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Difference between left join and right join in SQL Server [duplicate]

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Will left join causes duplicates?

Again, if we perform a left outer join where date = date, each row from Table 5 will join on to every matching row from Table 4. However, in this case, the join will result in 4 rows of duplicate dates in the joined DataSet (see Table 6).

What is the difference between left join and right join in SQL?

Different Types of SQL JOINs (INNER) JOIN : Returns records that have matching values in both tables. LEFT (OUTER) JOIN : Returns all records from the left table, and the matched records from the right table. RIGHT (OUTER) JOIN : Returns all records from the right table, and the matched records from the left table.

Is left join and right join same?

The main difference between these joins is the inclusion of non-matched rows. The LEFT JOIN includes all records from the left side and matched rows from the right table, whereas RIGHT JOIN returns all rows from the right side and unmatched rows from the left table.

IS LEFT join better than right join?

The most substantial difference between the left and right outer join lies in the unmatched records that are obtained besides matched records. The left join takes all matching records and unmatched records of the left table while the right join takes all matching records and unmatched records of the right table.


Select * from Table1 left join Table2 ...

and

Select * from Table2 right join Table1 ...

are indeed completely interchangeable. Try however Table2 left join Table1 (or its identical pair, Table1 right join Table2) to see a difference. This query should give you more rows, since Table2 contains a row with an id which is not present in Table1.


Table from which you are taking data is 'LEFT'.
Table you are joining is 'RIGHT'.
LEFT JOIN: Take all items from left table AND (only) matching items from right table.
RIGHT JOIN: Take all items from right table AND (only) matching items from left table.
So:

Select * from Table1 left join Table2 on Table1.id = Table2.id  

gives:

Id     Name       
-------------  
1      A          
2      B      

but:

Select * from Table1 right join Table2 on Table1.id = Table2.id

gives:

Id     Name       
-------------  
1      A          
2      B   
3      C  

you were right joining table with less rows on table with more rows
AND
again, left joining table with less rows on table with more rows
Try:

 If Table1.Rows.Count > Table2.Rows.Count Then  
    ' Left Join  
 Else  
    ' Right Join  
 End If  

(INNER) JOIN: Returns records that have matching values in both tables.

LEFT (OUTER) JOIN: Return all records from the left table, and the matched records from the right table.

RIGHT (OUTER) JOIN: Return all records from the right table, and the matched records from the left table.

FULL (OUTER) JOIN: Return all records when there is a match in either left or right table

For example, lets suppose we have two table with following records:

Table A

id   firstname   lastname
___________________________
1     Ram         Thapa
2     sam         Koirala
3     abc         xyz
6    sruthy       abc

Table B

id2   place
_____________
1      Nepal
2      USA
3      Lumbini
5      Kathmandu

Inner Join

Note: It give the intersection of two table.

Inner Join

Syntax

SELECT column_name FROM table1 INNER JOIN table2 ON table1.column_name = table2.column_name;

Apply it in your sample table:

SELECT TableA.firstName,TableA.lastName,TableB.Place FROM TableA INNER JOIN TableB ON TableA.id = TableB.id2;

Result will be:

firstName       lastName       Place
_____________________________________
  Ram         Thapa             Nepal
  sam         Koirala            USA
  abc         xyz              Lumbini

Left Join

Note : will give all selected rows in TableA, plus any common selected rows in TableB.

Left join

SELECT column_name(s) FROM table1 LEFT JOIN table2 ON table1.column_name = table2.column_name;

Apply it in your sample table

SELECT TableA.firstName,TableA.lastName,TableB.Place FROM TableA LEFT JOIN TableB ON TableA.id = TableB.id2;

Result will be:

firstName   lastName    Place
______________________________
 Ram         Thapa      Nepal
 sam         Koirala    USA
 abc         xyz        Lumbini
sruthy       abc        Null

Right Join

Note:will give all selected rows in TableB, plus any common selected rows in TableA.

Right Join

Syntax:

SELECT column_name(s) FROM table1 RIGHT JOIN table2 ON table1.column_name = table2.column_name;

Apply it in your samole table:

SELECT TableA.firstName,TableA.lastName,TableB.Place FROM TableA RIGHT JOIN TableB ON TableA.id = TableB.id2;

Result will bw:

firstName   lastName     Place
______________________________
Ram         Thapa         Nepal
sam         Koirala       USA
abc         xyz           Lumbini
Null        Null          Kathmandu

Full Join

Note : It is same as union operation, it will return all selected values from both tables.

Full join

Syntax:

SELECT column_name(s) FROM table1 FULL OUTER JOIN table2 ON table1.column_name = table2.column_name;

Apply it in your samp[le table:

SELECT TableA.firstName,TableA.lastName,TableB.Place FROM TableA FULL JOIN TableB ON TableA.id = TableB.id2;

Result will be:

firstName   lastName    Place
______________________________
 Ram         Thapa      Nepal
 sam         Koirala    USA
 abc         xyz        Lumbini
sruthy       abc        Null
 Null         Null      Kathmandu

Some facts

For INNER joins the order doesn't matter

For (LEFT, RIGHT or FULL) OUTER joins,the order matter

Find More at w3schools


select fields 
from tableA --left
left join tableB --right
on tableA.key = tableB.key

The table in the from in this example tableA, is on the left side of relation.

tableA <- tableB
[left]------[right]

So if you want to take all rows from the left table (tableA), even if there are no matches in the right table (tableB), you'll use the "left join".

And if you want to take all rows from the right table (tableB), even if there are no matches in the left table (tableA), you will use the right join.

Thus, the following query is equivalent to that used above.

select fields
from tableB 
right join tableA on tableB.key = tableA.key