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How to Detect and Remove Duplicate Records in SQL Server

Duplicate records in SQL Server can lead to inaccurate reporting, data inconsistencies, and performance issues. In this article, we’ll go over how to identify and safely remove duplicate rows while keeping at least one unique record.

Detecting Duplicates

To find duplicate records in a table, use the GROUP BY and HAVING clauses to count occurrences of each unique combination of values:

SELECT column1, column2, COUNT(*)
FROM YourTable
GROUP BY column1, column2
HAVING COUNT(*) > 1;

Replace column1, column2 with the columns that define a duplicate in your dataset.

If you need to see the actual duplicate rows, use a ROW_NUMBER() approach:

SELECT *
FROM (
    SELECT *, ROW_NUMBER() OVER (PARTITION BY column1, column2 ORDER BY id) AS row_num
    FROM YourTable
) t
WHERE row_num > 1;

Here, id should be a unique column to order the duplicates.

Removing Duplicates

Method 1: Using ROW_NUMBER()

The safest way to remove duplicates while keeping one unique record is by using ROW_NUMBER().

WITH CTE AS (
    SELECT *, ROW_NUMBER() OVER (PARTITION BY column1, column2 ORDER BY id) AS row_num
    FROM YourTable
)
DELETE FROM CTE WHERE row_num > 1;

This deletes all duplicate records while keeping the first occurrence.

Method 2: Using DISTINCT INTO a New Table

If you want to be extra cautious, create a new table with only unique records:

SELECT DISTINCT * INTO NewTable FROM YourTable;

Then, drop the old table and rename NewTable back to YourTable.

Final Thoughts

Always backup your data before running delete operations to prevent accidental data loss. By regularly cleaning up duplicates, you can keep your SQL Server database efficient and reliable.

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Related

String interpolation, introduced in C# 6.0, provides a more readable and concise way to format strings compared to traditional concatenation (+) or string.Format(). Instead of manually inserting variables or placeholders, you can use the $ symbol before a string to directly embed expressions inside brackets.

string name = "Walt";
string job = 'Software Engineer';

string message = $"Hello, my name is {name} and I am a {job}";
Console.WriteLine(message);

This would produce the final output of:

Hello, my name is Walt and I am a Software Engineer

String interpolation can also be chained together into a multiline string (@) for even cleaner more concise results:

string name = "Walt";
string html = $@"
    <div>
        <h1>Welcome, {name}!</h1>
    </div>";
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Primary constructors, introduced in C# 12, offer a more concise way to define class parameters and initialize fields.

This feature reduces boilerplate code and makes classes more readable.

Traditional Approach vs Primary Constructor

Before primary constructors, you would likely write something like the following:

public class UserService
{
    private readonly ILogger _logger;
    private readonly IUserRepository _repository;

    public UserService(ILogger logger, IUserRepository repository)
    {
        _logger = logger;
        _repository = repository;
    }

    public async Task<User> GetUserById(int id)
    {
        _logger.LogInformation("Fetching user {Id}", id);
        return await _repository.GetByIdAsync(id);
    }
}

With primary constructors, this becomes:

public class UserService(ILogger logger, IUserRepository repository)
{
    public async Task<User> GetUserById(int id)
    {
        logger.LogInformation("Fetching user {Id}", id);
        return await repository.GetByIdAsync(id);
    }
}

Key Benefits

  1. Reduced Boilerplate: No need to declare private fields and write constructor assignments
  2. Parameters Available Throughout: Constructor parameters are accessible in all instance methods
  3. Immutability by Default: Parameters are effectively readonly without explicit declaration

Real-World Example

Here's a practical example using primary constructors with dependency injection:

public class OrderProcessor(
    IOrderRepository orderRepo,
    IPaymentService paymentService,
    ILogger<OrderProcessor> logger)
{
    public async Task<OrderResult> ProcessOrder(Order order)
    {
        try
        {
            logger.LogInformation("Processing order {OrderId}", order.Id);
            
            var paymentResult = await paymentService.ProcessPayment(order.Payment);
            if (!paymentResult.Success)
            {
                return new OrderResult(false, "Payment failed");
            }

            await orderRepo.SaveOrder(order);
            return new OrderResult(true, "Order processed successfully");
        }
        catch (Exception ex)
        {
            logger.LogError(ex, "Failed to process order {OrderId}", order.Id);
            throw;
        }
    }
}

Tips and Best Practices

  1. Use primary constructors when the class primarily needs dependencies for its methods
  2. Combine with records for immutable data types:
public record Customer(string Name, string Email)
{
    public string FormattedEmail => $"{Name} <{Email}>";
}
  1. Consider traditional constructors for complex initialization logic

Primary constructors provide a cleaner, more maintainable way to write C# classes, especially when working with dependency injection and simple data objects.

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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!

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