I'm somewhat limited to reading posts, so I might have missed something,
but can you explain why you wanted to avoid the 3rd table solution ?
Because depending on that question, I can offer two other solutions, but
they have their own limitations.
Solution 1: the "2,5nd" table.
you create an extra table and write a procedure that makes a unique ID
for every combination of attributes (and this procedure needs to be run
every time you update/add attributes).
when you want to query items for a combination of attributes, you first
select the attribute combination ID, then query your item list for all
items with this specific ID.
It isn't exactly a 3rd table solution as it doesn't involve individual
cross-references between items and a set of attributes, and thus saves
you an INNER JOIN.
Solution 2: an alphanumeric bit-wise selection.
Instead of saving your combinations as binary number, you could extend
it to, for example, a string of 4 characters per attribute: 4 characters
times 26 characters makes 456976 possible combinations per attribute :
define MENS = ________AAAA ;
define WOMENS = ________AAAB ;
define GREEN = ____AAAA____ ;
define RED = ____AAAB____ ;
you write one PHP function that converts an array of combinations into
an ISO wildcard filter (or does the MySQL syntax provide regular
expressions ?), and apply this in a SELECT FROM ... WHERE ... LIKE
$findTheseAttribs = new array ( MENS, GREEN );
$SQLlike=createSQLwildcard($findTheseAttribs); // returns ____AAAAAAAA
$mySql = "SELECT * FROM t_myTable WHERE itemAttribute LIKE " . $SQLlike;
The advantage is that you can assign different filter widths per
attribute: MENS/WOMENS only need 1 character, size only needs 2 ( XXXS,
XXS, XS, S, ... pretty limited), while colour can have op to 10
characters to encode. This leaves reasonable room to expand/scale.
The drawback is that, when you add new attributes, your filter string
expands, and the LIKE-statement might fail on the difference in string
On 12/01/12 02:18, Karl DeSaulniers wrote:
Yeah, I was being somewhat facetious about the colors of a shirt. :)
I agree on the items and attributes drill-down before implementation
There will be more than T-Shirts. Watches, book-covers, etc, etc.
So I need to find a general logic to cover the items and attributes of
And this will make it scalable?
On Jan 11, 2012, at 4:39 PM, tamouse mailing lists wrote:
I am thinking of limiting the colors to 10 for now (after all there
so many ways to die a shirt. =)
Oh, please. There are lots more than 10 dyes in the world. Take a look
at a women's clothing catalog sometime or other...
Just look at this one t-shirt item alone:
Individual item characteristics are going to be a lot different than
categories. You'll need expandable attributes for all kinds of things.
Colour is the obvious one here. Also: Size: not everything comes in S,
M, L, or is measured in that way. If this is for an apparel store that
sells a variety of different items, you'll need to solve this
generally across a whole lot of different types of clothing.
I'd really suggest you do a deep analysis of the different types of
items that are going to be sold, the attributes of each one, and
figure out how to best represent that breadth and depth.
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