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As long as the dimension columns in the table don't have NULLs, wherever you see a NULL in the result of the CUBE query, it logically means all. Later I'll discuss how to deal with NULLs in the queried table. For example, the row containing NULL, NULL, 2004, 45 shows the total quantity (45) for the orders of all employees and all customers for the order year 2004. You might want to cache the result set from a CUBE query in the client or middle tier, or you might want to save it in a temporary table and index it. The code in Listing 6-15 selects the result set into the temporary table #Cube and then creates a clustered index on all dimensions.

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Later, when discussing nonclustered indexes, I ll elaborate on the reasoning behind this architecture and the need to uniquely identify a row in a clustered index..

ranking functions, but only with the PARTITION BY clause for aggregate functions . I hope that future versions of SQL Server will enhance the support for the OVER clause and provide a more complete implementation of the standard s feature set . Queries such as the one just shown have the potential to run substantially faster than any of the existing solutions . Better support for window specifications would also prevent developers from having to sacrifice performance if they require benefits specific to T-SQL solutions, such as dependency tracking .

Pointer to first IAM 1:1791 Pointer to first 1:47120 Pointer to root 1:47186

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SELECT empid, custid, YEAR(orderdate) AS orderyear, SUM(qty) AS totalqty INTO #Cube FROM dbo.Orders GROUP BY empid, custid, YEAR(orderdate) WITH CUBE; CREATE CLUSTERED INDEX idx_emp_cust_year ON #Cube(empid, custid, orderyear);

The Maximum Concurrent Sessions problem is yet another example of calculations that can benefit from processing the data in an ordered fashion . You record data for user sessions against different applications in a table called Sessions . Run the code in Listing 8-2 to create and populate the Sessions table .


USE tempdb; IF OBJECT_ID('dbo.Sessions', 'U') IS NOT NULL DROP TABLE dbo.Sessions; CREATE TABLE dbo.Sessions ( keycol INT NOT NULL IDENTITY, app VARCHAR(10) NOT NULL, usr VARCHAR(10) NOT NULL, host VARCHAR(10) NOT NULL, starttime DATETIME NOT NULL, endtime DATETIME NOT NULL, CONSTRAINT PK_Sessions PRIMARY KEY(keycol), CHECK(endtime > starttime) ); GO INSERT INTO dbo.Sessions VALUES ('app1', 'user1', 'host1', '20090212 ('app1', 'user2', 'host1', '20090212 ('app1', 'user3', 'host2', '20090212 ('app1', 'user4', 'host2', '20090212 ('app1', 'user5', 'host3', '20090212 ('app1', 'user6', 'host3', '20090212 ('app1', 'user7', 'host4', '20090212 ('app1', 'user8', 'host4', '20090212 ('app2', 'user8', 'host1', '20090212 ('app2', 'user7', 'host1', '20090212 ('app2', 'user6', 'host2', '20090212 ('app2', 'user5', 'host2', '20090212 ('app2', 'user4', 'host3', '20090212 ('app2', 'user3', 'host3', '20090212 ('app2', 'user2', 'host4', '20090212 ('app2', 'user1', 'host4', '20090212

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Single Page Allocation @0x3642C08E Slot 0 = (0:0) Slot 1 = (0:0) - - Extent Alloc Status Slot 1 80x3642C0C2 (1:0) (1:22064) = NOT ALLOCATED (1:22072) (1:24256) = NOT ALLOCATED (1:24264) = NOT ALLOCATED (1:24272) (1:32344) = ALLOCATED (1:32352) = NOT ALLOCATED ---

Any request for an aggregate can be satisfied using a seek operation within the clustered index. For example, the following query returns the total quantity for employee 1, generating the execution plan shown in Figure 6-3:

20061231 20061231 20061231

08:30', 08:30', 09:00', 09:15', 09:15', 10:30', 10:45', 11:00', 08:30', 09:00', 11:45', 12:30', 12:45', 13:00', 14:00', 15:30',

576 577 578 613 614 615

SELECT totalqty FROM #Cube WHERE empid = 1 AND custid IS NULL AND orderyear IS NULL;

'20090212 '20090212 '20090212 '20090212 '20090212 '20090212 '20090212 '20090212 '20090212 '20090212 '20090212 '20090212 '20090212 '20090212 '20090212 '20090212

999716 999717 999718 999757 999758 999759

10:30'), 08:45'), 09:30'), 10:30'), 09:30'), 14:30'), 11:30'), 12:30'), 08:45'), 09:30'), 12:00'), 14:00'), 13:30'), 14:00'), 16:30'), 17:00');

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Once you're done querying the #Cube table, drop it: DROP TABLE #Cube;

20061231 20061231 20061231 1:47186

CREATE INDEX idx_nc_app_st_et ON dbo.Sessions(app, starttime, endtime);

NULL 20030118 20030206 --20061116 20061205 20061225

The request is to calculate, for each application, the maximum number of sessions that were open at the same point in time Such types of calculations are required to determine the cost of a type of service license that charges by the maximum number of concurrent sessions Try to develop a set-based solution that works; then try to optimize it; and then try to evaluate its algorithmic complexity Later I ll discuss a cursor-based solution and show a benchmark that compares the set-based solution with the cursor-based solution .

An issue might arise if dimension columns allow NULLs. For example, run the following code to allow NULLs in the empid column and introduce some actual NULL values: ALTER TABLE dbo.Orders ALTER COLUMN empid INT NULL; UPDATE dbo.Orders SET empid = NULL WHERE orderid IN(10001, 20001);

NULL 1:47184 258 1:47585 210 1:47187 603 1:36836 540 1:36837 367 1.36838

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