How b-tree database indexes work and how to tell if they are efficient (100' level) | mattfleming.com
http://mattfleming.com/node/192

A team member thought we should add an index on a 90 million row table to improve performance. The field on which he wanted to create this index had only four possible values. To which I replied that an index on a low cardinality field wasn't really going to help anything. My boss then asked me why wouldn't it help? I sputtered around for a response but ended up telling him that I'd get back to him with a reasonable explanation.

Imported from http://twitter.com/newsycombinator/status/2645303258 How b-tree database indexes work and how to tell if they are efficient http://bit.ly/dd6mf

MySQLで索引を使っていないクエリーをログを調べずに見つける方法

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I still run into people lambasting git for the concept of the index from time to time. It seems strange and superfluous to users of other VCSs – like a speed bump that serves no purpose. Why not just commit the changes in the working copy? This perception is understandable; when I first heard of git, back as a Subversion user, I was one of these people. How times and minds change. Today, I use it and rely on it so much that I can’t imagine moving to any other VCS that doesn’t have this concept. (And none of the contemporary contenders do.) Because of this, I keep responding to such criticism, repeating myself. I figured I should put my explanation down somewhere where I can point people to.

PlayNice.ly is entirely based on a data-structure server called Redis. Redis is one of several new key-value databases which break away from traditional relational data architecture. It is simple, flexible, and blazingly fast. So why not use the tools we have already?

redis.smembers("word:" + metaphone("python"))

Interesting post about being able to search data in redis using indexing and phonetic algorthms.