What to do with slow query with where clause?

If it comes down to it, one solution would be to store an intermediate result set and filter it in a separate statement. I suggest this with the understanding that you can’t make changes to your vendor’s database and that you are basically stuck.

Is it a good idea to use cast ( )?

Using cast () is not a good suggestion. It uses the index but extra time is spent on converting each index value during the comparison. Note to self, make sure I explain in detail what I mean. Here are some good reads on the topic!

How to avoid casting to different date types?

Avoid casting to different date types if there’s a faster way (like the trick above), and definitely try to avoid using string literals for dates without wrapping them in a CONVERT () to ensure your string format will get interpreted correctly.

What does the subquery in the in clause depend on?

The subquery in the IN clause does not depend on anything in the outer query. You can safely move it into FROM clause; a sane query plan builder would do it automatically. Also, calling EXPLAIN PLAN on any query you’re going to use in production is a must.

When to use having and where clauses in the same query?

Use HAVING and WHERE Clauses in the Same Query (Visual Database Tools) In some instances, you might want to exclude individual rows from groups (using a WHERE clause) before applying a condition to groups as a whole (using a HAVING clause).

How to add a condition to A HAVING clause in SQL?

The Query and View Designer adds the condition to the HAVING clause of the SQL statement. The query shown in the example for this procedure joins two tables, titles and publishers. At this point in the query, the SQL statement contains a HAVING clause:

When to use the where clause in SQL Server?

If you invoke a function call on a value from a row in the query it will need to call the function for each row in the query. So for this example it has to evaluate each StartTime value to see if this is true. Buf it you use a function that returns only one value it will get run once.

How does the substring function work in SQL Server?

Therefore, SQL Server must perform the function individually for each row to find qualified data on the execution time. So, the data engine will read the entire index pages or the entire table rows so it causes more I/O activity.

How to turn on function in where clause?

Here are some simple statements that show you the affect of using a function in the WHERE clause. To get a better understanding of how these queries are working we are also getting the query plan. This can be done by hitting Ctrl-M in a query window to turn this function on before running the query.

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.

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.

Why is there a slow execution plan in SQL?

My guess is that the slow execution plan is doing the rate>0 filter in an unfortunate way, like as part of a scan on the inside of a loop join or something. If it comes down to it, one solution would be to store an intermediate result set and filter it in a separate statement.

When does a previously-fast SQL query starts running slow?

Fortunately, it doesn’t happen that often. Look at the query plan for the query (when it is running slow). I am guessing you will find a nested loop join occurring one or more times on tables with no indexes for the join. This really slows things down.

Why is query running slow on nested loops?

Also note that in production, the temp table #Ids doesn’t exist, it’s a Table Valued Parameter of the same 10’000 Ids passed on to the Stored Procedure. As pointed out by the accepted answer, the problem was the OR clause in the category_link JOIN. However, the code suggested in the accepted answer is very slow, slower even than the original code.

Which is the best way to run a SQL query?

Here’s when this works best: Running a query overnight is best when queries have: looping statements, cartesian JOINs, more than one schema query, complicated wildcard searches, SELECT DISTINCT statements, CROSS JOINs, and anything else that will burden the system. SQL Status Update #2: YaaaaaaH! You’re doing great.

Why does SQL query take too long to execute?

But when I add a WHERE clause to the query it takes too long time to execute the query. It takes more than 5 minutes for 13450 records. What could be the reason?

Why is b > 0 a range query in SQL?

The portion b>0 drastically changes it because the server can no longer optimize the query using a clustered index and other methods. When you add b>0 that turns this query into a range query which will require a lot more time because it does indeed have to check more values.

Why is select all so slow in SQL?

SQL newbies love using an asterisk to define their SELECT fields as “select all” like this: But this will query all the data from the table. If the data has tons of fields and rows, “select all” will tax the database resources and slow the entire system down.

Is there such thing as super slow query syndrome?

Your boss calls it “sequel,” but you’ve been calling it S-Q-L for months. And that’s not the worst. You’re suffering from “Super Slow Query Syndrome,” and sometimes, your queries bomb without a result. Don’t worry.

How to speed up a SELECT DISTINCT query?

A lot will depend on the details of the query and the tables involved– your saying you “know the problem is with the DISTINCT” really limits the scope of available answers. Oftentimes, you can make such queries run faster by working around the distinct by using a group by instead:

What to do with slow query with where clause?