22
09
2007
acts-as-tsearch is pretty cool, except for the fact that it uses Ruby (app layer) instead of PL/pgSQL (DB layer) to update the tsvectors that are indexed for full text search. That means that fixture data gets inserted without being full text indexed. D’oh!
Here’s some code that changes that.
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Categories : postgresql, ruby, ruby on rails, sql
4
08
2007
I’ve written before about tips for offshoring. One specific thing I said to watch for is the bait-and-switch of talent: during the sales process you’re shown rockstars, but the real code you get is written by clueless newbies. When you set up a project such that you’ve minimized the cost per hour of development, but you don’t have anyone checking the work product (i.e. code reviews) coming from the subcontractor, very bad things happen.
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Categories : humor, java, labor, management, offshoring, outsourcing, sql, testing
2
08
2007
From what I’ve seen, Rails’ weakest features lie in the way it prepares the test database and test data, and Ruby’s Test::Unit isn’t much better than the awful but ubuiquitous JUnit that Java developers are accustomed to. I set out this week to impose my preferences on Rails in this area, and that took some effort. Here’s what I did.
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Categories : architecture, databases, java, postgresql, ruby, ruby on rails, sql, testing
2
08
2007
For the last few days I’ve been struggling to bend Rails to my will regarding the proper way to assure data consistency. Today I made some progress. This builds upon some research I did a few months ago, and hopefully this is a more or less complete solution to the problem of making Rails work the way I want it to regarding test databases.
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Comments : 23 Comments »
Categories : architecture, databases, postgresql, ruby, ruby on rails, sql
15
07
2007
Once upon a time, before Google pwn3d internet search, there were several competing definitions for full text search. Altavista more or less gave you results matching the exact strings you gave it, but in a crazy order that made it painful to use. Excite (my favorite back then) used a dictionary to achieve stemming and synonym matches: searching for ‘dogs’ would also match documents that contained ‘canines’ or ‘dog’. Then Google blew them all away, and established a dominant set of expectations for how text search behaves.
I forgot about this, which is why I’m frustrated by the almost ridiculous complexity of the major server-side text search engines available right now. But it makes sense, once you learn what the options are.
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Categories : XML, architecture, databases, postgresql, ruby on rails, sql