How to Implement Full-Text Search in SQL Server

In C#, you can format an integer with commas (thousands separator) using ToString with a format specifier.

int number = 1234567;
string formattedNumber = number.ToString("N0"); // "1,234,567"
Console.WriteLine(formattedNumber);

Explanation:

"N0": The "N" format specifier stands for Number, and "0" means no decimal places. The output depends on the culture settings, so in regions where , is the decimal separator, you might get 1.234.567.

Alternative:

You can also specify culture explicitly if you need a specific format:

using System.Globalization;

int number = 1234567;
string formattedNumber = number.ToString("N0", CultureInfo.InvariantCulture);
Console.WriteLine(formattedNumber); // "1,234,567"

Raw string literals in C# provide a flexible way to work with multiline strings, with some interesting rules around how quotes work.

The key insight is that you can use any number of double quotes (three or more) to delimit your string, as long as the opening and closing sequences have the same number of quotes.

The Basic Rules

1. You must use at least three double quotes (""") to start and end a raw string literal
2. The opening and closing quotes must have the same count
3. The closing quotes must be on their own line for proper indentation
4. If your string content contains a sequence of double quotes, you need to use more quotes in your delimiter than the longest sequence in your content

Examples with Different Quote Counts

// Three quotes - most common usage
string basic = """
    This is a basic
    multiline string
    """;

// Four quotes - when your content has three quotes
string withThreeQuotes = """"
    Here's some text with """quoted""" content
    """";

// Five quotes - when your content has four quotes
string withFourQuotes = """""
    Here's text with """"nested"""" quotes
    """"";

// Six quotes - for even more complex scenarios
string withFiveQuotes = """"""
    Look at these """""nested""""" quotes!
    """""";

The N+1 Rule

The general rule is that if your string content contains N consecutive double quotes, you need to wrap the entire string with at least N+1 quotes. This ensures the compiler can properly distinguish between your content and the string's delimiters.

// Example demonstrating the N+1 rule
string example1 = """
    No quotes inside
    """; // 3 quotes is fine

string example2 = """"
    Contains """three quotes"""
    """"; // Needs 4 quotes (3+1)

string example3 = """""
    Has """"four quotes""""
    """""; // Needs 5 quotes (4+1)

Practical Tips

• Start with three quotes (""") as your default
• Only increase the quote count when you actually need to embed quote sequences in your content
• The closing quotes must be on their own line and should line up with the indentation you want
• Any whitespace to the left of the closing quotes defines the baseline indentation

// Indentation example
string properlyIndented = """
    {
        "property": "value",
        "nested": {
            "deeper": "content"
        }
    }
    """; // This line's position determines the indentation

This flexibility with quote counts makes raw string literals extremely versatile, especially when dealing with content that itself contains quotes, like JSON, XML, or other structured text formats.

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!