It's been said that second place is the first loser. So, who needs an SQL statement to find out who these under achievers are? Surprisingly, a lot of people. In fact, the official term for this type of query is "nth highest value of a column". That's because techniques for selecting the 2nd highest value may also be applied for any value. In today's blog, we'll learn how to use ORDER BY DESC in conjunction with the LIMIT clause to obtain the 2nd highest value, and others, from a table.
All-too-often, database developers and administrators use Nulls, Zeroes, and Empty Strings interchangeably within their database tables. That's unfortunate, because Null, Zero, and an Empty String each represent something different in relational databases (RDBMS). As such, using these values incorrectly, or choosing the wrong one, can have enormous ramifications on the operation of your database and applications that rely on it. In today's blog, we'll explore how to best utilize the Null, Zero, and Empty String in database design and general usage.
If you have worked with relational databases (RDBMS) for any length of time, you have almost certainly utilized the SQL COUNT() function. As such, you are no doubt already aware that the COUNT() function returns the number of rows or columns in a table, as filtered by the criteria specified in the WHERE clause. Its flexible syntax and widespread support makes it one of the most versatile and useful functions in SQL. In today's blog, we'll take a look at its many permutations and learn how to obtain a variety of counts.
When it comes to storing formatted fields in a database, the adage "store raw, display pretty", usually holds true. In most cases, raw values are the most conducive for working with in the database, allowing them to be queried, sorted, compared, and what-have-you. Yet, there are times that you may want to leave in special characters, where they are essential to formatting, such as HTML markup. In today's blog, we'll explore both options with examples using Navicat Premium.
Adding the DISTINCT keyword to a SELECT query causes it to return only unique values for the specified column list so that duplicate rows are removed from the result set. Since DISTINCT operates on all of the fields in SELECT's column list, it can't be applied to an individual field that are part of a larger group. That being said, there are ways to remove duplicate values from one column, while ignoring other columns. We'll be taking a look at a couple of those here today.
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