How to Implement Full-Text Search in SQL Server

Full-text search in SQL Server allows for efficient searching of text data stored in tables. Unlike the traditional LIKE operator, full-text search enables powerful linguistic-based searches, ranking results by relevance and supporting advanced features like inflectional search and proximity queries. In this guide, we will walk through the steps to implement full-text search in SQL Server.

Before using full-text search, ensure that your SQL Server instance supports and has full-text search enabled. You can check this by running:

SELECT SERVERPROPERTY('IsFullTextInstalled') AS FullTextInstalled;

If the result is 1, full-text search is installed; otherwise, you may need to install it.

Step 2: Create a Full-Text Catalog

A full-text catalog is a container for full-text indexes. To create one, use:

CREATE FULLTEXT CATALOG MyFullTextCatalog AS DEFAULT;

Step 3: Create a Full-Text Index

A full-text index is required on the columns you want to search. First, make sure your table has a unique index:

CREATE UNIQUE INDEX UI_MyTable ON MyTable(Id);

Then, create a full-text index:

CREATE FULLTEXT INDEX ON MyTable(
    MyTextColumn LANGUAGE 1033
)
KEY INDEX UI_MyTable
ON MyFullTextCatalog;

The LANGUAGE 1033 specifies English. You can change this according to the language used in your data.

Step 4: Perform Full-Text Searches

Once the index is created, you can perform full-text searches using CONTAINS and FREETEXT.

Using CONTAINS

CONTAINS allows you to search for exact words or phrases:

SELECT * FROM MyTable
WHERE CONTAINS(MyTextColumn, '"search term"');

You can also use logical operators like AND, OR, and NEAR:

SELECT * FROM MyTable
WHERE CONTAINS(MyTextColumn, '"SQL Server" NEAR "Index"');

Using FREETEXT

FREETEXT allows for a broader, natural language search:

SELECT * FROM MyTable
WHERE FREETEXT(MyTextColumn, 'search term');
  • Populate the Full-Text Index: Full-text indexes are updated automatically, but you can manually trigger an update:

    ALTER FULLTEXT INDEX ON MyTable START FULL POPULATION;
    
  • Monitor Full-Text Indexing: Check the status of your full-text population with:

    SELECT * FROM sys.fulltext_indexes;
    
  • Remove a Full-Text Index: If needed, drop the index using:

    DROP FULLTEXT INDEX ON MyTable;
    

Conclusion

Full-text search in SQL Server is a powerful tool for handling complex text-based queries. By enabling full-text search, creating an index, and using CONTAINS or FREETEXT queries, you can significantly improve search performance and relevance in your applications. With proper indexing and management, full-text search can be a game-changer for handling large text-based datasets.

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Related

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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Storing passwords as plain text is dangerous. Instead, you should hash them using a strong, slow hashing algorithm like BCrypt, which includes built-in salting and resistance to brute-force attacks.

Step 1: Install BCrypt NuGet Package

Before using BCrypt, install the BCrypt.Net-Next package:

dotnet add package BCrypt.Net-Next

or via NuGet Package Manager:

Install-Package BCrypt.Net-Next

Step 2: Hash a Password

Use BCrypt.HashPassword() to securely hash a password before storing it:

using BCrypt.Net;

string password = "mySecurePassword123";
string hashedPassword = BCrypt.HashPassword(password);

Console.WriteLine(hashedPassword); // Output: $2a$12$...

Step 3: Verify a Password

To check a user's login attempt, use BCrypt.Verify():

bool isMatch = BCrypt.Verify("mySecurePassword123", hashedPassword);
Console.WriteLine(isMatch); // Output: True

Ensuring proper hashing should be at the top of your list when it comes to building authentication systems.

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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!

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