Unless you have been hiding under a rock, you have one way or the other heard about the king of pop passing away. This is in my opinion a great loss to the world, as this man was like a god to me when I was a little boy.
Besides it being really sad that he died, it is also a good test for the systems us techies take care of: the web has seen some of it’s biggest spikes in traffic on june 25th.
That is not over yet though. Next tuesday there will be a memorial service in LA, which will also be live broadcasted on the web. For any system administrator and/or DBA responsible for a site that is news or social media related, this will be yet another good …

I was trying to demonstrate to a client how to monitor queries that generate internal temporary tables. With an EXPLAIN plan you see ‘Creating temporary’. Within MySQL you can use the SHOW STATUS to look at queries that create temporary tables.

There is the issue that the act of monitoring impacts the results, SHOW STATUS actually creates a temporary table. You can see in this example.

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

mysql> show global status like 'created_tmp%';
+-------------------------+-------+
| Variable_name           | Value |
+-------------------------+-------+
| Created_tmp_disk_tables | 48    |
| Created_tmp_files       | 5     |
| Created_tmp_tables      | 155   |
+-------------------------+-------+
3 rows in set (0.00 sec)

mysql> show global status like 'created_tmp%';
+-------------------------+-------+
| …

Welcome to the 152nd edition of Log Buffer, the weekly review of database blogs.

PostgreSQL

Courtesy the United States PostgreSQL Association, the big news: PostgreSQL 8.4 Released!.

Josh Berkus writes, “Now that PostgreSQL 8.4 is out, I thought I’d write a little about my favorite 8.4 feature. As Mr. Performance Whack-a-Mole, what makes me happy about 8.4 is the ability to whack moles faster … which is why I’m very fond of pg_stat_statements.”

On ad’s corner, …

It”s not the most common task in the world, but you might want to view processes from a particular user and once in a while you might even need to kill processes from a single user, be it during an attack or because you simply got a bug in an application bombarding your db server with connections!

Here is a small stored procedure which does exactly that!

call process_list("show","username","hostname");

– shows all processes owned by username@hostname

call process_list("kill","username","hostname");

– kills all processes owned by username@hostname

The code for this stored procedure can be found below. If you have any comments / suggestions feel free to comment below.

######################################################################
##                                        …

I'm pleased to announce the release of Condition Pushdown for ha_partition version 0.1.
http://launchpad.net/partitionconditionpushdownformysql

This release is a patch file for MySQL's table partitioning feature. (ndb is excluded)
This patch file works to add methods("cond_push" and "cond_pop") to ha_partition. As a result, every storage engine's table that use table partitioning can get condition-pushdown through ha_partition.

There was no problem because only ndb supported engine-condition-pushdown up to now.
This patch was needed because the Spider storage engine supported engine-condition-pushdown recently.

Enjoy!

Hi!

Yesterday I had the honour of presenting my mini-bi/datawarehousing tutorial "Starring Sakila" for MySQL University. I did a modified version of the presentation I did together with Matt Casters at the MySQL user's conference 2009. The structure of the presentation is still largely the same, although I condensed various bits, and I added practical examples of setting up the ETL process and creating a Pentaho Analysis View (OLAP pivot table) on top of a Mondrian Cube.

The slides, session recording, and materials such as SQL script, pentaho data integration jobs and transformations, and Sakila Rentals Cube for Mondrian are all available here on MySQL Forge.
Copyright Notice
Presentation slides, and …

Image via Wikipedia

The NoSQL event has triggered a bit of a hard time for the RDBMS the last week.  I won’t add any commentary as this follows what I have been talking about for a while, but here are some of the links.  Most notable is Michael Stonebraker’s post on the ACM site.

• The End of a DBMS Era (Might be Upon Us)
• Relational databases are dead -- who knew?
• …

At Percona we provide services both Onsite - visiting the customers and Remote - logging in to their systems or communicating via email,phone,instant messaging.

We believe both approaches have their benefits and drawbacks and mixing them right way allows you to get your problems solved most efficient way.

Onsite visits are great as they allow consultant to meet your team in person and great for relationship building. It is great for architecture design and review as you can sit down with the team and use drawing board. It also often allows the best focus both for consultant and for participating team - when consulting visit is arranged it is usually the top priority for some of the staff members which provide consultant with information and assistance he might need.

Onsite visits also often allow to get prompt attention from other team - looking for …

The Scaling with Flash webinar I've mentioned earlier was a success and we got the recording available. It contains Percona presentation, presentation of Schooner appliances and Q&A session. Enjoy.

Entry posted by peter | 3 comments

Add to: | …

I’ve had a few VCs ask how we compare to Hadoop and companies using MapReduce. With Google blessing MapReduce, it seems to be the cool new thing. I figure I’m going to have to explain this to VCs, so I might as well blog about it.

MapReduce is a process of dividing a problem into small pieces and distributing (mapping) those pieces to a large number of computers. Then it collects the processed data and merges (reduces) it into a result set. Hadoop provides the plumbing, so users focus on writing the query and Hadoop handles the dirty work of mapping and reducing. Such a query, using a procedural language like Java, is more complex than a comparable SQL query, but more on that below.

So what is MapReduce good for? It really shines when you want to summarize, analyze or transform a very large data set. This is why it is well suited to web data. Map reduce doesn’t utilize an index, so the tradeoff you need to consider is whether …