Reading a file line by line is useful when handling large files without loading everything into memory at once.
✅ Best Practice: Use File.ReadLines() which is more memory efficient.
Example
foreach (string line in File.ReadLines("file.txt")) { Console.WriteLine(line); }
Why use ReadLines()?
Reads one line at a time, reducing overall memory usage. Ideal for large files (e.g., logs, CSVs).
Alternative: Use StreamReader (More Control)
For scenarios where you need custom processing while reading the contents of the file:
using (StreamReader reader = new StreamReader("file.txt")) { string? line; while ((line = reader.ReadLine()) != null) { Console.WriteLine(line); } }
Why use StreamReader?
Lets you handle exceptions, encoding, and buffering. Supports custom processing (e.g., search for a keyword while reading).
When to Use ReadAllLines()? If you need all lines at once, use:
string[] lines = File.ReadAllLines("file.txt");
Caution: Loads the entire file into memory—avoid for large files!
Using SqlDataReader asynchronously prevents blocking the main thread, improving performance in web apps and large queries. Here’s how to do it properly.
Use await with ExecuteReaderAsync()
using (SqlConnection conn = new SqlConnection(connectionString)) { await conn.OpenAsync(); using (SqlCommand cmd = new SqlCommand("SELECT * FROM Users", conn)) using (SqlDataReader reader = await cmd.ExecuteReaderAsync()) { while (await reader.ReadAsync()) { Console.WriteLine(reader["Username"]); } } // ✅ Auto-closes reader } // ✅ Auto-closes connection
Why use async?
A couple of reasons:
⚡ Alternative: ConfigureAwait(false) for ASP.NET
Use ConfigureAwait(false) in library code to avoid deadlocks in UI frameworks like ASP.NET.
using (SqlConnection conn = new SqlConnection(connectionString)) { await conn.OpenAsync().ConfigureAwait(false); using (SqlCommand cmd = new SqlCommand("SELECT * FROM Users", conn)) using (SqlDataReader reader = await cmd.ExecuteReaderAsync().ConfigureAwait(false)) { while (await reader.ReadAsync().ConfigureAwait(false)) { Console.WriteLine(reader["Username"]); } } }
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.
To count the number of unique values in a column, SQL Server provides the COUNT(DISTINCT column_name) function. Here’s a simple example:
COUNT(DISTINCT column_name)
SELECT COUNT(DISTINCT column_name) AS distinct_count FROM table_name;
This query will return the number of unique values in column_name.
column_name
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.
column1
column2
By leveraging COUNT(DISTINCT column_name), you can efficiently analyze your database and extract meaningful insights. Happy querying!
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"
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