It is important that you monitor the MySQL error log. There are a few different options available for defining the details of the log. If not specified the default is [datadir]/[hostname].err. This is not an ideal location for 2 reasons.

First, a correctly configured MySQL datadir will have permissions only for the mysql user, and this is generally restrictive access to the user only and no group or world permissions. Other users/groups should have limited access to the mysql error log.

Second, the datadir is for data, not logs, especially logs that can potentially fill file systems. I am referring here to more then just the error log.

I would recommend you create a separate directory for MySQL logs such as the error, slow and general logs. An example I implement for single installation environments using Linux mysql packages is:

mkdir /var/log/mysql
chown mysql:mysql /var/log/mysql
chmod 750 /var/log/mysql

The EXPLAIN command is an important tool to review how a SQL query is executed and in this example includes what indexes are used.

By adding a covering index I ended up with the following EXPLAIN plan I was unable to explain. The end result was a boost in server performance which was the ultimate goal.

mysql> explain select max(md)  from e_r  where email = 'xxxx@gmail.com' and id = '36981';
+----+-------------+-------+------+---------------+------+---------+------+------+------------------------------+
| id | select_type | table | type | possible_keys | key  | key_len | ref  | rows | Extra                        |
+----+-------------+-------+------+---------------+------+---------+------+------+------------------------------+
|  1 | SIMPLE      | NULL  | NULL | NULL          | NULL | NULL    | NULL | NULL | Select tables …

Recently I was working on a project which used Infobright as the database. The version tested was 3.1.1 both on OpenSolaris as well as Solaris 10. Infobright is like a column-oriented database engine for MySQL primarily targeted towards data warehouse, data mining type of project deployments.

While everything was working as expected, one thing we did notice that as number of concurrent connections tried to query against the database we noticed that queries deteriorated fast in the sense that not much parallel benefits were being squeezed from the machine. Now this sucks! (apparently sucks is now a technical term). It sucks because the server has definitely many  cores and typically each Infobright query still can at the max peg a core. So the expectation will be typically to atleast handle concurrent queries which is close to the number of cores  (figuratively speaking though …

One of the most asked questions is how to setup MySQL replication. The MySQL Reference Manual provides a good Replication How To as a starting guide on MySQL Replication 101.

MySQL replication has many uses including read scalability, backups, failover, online maintenance, upgrade testing and verification, software upgrades, alternative data or structure for performance queries and even benchmarking to name the popular uses.

When reviewing an installation of MySQL replication I use the following as part of my checklist of steps used for confirming your replication environment is operational.

Master Variables

• server-id – Replication will not work without this correctly set and unique
• log-bin – Pre-requisite for working replication
• log-bin-index
• max_binlog_size
…

Recently I was working on a project which used Infobright as the database. The version tested was 3.1.1 both on OpenSolaris as well as Solaris 10. Infobright is like a column-oriented database engine for MySQL primarily targeted towards data warehouse, data mining type of project deployments.

While everything was working as expected, one thing we did notice that as number of concurrent connections tried to query against the database we noticed that queries deteriorated fast in the sense that not much parallel benefits were being squeezed from the machine. Now this sucks! (apparently sucks is now a technical term). It sucks because the server has definitely many  cores and typically each Infobright query still can at the max peg a core. So the expectation will be typically to atleast handle concurrent queries which is close to the number of cores  (figuratively speaking though …

Recently I was working on a project which used Infobright as the database. The version tested was 3.1.1 both on OpenSolaris as well as Solaris 10. Infobright is like a column-oriented database engine for MySQL primarily targeted towards data warehouse, data mining type of project deployments.

While everything was working as expected, one thing we did notice that as number of concurrent connections tried to query against the database we noticed that queries deteriorated fast in the sense that not much parallel benefits were being squeezed from the machine. Now this sucks! (apparently sucks is now a technical term). It sucks because the server has definitely many  cores and typically each Infobright query still can at the max peg a core. So the expectation will be typically to atleast handle concurrent queries which is close to the number of cores  (figuratively speaking though …

As a frequent traveler for my MySQL consulting (last 4 weeks were Sydney, San Francisco, New York and Vancouver), I like to keep abreast of any local tech event that includes MySQL that I may be able to attend.

Now there is a consolidated location that you can use, the Open Source Events Calendar. Kudos to the MySQL Community team members Lenz Grimmer and Giuseppe Maxia who have put this together.

We need your help. If you have a local event, please submit your event request. This projects needs the support of all.

You will also find valuable conference information including dates for close of proposals. A great tool for scheduling your upcoming conference year.

I’ve always believed that the MySQL Information_schema.tables.table_rows figure for Innodb tables to be while approximate, approximately accurate.

Today I found that the figures varied on one table from 10x to 100x wrong.

Before performing an ALTER I always verify sizes for reference.

+---------+------------+--------+------------+------------+----------------+------------+------------+-----------+------------+
| table_s | table_name | engine | row_format | table_rows | avg_row_length | total_mb   | data_mb    | index_mb  | today      |
+---------+------------+--------+------------+------------+----------------+------------+------------+-----------+------------+
| XXXXX   | s_a        | InnoDB | Compact    |     208993 |           7475 |  1491.5312 |  1490.0156 |    1.5156 | 2009-09-09 |

mysql> alter table s_a modify col VARCHAR(255);
Query OK, 23471 rows affected (4 min 26.23 sec)

After

 …

MySQL provides a level of statistics for your INSERT, UPDATE, DELETE, REPLACE Data Manipulation Language (DML) commands using the STATUS output of various Com_ variables, however it is per server stats. I would like per table stats.

You can achieve this with tools such as MySQL Proxy and mk-query-digest, however there is actually a very simple solution that requires no additional tools.
The following 1 line Linux command (reformatted for ease of reading) gave me exactly what I wanted, and it had ZERO impact on the database.

$ mysqlbinlog /path/to/mysql-bin.000999 |  \
   grep -i -e "^update" -e "^insert" -e "^delete" -e "^replace" -e "^alter"  | \
   cut -c1-100 | tr '[A-Z]' '[a-z]' |  \
   sed -e "s/\t/ /g;s/\`//g;s/(.*$//;s/ set .*$//;s/ as .*$//" | sed -e "s/ where .*$//" |  \
   sort | uniq -c | sort -nr  

  33389 update e_acc
  17680 insert into r_b
  17680 insert into e_rec
  14332 insert into rcv_c
  13543 update e_rec
  10805 …

While not a MySQL topic, as most of my readers view my MySQL Blog, my WordPress blog has been hacked? Has yours?

Like many, I’m sure you may have read about it like at Wordpress blogs under attack from hack attack but I was surprised when my custom permlinks did not work.

Being surprised I looked at Administrator accounts, and I found that there was one more number then being displayed in the list. I had to dig into the database to find the problem.

mysql> select * from wp_users where ID in (select user_id from wp_usermeta where meta_key = 'wp_capabilities' and meta_value like '%admin%');
+-----+-------------+------------------------------------+---------------+------------------------------+---------------------------+---------------------+---------------------+-------------+--------------+
| ID  | user_login  | user_pass                          | user_nicename | …