04 | Grouping and Aggregating Data
Brian Alderman | MCT, CEO / Founder of MicroTechPoint
Tobias Ternstrom | Microsoft SQL Server Program Manager
Querying Microsoft SQL Server 2012 Jump Start
01 | Introducing SQL Server 2012
SQL Server types of statements; other SQL statement elements; basic SELECT statements
02 | Advanced SELECT Statements
DISTINCT, Aliases, scalar functions and CASE, using JOIN and MERGE; Filtering and sorting data, NULL
values
03 | SQL Server Data Types
Introduce data types, data type usage, converting data types, understanding SQL Server function types
04 | Grouping and Aggregating Data
Aggregate functions, GROUP BY and HAVING clauses, subqueries; self-contained, correlated, and EXISTS; Views, inline-table
valued functions, and derived tables
| Lunch Break
Eat, drink, and recharge for the afternoon session
Common
•
•
•
•
•
•
SUM
MIN
MAX
AVG
COUNT
COUNT_BIG
Statistical
•
•
•
•
STDEV
STDEVP
VAR
VARP
Other
• CHECKSUM_AGG
• GROUPING
• GROUPING_ID
SELECT COUNT (DISTINCT SalesOrderID) AS
UniqueOrders,
AVG(UnitPrice) AS Avg_UnitPrice,
MIN(OrderQty)AS Min_OrderQty,
MAX(LineTotal) AS Max_LineTotal
FROM Sales.SalesOrderDetail;
UniqueOrders Avg_UnitPrice Min_OrderQty Max_LineTotal
------------- ------------ ------------ ------------31465
465.0934
1
27893.619000
SELECT SalesPersonID, YEAR(OrderDate) AS OrderYear,
COUNT(CustomerID) AS All_Custs,
COUNT(DISTINCT CustomerID) AS Unique_Custs
FROM Sales.SalesOrderHeader
GROUP BY SalesPersonID, YEAR(OrderDate);
SalesPersonID OrderYear All_Custs Unique_custs
--------------------- ----------- -----------289
2006
84
48
281
2008
52
27
285
2007
9
8
277
2006
140
57
SELECT <select_list>
FROM <table_source>
WHERE <search_condition>
GROUP BY <group_by_list>;
SELECT SalesPersonID, COUNT(*) AS Cnt
FROM Sales.SalesOrderHeader
GROUP BY SalesPersonID;
Logical Order
Phase
Comments
5
SELECT
1
FROM
2
WHERE
3
GROUP BY
Creates groups
4
HAVING
Operates on groups
6
ORDER BY
SELECT CustomerID, COUNT(*) AS cnt
FROM Sales.SalesOrderHeader
GROUP BY CustomerID;
SELECT productid, MAX(OrderQty) AS largest_order
FROM Sales.SalesOrderDetail
GROUP BY productid;
SELECT CustomerID, COUNT(*) AS
Count_Orders
FROM Sales.SalesOrderHeader
GROUP BY CustomerID
HAVING COUNT(*) > 10;
• Using a COUNT(*) expression in HAVING clause is useful to solve
common business problems:
• Show only customers that have placed more than one order:
SELECT Cust.Customerid, COUNT(*) AS cnt
FROM Sales.Customer AS Cust
JOIN Sales.SalesOrderHeader AS Ord ON Cust.CustomerID =
ORD.CustomerID
GROUP BY Cust.CustomerID
HAVING COUNT(*) > 1;
• Show only products that appear on 10 or more orders:
SELECT Prod.ProductID, COUNT(*) AS cnt
FROM Production.Product AS Prod
JOIN Sales.SalesOrderDetail AS Ord ON Prod.ProductID =
Ord.ProductID
GROUP BY Prod.ProductID
HAVING COUNT(*) >= 10;
Working with subqueries
Writing scalar subqueries
SELECT SalesOrderID, ProductID, UnitPrice, OrderQty
FROM Sales.SalesOrderDetail
WHERE SalesOrderID =
(SELECT MAX(SalesOrderID) AS LastOrder
FROM Sales.SalesOrderHeader);
Writing multi-valued subqueries
SELECT CustomerID, SalesOrderId,TerritoryID
FROM Sales.SalesorderHeader
WHERE CustomerID IN (
SELECT CustomerID
FROM Sales.Customer
WHERE TerritoryID = 10);
Writing queries using EXISTS with subqueries
SELECT CustomerID, PersonID
FROM Sales.Customer AS Cust
WHERE EXISTS (
SELECT *
FROM Sales.SalesOrderHeader AS Ord
WHERE Cust.CustomerID = Ord.CustomerID);
SELECT CustomerID, PersonID
FROM Sales.Customer AS Cust
WHERE NOT EXISTS (
SELECT *
FROM Sales.SalesOrderHeader AS Ord
WHERE Cust.CustomerID = Ord.CustomerID);
CREATE VIEW HumanResources.EmployeeList
AS
SELECT BusinessEntityID, JobTitle, HireDate,
VacationHours
FROM HumanResources.Employee;
SELECT * FROM HumanResources.EmployeeList
CREATE FUNCTION Sales.fn_LineTotal (@SalesOrderID INT)
RETURNS TABLE
AS
RETURN
SELECT SalesOrderID,
CAST((OrderQty * UnitPrice * (1 - SpecialOfferID))
AS DECIMAL(8, 2)) AS LineTotal
FROM Sales.SalesOrderDetail
WHERE SalesOrderID = @SalesOrderID ;
Writing queries with derived tables
SELECT <column_list>
FROM (
<derived_table_definition>
) AS <derived_table_alias>;
Derived Tables Must
• Have an alias
• Have names for all
columns
• Have unique names
for all columns
• Not use an ORDER BY
clause (without TOP or
OFFSET/FETCH)
• Not be referred to
multiple times in the
same query
Derived Tables May
• Use internal or
external aliases for
columns
• Refer to parameters
and/or variables
• Be nested within other
derived tables
DECLARE @emp_id INT = 9;
SELECT orderyear, COUNT(DISTINCT custid) AS cust_count
FROM (
SELECT YEAR(orderdate) AS orderyear, custid
FROM Sales.Orders
WHERE empid=@emp_id
) AS derived_year
GROUP BY orderyear;
WITH CTE_year AS
(
SELECT YEAR(OrderDate) AS OrderYear, customerID
FROM Sales.SalesOrderHeader
)
SELECT orderyear, COUNT(DISTINCT CustomerID) AS CustCount
FROM CTE_year
GROUP BY OrderYear;
Common
•
•
•
•
•
•
SUM
MIN
MAX
AVG
COUNT
COUNT_BIG
Statistical
•
•
•
•
STDEV
STDEVP
VAR
VARP
Other
• CHECKSUM_AGG
• GROUPING
• GROUPING_ID
Views are named tables expressions with definitions stored in a database
that can be referenced in a SELECT statement just like a table
Views are defined with a single SELECT statement and then saved in the
database as queries
Table-valued functions are created with the CREATE FUNCTION. They
contain a RETURN type of table
Derived tables allow you to write more modular queries
as named query expressions that are created within an outer SELECT
statement. They represent a virtual relational table so are not stored in
the database
CTEs are similar to derived tables in scope and naming requirements but
unlike derived tables, CTEs support multiple definitions, multiple
references, and recursion
Querying Microsoft SQL Server 2012 Jump Start
01 | Introducing SQL Server 2012
SQL Server types of statements; other SQL statement elements; basic SELECT statements
02 | Advanced SELECT Statements
DISTINCT, Aliases, scalar functions and CASE, using JOIN and MERGE; Filtering and sorting data, NULL
values
03 | SQL Server Data Types
Introduce data types, data type usage, converting data types, understanding SQL Server function types
04 | Grouping and Aggregating data
Aggregate functions, GROUP BY and HAVING clauses, subqueries; self-contained, correlated, and EXISTS; Views, inline-table
valued functions, and derived tables
| Lunch Break
Eat, drink, and recharge for the afternoon session
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