A list is simply a list of things. The list has no structure, except in some cases, the length of the list may be known. The list may contain duplicate items. In the following example the number 1 is included twice.

Example list:

1
2
3
1

A set is similar to a list, but has the following differences:

1. The size of the set is always known
   
2. A set may not contain duplicates
   

You can convert a list to a set by creating a 'weighted list'. The weighted list includes a count column so that you can determine when an item in the list appears more than once:

1,2
2,1
3,1

Notice that there are two number 1 values in the weighted list. In order to make insertions into such a list scalable, consider using partitioning to avoid large indexes.

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Apache OpenOffice.org proposal approved. SkySQL Tekes new funding. And more.

# The proposal for OpenOffice.org to become an Apache incubator project was unanimously approved.

# Rob Weir discussed how the relationship between OpenOffice.org and LibreOffice need not be a zero-sum game.

# Simon Phipps offered his thoughts on the potential positive and negative outcomes.

# Tekes, the main public funding agency for research, development, and innovation in Finland, …

The realities of today’s successful web services are creating new demands that many legacy databases were just not designed to handle:

- The need to scale writes, as well as reads, both within and across geographically dispersed data centers;

- The need to scale operational agility to keep pace with database load and application requirements. This means being able to add capacity and performance to the database, and to evolve the schema – all without downtime;

- The need to scale queries by having flexibility in the APIs used to access the database;

- The need to scale the database while maintaining continuous availability for both failures as well as scheduled maintenance events.

Each of the requirements above warrant their own dedicated blog, which I’ll find time to write over the next few weeks.

But to get started, I wanted to discuss how the MySQL Cluster database addresses the first …

The most basic and most oft-repeated task that a DBA has to accomplish is to look at slow logs and filter out queries that are suboptimal, that consume lots of unnecessary resources and that hence slow down the database server. This post looks at why and how VIEWs can help against such suboptimal operations.

As the birds have started their yearly migration back to their homes from the warmer areas to the relative less cooler areas in summer, bloggers are also touching base with the technologies which they cherish most and coming back with some master strokes. This new cool edition of Log Buffer, the coolest blog carnival covering hottest topics encompass that home coming. Now Chill with Log Buffer #222!!!

Oracle:

Charles Hooper blogs about an Overly Complicated Use Case Example regarding Row Values to Comma Separated Lists.

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Join us for a live webinar and download a new whitepaper where we discuss how to realize new value from data collected during web session management.

Session management has long been a key component of any web infrastructure – enhancing the user browsing experience through improved reliability, reduced latency and tighter security.

Increasingly organizations are looking to unlock more value from session management to further improve user loyalty (i.e. making the web service more “sticky”) and improve monetization of web services.  There are two distinct developments that offer the promise of unlocking more value from session data:
1.    Provide highly personalized browsing experiences by …

Here’s why I do: it’s time for me to build a new master database server. Our current main slave is too underpowered to be handle our entire load in an emergency, which means that our failover situation isn’t that great. I’ll replace the master with something new and shiny, make some performance improvements while I’m at it, and the old master will work just fine in an emergency.

For IO intensive servers, I conserve space and electricity by using 1U machines with 6 or 8 2.5″ drives.

I’d normally buy 8 Seagate Savvio 15K SAS drives and set them up as a RAID 10 array. This would run me about $1850.

We’re pretty frugal when it comes to our technology budget and I can’t really stomach spending that kind of money to effectively get 550 GB of redundant, fast magnetic disk storage. SATA MLC SSDs that blow traditional drives out of the water are currently under $2 / GB.

Disclaimer

MySQL has those curious size attributes you can apply to integer data types. For example, when creating a table, you might see:

mysql> CREATE TABLE foo (
    -> field_ti tinyint(1),
    -> field_si smallint(2),
    -> field_int int(4),
    -> field_bi bigint(5)
    -> );
Query OK, 0 rows affected (0.05 sec)

mysql> desc foo;
+-----------+-------------+------+-----+---------+-------+
| Field     | Type        | Null | Key | Default | Extra |
+-----------+-------------+------+-----+---------+-------+
| field_ti  | tinyint(1)  | YES  |     | NULL    |       |
| field_si  | smallint(2) | YES  |     | NULL    |       |
| field_int | int(4)      | YES  |     | NULL    |       |
| field_bi  | bigint(5)   | YES  |     | NULL    |       |
+-----------+-------------+------+-----+---------+-------+
3 rows in set (0.03 sec)

mysql>

I had always assumed those size attributes were limiters, MySQL's way of providing some sort of constraint on …