Often times, production data needs to be moved to different environments for testing/developing purposes. However, some of that data can be people’s name, birthday, address, account number, etc., that we don’t want testers and/or developers to see, due to privacy and regulatory concerns. Hence the need to mask those data. I can certainly see this needs grow over time for all database platforms. There are software out there that does this sort of task, or similar tasks, such as data generation tool. Oracle actually has a Data Masking Pack since 10g for this purpose. Here are some of my thoughts on this topic.

One method of masking data is through reshuffling, which shuffles the value in target column(s) that you want to protect randomly across different rows.

Another way of doing it is through data generation. For instance, for target column(s), we just replace its value with something else.

For reshuffling, obviously …

Month ago I was on a vacation and as usual even though our hotel provided us with an internet connection on a pretty decent speeds, I wasn’t able to work there because they’ve banned all tcp ports but some major ones (like 80, 21, etc) and I needed to be able to use ssh, mysql, IMs and other non-web software.

After a short research I’ve found a pretty simple to set up and easy to use approach to such a connection problems I’d like to describe here.

First, you’ll need someone (or you can do it before leaving home) to start an ssh daemon on port 80 on one of your servers. I use one of my Slicehub slices for this to permanently have an ability to use it. You can do it like this (if it is a temporary solution):

Notice: this `which sshd` was used because on some OSes sshd does not want to start w/o an …

Yes, it's finally out. Over 250,000 users have downloaded MySQL 5.1 setting a new record. READ MORE

I forgot to post about this but I uploaded a small catch up interview with Salle, the Manager for EMEA Support for MySQL on life and what it means to be in the Support Team of MySQL. Let me introduce you to another long time employee of MySQL :)

Hello Kettle fans,

Like Roland I got confirmation earlier this week that I could present my talk on “MySQL and Pentaho Data Integration in a cloud computing setting”, at the next MySQL user conference.

I’m very excited about the work we’ve done on the subject and it’s going to be great talking about it in April.

See you there!
Matt

We’re very excited to see MySQL 5.1.30 make it to GA status and are very proud of the work that the MySQL engineering team has done to get MySQL 5.1 out of the door.

Maybe you’ve seen some claims by others in the MySQL community that MySQL 5.1 runs slower than MySQL 5.0. Maybe you’ve also seen some claims by others in the MySQL community that MySQL 5.1 runs faster than MySQL 5.0.

Guess what? They’re both right.

With database or any other hardware/software performance tests, you’re always going to see different results because there are *so* many variables that go into the equation.

That being the case, I thought I’d share a little of what we in the MySQL QA group have seen on the 5.1 vs. 5.0 front. Part of our job in MySQL QA is to routinely test each MySQL build and compare it to prior versions before release, to see if any performance regressions have occurred and I would like …

There is a new blog in the MySQL Community arena.

It is a collaborative podium for guest posts. We will host colleagues or community members who have no blog and need a temporary place for their message. The first experiment was successful, and we decided to have a more stable place for it.

We start today by hosting Trim Perhad, System QA manager of MySQL, who presents some interesting performance results.

To complement my patches to show import progress using the mysql client I have created a minor patch to mysqldump.  This new patch for MySQL 5.1.30 will show you the number of rows dumped so far every 10,000 rows when using the --verbose parameter.  The output should be similar to this:

-- Retrieving table structure for table testing...
-- Sending SELECT query...
-- Retrieving rows...
-- 20000 rows dumped

A friend suggested the creation of a "Technical Professional Purity Test", and suggested two questions:

Have you ever have you ever implemented a solution you knew would doom the client?

Have you ever yelled at your manager for interrupting your workflow?


Please, suggest more!

How?

Seriously, how do I do this?

Following constraints: T1000 has no local DVD drive. No other Solaris hosts on network.

(Note that it takes about 15 seconds to find the Debian install instructions. “Put this file on tftp server, boot.”)