CASE\n WHEN condition1 THEN result1\n ELSE default_result\nEND<\/code><\/pre>\n\n\n\nYou add more conditions by additional WHEN\/THEN sections. Snowflake evaluates these sequentially in the order that you write them.<\/p>\n\n\n\n
CASE \n WHEN condition1 THEN result1\n WHEN condition2 THEN result2\n ...\n ELSE default_result\nEND<\/code><\/pre>\n\n\n\n<\/span>Practical Example<\/span><\/h2>\n\n\n\nLet\u2019s say you have a product table where each product has a price and a category.<\/p>\n\n\n\n
You want conditions that group the products along these lines:<\/p>\n\n\n\n
\nBudget Groceries<\/li>\n\n\n\n Budget Electronics<\/li>\n\n\n\n Premium Groceries<\/li>\n\n\n\n Premium Electronics<\/li>\n<\/ul>\n\n\n\nHere’s how you can use a CASE statement with multiple conditions:<\/p>\n\n\n\n
SELECT name, price, category,\nCASE \n WHEN price < 10 AND category = \u201cGroceries\u201d THEN 'Budget Groceries '\n WHEN price >= 10 AND category = \u201cGroceries\u201d THEN 'Premium Groceries '\n WHEN price < 10 AND category = \u201cElectronics\u201d THEN 'Budget Electronics '\n WHEN price >= 10 AND category = \u201cElectronics\u201d THEN 'Premium Electronics '\n ELSE 'Uncategorized'\nEND AS price_category\nFROM product;<\/code><\/pre>\n\n\n\nAlways remember that the conditions are evaluated in order, and the CASE statement will return the result from the first condition that is true.<\/p>\n\n\n\n
So, the order of conditions in your CASE statement can significantly impact your results.<\/p>\n\n\n\n
<\/span>5 Key Factors To Consider With Multiple Conditions<\/span><\/h2>\n\n\n\n
You need to keep some key factors in mind when writing CASE statements with multiple conditions. Here are our top five to be aware of:<\/p>\n\n\n\n
\nOrder of Evaluation<\/li>\n\n\n\n Coverage<\/li>\n\n\n\n Complexity<\/li>\n\n\n\n Performance<\/li>\n\n\n\n Handling Nulls<\/li>\n<\/ol>\n\n\n\nOrder of Evaluation Of Conditions<\/h3>\n\n\n\n The conditions in a CASE statement are evaluated in the order they appear, from top to bottom.<\/p>\n\n\n\n
Once a condition is met, the CASE statement will return the corresponding result and ignore the rest of the conditions. Therefore, you should order your conditions carefully to avoid unintended results.<\/p>\n\n\n\n
For efficiency, you will often want to put the most likely condition first. That means you save processing time and resources on evaluating the next ones.<\/p>\n\n\n\n
Coverage of Conditions<\/h3>\n\n\n\n You should ensure that your conditions collectively cover all possible scenarios you’re interested in.<\/p>\n\n\n\n
Any rows that don’t meet any condition will fall into the ELSE category (as long as you specified one).<\/p>\n\n\n\n
When you\u2019re testing with realistic data, check for ELSE clauses that frequently trigger. This may mean that your conditions are not comprehensive enough.<\/p>\n\n\n\n
Complexity of Conditions<\/h3>\n\n\n\n Overly complicated conditions can make your code harder to read and maintain.<\/p>\n\n\n\n
If you’re dealing with very complex logic, consider breaking it down into multiple steps. You should also use comments to explain your reasoning.<\/p>\n\n\n\n
Performance Impact<\/h3>\n\n\n\n Each condition in a CASE statement adds to the computational work that Snowflake needs to perform.<\/p>\n\n\n\n
While this is not usually a problem for small datasets, it can slow down your queries on larger datasets. Keep an eye on performance and look for optimization opportunities.<\/p>\n\n\n\n
NULL Handling<\/h3>\n\n\n\n NULL represents missing or unknown data. If the field you’re working with contains NULL values, you need to decide how to handle them in your conditions.<\/p>\n\n\n\n
The default behavior is that NULL values in any condition of a CASE statement will yield NULL as the result. If that\u2019s not what you want, be sure to have a condition that handles them explicitly.<\/p>\n\n\n\n
<\/span>4 Common Errors<\/span><\/h2>\n\n\n\n
I\u2019ve experienced my fair (or unfair) share of errors when writing complex CASE statements.<\/p>\n\n\n\n
Here are my most common four types of errors, and my best tips on how to avoid them.<\/p>\n\n\n\n
Incorrect Operators<\/h3>\n\n\n\n In the examples, I used a condition on the monetary value of price. It\u2019s very easy when using greater than\/less than operators to get the boundaries wrong.<\/p>\n\n\n\n
For example, suppose these are your conditions:<\/p>\n\n\n\n
WHEN price > 10 THEN \u2026\nWHEN price < 10 THEN \u2026<\/code><\/pre>\n\n\n\nIf those are the only two conditions, then you haven\u2019t specified what should happen when the price is exactly $10.<\/p>\n\n\n\n
Misordered Conditions<\/h3>\n\n\n\n Because CASE statements evaluate conditions in the order they are listed, it’s possible to end up with inaccurate results if the conditions are not correctly ordered.<\/p>\n\n\n\n
If you put a very broad condition before more specific conditions, it can capture cases intended for the latter. The trick here is to put your specific conditions first.<\/p>\n\n\n\n
Missing ELSE Clause<\/h3>\n\n\n\n While the ELSE clause is technically optional, excluding it can lead to NULL results when none of the conditions in the CASE statement are met.<\/p>\n\n\n\n
If that’s not what you want, always include an ELSE clause to handle any unexpected cases.<\/p>\n\n\n\n
Data Type Mismatches<\/h3>\n\n\n\n The data types of the results in each THEN clause should ideally be the same or compatible.<\/p>\n\n\n\n
Incompatible data types can result in errors or unexpected results.<\/p>\n\n\n\n
<\/span>How To Troubleshoot Errors<\/span><\/h2>\n\n\n\nTroubleshooting errors with these complex statements can be challenging.<\/p>\n\n\n\n
Here are my best tips for dealing with unexpected results.<\/p>\n\n\n\n
Simplify the query<\/h3>\n\n\n\n Try simplifying your query by reducing the number of conditions or dividing the logic into smaller parts.<\/p>\n\n\n\n
Test these smaller statements and gradually add complexity.<\/p>\n\n\n\n
The error may not be with your CASE conditions. The fault may lie within the data itself.<\/p>\n\n\n\n
Check your data for missing values, incorrect data types, or unexpected values that might be causing issues.<\/p>\n\n\n\n
Review the Logical Flow<\/h3>\n\n\n\n Get away from your SQL editor and make a diagram of the steps and logic you are trying to implement.<\/p>\n\n\n\n
Pay particular attention to the order of conditions and watch for ones that are unintentionally overriding others.<\/p>\n\n\n\n