This time we’re going bigger than ever. Fabric, Power BI, SQL, AI and more. We're covering it all. You won't want to miss it.
Learn moreDid you hear? There's a new SQL AI Developer certification (DP-800). Start preparing now and be one of the first to get certified. Register now
Why is inner join more efficient that left outer, and doesn't this mean we will skip the products with ProductSubCategory with no parent ProductCategory?
Solved! Go to Solution.
Yes, Left outer join produce the same result
and for the second part i give the answer based on the question was you posted according to that left outer join is answer in the second blank for the second question that assumtion take by us and me and other so only we need inner join or left outer in such cases.
Yes, Left outer join produce the same result
and for the second part i give the answer based on the question was you posted according to that left outer join is answer in the second blank for the second question that assumtion take by us and me and other so only we need inner join or left outer in such cases.
There would be two answers the join kind first question is asked every productcate. has productsubcate. use inner join and in second question Not every productsubcate have productcate so in suct case use left outer join if Productsubcate table on the left hand side and product category table on the right hand side as mentioned in the questions.
According to the your question there different working of the inner join and left outer join but it's obvious inner join is very effecient and you are right left outer join is used for the second question that mentioned in the above question.
Just Click ✅Accept the solution if you got the answer.
First part: If every product has a subcategory and vice versa, wouldn't outer left and inner produce the same results?
Second part: If the objective is to maximise performance, then why should I need to include the subcategories which has no corresponding parent category? There are too many assumptions here.
Check out the April 2026 Power BI update to learn about new features.
Sign up to receive a private message when registration opens and key events begin.
If you have recently started exploring Fabric, we'd love to hear how it's going. Your feedback can help with product improvements.
| User | Count |
|---|---|
| 34 | |
| 31 | |
| 25 | |
| 20 | |
| 16 |
| User | Count |
|---|---|
| 61 | |
| 49 | |
| 28 | |
| 23 | |
| 23 |