Aggregate and Analytic functions in SQL Server operate on a set of rows. However, unlike such aggregate functions as sum, count and average that return scalar values, analytic functions return a group of rows that can be further analyzed. In this article, we will see some of the most commonly used analytic functions in SQL server. We will be discussing the following functions:
Suppose you are designing an SQL Server database application for a company’s CEO and you have to display the fifth most highly paid employee in the company.
What would you do? Read More
In my previous article about T-SQL regular expressions, I have explained the LIKE operator, its usage and provided several examples with it. In this article, we are going to discuss the SUBSTRING, PATINDEX, and CHARINDEX functions of T-SQL. These functions can be used to perform pattern matching. Read More
Microsoft SQL Server has many built-in functions that can be used to format the output and represents it in the desired format.
In this article, the following built-in string functions supported in Transact SQL will be discussed with examples provided:
The statistical median is the value which separates a dataset into halves – one comprises greater values, and the other comprises lesser ones. For a specified dataset, it can be considered as the “middle” value. For example, in the dataset {1, 3, 3, 4, 5, 6, 7, 8, 9}, the median is 5, which is fourth largest, and fourth smallest number in the dataset.
To calculate the median of any dataset, we first need to arrange all values from the dataset in a specific order. After arranging the data, we must determine the middle value of the specified dataset. If the dataset contains an odd number of values, than the middle value of the entire dataset will be considered as a median. Read More
In this article, I will demonstrate several ways to split the delimited string and insert it in into a column of a table in SQL Server. You can do it using the following methods:
This article is focused on the T-SQL (Transact-SQL) IsNumeric function and its proper use in day-to-day SQL scripting tasks.
We will also see why it is important to understand how and why IsNumeric can be used – both incorrectly and correctly.
There may be some better alternatives to IsNumeric depending on the context. However, in the cases we’re going to cover in this article, I see this function as the best possible choice. Read More
Data types are attributes that specify the kind of data that objects such as columns, local variables, expressions, and parameters can hold. Across the RDBMS world, data types are typically grouped into string, numeric, and date data types.
T-SQL supports 6 date and time data types namely:
The first two data types are considered as legacy versions of the newer ones. In this article, we focus on the date data types and, specifically, on the datetime and datetime2 data types available in SQL Server. Table 1 gives details of the various date and time data types available in SQL Server. Read More
Assuming you maintain a table containing customer data, and your boss asks you to send him the current list of customers and their phone numbers. You would typically extract the data and send him a spreadsheet with rows and columns. You could also decide to be a bit stylish and send him the required information in a more people-friendly format. SQL Server provides functions that allow us to achieve this by combining English expressions with data within tables to present an output that is easier for non-technical people to read. These functions can also be put to more subtle uses.
What is NULL? NULL or the NULL marker is the way we represent an unknown value in SQL, by SQL I am referring to the standard Structured Query Language, not MS SQL Server. The last sentence takes us a little back to 1969 when the standard was first defined by Dr. E.F. Codd. NULL becomes necessary because we need to think in terms of what is called three-valued predicate logic. A predicate is the property of an expression that either holds or does not hold. At face value, one would think of two possibilities: TRUE or FALSE. However, there is a third possibility: UNKNOWN. Read More