1. The FIRST_VALUE() is a window function in SQL that retrieves the value of a specified expression from the first row of the result set within a window frame defined by the OVER clause. This can be particularly useful when you want to retrieve a specific column value from the first row of each partition or ordered set of rows.

Here's the basic syntax of the FIRST_VALUE() function:

FIRST_VALUE(expression) OVER (PARTITION BY partition_expression ORDER BY sort_expression)

• expression: Specifies the column or expression whose value you want to retrieve from the first row.

• PARTITION BY partition_expression: This clause is optional and allows you to divide the result set into partitions. The FIRST_VALUE() function retrieves the value from the first row within each partition. If omitted, the function considers the entire result set as a single partition.

• ORDER BY sort_expression: Specifies the column or columns by which the rows should be ordered to determine the first row.

Here's an example to illustrate the usage of the FIRST_VALUE() function:

Suppose you have a table named "employees" with columns "employee_id", "name", "department", and "salary". You want to retrieve the name of the highest-paid employee within each department:

SELECT
    department,
    MAX(salary) AS max_salary,
    FIRST_VALUE(name) OVER (PARTITION BY department ORDER BY salary DESC) AS highest_paid_employee
FROM
    employees
GROUP BY
    department;

In this query:

• The MAX(salary) calculates the maximum salary within each department.

• The FIRST_VALUE(name) function retrieves the name of the employee with the highest salary within each department. The rows are ordered by salary in descending order.

1. The result set will show each department, the maximum salary within that department, and the name of the employee with the highest salary within the department.

2. The FIRST_VALUE() function is particularly useful when you want to extract specific information from the first row of each partition or ordered set of rows, as part of your data analysis and reporting tasks.

Last Value

1. In standard SQL, there is no built-in window function called LAST_VALUE() that directly retrieves the value from the last row of a window frame. While SQL supports various window functions for retrieving values from specific rows in a window frame, LAST_VALUE() is not natively available in most database systems.

If you need to retrieve the value from the last row of a window frame, you might need to use a combination of other window functions and filtering techniques. Here's one approach:

SELECT
    department,
    MAX(salary) AS max_salary,
    LAST_VALUE(name) OVER (PARTITION BY department ORDER BY salary ASC ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) AS last_employee
FROM
    employees
GROUP BY
    department;

1. In this example, the LAST_VALUE() function appears to be used, but it's achieved by ordering the rows in ascending order based on the salary and using the full range window frame (ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING). However, please note that this approach might not work in all scenarios, especially if there are duplicate salary values, as it could return one of the employees with the lowest salary.

2. If you're looking to retrieve the last value within a specific context (e.g., based on a certain ordering), it's often necessary to consider the ordering of the rows and potentially use a different approach depending on the data and the specific database system you're using. In some database systems, you might need to use subqueries or other techniques to achieve similar results.

Lead ()

1. The LEAD() window function is used in SQL to retrieve the value from a subsequent row within a window frame defined by the OVER clause. It's particularly useful for comparing values between the current row and the following row(s) based on a specified ordering.

Here's the basic syntax of the LEAD() function:

LEAD(expression, offset, default_value) OVER (PARTITION BY partition_expression ORDER BY sort_expression)

• expression: Specifies the column or expression whose value you want to retrieve from the subsequent row.

• offset: Specifies the number of rows ahead to look for. For example, LEAD(expression, 1) retrieves the value from the next row, and LEAD(expression, 2) retrieves the value from the row after the next row.

• default_value: Specifies a value to be returned if the offset goes beyond the available rows in the partition.

• PARTITION BY partition_expression: This clause is optional and allows you to divide the result set into partitions. The LEAD() function retrieves the value from the subsequent row within each partition. If omitted, the function considers the entire result set as a single partition.

• ORDER BY sort_expression: Specifies the column or columns by which the rows should be ordered to determine the subsequent row.

Here's an example to illustrate the usage of the LEAD() function:

Suppose you have a table named "sales" with columns "sale_date" and "revenue". You want to retrieve the revenue from the next sale for each row:

SELECT
    sale_date,
    revenue,
    LEAD(revenue, 1, 0) OVER (ORDER BY sale_date) AS next_sale_revenue
FROM
    sales;

In this query:

• The LEAD(revenue, 1, 0) function retrieves the revenue from the next sale (1 row ahead) for each row. If there's no next sale, the default value of 0 is returned.

• The rows are ordered by "sale_date" to determine the subsequent row.

The result set will show each sale's date, its revenue, and the revenue from the next sale.

The LEAD() function is especially helpful for analyzing trends and changes between consecutive rows within a window frame.

Lag()

1. The lag() function is used to access a previous row's value within a result set or a column of a table. It's particularly useful for calculating the difference between current and previous values, identifying trends, and performing various calculations involving sequential data.

In SQL, the lag() function is typically used in combination with the OVER() clause to define the partition and order within which the function operates. The basic syntax for using the lag() function in SQL is as follows:

SELECT column_name,
       lag(column_name, offset, default_value) OVER (PARTITION BY partition_column ORDER BY order_column) AS lagged_value
FROM table_name;

• column_name: The column for which you want to calculate the lag.

• offset: The number of rows back from the current row to access the lagged value. For example, if you set offset to 1, you'll access the value from the previous row.

• default_value: An optional parameter that specifies the value to return if the lagged row is not available (e.g., for the first row in the partition).

• PARTITION BY partition_column: Defines how the data should be partitioned before applying the lag function.

• ORDER BY order_column: Specifies the order within each partition for the lag operation.

Here's a simple example:

Suppose you have a table named sales with columns sale_date and revenue, and you want to calculate the revenue difference between each day's sales and the previous day's sales:

SELECT sale_date,
       revenue,
       revenue - lag(revenue, 1, 0) OVER (ORDER BY sale_date) AS revenue_difference
FROM sales;

This query would give you a result set with columns sale_date, revenue, and revenue_difference, where revenue_difference shows the difference between each day's revenue and the revenue of the previous day.

Keep in mind that the exact syntax and availability of the lag() function may vary depending on the specific SQL database system you are using.