How to Extract Hashtags from Text in SQL Server Using string_split

Learn how to efficiently extract hashtags from text data stored in SQL Server with our step-by-step guide using T-SQL.
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How to Extract Hashtags from Text in SQL Server Using string_split

Extracting hashtags can be a common task when working with text data, especially in scenarios involving social media or tagging systems. If you're currently utilizing a C- application to extract hashtags using regular expressions but wish to transition that functionality to SQL Server, you're in the right place! In this guide, we will walk you through the solution to this problem step by step.

The Challenge

You have a table called -Keywords that stores various strings containing hashtags, and you want to extract those hashtags into a new table called -HashtagsResult. Here’s what your challenge looks like:

Initial Dataset

You have the following table structure and data in your -Keywords table:

[[See Video to Reveal this Text or Code Snippet]]

Desired Outcome

You want to create a new table, -HashtagsResult, that looks like this:

[[See Video to Reveal this Text or Code Snippet]]

The Solution

To achieve hashtag extraction from the -Keywords table, we can utilize the T-SQL function string_split. Here’s how it works:

Step 1: Splitting the Strings

We will use string_split to separate the text in the Word column by spaces. This function returns a single-column table whose rows represent the substrings of the original string.

Step 2: Filtering for Hashtags

After splitting the string, we will filter for values that begin with the - character, as those represent our hashtags.

Step 3: Putting It All Together in a SQL Query

Below is the complete query that performs the extraction and inserts the results into the -HashtagsResult table:

[[See Video to Reveal this Text or Code Snippet]]

Explanation of The Code

CROSS APPLY: This SQL operator allows us to join each row from -Keywords with the resulting rows from string_split.

string_split(Word, ' '): This splits each string in the Word column by spaces, generating rows for each word.

Final Result

After running the above code, you can retrieve the resulting table with:

[[See Video to Reveal this Text or Code Snippet]]

This will give you a beautifully extracted list of hashtags from your original dataset, neatly organized with their associated IDs.

Conclusion

With this straightforward and efficient approach using string_split, you can easily transition your hashtag extraction from a C- application to SQL Server SQL queries. This not only reduces the complexity of maintaining a separate C- codebase but also leverages the power of SQL for data processing.

Feel free to use the code snippets provided in this guide to enhance your own database management and data processing tasks. Happy querying!