The NoSQL event in New York had a number of presentations on non relational technologies including of Hadoop, MongoDB and CouchDB.

Coming historically from a relational background of 20 years with Ingres, Oracle and MySQL I have been moving my focus towards non relational data store. The most obvious and well used today is memcached, a non persistent distributed key/value pair store. There are a number of persistent key/value stores in the marketplace, Tokyo Cabinet, …

Feels like a long time ago, but my talk at the MySQL User’s Conference back in April 09 on running MySQL Multiple Times to get better performance is now available online at YouTube. The original PDF of the presentation is available here.View it here: YouTube – Improving Performance by Running MySQL Multiple Times

Feels like a long time ago, but my talk at the MySQL User’s Conference back in April 09 on running MySQL Multiple Times to get better performance is now available online at YouTube. The original PDF of the presentation is available here.

View it here: YouTube – Improving Performance by Running MySQL Multiple Times

Has anyone read the report Microsoft, IBM and Oracle Lead the SMB and Mid-Market Database Segment - Yankee Group - 7/31/2006 - 5 Pages - ID: YANL1327246?

Paying 800USD just to know the percentages of each database is a bit expensive for my small startup budget, especially since it is not me who needs the information.

I was asked today to confirm the operation of INET_ATON() and INET_NTOA() functions for converting IP4 strings to numeric representations. My tests on the machine I was just connected to at the very instant reported the following results.

mysql> SELECT VERSION();
+-----------------+
| VERSION()       |
+-----------------+
| 5.1.31-1ubuntu2 |
+-----------------+
1 row in set (0.00 sec)

mysql> SELECT INET_ATON('74.165.97.204') AS ipn;
+------------+
| ipn        |
+------------+
| 1252352460 |
+------------+
1 row in set (0.00 sec)

mysql> SELECT INET_NTOA(1252352460) as ipa;
+---------------+
| ipa           |
+---------------+
| 74.165.97.204 |
+---------------+
1 row in set (0.01 sec)

The results on the client via ODBC using MySQL 5.0.45 was?

ipn
1252352460

ipa
37342E3136352E39372E323034

What is causing this? It was immediately suspicious the pattern of 2E (the only letter), which translates from Hex to decimal …

Just how effective is the Query Cache on performance? If you are not comfortable reading the MySQL code you can cheat very easily with the SHOW PROFILE command. This demonstration will show you at a high level the relative impact without and with the Query Cache. First let us confirm the Query Cache is not used.

mysql> SHOW GLOBAL VARIABLES LIKE 'query_cache%';
+------------------------------+---------+
| Variable_name                | Value   |
+------------------------------+---------+
| query_cache_limit            | 1048576 |
| query_cache_min_res_unit     | 4096    |
| query_cache_size             | 0       |
| query_cache_type             | ON      |
| query_cache_wlock_invalidate | OFF     |
+------------------------------+---------+
5 rows in set (0.00 sec)

We now enable profiling.

mysql> SET PROFILING=1;

We run our …

Maximize your strengths, minimize your weaknesses.

You can apply this approach to many things in life, I apply it to describing and using MySQL the product, and it’s components. The Query Cache like many features in MySQL, and indeed features in many different RDBMS products (don’t get me started on Oracle *features*) have relative benefits. In one context it can be seen as ineffective, or even detrimental to your performance, however it’s course grain nature makes it both trivial to disable dynamically (SET GLOBAL query_cache_size=0;), and also easy to get basic statistics on current performance (SHOW GLOBAL STATUS LIKE ‘QCache%’;) to determine effectiveness and action appropriately.

The Query Cache is course grained, that is it is rather simple/dumb in nature. When you understand the path of execution of a query within the MySQL kernel you learn a few key things.

• When enabled, by default the Query …

Just recently I came across the presentation “Bend SQL to your will with EXPLAIN” by Ligaya Turmelle via the Linked In – MySQL Speakers and Presenters group. Slides available at Slideshare. While I know a little about MySQL, I always enjoy spending time reviewing content when possible, perhaps as a good reference when asked, perhaps to glean some small point of knowledge I didn’t know, or didn’t understand completely, or had forgotten about. It’s also fun to randomly find worthwhile information.

EXPLAIN is an essential tool for MySQL developers, if you don’t know what QEP is, the listed google search link …

I generally use the following MySQL INFORMATION_SCHEMA (I_S) query to Calculate Your MySQL Database Size. This query and most others that access the MySQL INFORMATION_SCHEMA can be very slow to execute because they are not real tables and are not governed by physical data, memory buffers and indexes for example but rather internal MySQL data structures.

Mark Leith indicates in his post on innodb_stats_on_metadata that Innodb performs 8 random(ish) dives in to the index, when anybody accesses any of SHOW TABLE STATUS, SHOW INDEX, INFORMATION_SCHEMA.TABLES,INFORMATION_SCHEMA.STATISTICS for InnoDB tables. This can have an effect on performance, especially with a large number of Innodb tables, and a poor ratio of innodb_buffer_pool_size to disk data+index footprint.

What is even more …

The MySQL Innodb storage engine provides ACID compliance, the ‘I’ being isolation. There are four states defined in MySQL with the tx_isolation system variable, READ-UNCOMMITTED, READ-COMMITTED, REPEATABLE-READ and SERIALIZABLE.

Generally MySQL installations do not modify the default value of tx_isolation = REPEATABLE-READ, however I have seen with a number of clients the default value has been changed to READ-COMMITTED. When I attempt to identify the reason why, I have always received the same reason. Oracle uses a default transaction isolation of READ-COMMITTED. See how Oracle Manages Data …