Forecasting Oracle Performance

Forecasting Oracle Performance. By Craig Shallahamer, Apress 2007. Page count: about 250 pages. (Here’s a link to the publisher’s site). Short version: buy it and read it, but make sure you don’t rely on it alone; deepen your knowledge through other sources.

I bought and read this book because I’m interested in performance, performance forecasting, and capacity planning. I’m not interested in forecasting Oracle performance per se. However, I have noticed that there is a lot of good literature in the Oracle arena that can apply to other databases (*cough* …

A big congratulations to Ubuntu for the release of 10.04 LTS. While I haven’t had the chance to upgrade, I see everyone on Twitter and in the blogosphere say they are really like the Lucid experience.

A couple of days ago, I made mention that there were VirtualBox images of MariaDB out there. Turns out there were so many downloads, Mark has had to upgrade his Internet connection!

Anyway, to the point: Mark has created Ubuntu 10.04 LTS VM’s with MariaDB 5.1.44 and MariaDB 5.2 BETA. Don’t hesitate to download them, and send feedback.

Have a good weekend …

While I was running around WordCamp San Francisco 2010 getting ready for the keynote, guest photographer Sheri Bigelow had my D3S and was snapping all around. Here are the photos from that day.

…

Another thing I find interesting about MongoDB is its approach to Durability, Data Consistency and Availability. It is very relaxed and will not work for some applications but for others it can be usable in current form. Let me explain some concepts and compare it to technologies in MySQL space.

First I think MongoDB is best compared no to MySQL Server but MySQL Cluster, especially in newer versions which implement "sharding". Same as commit to NDB Storage engine does not normally mean commit to disk, but rather commit to network it does not mean commit to disk with MongoDB, furthermore MongoDB uses Asynchronous replication, meaning it may take some time before data will be at more than one node. You can also use getLastError() to ensure data is propagated to the slave. So you can see it as a hybrid between MySQL Cluster and innodb_flush_log_at_trx_commit=2 mode. The second difference of course the fact MongoDB is not crash safe - similar to …

Do you have MyISAM tables you reload with new data?

Do your queries, using that table, get blocked because the table is locked?

Do the waiting queries create idle connections slowing down the table load?

Do you wish you could just replace the table?

Years ago I was told you can replace CSV tables by simply replacing the CSV file. I figured this would also be true of a MyISAM file and it is. I use this perl script to replace MyISAM tables forcast and current observation weather data. The processing and tables are created on another computer. Weather forecasting is CPU and database expensive. I then copy (rsync) the files to the production system and run this script.

#!/usr/bin/perl
################################################################################
################################################################################
# mg_hot_replace_table.pl - Hot Replace a MySQL table.
#
# 2010-05-01 …

I went to MongoSF today - quite an event, and I hope to have a chance to write more about it. This post is about one replication problem and how MongoDB solves it.

If you're using MySQL Replication when your master goes down it is possible for some writes to be executed on the master, but not on the slave, which gets promoted to the master. When Master comes back up it has some updates done to it which cause it to be inconsistent with data on the new Master. In MySQL world we can chose to either ignore this problem (or may be even replay those changes on slaves and hope it works out), re-clone it from the slave or use mk-table-checksum to find inconsistencies and re-sync them with mk-table-sync. Both of these operations can be very expensive for large databases.

MongoDB approach used …

I work in all markets of the database industry, from web & startup through the largest and most established enterprises.  And to be completely honest, the name Ingres has not come up in conversation very much at all.  10 years ago maybe more often, but recently not all that much.  But Ingres has been quietly ticking away.  Despite being largely off the radar, they still have a sizable and loyal customer base, global offices and a focused & dedicated management team.  And importantly they have an open source business model which actually appears to be working.

I wrote last year that their "behind the scenes" status had the potential to change.  Ingres had been very clever and worked out a partnership relationship with Peter Bonzc’s Vectorwise.  And …

For the Friday after the MySQL conference, Oracle had invited all storage engines to the traditional storage engine summit, but this was then canceled (or postponed) in the last minute. Since the engine vendors had already booked the day anyway, we agreed to sponsor the facility so the meeting could take place. In addition to those who had planned to be there, the meeting was also attended by Mikael Ronström, Jonas Oreland and Sanja Byelkin who had their flights cancelled. (Oracle was already represented by Konstantin Osipov.)

Also see http://askmonty.org/wiki/Storage_Engine_Summit_2010 for more complete notes of the summit.

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Welcome to Log Buffer. This week’s issue #187 was another group effort. Thanks to all our contributors – you rock!

Suggested by Pythian’s Bradd Piontek, is a post he really liked because he used to write pipelined functions for Dynamic Search queries, – Tom Kyte’s something new I learned about estimated cardinalities. He’s also highlighted something new Tom learned about sqlplus. And the fact that Richard Foote announced the …

I recently discovered that there’s a youtube video of the talk I gave at OpenSQL Camp in Portland in 2009.

This is a whiteboard presentation and is less well developed than the talk I gave a the MySQL conference (I posted those slides two days ago. But since it includes audio it may be easier to understand.

This talk presents the data structure underlying the TokuDB storage engine for MySQL.