When it comes to solving SQL problems, there are often multiple approaches to get the desired result. I recently came across a case study on Danny’s Diner, where the goal was to find the first item from the menu purchased by each customer.
I decided to tackle this problem using ARRAY_AGG instead of the typical window function approach. But which one is better in terms of performance?
## My Approach
I created an array of products ordered by date for each customer, and then extracted the first element from each array. Here’s the SQL solution:
WITH ITEM_LIST as(
SELECT customer_id, array_agg(product_name order by order_date) as items
FROM sales
JOIN menu ON menu.product_id = sales.product_id
GROUP BY customer_id
)
SELECT customer_id, items[1]
FROM item_list
ORDER BY CUSTOMER_ID
## Performance Comparison
So, how does this approach compare to using window functions? In terms of performance, it really depends on the specific use case and the size of the dataset.
Generally, ARRAY_AGG is faster and more efficient when dealing with smaller datasets. However, as the dataset grows, window functions can become more efficient.
## Potential Drawbacks
One potential drawback of using ARRAY_AGG is that it can be less flexible than window functions. For example, if you need to perform more complex aggregations or calculations, window functions might be a better choice.
Additionally, there may be scenarios where ARRAY_AGG gives incorrect results, such as when dealing with duplicate values or nulls. In these cases, window functions can provide more accurate results.
## Conclusion
In conclusion, both ARRAY_AGG and window functions have their advantages and disadvantages. When it comes to performance, it’s essential to test and compare the two approaches based on the specific use case and dataset.
By understanding the strengths and weaknesses of each approach, you can make informed decisions about which one to use in your SQL queries.
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*Further reading: [8weeksqlchallenge](https://8weeksqlchallenge.com/case-study-1/)*