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CHECKPOINT; DBCC FREEPROCCACHE WITH NO_INFOMSGS; DBCC DROPCLEANBUFFERS WITH NO_INFOMSGS; DECLARE @dt1 AS DATETIME, @dt2 AS DATETIME, @dt3 AS DATETIME, @dt4 AS DATETIME; SET @dt1 = GETDATE(); -- Set-Based Solution SELECT app, MAX(concurrent) AS mx FROM (SELECT app, (SELECT COUNT(*) FROM dbo.Sessions AS S WHERE T.app = S.app AND T.ts >= S.starttime AND T.ts < S.endtime) AS concurrent FROM (SELECT app, starttime AS ts FROM dbo.Sessions) AS T) AS C GROUP BY app; SET @dt2 = GETDATE(); DBCC FREEPROCCACHE WITH NO_INFOMSGS; DBCC DROPCLEANBUFFERS WITH NO_INFOMSGS; SET @dt3 = GETDATE(); -- Cursor-Based Solution DECLARE @app AS VARCHAR(10), @prevapp AS VARCHAR (10), @ts AS datetime, @event_type AS INT, @concurrent AS INT, @mx AS INT; DECLARE @Result TABLE(app VARCHAR(10), mx INT); DECLARE C CURSOR FAST_FORWARD FOR SELECT app, starttime AS ts, 1 AS event_type FROM dbo.Sessions UNION ALL SELECT app, endtime, -1 FROM dbo.Sessions ORDER BY app, ts, event_type; OPEN C; FETCH NEXT FROM C INTO @app, @ts, @event_type; SELECT @prevapp = @app, @concurrent = 0, @mx = 0; WHILE @@FETCH_STATUS = 0 BEGIN IF @app <> @prevapp BEGIN INSERT INTO @Result VALUES(@prevapp, @mx); SELECT @prevapp = @app, @concurrent = 0, @mx = 0; END SET @concurrent = @concurrent + @event_type; IF @concurrent > @mx SET @mx = @concurrent; FETCH NEXT FROM C INTO @app, @ts, @event_type; END

I covered the logical processing phases involved with joins earlier and will also discuss joins in more detail in 7, Joins and Set Operations. Here I ll brie y describe the other three operators and the way they t in the logical query processing model. Table operators get one or two tables as inputs. Call them left input and right input based on their position in respect to the table operator keyword (JOIN, APPLY, PIVOT, UNPIVOT). Just like joins, all table operators get a virtual table as their left input. The rst table operator that appears in the FROM clause gets a table expression as the left input and returns a virtual table as a result. A table expression can stand for many things: a real table, a temporary table, a table variable, a derived table, a CTE, a view, or a table-valued function. More Info For details on table expressions, please refer to 6, Subqueries, Table

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IF @prevapp IS NOT NULL INSERT INTO @Result VALUES(@prevapp, @mx); CLOSE C; DEALLOCATE C; SELECT * FROM @Result; SET @dt4 = GETDATE(); PRINT CAST(@numrows AS VARCHAR(10)) + ' rows, set-based: ' + CAST(DATEDIFF(ms, @dt1, @dt2) / 1000. AS VARCHAR(30)) + ', cursor: ' + CAST(DATEDIFF(ms, @dt3, @dt4) / 1000. AS VARCHAR(30)) + ' (sec)';

The average gross leaf row size (call it leaf_row_size) In a clustered index, this is actually the data row size. By gross, I mean that you need to take the internal

OrderID 11077 11076 11075 CustomerID RATTC BONAP RICSU OrderDate 1998-05-06 00:00:00.000 1998-05-06 00:00:00.000 1998-05-06 00:00:00.000

overhead of the row and the 2-byte pointer stored at the end of the page pointing to the row. The row overhead typically involves a few bytes. In our Orders table, the gross average data row size is roughly 200 bytes.

Change the value of the @numrows variable to determine the number of rows in the table . I ran this code with numbers varying from 10,000 through 100,000 in steps of 10,000 . Figure 8-4 shows a graphical depiction of the benchmark test I ran .

The average leaf page density (call it page_density) This value is the average percentage of population of leaf pages Reasons for pages not being completely full include data deletion, page splits caused by insertion of rows to full pages, having very large rows, and explicit requests not to populate the pages in full by specifying a llfactor value when rebuilding indexes In our case, we created a clustered index on the Orders table after populating it with the data, we did not add rows after creating the clustered index, and we did not specify a llfactor value Therefore, page_density in our case is close to 100 percent The number of rows that t in a leaf page (call it rows_per_leaf_page) The formula to calculate this value is (page_size - header_size) * page_density / leaf_row_size.

Sorting first by OrderDate DESC guarantees that you will get the most recent orders. Because OrderDate is not unique, I added OrderID DESC to the ORDER BY list as a tiebreaker. Among orders with the same OrderDate, the tiebreaker will give precedence to orders with higher OrderID values.

Max Concurrent Sessions Benchmark 60 50 Run Time (seconds) 40 30 20 10 0

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