Compare Successive Rows within the same table 

(how to compare successive rows within the same table)

How to Use LEAD in SQL

The LEAD function in SQL is a window function that allows you to access the value of a column in the next row within the same result set, based on a specified ordering. It's particularly useful when you want to compare values from successive rows.

Syntax

LEAD(column_name, offset, default_value) OVER (
    PARTITION BY partition_column
    ORDER BY order_column
)

• column_name: The column to fetch the value from the next row.
• offset: (Optional) Specifies how many rows ahead to look. Default is 1.
• default_value: (Optional) A value to return if there’s no next row. Default is NULL.
• PARTITION BY: (Optional) Divides the rows into partitions to reset the window function for each partition.
• ORDER BY: Defines the order of rows to determine what the "next row" is.

Example Use Cases

1. Comparing Successive Rows

Suppose you have a table sales:

To calculate the difference between the current day's sales and the next day's sales:

SELECT
    id,
    sale_date,
    sales_amount,
    LEAD(sales_amount, 1) OVER (ORDER BY sale_date) AS next_sales,
    LEAD(sales_amount, 1) OVER (ORDER BY sale_date) - sales_amount AS sales_difference
FROM sales;

Output:

2. Filling Missing Data

Suppose a students table contains scores and you want to fill missing future scores with a default value (e.g., 0):

You can use LEAD with a default value:

SELECT
    student_id,
    exam_date,
    score,
    LEAD(score, 1, 0) OVER (ORDER BY exam_date) AS next_score
FROM students;

Output:

3. Using Partitions

If you want to compare data within groups (e.g., by region), use PARTITION BY.

Table sales_by_region:

To calculate next day's sales within each region:

sql
Copy code
SELECT
    region,
    sale_date,
    sales_amount,
    LEAD(sales_amount) OVER (PARTITION BY region ORDER BY sale_date) AS next_sales
FROM sales_by_region;

Output:

Key Points

1. LEAD is for Next Rows: Fetches the value from the next row based on the specified order.
2. Use PARTITION BY for Groups: Processes rows within each group independently.
3. Custom Defaults: Specify a default value when there’s no next row.
4. Performance: Ensure proper indexing for large datasets when using ORDER BY.

When to Use LEAD

• Trend Analysis: Compare successive values (e.g., stock prices, sales trends).
• Filling Gaps: Predict or backfill missing values.
• Event Durations: Calculate time differences between events.
• Comparing Groups: Analyze changes within partitions like regions or categories.

This function is powerful for row-based comparisons in SQL, making it easier to solve many real-world problems.