql> SET SESSION sql_log_bin=0;

However, sometimes you want to apply binary logs to a MySQL instance, without having those changes applied to the binary logs themselves. One option is to restart the server binary logging disabled, and after the load is finished, restart the server with binary logging re-enabled. This is not always possible nor desirable, so there’s a better way, that works in at least versions 4.1 and up:

The mysqlbinlog utility

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Recently with a client while running a number of disaster recovery tests I came across a nasty situation which was not part of the original plan and provided a far worse disaster situation then expected.

I should preface this condition with some of the environment conditions.

• MySQL 5.0 Enterprise 5.0.54
• RHEL 5 64bit
• Master and 2 Slaves
• MySQL Data and MySQL Binary Logs/MySQL Error Logs are on separate disk partitions

While running stress tests under high load, we tested the filling of partition containing the logs. This partition included the binary log and MySQL error log.

The observed output was.

• An error message was written to the MySQL error log. See below.
• Application throughput dropped, but did not stop.
• Binary logs stopped occuring.
• MySQL proactively

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About a month ago, I published the results of MySQL 5.x performance with logging. The results covered several versions, from 5.0.45 to 5.1.33. Among the conclusions of the post was the consideration that MySQL 5.0.x is faster than MySQL 5.1 in read only operations. I hinted that better results may come for MySQL 5.1. When I wrote that post I had, in fact, an ace up my sleeve, because I had already benchmarked the performance of MySQL 5.4, using the same criteria shown in my previous post. The results, as you can

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There has been much talking about MySQL performance related to logging. Since MySQL 5.1.21, when Bug #30414 was reported (Slowdown (related to logging) in 5.1.21 vs. 5.1.20) I have been monitoring the performance of the server, both on 5.0 and 5.1.
Recently, I got a very powerful server, which makes these measurements meaningful.
Thus, I measured the performance of the server, using all publicly available sources, because I want this benchmark to be repeatable by everyone.
I will first describe the method used for the benchmarks, and then I report the results.

The server

The server is a Linux Red Hat Enterprise 5.2, running on a 8core processor, with 32 GB RAM and 1.5 TB storage.

$ cat /etc/redhat-release
Red Hat Enterprise Linux Server release 5.2 (Tikanga)

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Recently I had an interesting issue crop up. Due to an unfortunate migration incident in which involved master/master replication and not checking to see if replication was caught up, we ended up with an infinite replication loop of a number of SQL statements. awk helped immensely in the aftermath cleanup.

The basics of the replication infinite loop were (more…)

If you have tried using row based replication, you may have noticed two things: (1) it fixes many inconsistencies of statement-based replication, but (2) the binlog is unfit for humans. Inspecting it after a problem occurs won't provide any useful information.
The instructions look like line noise, and when you don't see the result you were expecting you wonder if that's the case.

For example, after executing this code:

create table t1 (id int, c char(10), d date);
insert into t1 values (1, 'abc', '2008-01-01');
insert into t1 values (2, 'def', '2008-08-19');
insert into t1 values (3, 'ghi', current_date());

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