SQL Query Optimization and performance tuning | How to optimize SQL Queries | SQL Query tune
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- เผยแพร่เมื่อ 5 ก.ย. 2024
- In this video you will know how to speed up sql queries to improve database performance and also known how to write efficient sql queries to improve sql database.
@DatabaseAcademyRT @Oracle #sql #oracledatabase #sqlqueries #performance #plsql
In this tutorial, you will learn how to optimize the SQL query with example.
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Great.
great
Thank you so much,
You are welcome!
Expecting more plsql video’s
th-cam.com/video/xDWE6n2yDFo/w-d-xo.htmlsi=DL3WmFzTDNcu8Dsc
Nicely explain Great 👍
Thank you
Very nice and great
Thanks a lot
Sir Could you explain more videos on performance tuning
Sure I'll create a new video on performance tuning.
Nice video and topic 👍 what books would you recommend to learn more about writing styles in sql ?
I learned these things with my experience and referring to oracle books.
So the union all is basically for large data sir and for columns which index is not created
If we use OR in where condition then index will not be used if we have index on filter column. To use index we can use union so that index will be used and query performance will be improved.
Thank you so much for this excellent video. I have one doubt. Yoi have explained for select statement same like what are all the possible things we will perform for an update statement for performance tuning. Plz reply
Thanks for your comment.
1. While updating records you should take care about where conditions the same way as mentioned in the video.
2.You can use Bulk collect and FORALL to update records in bulk.
thanks for great video.
I have question:
at 2:03 if I set index on n2 column too, then will it be used in OR query?
An "OR" condition typically involves evaluating multiple expressions, and it may result in a full table scan rather than using an index.
Have you created an index on n1 or n2 columns already?
If there is large amount of data then it’s mandatory to create indexes on joining columns
We should create an index only when we have performance issues and have a large amount of data. Index will slow down your DML operation.