Calculated fields are an important tool in data management for manipulating and presenting data more effectively. This tool allows users to perform calculations directly in SQL queries, obtaining the desired results without changing the data in the table. By using calculated fields, users can save time and resources and increase efficiency in data processing.
Calculated fields are columns that don’t physically exist in a database table, but are dynamically created when a query is executed. This allows users to perform mathematical operations or string manipulations on existing data, generating new values from existing columns.
For example, we can use a calculated field to calculate the total price of multiple items by multiplying the number of items by the price per item and displaying the results in a single query.
The data stored in the table is static information that only changes if there is a manual update. In contrast, the calculation results from calculated fields are dynamic and can change each time a query is executed. This means that calculated fields can provide the latest value based on the current conditions without changing the table’s original data.
For example, if we have columns for price and quantity, we can use calculated fields to calculate the total price directly when querying, instead of storing the total price as separate columns in the table.
Advantages of Using Calculated Fields
Improve data capture efficiency.
Calculated fields allow users to retrieve processed data directly from the database without the need for additional processing on the client side. This speeds up application response and reduces network load, as only the necessary data is sent.
The efficiency of data processing on the server
Database Management Systems (DBMS) are designed to process data quickly and efficiently. With calculated fields, all calculations are performed on the server, which is usually faster than if it were done on the client. It also reduces the use of client resources, such as CPU and memory, thereby improving the overall performance of the application.
Reduce processing requirements at the client.
With calculated fields, much of the processing that would normally be done by a client application can be moved to the database server. This means that the application does not need to perform calculations or change the data format after retrieving it from the database, which saves time and reduces code complexity.
Simplify queries for specific reports or needs.
Calculated fields allow users to simplify complex queries to be easier to understand and manage. For example, instead of taking multiple separate columns and performing calculations in the app, the user can create a single query with a calculated field that provides the desired final result. This not only improves the readability of queries but also makes it easier to create reports or analyze data.
How to Create Calculated Fields in SQL
Calculated fields are created by adding a formula or function in the SELECT command. This formula can be text merging, number calculation, or other data processing. The result columns of this calculation are not stored in the table but are automatically created when the query is executed.
String Merge with Concat()
One common use of Calculated Fields is to combine strings from multiple columns into one. The Concat() function in SQL is used to combine two or more strings into a single string.
The Concat() function allows us to combine the values of multiple columns. In addition, we can use aliases with US keywords to name the calculated columns to make them more accessible and understandable.
Code Examples
Here’s an example SQL query that uses Concat() to combine the vendor name and vendor country into a single new column named vend_title:
SELECT Concat(vend_name, ' (', vend_country, ')') AS vend_title
FROM vendors
ORDER BY vend_name;Code Sample Analysis
Concat(): In this example, the Concat() function combines three elements:
- The vendor name from the vend_name column.
- Strings in the form of spaces and opening brackets ‘ (‘.
- Country name from vend_country column.
- Cap brackets ‘)’.
Alias: Using AS vend_title, we give the combined result a name, so that the result can be referenced as vend_title in the client application.
Output: The result of this query will result in a new column containing the combination of vendor name and country in the desired format, such as:
+----------------------+
| vend_title |
+----------------------+
| ACME (USA) |
| Anvils R Us (USA) |
| Furball Inc. (USA) |
| Jet Set (England) |
| Jouets Et Ours (France) |
| LT Supplies (USA) |
+----------------------+Removing Spaces with the Trim() Function
In data management, we often encounter unwanted spacing issues around string values. To solve this problem, SQL offers several trimming functions, namely RTrim(), LTrim(), and Trim(). These functions are very useful for cleaning the data before proceeding with the further process.
RTrim(), LTrim(), and Trim() functions
- RTrim(): Removes all spaces on the right side of the string.
- LTrim(): Removes all spaces on the left side of the string.
- Trim(): Removes all spaces on either side of the string.
These three functions help ensure that the data retrieved from the database is clean and ready to use, especially when performing string joins or calculations.
Use Cases for Data Cleaning
Here’s an example SQL query that uses the RTrim() function to remove unwanted spaces before combining vendor names and vendor countries:
SELECT Concat(RTrim(vend_name), '(', RTrim(vend_country), ') AS vend_title
FROM vendors
ORDER BY vend_name;Code Sample Analysis
Concat(RTrim(vend_name), ‘(‘, RTrim(vend_country), ‘)’): In this query, we use RTrim() on the vend_name and vend_country fields to make sure there are no extra spaces at the end of the vendor or country name. This is essential to maintain a neat and professional output format.
Alias: Using AS vend_title, we give this combined result a name, making it easy to reference in the client application.
Output: The result of this query will result in a new column named vend_title that contains a combination of vendor name and country without additional spaces, such as:
+----------------------+
| vend_title |
+----------------------+
| ACME (USA) |
| Anvils R Us (USA) |
| Furball Inc. (USA) |
| Jet Set (England) |
| Jouets Et Ours (France) |
| LT Supplies (USA) |
+----------------------+Perform Mathematical Calculations with Calculated Fields
In SQL, we can perform various mathematical calculations using basic operators. Here are the most frequently used operators:
- +: Summing
- –: Reduction
- \*: Multiplication
- /: Distribution
These operators allow us to perform different types of calculations on the data retrieved from the table. We can also use parentheses to set the order of operations in the calculation.
Example of Calculation Code
Here’s an example of a SQL query that performs a mathematical calculation to calculate the total price of an item in an order:
SELECT prod_id, quantity, item_price, quantity * item_price AS expanded_price
FROM orderitems
WHERE order_num = 20005;Code Sample Analysis
prod_id, quantity, item_price: These columns are taken from the order items table, which contains information about the product, the quantity ordered, and the price per unit.
quantity * item_price AS expanded_price: Here, we do the calculation by multiplying the quantity by item_price (price per unit). The result of this calculation is named alias expanded_price, which will appear as a new column in the query results.
WHERE order_num = 20005: This condition ensures that only items from the order with the number 20005 are picked.
Output
The result of this query will generate a table with the following information:
+---------+----------+------------+---------------+
| prod_id | quantity | item_price | expanded_price|
+---------+----------+------------+---------------+
| ANV01 | 10 | 5.99 | 59.90 |
| ANV02 | 3 | 9.99 | 29.97 |
| TNT2 | 5 | 10.00 | 50.00 |
| FB | 1 | 10.00 | 10.00 |
+---------+----------+------------+---------------+In that output, the expanded_price column shows the total price for each item based on the quantity ordered.
