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SQL Week 2 Practice Problems

Practice Topics

  • Aggregation with GROUP BY
  • Filtering Using HAVING
  • Basic Joins

Aggregation with GROUP BY

Overview

Aggregation is when you collapse a detailed dataset into a summarized one. Picture an Excel file with a pivot table tab summarizing a more detailed data tab. Aggregation is the equivalent of the pivot table tab.

When you set up a pivot table in Excel, you have to drag fields from a dataset into the rows, columns, and values areas. The values area is where you determine which measures you want to summarize, then you set them as a SUM, MIN, MAX, COUNT, or AVERAGE. You do the same thing when using aggregation in a SQL query -> identify the measures you want to summarize, then wrap those fields with common aggregate functions such as SUM(), COUNT(), MIN(), MAX(), AVG(), or COUNT(DISTINCT ).

When setting up a pivot table in Excel, you also define the fields that you want to display and summarize by in the rows area. You do the same thing when using aggregation in a SQL query. In this case, you list the fields that you want to summarize by in the SELECT statement (before the aggregate fields such as SUM(), COUNT(), etc.). Then, list those same fields in the GROUP BY statement (after the FROM and WHERE statements). When any field listed in the GROUP BY has a change in value, the aggregate fields will reset.

Example: Using the AdventureWorks2019.Sales.SalesOrderHeader table, determine the number of invoices (hint: use COUNT(*) ) and the total sales amount (hint: use SUM(TotalDue) ) for each CustomerId. Use a table alias name and be sure to attach the alias to columns in the SELECT and GROUP BY.

SQL Code Highlighting 
SELECT
    a.CustomerID,
    COUNT(*) AS NumOfInvoices,
    SUM(a.TotalDue) AS TotalSalesAmount
FROM
    AdventureWorks2019.Sales.SalesOrderHeader a
GROUP BY
    a.CustomerID;

Self Practice

  • Write a query to find the average ListPrice of all products in the AdventureWorks2019.Production.Product table.
  • Write a query to count the number of employees in the AdventureWorks2019.HumanResources.Employee table.
  • Write a query to find the total number of products for each Color in the AdventureWorks2019.Production.Product table. Group by Color.
SQL Code Highlighting 
SELECT
    AVG(ListPrice) AS AverageListPrice
FROM
    AdventureWorks2019.Production.Product;
SQL Code Highlighting 
SELECT
    COUNT(*) AS NumberOfEmployees
FROM
    AdventureWorks2019.HumanResources.Employee;
SQL Code Highlighting 
SELECT
    Color,
    COUNT(*) AS NumberOfProducts
FROM
    AdventureWorks2019.Production.Product
GROUP BY
    Color;

Filtering Using HAVING

Overview

Filtering in the HAVING statement exclusively applies to aggregation. It is very similar to filtering in the WHERE statement with one BIG exception -> this filter is applied at the very end of an aggregate query. By contrast, filtering in the WHERE statement applies to detailed records before aggregation is applied.

Imagine our Excel comparison from above. Filtering using HAVING would be equivalent to filtering on the result of a pivot table. Filtering using WHERE would be equivalent to filtering on the detailed data tab that the pivot table is built upon.

Example: Using the AdventureWorks2019.Sales.SalesOrderHeader table, determine the number of invoices (hint: use COUNT(*) ) and the total sales amount (hint: use SUM(TotalDue) ) for each CustomerId. Use a table alias name and be sure to attach the alias to columns in the SELECT, GROUP BY, and HAVING. Only return records with an aggregated total sales amount less than one million dollars.

SQL Code Highlighting 
SELECT
    a.CustomerID,
    COUNT(*) AS NumOfInvoices,
    SUM(a.TotalDue) AS TotalSalesAmount
FROM
    AdventureWorks2019.Sales.SalesOrderHeader a
GROUP BY
    a.CustomerID
HAVING
    SUM(a.TotalDue) < 1000000;

Self Practice

  • Write a query to find the number of SalesOrderID for each CustomerID in the AdventureWorks2019.Sales.SalesOrderHeader table, but only include customers with more than 5 orders.
SQL Code Highlighting 
SELECT
    CustomerID, 
    COUNT(SalesOrderID) AS NumberOfOrders
FROM
    AdventureWorks2019.Sales.SalesOrderHeader
GROUP BY
    CustomerID
HAVING
    COUNT(SalesOrderID) > 5;

Basic Joins

Overview

Table joins are used to combine two or more tables within the same SQL query. The purpose of brining multiple tables together within the same query is because most queries need to do one of two things:

  1. Increase the number of fields available to display in a query’s output.
  2. Filter records based on existing (or non-existing) scenarios found in related tables.
Tables are joined based on relationships (common fields) that exist across tables. For example, if you need to add customer LastNames to each invoice, you must retrieve them from the AdventureWorks2019.Person.Person table. To do this, you would follow the below steps:
  1. Connect the AdventureWorks2019.Sales.SalesOrderHeader table to the AdventureWorks2019.Sales.Customer table based on the common field, CustomerID.
  2. Connect the AdventureWorks2019.Person.Person table to the AdventureWorks2019.Sales.Customer table based on PersonID in the Customer table and BusinessEntityID in the Person table. BusinessEntityID is a generic field name for PersonID, so we treat it as the same.
  3. Select the LastName from the AdventureWorks2019.Person.Person table.

Example: As described above, display the CustomerID and TotalDue for each invoice from the AdventureWorks2019.Sales.SalesOrderHeader table, then add customer FirstName and LastName from the AdventureWorks2019.Person.Person table. Remember to use the AdventureWorks2019.Sales.Customer as a bridge table to connect the SalesOrderHeader to the Person table.

SQL Code Highlighting 
SELECT
    a.CustomerID,
    a.TotalDue,
    c.FirstName,
    c.LastName
FROM
    AdventureWorks2019.Sales.SalesOrderHeader a
INNER JOIN
    AdventureWorks2019.Sales.Customer b
    ON a.CustomerID = b.CustomerID
INNER JOIN
    AdventureWorks2019.Person.Person c
    ON b.PersonID = c.BusinessEntityID;

Self Practice

  • Write a query to join the AdventureWorks2019.Person.Person table and the AdventureWorks2019.HumanResources.Employee table on BusinessEntityID and select FirstName, LastName, and JobTitle.
  • Write a query to join the AdventureWorks2019.Sales.SalesOrderDetail table and the AdventureWorks2019.Production.Product table on ProductID and select SalesOrderID, ProductID, and Name.
SQL Code Highlighting 
SELECT
    p.FirstName,
    p.LastName,
    e.JobTitle
FROM
    AdventureWorks2019.Person.Person p
INNER JOIN
    AdventureWorks2019.HumanResources.Employee e
    ON p.BusinessEntityID = e.BusinessEntityID;
SQL Code Highlighting 
SELECT
    sod.SalesOrderID,
    sod.ProductID,
    p.Name
FROM
    AdventureWorks2019.Sales.SalesOrderDetail sod
INNER JOIN
    AdventureWorks2019.Production.Product p
    ON sod.ProductID = p.ProductID;

Conclusion

As we wrap up this week’s SQL homework assignments, we’ve delved into more complex aspects of SQL, including aggregation, GROUP BY clauses, HAVING clauses, and basic joins. These exercises are designed to build your confidence and proficiency in SQL, equipping you with the skills necessary for more advanced queries in the future.

Remember, consistent practice is key to mastering SQL. If you find yourself needing extra help or wanting to deepen your understanding, don’t hesitate to sign up for our private or group training sessions. These sessions offer personalized guidance and a collaborative learning environment to further enhance your SQL skills. Stay tuned for next week’s assignments, and keep pushing your boundaries as you continue on your journey to becoming an SQL expert!

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