Joins are useful for bringing data together from different tables based
on their database relations. First we will see how the join operates between
tables. Then we will explore the Order of Execution when Join and where
condition both exists. Finally we will move our exploration to the Importance
of the Join order.
2. Run the attached script
The downloaded script has the three
table and table data for this article. You should also run the Northwnd script
as some example here uses the NorthWnd DB. Once you downloaded the script CreateObject.zip
run the script in the NorthWnd Db. <o:p />
Below is the three
tables created by the Script:
We are going to use these tables to perform the joins. These tables are
just for demo purpose and So I do not have proper table relationship in terms
of Primary and Foreign keys. OK, Let us move on.
3. Cartesian Product of Table
Usually join will be performed between
two tables based on the key columns between two tables those together constitutes
the database table relationship. For Example DeptId in the employee
table and DeptId in the Department table make the
relationship between these two tables.
The below one is the
example Joining the tables without using the key columns. Here, TableA
and TableB are clubbed together to form the whole result set
based on Cartesian Product. The Cartesian product will take a
single record in the first table and attaches with all the records in the
second table. Then takes the Second records in the first table and attaches
with all the records the second table and this continue till the end of the
records on the first table.
4. Joining Two tables
When joining the
two tables to avoid the bulk number of records that results as shown in the
previous example, we should chose a join column from both the tables. The
example given below joins Table_A and Table_B based
on the Column called ID. Since the column in both the tables mapped based on the
ID column, we will reduce huge records that are logically not useful and not
related the ID map.
Below is the Result
of the Join:
Note that the Row Number 1 and Row number 5 are returned as the join
result as they satisfies the mapping condition A.Id = B.Id. In
the query it is shown in the Red Box.
5. Joining multiple tables
The above example
joint two tables. To join multiple tables, we should use the result of the
previous join and pick a column from it, then pick a column in the new table
then specify the join condition as the previous example. This way we can join
multiple numbers of tables. Consider whatever joint so far as the single table
and join it with the new one.
First Table_A is joins with Table_B, which
is nothing but the previous example. Then the joint result of A and B is
considered as single table say AB. Then the AB is joint with the Table_C.
This is shown in the below picture:
6. Join Types
There are three type of join available
based the way we join columns on two different tables.
1) Full outer Join
2) Inner Join
3) Left outer
4) Right outer
What we saw in
the previous two examples are the inner joins. If we join the same table we
called it as Self join and it is special category do not get
confuse it with the join types. Let us see an example for the join types in
next coming examples.
Before we go into
those examples, remember that the result computed so for is considered as LEFT
and the new table coming to join the existing result is RIGHT. This
is useful when we are joining multiple tables with different type of joins.
7. Full Outer Join
A full outer join is
somewhat different from the Cartesian product. Cartesian product will get all
the possible row combination between the two joining tables. But, Full outer join takes all the matching columns by join condition, all table rows from the left table that does not match the right side table, and, all tables rows in the right that does not match the left. It
applies null for unmatched row on the other end (Left side Table column or Right side table column) when doing so. The below
example shows the full outer join between Table_A and Table_C
1. In the above
picture the Blue Row the matching row on both the table.
2. Second row
(Green First, red next) is the unmatched one. Row exists on the Left table and
null substituted for all the columns in the Right.
3. Third row (Red
First, Green next) is also the unmatched one. Row exists on the Right side
table, null returned for the left one
Look at the from
The Table_A is taken
first and joint with Table_C. Here, The result set computed so for always
treated as Left side of join and the new table going to be joint
is treated as Right side of join.
8. Left Join
Left join makes
sure to take all the rows on the left side of the table by placing the null
entries for the table joining on the right side when there is unmatched row on
the right side.
In the above
example, Id value of 2 in the Left table does not exist on the right side table
Table_C.Id. But, we still got the 2,BBB row from the Table_A by
placing the null entries for the right side table. This is shown in Green and
red boxes above.
Also note that when
SQL is processing, it takes the rows for the Table_A first (So Left) then joins
it with the Table_C (Right side). It
does not matter whether we provide A.Id = C.Id or C.Id = A.Id
9. Right Join
It is the
reverse of the left join. It implies take all the rows on the right side of
table by placing the null on the left table for unmatched rows. Below is the
example for it:
Blue Box :
Green : Row
exits on the right side table Table_B and match (Based on Id column) not
available on the left
Red : Null placement
for the columns
10. Inner Join
In inner join only
the matched rows are retrieved. Please refer the section four. Inner join
returns same result and hence one no need to worry about the placing a table on
left or right.
11. Self Join
Joining the table
with the same table is called the Self Join. To explain this let us go
the table on the Northwnd database (Attached with this article).
Have a look at the columns in the employee table. The EmployeeId
column is the Primary key column and each row belongs to a single employee. The
reports to column refer some other row in the same table stating
that referred row is the manager for the referring row. But the referred row
(manager) is also an employee possible having a valid entry on its ReportsTo
column. So in the NorthWnd database this relationship achieves a hierarchical
Now have look at the below example:
Here, the row pointed by ReportTo column is Manager. So the table on the
left hand side is employee and table on the Right hand side is Manager. When
the FirstName is referred on the left table of the joint result,
it is Employee name and the same FirstName on the right table of
the join result is Manager name.
When the query
involves the combination of the outer and inner join the
execution sequence is important. If you have only inner join the execution
sequence is not much important as they are going to provide the same result.
Well, What I am taking about?
Let is Say you
have a query, which has both inner join and outer join (Left or Right). Also
let us assume you have where clause that filters the records based on column
that is not a joining id column. The question comes which operation is
performed first. We have two options:
1) Apply the
where clause first because joining later will improve the performance then
perform the join
2) Apply the
Join then perform the where clause
The above two option
returns same result when all the joins involved are inner joins. But
the result may differ when we have at least one outer join. OK. SQL chose the
second option because as per its operation Sequence From clause is completed
first, then applies the where clause
Given below is an Example and the result:
How the Sequence differs is shown below:
So keep in mind the operation sequence as SQL first completes the join
first then applies the where clause when the query has one or more outer joins.
13. Order of the
Operation sequence the Order of the join also important when you want mix the
inner joins with outer (Left or Right) joins. Again, if the entire join
involved between the tables are inner joins the order of the join
does not matter. But it matters when we mix the inner and outer joins.
What is Order of the Join? If my query joins three tables like [X inner
Y] Left Z, the order here is inner join performed first, and then the left join.
OK. Let us go
back to the NorthWnd Database again. The result you want to
achieve is Get all the customers names whether they have order or not. Also
list the Qty of order placed by the customer if they actually has some order.
Look at the Query and
result below: [Outer Join then Inner Join]
From the above
query, you can see the order of join as mentioned below:
1) A right join
between Orders and Customers. SQL first queries the
Orders table (As it appears first) and treats the result as Left.
Then it queries the Customers table next and treats the result
set as Right. Finally from both the result set Right
join is performed that means SQL ensures you that it will not lose any rows on
the Right side result set that is it will not lose any rows from the Customers
table. So you will get all customers including the two who don’t placed any
orders and since a matching records for those two rows are not available you
will get null columns for the Orders. Now the resulting join result is
available for the next join and this join result is now treated as Left.
2) Now the above
returned result (Left side) is joint with the Order Details table. SQL knows it
already has the Left result set so it query the table Order Details
to have the Right. Finally an Inner join is performed between Left
and Right based on the Order Id. But note that we
have two null entries for the ordered column for which there are
no corresponding customers in the Left side result. So the Inner
join just skips those records. So we got a total of 2155 missing the two
customers who does not place any orders, which is not the result we need. Read
the Underlines text at the top of this section.
Now look at the Query and Result below: [Inner Join then Outer Join]
Here, Inner join
based on the OrderId between Orders and Order
Details is performed first. This result (Left side) is then Right joint
against the Cutomers table [Right].
Now let us
analyze how this is giving the result we want.
The inner join
between Order and Order Details brings all the
matching records based on the order id. Note that we are not losing any order
id here by null values. Then by keeping this already brought result on the left,
Customers table is queried and kept in the Right. Then
the right join is performed between Customers and Left side
result based on the Customer Id. Now we get all the customers
including the two for which we don’t have any matching records on the Left side
Keep in mind that
join order is important when you mix the inner join with outer join.
14. Other way of
achieving the same result
When I had a talk
with one of my office friend (VaraPrasad), he told that the result you are
expecting could be achieved without using the Right Join. How? That is the
question I asked him. He told that Crystal reports does it, I will show you.
Good, now this section is added to this article based on what I got from him.
OK. Now let us
see how this works and gives the expected result of not losing any customers.
Note that the Rule remains same, whatever computed so for is Left
and the Joining table is on the Right.
1) SQL first
queries the table Customers and keeps it as the result on the Left.
2) It reads the
Open parenthesis, and queries the table Orders and keeps it Left
again. Why? SQL Says “Boss, I know that I am not going to join this table and
Table I am going join is not ready yet. So I kept is Left side result.
3) Now the Order
Details table is queried and kept as Right side of join
as Left side is already available.
4) A join between Order
and Order Details is performed based on the Order Id. The
resultant records are treated as right because the Customer table is already
queried and kept in the Left. Now thee left join between the Left
and Right side of result set brings all customers as the join type left outer
Note: The scripts for creating the Demo tables and
NorthWnd database is available as download.