Sql how does join work
All this data is hypothetical and you can create in any of your existing databases. CompanyID in this table is the foreign key that is referencing to the Primary key of the PizzaCompany table created above. The following table shows data in the Foods table. This table stores information like units sold per food item and also the pizza outlet CompanyId that delivers it.
Now, if we would like to see the items and also the units sold by each pizza company, we can combine these two tables with the help of an inner join clause being used on the field CompanyId in our case this shares a foreign key relationship. For each row in the table PizzaCompany, Inner Join compares and finds the matching rows in the table Foods and returns all the matching rows as shown below.
With the help of the above result set, we can make out the items and also the count of items delivered by pizza outlets in various cities. I am going to quickly create a table WaterPark and load some arbitrary data into it as shown below.
As the saying goes, the picture is worth a thousand words. Now we are going to include this third table in the SQL Inner Join clause to see how it is going to impact the result set. Execute the code below to see all the food distribution across the waterparks by the Pizza outlets. As shown below, with the addition of inner join on WaterPark, CompanyId 6,7 apart from 5 are also excluded from the final result set as the condition w.
CompanyId is not satisfied for Ids 6,7. This is how SQL Inner join helps to return specific rows of data from multiple tables. Assume that we would like to get the rows where units sold were more than 6.
In the following query, the WHERE clause is added to extract results with value more than 6 for units sold. Execute above code in SSMS to see the below result. Four such records are returned by this query. SQL Inner Join permits us to use Group by clause along with aggregate functions to group the result set by one or more columns. Group by works conventionally with Inner Join on the final result returned after joining two or more tables.
To understand what's happening here, we have to dive a little deeper into how joins work. We won't go into too much depth, though - just enough to clarify how the above command works. It's convenient to think of this virtual table as containing all columns from the records in the FROM table as well as all columns from the JOIN table.
If you add a second JOIN , like we did above, PostgreSQL creates yet another virtual table that contains all of the columns from the previous virtual table as well as all of the columns from the matching rows in the second JOIN table. In the command shown above, the first JOIN combines data from users and checkouts into a virtual table that contains users. The second JOIN combines the data from this virtual table with the title column from the books table.
Together, the command creates a virtual table that contains the 3 columns we're displaying. You may have noticed that some of the queries we list above can get a bit long. We can cut back on the length of these queries by using aliasing.
Aliasing allows us to specify another name for a column or table and then use that name in later parts of a query to allow for more concise syntax. Let's use our three table join from above as an example. Using aliasing, the query would look like this:. Here we specify single letter aliases for our tables, and use those aliases instead of our table names in order to prepend the columns from those tables in the column list and in the join conditions.
This is commonly referred to as 'table aliasing'. We can even use a shorthand for aliasing by leaving out the AS keyword entirely. Aliasing isn't just useful for shortening SQL queries. We can also use it to display more meaningful information in our result table. For instance, if we want to display the number of checkouts from the library we could write something like:.
If you're a user just trying to access information, then most likely you wouldn't know about the exact tables being queried; being explicit about what information we're displaying can be important in a case like that.
Thus far in this chapter, we've looked at using JOIN s to work with more than one table. Although joining tables together is probably the most common way of working with multiple tables, you can often achieve the same results through use of a subquery. Before we compare subqueries and joins, let's examine what a subquery is. This is called nesting, and the query that is nested is referred to as a subquery.
For example, suppose we need to select users that have no books checked out. If no relation is found, that would mean that the user has not checked out any books. This might seem a bit confusing, so let's break it down. Our initial checkouts table looks like this:. This virtual table can then effectively be used by our NOT IN clause as a list of values against which to check the values in the id column of our users table.
The only value in that column that is not in the results of the nested query is the id for 'Harry Potter': 3. These all work slightly differently, but essentially they all compare values to the results of a subquery. We won't go into too much detail about subqueries here as you'll get to work with them some more later in course LS One thing it is useful to know though is that in some situations a subquery can be used as an alternative to a join.
As you write more queries, you may find that there is more than one way to write a query and achieve the same results. The most common choices are between subqueries and JOINs. For instance, we can get the same result table as in our previous example by using a JOIN clause instead of a subquery.
When creating queries that return the same result, a differentiator between them may be their performance when compared to each other. However, full outer joins are a different matter in Oracle at least , since the way the columns are joined influences the result.
You stated interest in "internals", and then asked an example that illustrates "semantics". I'm answering semantics. These choices include:. Also note: due to the optimizer making these choices, and changing these choices based on what it considers to be optimal - the order of the results can change. The default ordering of results is always "what is easiest".
If you don't want the default ordering, you need to specify ordering in your query. To see exactly what the optimizer will do with a query at that moment, because it can change its mind , you need to view the execution plan.
With query A what you get includes entries in table 1 with a corresponding entry in table3 without corresponding entries in table3 nulls for t2 columns.
With query B uou don't get those entries because you only go to table3 through table2. If you don't have a corresponding entry in table2, the table2. Stack Overflow for Teams — Collaborate and share knowledge with a private group. Create a free Team What is Teams? Collectives on Stack Overflow. Learn more. How does SQL join work? Ask Question. Asked 12 years, 10 months ago. Active 10 years, 4 months ago.
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