Guest_name origin_cityroom_numberday_inday_outageroom_levelamount_invoicedJuan B. San Pedro10012012-12-282013-01-0732standard$9500Mary J. San Francisco10022013-01-022013-01-1223standard$6700Peter S. Dubai20022013-01-022013-01-2965premium$34000Clair BGenova20012014-07-022014-08-0221standard$16000Meiling Y. San Francisco20022014-11-022014-11-1252standard$9500Olek V. Dubai20032015-01-022015-01-3137premium$28400Benjamin L. San Pedro20022016-01-022016-01-1561premium$15400Arnaldo V. Genova10012017-01-012017-01-0443standard$2500Mary J. San Francisco10022017-01-022017-01-0723standard$4800Wei W. Los Angeles20022018-01-022018-01-2231standard$12000Meiling Y. San Francisco20012018-01-022018-01-2252premium$17500Peter S. Dubai20022019-01-022019-02-2565premium$32000Arnaldo V. Genova20032019-08-052019-08-1743standard$11200Mary J. San Francisco10012019-01-022019-01-1223standard$8900guest_namepreferred_activitycity_namestatecountrycontinentactivityCity_nameStateCountryContinent32Juan B.trekking San PedroAndaluciaSpainEuropeMary J.trekking San FranciscoCaliforniaUnited StatesAmericaPeter S.trekkingDubaiDubaiArabiaAsiaChiara BskiingGenovaLiguriaItalyEuropeMeiling Y.trekking San FranciscoCaliforniaUnited StatesAmericaOlek V.relaxingDubaiDubaiArabiaAsiaBenjamin L.skiing San PedroBuenos AiresArgentinaAmericaWei W.trekking Los AngelesCaliforniaUnited StatesAmericaArnaldo V.skiingGenovaLiguriaItalyEuropeWe want to calculate some statistics, so we can book more guests. We can group records in the table room_guest based on the value of the column origin_city.
The following table shows each group of records in a different color. Guest_name origin_cityroom_numberday_inday_outageroom_levelamount_invoicedPeter S. Dubai20022013-01-022013-01-2965premium$34000Olek V. Dubai20032015-01-022015-01-3137premium$28400Peter S. Dubai20022019-01-022019-02-2565premium$32000Clair BGenova20012014-07-022014-08-0221standard$16000Arnaldo V. Genova10012017-01-012017-01-0443standard$2500Arnaldo V. Genova20032019-08-052019-08-1743standard$11200Wei W. Los Angeles20022018-01-022018-01-2231standard$12000Mary J. San Francisco10022013-01-022013-01-1223standard$6700Mary J. San Francisco10022017-01-022017-01-0723standard$4800Meiling Y. San Francisco20022014-11-022014-11-1252standard$9500Meiling Y. San Francisco20012018-01-022018-01-2256premium$17500Mary J. San Francisco10012019-01-022019-01-1223standard$8900Benjamin L. San Pedro20022016-01-022016-01-1561premium$15400Juan B. San Pedro10012012-12-282013-01-0732standard$9500Now, suppose the hotel’s owner wants to know how many guests come from each city.
In other words, we need the aggregate function COUNT(*), which returns the number of records in a group. COUNT() is a very common function; we’ll return to it later in this article.
It includes a complete description of GROUP BY and several examples of its most common errors. I’d go so far as to say that every SQL query using a GROUP BY clause should have at least one aggregate function.
Metrics are calculated by aggregation functions like COUNT(), SUM(), AVG(), MIN(), and MAX(). However, all of them have something in common: all aggregate functions return a value based on all the records in the group.
The hotel owner wants to know the maximum value invoiced for each room. In the previous query, we created a report analyzing how much money each room is generating.
Origin_city quantity_of_guestsNULL2Dubai3Genova3Los Angeles1San Francisco5San Pedro2 The WHERE clause is frequently used in SQL queries, so it’s important to understand how it works when combined with GROUP BY. As an example, let's use the previous query, but this time we’ll filter for guests coming from the cities of San Francisco and Los Angeles.
As expected, this result set is shorter than the previous ones; the WHERE clause filtered out many guests, and only the records for rooms in San Francisco and Los Angeles were processed by the GROUP BY clause. Room_number room_levelmax_amount_invoicedmin_amount_ invoicedaverage_amount_invoiced1001standard8900.008900.008900.001002standard6700.004800.005750.002001premium17500.0017500.0017500.002002standard12000.009500.0010750.00 When you’re getting started with GROUP BY, it’s common to run into the following problems.
Let’s look at a similar case where we need to add more than one extra column into the GROUP BY clause. In our data set, we have two different cities named San Pedro, one in Argentina and the other in Spain.
To count these cities separately, we need to group records using the columns city_origin, state, and country. Then we will repeat the first query but add the columns state and country to the GROUP BY clause.
We also maintain the original COUNT(*) so that the reader can compare both results: Origin_citystatecountrynumber_of_unique_guestsnumber_of_guestsDubaiDubaiUAE23GenovaLiguriaItaly23Los AngelesCaliforniaUnited States11San FranciscoCaliforniaUnited States25San PedroBuenos AiresArgentina11San PedroAndaluciaSpain11Before closing this section, I suggest you watch this 5-minute video on GROUP BY for beginners.
We know the aggregate functions MIN(), MAX(), AVG(), and SUM() compute various statistics. For those readers who want to go a step further, I’ll leave you a link to our SQL Basics course, which covers many interesting topics.
The Subgroup BY clause is used in collaboration with the SELECT statement to arrange identical data into groups. The basic syntax of a GROUP BY clause is shown in the following code block.
If you want to know the total amount of the salary on each customer, then the GROUP BY query would be as follows. 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.
See your article appearing on the GeeksforGeeks main page and help other Geeks. Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.
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. Summary : in this tutorial, you will learn how to use Subgroup BY clause to group rows based on one or more columns.
Grouping is one of the most important tasks that you have to deal with while working with the databases. The GROUP BY clause is an optional clause of the SELECT statement that combines rows into groups based on matching values in specified columns.
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.
To sort the departments by headcount, you add an ORDER BY clause as the following statement: Note that you can use either the headcount alias or the COUNT(employee_id) in the ORDER BY clause.
To find the department whose headcount is greater than 5, you use the HAVING clause as the following query: 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.
One of our subscribers reached us and asked How Grouping works in SQL ? We will discuss in detail about grouping in SQL and how it actually works behind the scenes.
Also, this is our first post in Questions category, and we will be doing more than there are bundles of requests in the queue. While working with SQL reports, a lot of times we will come across scenarios where we want to summarize the data.
Examples and queries that we will see here will run on our University Management System database. If you want to use these SQL queries for practice, create the same database, you need to just copy and paste the script from here.
If you run the below SQL query, you will have a good look at the data we have. We need first five students with top marks out of these forty rows.
Objective is to find the top 5 students. Let’s break up the table and visualize what is we want. Now it is clear that we want top achievers which are actually the students who have obtained the highest marks.
We have applied the aggregate function but haven’t told our SQL Server on what basis it should be grouped. We want to group the grades against each student that is why we are writing Filename in query.
To apply SQL aggregate function of SUM on grades' column you need to put First Name in Group By Clause. Each student was taking up more than one course so SQL Server first combines the elements into group.
Grouping is applied on all columns as combination in the same order they appear in query. Now if you like this article, do share with your friends and colleagues and recommend us.