You often use the GROUP BY in conjunction with an aggregate function such as MIN, MAX, AVG, SUM, or COUNT to calculate a measure that provides the information for each group. It is not mandatory to include an aggregate function in the SELECT clause.
However, if you use an aggregate function, it will calculate the summary value for each group. We will use the employees and departments tables in the sample database to demonstrate how the GROUP BY clause works.
For example, in the shipping department, there are 2 employees holding the shipping clerk job, 1 employee holding the stock clerk job, and 4 employees holding the stock manager job. The following statement also retrieves the phone numbers but instead of using the GROUP BY clause, it uses the DISTINCT operator.
The result set is the same except that the one returned by the DISTINCT operator is not sorted. We can use an SQL group by and aggregates to collect multiple types of information.
For example, an SQL group by can quickly tell us the number of countries on each continent. Group by X means put all those with the same value for X in the same row.
The alternate having is placed after the group by and allows you to filter the returned data by an aggregated column. It predates column based notation and was SQL standard until the 1980s.
A query select statement can have a column name changed and continue to run, producing an unexpected result. SQL coders tend toward a consistent pattern of selecting dimensions first and aggregates second.
A common practice is to use ordinal positions for ad hoc work and column names for production code. This will ensure you are being completely explicit for future users who need to change your code.
When you are aggregating the full table there is an implied SQL group by. This does not conform to the standard use of null, which is never equal to anything including itself.
In MySQL, unless you change some database settings, toucan run queries like only a subset of the select dimensions grouped, and still get results. As an example, in MySQL this will return an answer, populating the state column with a randomly chosen value from those available.
Group by is a commonly used keyword, but hopefully you now have a clearer understanding of some of its more nuanced uses. GROUP BY clause is used with the SELECT statement.
The above query will produce the below output: As you can see in the above output, the rows with duplicate Names are grouped under same NAME and their corresponding SALARY is the sum of the SALARY of duplicate rows. This means to place all the rows with same values of both the columns column1 and column2 in one group.
And those whose only SUBJECT is same but not YEAR belongs to different groups. We can use HAVING clause to place conditions to decide which group will be the part of final result-set.
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Get hold of all the important CS Theory concepts for SDE interviews with the CS Theory Course at a student-friendly price and become industry ready. For most relational database systems, this order explains which names (columns or aliases) are valid because they must have been introduced in a previous step.
At least in PostgreSQL toucan use the column number in the result set in your GROUP BY clause: Of course this starts to be a pain if you are doing this interactively and you edit the query to change the number or order of columns in the result.
SQL Server doesn't allow you to reference the alias in the GROUP BY clause because of the logical order of processing. I'm not answering why it is so, but only wanted to show a way around that limitation in SQL Server by using CROSS APPLY to create the alias.
Caution that using alias in the Group By (for services that support it, such as Postgres) can have unintended results. For example, if you create an alias that already exists in the inner statement, the Group By will chose the inner field name.
Beware of using aliases when grouping the results from a view in SQLite. Back in the day I found that RDB, the former DEC product now supported by Oracle allowed the column alias to be used in the GROUP BY.
I wouldn't recommend renaming an alias as a change in capitalization, that causes confusion. They are used for some kind of specific operations, like to compute the average of numbers, the total count of the records, the total sum of the numbers etc.
First, the SQL Engine extracts the record from the Invoice table on the basis of WHERE clause and then, these above GROUP functions will apply to the extracted group of records. Here, we’re getting the results after applying the group functions on the complete filtered table.
In this query, we’re getting the total counts of records on the basis of same BillingCountry attribute values. As toucan see, we can ’t understand the result just by output values so it is a best practice to also print the attribute on the basis of what we’re getting to make the result more meaningful.
Because Avg() is an aggregate function which applies on the collection and InvoiceD ate is a Daytime field whose value is always different, so if we’ve just applied the Group By on Customer ID, it is not enough because we need to cover InvoiceD ate as well. Before InvoiceD ate, we were getting only 1 record of Customer 2 because 2 is the discrete value.
And after putting InvoiceD ate in the query we’re getting nearly all the records because it is continuous. Actually, we can ’t apply the condition to Aggregate functions with the help of WHERE clause.
SELECT , City, AVG (Total) AS CityAverage, SUM (Total) AS Littoral FROM Customer JOIN Invoice ON Customer. CustomerId = Invoice. CustomerId WHERE <> NULL GROUP BY , City HAVING SUM (Total) > 40 ORDER BY , City. You might be wondering why we put State column name in square brackets.
And if you try to run the query without putting State attribute name in square brackets, you ’ll get the error. Because SQL Server became confused about whether it is your table attribute name or its reserved State keyword.
Now you might be thinking InvoiceD ate is obviously not an aggregate function and it is working. Always put WHERE clause before GROUP BY and HAVING clause after GROUP BY otherwise it will not accept and show an error in the Messages window.
Mostly, when we’re doing some kind of reporting in SQL Server, and we want to get the results on the basis of collections of records we’ve some functions in SQL Server to summarize the results. To understand the GROUPING SETS, let’s create a new table of Employees.
SELECT Country, Gender, SUM (Salary) as TotalSalary FROM Employees GROUP BY Country, Gender Now we want to show the total salaries of individual countries as well.
SELECT Country, Gender, SUM (Salary) as TotalSalary FROM Employees GROUP BY Country, Gender UNION ALL SELECT Country, NULL, SUM (Salary) as TotalSalary FROM Employees GROUP BY Country UNION ALL SELECT NULL, Gender, SUM (Salary) as TotalSalary FROM Employees GROUP BY Gender Now lets we get the final total salaries without any kind of classification.
SELECT Country, Gender, SUM (Salary) as TotalSalary FROM Employees GROUP BY Country, Gender UNION ALL SELECT Country, NULL, SUM (Salary) as TotalSalary FROM Employees GROUP BY Country UNION ALL SELECT NULL, Gender, SUM (Salary) as TotalSalary FROM Employees GROUP BY Gender UNION ALL SELECT NULL, NULL, SUM (Salary) as TotalSalary FROM Employees And if we need some more kind of reporting feature then we’ll also need some more UNION ALL.
SELECT Country, SUM (Salary) as TotalSalary, AVG (Salary) AS AverageSalary FROM Employees GROUP BY ROLL UP (Country) It means ROLL UP adds a single row if we’re Grouping one column.
SELECT Country, Gender, SUM (Salary) as TotalSalary FROM Employees GROUP BY ROLL UP (Country, Gender) Here we’re grouping the Salary by Country and Gender and it will also display the Subtotal of Country salaries and then the Grand Total.
SELECT Country, Gender, SUM (Salary) as TotalSalary FROM Employees GROUP BY Country, Gender WITH ROLL UP This is used to get the Sum of Salaries grouped by all the combinations of Country and Gender.
SELECT Country, Gender, SUM (Salary) as TotalSalary FROM Employees GROUP BY Country, Gender WITH CUBE Note If you ’re applying ROLL UP & CUBE on the single column, you won’t see any difference.
Suppose we want to get the total population of a country, state and city. So if we use ROLL UP here, it will calculate the population of country, state and city first and then it comes to country and state and then it calculates the population of country and then sum all the grand total population.
If you have hierarchical data (Country > State > City or Department > Manager > Salesman) then obviously you ’ll use the hierarchical results in most of the cases. Now we want to get all these aggregate functions results for each Employee with respect to its Gender.