How to optimize slow query with many joins?

How to optimize slow query with many joins?

If, by chance, it doesn’t, you should hint or force the multi-column index. It doesn’t appear that you are using any fields in any of the joined tables, so remove the joins. This will remove all of the additional work of the query, and get you down to one, simple execution plan (one line in the EXPLAIN result).

What to do when SQL query joins multiple tables?

Create an index on these tables or define the joined field as a PRIMARY KEY. As i can see, t1 table is the one which is being joined with all the tables, instead of putting them in a single query with so many joins, you can possibly try a Union of different queries something like this.

How long does it take to join a table in SQL?

After joining 12 tables, there was no significant change in query execution time. By the time I had joined the 13th table the execution time jumped to a 1 second; 14th table 4 seconds, 15th table 20 s, 16th 90 seconds. Keijro’s suggestion to use a correlated subqueries instead of joins e.g.

Which is worse correlated subqueries or joins in SQL?

I am a little suprised as I thought correlated subqueries perform worse than joins. Depending on how much data is in the tables, you may need to place indexes on the columns that are being joined against. Often slow querying speed comes down to lack of an index in the right place.

Why is MY SQL Server query so slow?

If you execute this query: It will be very very very slow. If you change that query to use two inner joins instead of a left join, it will be very fast. If you change it to use two left joins instead of an inner join, it will be very fast.

Is it slow to use two inner joins in SQL?

It will be very very very slow. If you change that query to use two inner joins instead of a left join, it will be very fast. If you change it to use two left joins instead of an inner join, it will be very fast. You can observe this same behavior if you use a sql table variable instead of the freetexttable as well.