Using Regular Expressions to Split Strings in Oracle SQL: A Step-by-Step Guide

Introduction to Regular Expressions in Oracle SQL

Regular expressions are a powerful tool for pattern matching and string manipulation. In Oracle SQL, regular expressions can be used to split strings into individual components based on specific patterns. This article will explore how to use regular expressions in Oracle SQL to split a string by a pattern.

Background: What is Regular Expression?

A regular expression (regex) is a sequence of characters that forms a search pattern used for matching similar characters in words, phrases, and other text. Regex can be used to match patterns in strings, validate input data, and extract data from strings.

In Oracle SQL, the REGEXP function is used to perform regular expression operations on strings.

Understanding the Problem

The problem at hand involves splitting a string by a pattern. In this case, we have a string that contains email addresses separated by the ‘@’ symbol. The goal is to split this string into individual email addresses, even if there are multiple domains separated by ‘@’.

Step 1: Preparing the Data

To demonstrate the use of regular expressions in Oracle SQL, let’s create a sample table and insert some data.

CREATE TABLE test (email VARCHAR2(100));

INSERT INTO test (email) VALUES (
    '<a>[email@localhost]</a>',
    '<a>[email@localhost](yahoo.com)</a>'
);

Step 2: Splitting the String using Regular Expression

To split the string by the ‘@’ symbol, we can use the REGEXP_SUBSTR function in combination with the REGEXP_COUNT function.

WITH test (email) AS (
    SELECT '<a>[email@localhost]</a>' FROM DUAL UNION ALL
    SELECT '<a>[email@localhost](yahoo.com)</a>' FROM DUAL
)
SELECT LTRIM(REGEXP_SUBSTR(email, '@(\w+\.\w+)', 1, level)) RES
FROM test,
       TABLE(CAST(MULTISET(SELECT LEVEL FROM DUAL CONNECT BY LEVEL <= REGEXP_COUNT(email, '@')) AS SYS.ODCINumberList));

Let’s break down what’s happening in this query:

We use the REGEXP_SUBSTR function to extract the pattern we’re interested in. In this case, we want to extract everything after the first ‘@’ symbol that contains two or more word characters separated by a dot.
The second argument to REGEXP_SUBSTR is a level number, which tells Oracle how many times to repeat the pattern until it’s no longer found in the string.
We use the LEVEL column from the MULTISET function to get the different levels of repetition. This allows us to handle cases where there are multiple domains separated by ‘@’.
Finally, we use the LTRIM function to remove any leading ‘@’ symbols.

Step 3: Handling Multiple Domains

In some cases, there may be multiple domains separated by ‘@’. For example, if we have an email address like <a>[email@localhost](yahoo.com)(google.com)</a>, we want to split this string into two separate domains: yahoo.com and google.com.

To handle this scenario, we can modify the query to repeat the pattern until it’s no longer found in the string, as shown above. This will give us all the domains separated by ‘@’.

Step 4: Handling Empty Strings

What if our input data contains empty strings? In this case, we want to exclude those empty strings from our results.

To handle this scenario, we can add a condition to our query that checks for non-empty strings before attempting to split them.

WITH test (email) AS (
    SELECT '<a>[email@localhost]</a>' FROM DUAL UNION ALL
    SELECT NULL FROM DUAL
)
SELECT CASE WHEN email IS NOT NULL THEN LTRIM(REGEXP_SUBSTR(email, '@(\w+\.\w+)', 1, level)) END RES
FROM test,
       TABLE(CAST(MULTISET(SELECT LEVEL FROM DUAL CONNECT BY LEVEL <= REGEXP_COUNT(email, '@' )) AS SYS.ODCINumberList));

In this modified query, we use a CASE statement to check if the email column is not null before attempting to split it. If it’s empty or null, the result will be null.

Conclusion

Regular expressions are a powerful tool for pattern matching and string manipulation in Oracle SQL. By using the REGEXP_SUBSTR function and combining it with other functions like REGEXP_COUNT and MULTISET, we can split strings by specific patterns and extract data from them.

In this article, we explored how to use regular expressions in Oracle SQL to split a string by a pattern. We covered topics such as preparing the data, splitting the string using regular expression, handling multiple domains, and handling empty strings.

By mastering regular expressions and their application in Oracle SQL, you can unlock new possibilities for data manipulation and analysis.

Additional Resources

Last modified on 2023-09-06