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  • Data Access Layer, Best Practices

    - by labratmatt
    I'm looking for input on the best way to refactor the data access layer (DAL) in my PHP based web app. I follow an MVC pattern: PHP/HTML/CSS/etc. views on the front end, PHP controllers/services in the middle, and a PHP DAL sitting on top of a relational database in the model. Pretty standard stuff. Things are working fine, but my DAL is getting large (codesmell?) and becoming a bit unwieldy. My DAL contains almost all of the logic to interface with my database and is full of functions that look like this: function getUser($user_id) { $statement = "select id, name from users where user_id=:user_id"; PDO builds statement and fetchs results as an array return $array_of_results_generated_by_PDO_fetch_method; } Notes: The logic in my controller only interacts with the model using functions like the above in the DAL I am not using a framework (I'm of the opinion that PHP is a templating language and there's no need to inject complexity via a framework) I generally use PHP as a procedural language and tend to shy away from its OOP approach (I enjoy OOP development but prefer to keep that complexity out of PHP) What approaches have you taken when your DAL has reached this point? Do I have a fundamental design problem? Do I simply need to chop my DAL into a number of smaller files (logically divide it)? Thanks.

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  • QueryReadStore loads JSON into DataGrid, but JsonRestStore does not (from the same source)

    - by labratmatt
    I'm building a Dojo DataGrid from JSON data provided by my REST interface. The DataGrid loads the data fine using a QueryReadStore, but doesn't seem to work with the same same data piped into a JsonRestStore. I'm using the following Dojo libs with Dojo 1.4.1: dojo.require("dojox.data.JsonRestStore"); dojo.require("dojox.grid.DataGrid"); dojo.require("dojox.data.QueryReadStore"); dojo.require("dojo.parser"); I declare my stores in the following manner: var storeJRS = new dojox.data.JsonRestStore({target:"api/collaborations.php/1", idAttribute: 'items[].id'}); var storeQRS = new dojox.data.QueryReadStore({url:"api/collaborations.php/1", requestMethod:"get"}); I create my grid layout like this: var gridLayout = [ new dojox.grid.cells.RowIndex({ name: "Row #", width: 5, styles: "text-align: left;" }), { name: "Name", field: "name", styles: "text-align:right;", width:20 }, { name: "Description", field: "description", width:30 } ]; I create my DataGrid as follows: The above works, but if I use QueryReadStore as my store, the grid is created with the headers (Name, Description), but it isn't populated with any rows: <div dojoType="dojox.grid.DataGrid" jsid="grid3" store="storeQRS" structure="gridLayout" style="height:500px; width:1000px;"></div> Using FireBug, I can see that QueryReadStore is getting my JSON data from my REST interface. It looks like the following: {"numRows":6,"items":[{"name":"My Super Cool Collab","description":"This is for all the super cool people in the super cool group","id":1},{"name":"My Other Super Cool","description":"This is for all the other super cool people","id":3},{"name":"This is another coll","description":"This is just some other collab","id":4},{"name":"some new collab","description":"this is a new collab","id":5},{"name":"yet another new coll","description":"uh huh","id":6},{"name":"asdf","description":"asdf","id":7}]} Any ideas? Thanks.

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  • KD-Trees and missing values (vector comparison)

    - by labratmatt
    I have a system that stores vectors and allows a user to find the n most similar vectors to the user's query vector. That is, a user submits a vector (I call it a query vector) and my system spits out "here are the n most similar vectors." I generate the similar vectors using a KD-Tree and everything works well, but I want to do more. I want to present a list of the n most similar vectors even if the user doesn't submit a complete vector (a vector with missing values). That is, if a user submits a vector with three dimensions, I still want to find the n nearest vectors (stored vectors are of 11 dimensions) I have stored. I have a couple of obvious solutions, but I'm not sure either one seem very good: Create multiple KD-Trees each built using the most popular subset of dimensions a user will search for. That is, if a user submits a query vector of thee dimensions, x, y, z, I match that query to my already built KD-Tree which only contains vectors of three dimensions, x, y, z. Ignore KD-Trees when a user submits a query vector with missing values and compare the query vector to the vectors (stored in a table in a DB) one by one using something like a dot product. This has to be a common problem, any suggestions? Thanks for the help.

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