Column Statistics

Use Wheels to get statistics on the values in a column, like row counts, averages, highest values, lowest values, and sums.

Since CFWheels simplifies so much for you when you select, insert, update, and delete rows from the database, it would be a little annoying if you had to revert back to using cfquery and COUNT(id) AS x type queries when you wanted to get aggregate values, right?

Well, good news. Of course you don't need to do this; just use the built-in functions sum(), minimum(), maximum(), average() and count().

Let's start with the count() function, shall we?

Counting Rows

To count how many rows you have in your authors table, simply do this:

authorCount = model("author").count();

What if you only want to count authors with a last name starting with "A"? Like the findAll() function, count() will accept a where argument, so you can do this:

authorCount = model("author").count(where="lastName LIKE 'A%'");

Simple enough. But what if you wanted to count only authors in the USA, and that information is stored in a different table? Let's say you have stored country information in a table called profiles and also setup a hasOne / belongsTo association between the author and profile models.

Just like in the findAll() function, you can now use the include argument to reference other tables.

In our case, the code would end up looking something like this:

authorCount = model("author").count(include="profile", where="countryId=1 AND lastName LIKE 'A%'");

Or, if you care more about readability than performance, why not just join in the countries table as well?

authorCount = model("author").count(include="profile(country)", where="name='USA' AND lastName LIKE 'A%'");

In the background, these functions all perform SQL that looks like this:

MySQL

SELECT COUNT(*)
FROM authors
WHERE ...

However, if you include a hasMany association, CFWheels will be smart enough to add the DISTINCT keyword to the SQL. This makes sure that you're only counting unique rows.

For example, the following method call:

authorCount = model("author").count(include="books", where="title LIKE 'Wheels%'");

Will execute this SQL (presuming id is the primary key of the authors table and the correct associations have been setup):

MySQL

SELECT COUNT(DISTINCT authors.id)
FROM authors LEFT OUTER JOIN books ON authors.id = books.authorid
WHERE ..

OK, so now we've covered the count() function, but there are a few other functions you can use as well to get column statistics.

Getting an Average

You can use the average() function to get the average value on any given column. The difference between this function and the count() function is that this operates on a single column, while the count() function operates on complete records. Therefore, you need to pass in the name of the property you want to get an average for.

The same goes for the remaining column statistics functions as well; they all accept the property argument.

Here's an example of getting the average salary in a specific department:

avgSalary = model("employee").average(property="salary", where="departmentId=1");

You can also pass in distinct=true to this function if you want to include only each unique instance of a value in the average calculation.

Getting the Highest and Lowest Values

To get the highest and lowest values for a property, you can use the minimum() and maximum() functions.

They are pretty self explanatory, as you can tell by the following examples:

highestSalary = model("employee").maximum("salary");
lowestSalary = model("employee").minimum("salary");

Getting the Sum of All Values

The last of the column statistics functions is the sum() function.

As you have probably already figured out, sum() adds all values for a given property and returns the result. You can use the same arguments as with the other functions (property, where, include, and distinct).

Let's wrap up this chapter on a happy note by getting the total dollar amount you've made:

howRichAmI = model("invoice").sum("billedAmount");

Grouping Your Results

All of the methods we've covered in this chapter accepts the group argument. Let's build on the example with getting the average salary for a department above, but this time, let's get the average for all departments instead.

avgSalaries = model("employee").average(property="salary", group="departmentId");

When you choose to group results like this you get a cfquery result set back, as opposed to a single value.

Limited Support

The group argument is currently only supported on SQL Server and MySQL databases.