How to Read and Write to a CSV File in C#

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!

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.

Removing duplicates from a list in C# is a common task, especially when working with large datasets. C# provides multiple ways to achieve this efficiently, leveraging built-in collections and LINQ.

Using HashSet (Fastest for Unique Elements)

A HashSet<T> automatically removes duplicates since it only stores unique values. This is one of the fastest methods:

List<int> numbers = new List<int> { 1, 2, 2, 3, 4, 4, 5 };
numbers = new HashSet<int>(numbers).ToList();
Console.WriteLine(string.Join(", ", numbers)); // Output: 1, 2, 3, 4, 5

Using LINQ Distinct (Concise and Readable)

LINQ’s Distinct() method provides an elegant way to remove duplicates:

List<int> numbers = new List<int> { 1, 2, 2, 3, 4, 4, 5 };
numbers = numbers.Distinct().ToList();
Console.WriteLine(string.Join(", ", numbers)); // Output: 1, 2, 3, 4, 5

Removing Duplicates by Custom Property (For Complex Objects)

When working with objects, DistinctBy() from .NET 6+ simplifies duplicate removal based on a property:

using System.Linq;
using System.Collections.Generic;

class Person
{
    public string Name { get; set; }
    public int Age { get; set; }
}

List<Person> people = new List<Person>
{
    new Person { Name = "Alice", Age = 30 },
    new Person { Name = "Bob", Age = 25 },
    new Person { Name = "Alice", Age = 30 }
};

people = people.DistinctBy(p => p.Name).ToList();
Console.WriteLine(string.Join(", ", people.Select(p => p.Name))); // Output: Alice, Bob

For earlier .NET versions, use GroupBy():

people = people.GroupBy(p => p.Name).Select(g => g.First()).ToList();

Performance Considerations

• HashSet<T> is the fastest but only works for simple types.
• Distinct() is easy to use but slower than HashSet<T> for large lists.
• DistinctBy() (or GroupBy()) is useful for complex objects but may have performance trade-offs.

Conclusion

Choosing the best approach depends on the data type and use case. HashSet<T> is ideal for primitive types, Distinct() is simple and readable, and DistinctBy() (or GroupBy()) is effective for objects.