String Interpolation in C#: A Cleaner Way to Format Strings

Closing a SqlDataReader correctly prevents memory leaks, connection issues, and unclosed resources. Here’s the best way to do it.

Use 'using' to Auto-Close

Using using statements ensures SqlDataReader and SqlConnection are closed even if an exception occurs.

Example

using (SqlConnection conn = new SqlConnection(connectionString))
{
    conn.Open();
    using (SqlCommand cmd = new SqlCommand("SELECT * FROM Users", conn))
    using (SqlDataReader reader = cmd.ExecuteReader())
    {
        while (reader.Read())
        {
            Console.WriteLine(reader["Username"]);
        }
    } // ✅ Auto-closes reader here
} // ✅ Auto-closes connection here

This approach auto-closes resources when done and it is cleaner and less error-prone than manual closing.

⚡ Alternative: Manually Close in finally Block

If you need explicit control, you can manually close it inside a finally block.

SqlDataReader? reader = null;
try
{
    using SqlConnection conn = new SqlConnection(connectionString);
    conn.Open();
    using SqlCommand cmd = new SqlCommand("SELECT * FROM Users", conn);
    reader = cmd.ExecuteReader();

    while (reader.Read())
    {
        Console.WriteLine(reader["Username"]);
    }
}
finally
{
    reader?.Close();  // ✅ Closes reader if it was opened
}

This is slightly more error prone if you forget to add a finally block. But might make sense when you need to handle the reader separately from the command or connection.

When working with SQL Server, you may often need to count the number of unique values in a specific column. This is useful for analyzing data, detecting duplicates, and understanding dataset distributions.

Using COUNT(DISTINCT column_name)

To count the number of unique values in a column, SQL Server provides the COUNT(DISTINCT column_name) function. Here’s a simple example:

SELECT COUNT(DISTINCT column_name) AS distinct_count
FROM table_name;

This query will return the number of unique values in column_name.

Counting Distinct Values Across Multiple Columns

If you need to count distinct combinations of multiple columns, you can use a subquery:

SELECT COUNT(*) AS distinct_count
FROM (SELECT DISTINCT column1, column2 FROM table_name) AS subquery;

This approach ensures that only unique pairs of column1 and column2 are counted.

Why Use COUNT DISTINCT?

• Helps in identifying unique entries in a dataset.
• Useful for reporting and analytics.
• Efficient way to check for duplicates.

By leveraging COUNT(DISTINCT column_name), you can efficiently analyze your database and extract meaningful insights. Happy querying!

Understanding the difference between COUNT() and COUNT(DISTINCT) in SQL is crucial for accurate data analysis.

COUNT() returns the total number of rows that match your query criteria, including duplicates, while COUNT(DISTINCT) returns the number of unique values in a specified column, effectively eliminating duplicates from the count.

For example, if you have a table of customer orders where a single customer can place multiple orders, COUNT(customer_id) would give you the total number of orders, whereas COUNT(DISTINCT customer_id) would tell you how many unique customers have placed orders.

The choice between these functions depends on your specific reporting needs. Use COUNT() when you need the total number of records, such as counting all sales transactions or total number of website visits.

Use COUNT(DISTINCT) when you need to know unique occurrences, like the number of different products sold or unique visitors to your website. It's also worth noting that COUNT(*) counts all rows including NULL values, while COUNT(column_name) excludes NULL values from that specific column, which can lead to different results depending on your data structure.

Example

-- Example table: customer_orders
-- customer_id | order_date  | product_id
-- 1          | 2024-01-01  | 100
-- 1          | 2024-01-02  | 101
-- 2          | 2024-01-01  | 100
-- 3          | 2024-01-03  | 102

-- Count all orders
SELECT COUNT(*) as total_orders
FROM customer_orders;
-- Result: 4 (counts all rows)

-- Count unique customers who placed orders
SELECT COUNT(DISTINCT customer_id) as unique_customers
FROM customer_orders;
-- Result: 3 (counts unique customer_ids: 1, 2, 3)

-- Count unique products ordered
SELECT COUNT(DISTINCT product_id) as unique_products
FROM customer_orders;
-- Result: 3 (counts unique product_ids: 100, 101, 102)

-- Compare regular COUNT with COUNT DISTINCT
SELECT 
    COUNT(customer_id) as total_orders,
    COUNT(DISTINCT customer_id) as unique_customers
FROM customer_orders;
-- Result: total_orders = 4, unique_customers = 3