I have recently noticed that SQL Server 2016 appears to be ignoring left joins if any column is not used in the select or where clause. Also not found in Actual execution plan.
This is good for if anyone added extra join but still not affecting performance.
I have query that took 9 sec, if I add column in select clause for Left join tables but without that only 1 sec.
Can anyone please check and suggest, Is that true or not?
Query with Actual execution plan. You can see there is no any table from left join in execution plan.
I'm not 100% sure what the question is asking, but a SQL optimizer can ignore left join. Consider this type of query:
select a.*
from a left join
b
on a.b_id = b.id;
If b.id is declared as unique (or equivalently a primary key) then the above query returns exactly the same result set as:
select a.*
from a;
I am not per se aware that SQL Server started putting this optimization in 2016. But the optimization is perfectly valid and (I believe) other optimizers do implement it.
Remember, SQL is a declarative language, not a procedural language. The SQL query describes the result set, not how it is produced.
If you have a left join and your matching condition don't return any data from the joined table it will return data as inner join return, when select statement does not contains columns from right tables. Not only in ms server 2016 but most of the DB's.
Left join reduces the performance of the query if there are large amount of data available in join tables.
Related
I have 2 equivalent queries in Snowflake - one with left join and the other with inner join:
SELECT *
FROM A
INNER JOIN B ON a.id=b.id;
SELECT *
FROM A
LEFT JOIN B ON a.id=b.id
WHERE b.id IS NOT NULL;
The inner join does not finish after an hour while the left join takes only few seconds. Why would it happen?
EDIT:
There are two possibilities.
One is that there is really a difference in performance between the queries. That would occur because Snowflake chooses very different execution plans for the two queries. Of course the queries are not the same, but I might expect the execution plans to be similar. You can check explain to investigate this.
The second is that the queries actually have quite similar performance, but you start seeing results from the first query quickly. Why? Because every row in the first table is going to be in the result set -- even if there is no match. By contrast, if there is no match at all between the two tables, the second query has to process all the data before it knows there is no match.
I am writing a distributed SQL query planner(Query Engine). Data will be fetched from RDBMS(PostgreSQL) nodes involving network I/O.
I want to optimize JOIN queries.
Logical Order of Execution is:
Do JOIN(make use of ON clause)
Apply WHERE clause on the joined result.
I was thinking about applying Filter(WHERE clause specific to a table) first itself, and then do join.
In what cases would that result in wrong results?
Example:
SELECT *
FROM tableA
LEFT JOIN tableB ON(tableA.col1 = tableB.col1)
LEFT JOIN tableC ON(tableB.col2 = tableC.col1)
WHERE tableA.colY < 100 AND tableB.colX > 50
Logical Execution:
joinResult = (tableA left join tableB ON() ) left join tableC ON()
Filter joinResult using given WHERE clause.
Proposed Execution:
filteredA = tableA WHERE tableA.colY < 100
filteredB = tableB WHERE tableB.colX > 50
Result = (filteredA left join filteredB ON(..))left join tableC ON(..)
Can I optimize any query like this? That is filtering the table first and then applying join above that.
Edit:
Some people are confusing and talking about this specific example. I am not talking about this specific example query, I am writing a query planner and I want to handle all type of queries
Please note that, each of the tables is sharded and stored in different machines, and the current execution model is to fetch each of the tables and then do join locally. So if I apply the WHERE filter before fetching, it would be better.
This is actually a complex topic.
We can filter the table in some cases. We can also reorder outer joins and then push the filter quals inside.
I was going through a research paper regarding this, but I haven't completed it yet(may not complete it also).
So for now, for those who are looking for answers, you could probably go through this research paper particularly section 2.2. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.43.2531&rep=rep1&type=pdf
For now I'm relying on PostgreSQL's planner and taking its output and reconstructing the query for my requirements.
For inner joins, is there any difference in performance to apply a filter in the JOIN ON clause or the WHERE clause? Which is going to be more efficient, or will the optimizer render them equal?
JOIN ON
SELECT u.name
FROM users u
JOIN departments d
ON u.department_id = d.id
AND d.name = 'IT'
VS
WHERE
SELECT u.name
FROM users u
JOIN departments d
ON u.department_id = d.id
WHERE d.name = 'IT'
Oracle 11gR2
There should be no difference. The optimizer should generate the same plan in both cases and should be able to apply the predicate before, after, or during the join in either case based on what is the most efficient approach for that particular query.
Of course, the fact that the optimizer can do something, in general, is no guarantee that the optimizer will actually do something in a particular query. As queries get more complicated, it becomes impossible to exhaustively consider every possible query plan which means that even with perfect information and perfect code, the optimizer may not have time to do everything that you'd like it to do. You'd need to take a look at the actual plans generated for the two queries to see if they are actually identical.
I prefer putting the filter criteria in the where clause.
With data warehouse queries, putting the filter criteria in the join seems to cause the query to last significantly longer.
For example, I have Table1 indexed by field Date, and Table2 partitioned by field Partition. Table2 is the biggest table in the query and is in another database server. I use driving_site hint to tell the optimizer to use Table2 partitions.
select /*+driving_site(b)*/ a.key, sum(b.money) money
from schema.table1 a
join schema2.table2#dblink b
on a.key = b.key
where b.partition = to_number(to_char(:i,'yyyymm'))
and a.date = :i
group by a.key`
If I do the query this way, it takes about 30 - 40 seconds to return the results.
If I don't do the query this way, it takes about 10 minutes until I cancel the execution with no results.
There's a similar question here, but my doubt is slight different:
select *
from process a inner join subprocess b on a.id=b.id and a.field=true
and b.field=true
So, when using inner join, which operation comes first: the join or the a.field=true condition?
As the two tables are very big, my goal is to filter table process first and after that join only the rows filtered with table subprocess.
Which is the best approach?
First things first:
which operation comes first: the join or the a.field=true condition?
Your INNER JOIN includes this (a.field=true) as part of the condition for the join. So it will prevent rows from being added during the JOIN process.
A part of an RDBMS is the "query optimizer" which will typically find the most efficient way to execute the query - there is no guarantee on the order of evaluation for the INNER JOIN conditions.
Lastly, I would recommend rewriting your query this way:
SELECT *
FROM process AS a
INNER JOIN subprocess AS b ON a.id = b.id
WHERE a.field = true AND b.field = true
This will effectively do the same thing as your original query, but it is widely seen as much more readable by SQL programmers. The optimizer can rearrange INNER JOIN and WHERE predicates as it sees fit to do so.
You are thinking about SQL in terms of a procedural language which it is not. SQL is a declarative language, and the engine is free to pick the execution plan that works best for a given situation. So, there is no way to predict if a join or a where will be executed first.
A better way to think about SQL is in terms of optimizing queries. Things like assuring that your joins and wheres are covered by indexes. Also, at least in MS Sql Server, you can preview an estimated or actual execution plan. There is nothing stopping you from doing that and seeing for yourself.
I have a question about JOINS.
Does Sql JOINs reduce performance in a query?
I have query with many JOIN in it . Can I say that the bad performance is come from these JOINS? if yes ,what should I do instead of JOIN in a query?
here is a piece of my query
......
FROM (((((tb_Pinnummern INNER JOIN tb_Fahrzeug ON tb_Pinnummern.SG = tb_Fahrzeug.Motor_SG) INNER JOIN tb_bauteile ON tb_Pinnummern.Bauteil = tb_bauteile.ID) LEFT JOIN Fehlercodes_akt_Liste AS Fehlercodes_akt_Liste_FC_Plus ON Fehlercodes_akt_Liste_FC_Plus.ID=tb_bauteile.[FC_Plus]) LEFT JOIN Fehlercodes_akt_Liste AS Fehlercodes_akt_Liste_FC_Minus ON Fehlercodes_akt_Liste_FC_Minus.ID=tb_bauteile.[FC_Minus]) LEFT JOIN Fehlercodes_akt_Liste AS Fehlercodes_akt_Liste_FC_Unterbrechung ON Fehlercodes_akt_Liste_FC_Unterbrechung.ID=tb_bauteile.[FC_Unterbrechung]) LEFT JOIN Fehlercodes_akt_Liste AS Fehlercodes_akt_Liste_FC_Aderschl ON Fehlercodes_akt_Liste_FC_Aderschl.ID=tb_bauteile.[FC_Aderschl]
WHERE (((tb_Fahrzeug.ID)=[forms]![frm_fahrzeug]![id]));
Yes it does.. increasing Number of records and joins among tables will increase time of execution.. A LEFT/RIGHT JOIN is absolutely not faster than an INNER JOIN. INDEXING on right column of tables will improve query performance.
If you have too much join in your query and its execution frequency is high, take an alternative i.e. create SQL VIEW or Materialized VIEW (Materialized VIEW - if you are using Oracle).
Well joins obviously need to be processed and this processing will consume cpu, memory and IO.
As well as this we have to consider that joins can perform really, really badly if the right indexes etc are not in place.
However, an SQL join with the correct supporting indexes will produce the result you require faster than any other method.
Just consider what you would need to do to calculate the same result as your SQL above. Read the first table, then sort into the correct order, then read the second table and sort it then merge the two result sets before proceeding to the third table ......
Or read all the rows from the first table and for each row issue SQL to retrieve the matching rows.
Joins will definitely degrade the performance the SQL query that you will be executing.
You should generate the SQL plan for the SQL that you have written and look at methods to reduce the cost of the SQL. Any query analyzing tool should help you with that.
From what I understand in the query that you have defined above, you are trying to fetch all rows from the tables that are in the inner joins and get specific columns (if present) from the tables in the left join.
That being the case, a query written in the below given format should help :
select (select Fehlercodes_akt_Liste_FC_Plus.column1 from Fehlercodes_akt_Liste AS Fehlercodes_akt_Liste_FC_Plus where Fehlercodes_akt_Liste_FC_Plus.ID=tb_bauteile.[FC_Plus]),
(select Fehlercodes_akt_Liste_FC_Minus.column2 from Fehlercodes_akt_Liste AS Fehlercodes_akt_Liste_FC_Minus where Fehlercodes_akt_Liste_FC_Minus.ID=tb_bauteile.[FC_Minus]),
(select Fehlercodes_akt_Liste_FC_Unterbrechung.column3 from Fehlercodes_akt_Liste AS Fehlercodes_akt_Liste_FC_Unterbrechung where Fehlercodes_akt_Liste_FC_Unterbrechung.ID=tb_bauteile.[FC_Unterbrechung]),
(select Fehlercodes_akt_Liste_FC_Aderschl.column4 from Fehlercodes_akt_Liste AS Fehlercodes_akt_Liste_FC_Aderschl where Fehlercodes_akt_Liste_FC_Aderschl.ID=tb_bauteile.[FC_Aderschl]),
<other columns>
FROM
(tb_Pinnummern INNER JOIN tb_Fahrzeug ON tb_Pinnummern.SG = tb_Fahrzeug.Motor_SG)
INNER JOIN tb_bauteile ON tb_Pinnummern.Bauteil = tb_bauteile.ID) as <aliastablename>
WHERE <aliastablename>.ID=[forms]![frm_fahrzeug]![id];
Sql Joins do not at all reduce performance : on the contrary : very often they will exponentially speed up a query, assuming offcousre the underlaying database model is well implemented. Indexes are very important in this matter.