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  1. 31 maj 2023 · Rather slow, but working method to include any of words: SELECT * FROM mytable WHERE column1 LIKE '%word1%' OR column1 LIKE '%word2%' OR column1 LIKE '%word3%'. If you need all words to be present, use this: SELECT * FROM mytable WHERE column1 LIKE '%word1%' AND column1 LIKE '%word2%' AND column1 LIKE '%word3%'.

  2. 28 maj 2024 · In this article, we explored different options for executing IF-THEN logic in a SQL SELECT statement. These options include using CASE , IIF() , and CHOOSE() . Furthermore, if we want a query that’s used in almost every dialect, we must choose the CASE statement.

  3. 2 mar 2017 · Suppose STUDENTID contains some characters or numbers that you already know i.e. 'searchstring' then below query will work for you. You could try this: select * from STUDENTS where CHARINDEX('searchstring',STUDENTID)>0

  4. 12 maj 2024 · In this tutorial, we explored different options to filter rows that contain specific words or phrases. Combined with wildcards, the LIKE operator offers a powerful and flexible approach to pattern matching and is available in all SQL implementations. Pattern-matching operators available in each database enable advanced search operations.

  5. 23 sie 2021 · You can match whitespace with the POSIX class "[[:blank:]]" or "[[:space:]]". The difference between these two classes is that the class blank matches only spaces and tabs, while space matches all blank characters, including carriage returns, new lines, form feeds, and vertical tabs. Match Non-Whitespace Characters

  6. 6 mar 2024 · This article covers practical examples using Full-Text Search in SQL Server. In our practice, we mostly use string functions (substring, left, right, etc) and LIKE predicate for searching any...

  7. 12 lut 2024 · Example of SQL SELECT WHERE Field Contains Words. To search for a record that contains a specific word in a specific field, we will use SELECT statement in SQL with WHERE clause to filter the results based on a specific word. Consider a table named products with columns product_id and product_name.

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