Chris Nizzardini, Salt Lake City Utah, Web Developer Specializing in LAMP+Ajax Since 2006

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Archive for August, 2008

writing classes in javascript using mootools

Posted by chris on August 8th, 2008 Comments(0)

This is actually really simple and gives you some nice OOP functionality a web developer would not normally have in their web applications.

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var Customer = new Class({
	initialize: function(firstName, lastName, address, address2, city, state, zip, phone, email){
		this.firstName = firstName;
		this.lastName = lastName;
		this.address = address;
		this.address2 = address2;
		this.city = city;
		this.state = state;
		this.zip = zip;
		this.phone = phone;
		this.email = email;
	},
	quickSet: function(){
		this.firstName = $('firstName').value;
		this.lastName = $('lastName').value;
		this.address = $('address').value;
		this.address2 = $('address2').value;
		this.city = $('city').value;
		this.state = $('state').value;
		this.zip = $('zip').value;
		this.phone = $('ph1').value+$('ph2').value+$('ph3').value;
		this.email = $('email').value;
	}
});

In this example initialize is the constructor, which is required for a mootools class, where quickSet is a method I created for this class.

In ajax/dom/javascript ()

using functions in mysql where clauses breaks speed gains from indexing?

Posted by chris on August 8th, 2008 Comments(0)

I was conversing with a co-worker today and asked him to take a look at some queries of mine hoping he could determine why they were so sluggish. I had already ruled out a bad inner join, sub select, and lack of indexes. The query looked at a months worth of data using something like:

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WHERE DATE(date_time) '2008-08-08'

For whatever reason this will cause MySQL (at least MySQL 4) to ignore the indexing on the date_time field. Changing your query to this:

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WHERE date_time BETWEEN '2008-08-08 00:00:00' AND '2008-08-08 23:59:59'

Can save significant execution time. In my tests on a table with over 300,000 records this dropped by query execution time from roughly 4 seconds to .4 seconds, 10x faster! Using mysql functions in your select clause does not seem to negatively impact execution time.

In SQL ()