More Efficient Query than the EXISTS Condition
I was reading up on the SQL EXISTS Condition and found this snippet from Techonthenet.com
Note: SQL Statements that use the SQL EXISTS Condition are very inefficient since the sub-query is RE-RUN for EVERY row in the outer query's table. There are more efficient ways to write most queries, that do not use the SQL EXISTS Condition
Unless I skipped over it, the article does not explain a more efficient query that doesn't need this condition. Anyone have an idea of what they could be referring to?
You can usually use some "clever"
inner join or something like that.
However, all in all, the advice is severely outdated. Yes, there used to be a time when subqueries had a huge cost, but that isn't necessarily the case anymore - as always, profile. And examine execution plans. It's very much possible your DB engine can handle subqueries just fine - in fact, it can be much faster than the hacky
inner join (and similar solutions) :)
Always make sure you understand the rationale behind the advice, and to what it actually applies. A simple example on MS SQL:
select * from order where exists (select * from user where order.CreatedBy = user.Id)
What a horrible sub-query, right? Totally going to run the subquery for every row of the
order table, right? Well, the execution planner is smart enough to translate this into a simple left join - involving just two table scans (or, if applicable, index seeks). In other cases, the engine might decide to build hash sets, or temporary tables, or do any other smart thing to make sure the query is fast (within the other trade-offs, like memory usage). Nowadays, you will rarely find that your query tweaks are smarter than what the execution planner does - if your DB engine is up to the task. In fact, this is the whole reason we use SQL - a declarative language - in the first place! Instead of saying how the results should be obtained, you say what relationships lead to the result set you want, giving the DB engine a massive freedom in how to actually get the data - whether it means going through every single row in a table one by one, or seeking through an index.
The default should always be to write the query in a way that makes the most sense. Once you've got a nice, clean and easy to understand query, think about any performance implications, and profile the results (using realistic test data). Look at the execution plan of the query - if you care about SQL performance, you really need to understand execution plans anyway; they tell you all there is to know about the way the query is actually executed, and how to improve various parts of the query (or, more often, the indices and statistics involved).
What is the difference between 'EXISTS' and 'IN' operators in SQL , keyword evaluates true or false, but IN keyword compare all value in the corresponding sub query column. There are more efficient ways to write most queries, that do not use the EXISTS condition. DDL/DML for Examples If you want to follow along with this tutorial, get the DDL to create the tables and the DML to populate the data.
First of all, don't trust general statements like
Note: SQL Statements that use the SQL EXISTS Condition are very inefficient since the sub-query is RE-RUN for EVERY row in the outer query's table.
This can be true for some database systems, but other database systems might be able to find a more efficient execution plan for such statements. For example, I tried such a statement on my Oracle database and it uses a hash join to execute the statement efficiently.
Now for the alternatives:
In many cases, you can use an
IN subquery. This might work out well even on database systems that would execute
So, instead of
select * from foo where exists (select 1 from bar where foo.x = bar.y)
select * from foo where x in (select y from bar)
The same can be written with
select * from foo where x = any (select y from bar)
In many cases, it's most desirable to use a join, e.g.
select foo.* from foo inner join bar on foo.x = bar.y
You might have to use
DISTINCT to make sure you don't get duplicate results when a row in
foo matches more than one row in
select distinct foo.* from foo inner join bar on foo.x = bar.y
23 rules for faster SQL queries, performance, save time for both database administrators and SQL developers. If the tables are located at more than one site, then the optimizer decomposes the query into separate SQL statements to access each of the remote tables. This is called a distributed SQL statement. The site where the query is executed, called the driving site , is usually the local site.
When you have main query result set small and result set of sub-query is Large and sub-query uses appropriate indexes - EXISTS / NOT EXISTS is better option in place of IN / NOT IN Clause.
When you have index on larger result set of main query and smaller result set in the sub-query - IN / NOT IN is better option in place of EXISTS / NOT EXISTS Clause.
SQL Exists vs. IN clause, This SQL tutorial explains how to use the SQL EXISTS condition with syntax and examples. The SQL There are more efficient ways to write most queries, that do not use the EXISTS condition. Then try the examples in your own database! SQL statements that use the EXISTS condition are very inefficient since the sub-query is RE-RUN for EVERY row in the outer query's table. There are more efficient ways to write most queries, that do not use the EXISTS condition. Example - With SELECT Statement Let's look at a simple example.
SQL: EXISTS Condition, it is your responsibility to write code which is efficient and optimal. SELECT * with WHERE conditions will use clustered index by default so it may Most of the time, IN and EXISTS give you the same results with the WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino'. Oracle SQL statements that use the Oracle EXISTS condition are very inefficient since the sub-query is RE-RUN for EVERY row in the outer query's table. There are more efficient ways to write most queries, that do not use the EXISTS condition. Example - With SELECT Statement Let's look at a simple example.
How to design SQL queries with better performance: SELECT * and , Should you always use EXISTS rather than COUNT when checking for Another option is just to use JOIN conditions, instead of a subquery, to get the Sales. Although logically the former is more efficient, in fact the query Chances Are, You’re Doing it Wrong Posted on March 9, 2016 March 6, 2016 by lukaseder I’ve noticed this very consistently with a lot of customers, and also with participants of our Data Geekery SQL Workshop (which I highly recommend to everyone, if you excuse the advertising) : A lot of developers get the distinction between JOIN and SEMI
Finding Correlated Rows Using EXISTS or COUNT, It used to be that the EXISTS logical operator was faster than IN, when For example, in cases where the query had to perform a certain task, but only to include a WHERE clause in the IN condition to eliminate the NULL s. Thus, I'll try refactoring a query or creating necessary covering indexes to get ahead of the MySQL Query Optimizer's hidden bad habits. @gbn's answer seems more complete in that SQL Server may have more "soundness of mind" evaluating queries.
Consider using [NOT] EXISTS instead of [NOT] IN with a subquery , Answer: Most Oracle IN clause queries involve a series of literal values, and Conversely, the IN clause is faster than EXISTS when the subquery results is very I found that the PART 2's (FIRST EXISTS) WHERE conditions is repeatation of PART1's condtions. Hence I want to eliminate it, which I've done in QUERY 2. The PART1 of Query1 without EXISTS fetch me reults in 5 minutes but with SINGLE EXISTS (QUERY 2) it runs for 4 hours . So I wrote another yet query by creating a new table, NEWTAB