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In the answer I gave, the number 47 (or the word 47th) is an ordinal number. In mathematics, an ordinal number is a number that can represent a position in order (as opposed to a cardinality). In the nite realm, the ordinal numbers and the cardinal numbers are the same, but we still have a reason to look at them separately.

This is very straightforward: the base table is scanned and the rows matching the spatial predicate pass through the Filter operator . If the spatial index is used, we find a much more complex query plan, as shown in Figure 14-22 . This requires some additional explanation . We can roughly divide the query plan into four stages, labeled A through D in Figure 14-22: A. The first stage computes a set of grid cells for the query object @point . B. Next, the grid cells for the query object are joined with the spatial index . In a query plan, this Clustered Index Seek (Spatial) is your clue that a spatial index has been used . The primary keys for the matching spatial objects are extracted and duplicates are eliminated . C. Next, the primary keys for the spatial objects are joined back to the base table to extract the spatial objects themselves, as well as any other necessary columns from the base table . D. Finally, the secondary filter is applied to the rows that passed through the primary filter and the result of the query is assembled .

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The script that creates the Sessions table also creates the covering index idx_nc_app_st_et based on the key list (app, starttime, endtime), which is the optimal index for this query. In the plan, this index is fully scanned (Index Scan operator) to return all rows. As rows are streamed out from the Index Scan operator, a Nested Loops operator invokes a series of activities (Clustered Index Scan, followed by Stream Aggregate) to calculate the count of active sessions for each row. Because the Sessions table is so tiny (only one page of data), the optimizer simply decides to scan the whole table (unordered clustered index scan) to calculate each count. With a larger data set, instead of scanning the table, the plan would perform a seek and ordered partial scan of the covering index to obtain each count. Finally, another Stream Aggregate operator groups the data by app to calculate the maximum count for each group. Now that you re familiar with the problem, suppose you were asked to prepare sample data with 1,000,000 rows in the source table (call it BigSessions) such that it would represent a realistic environment. Ideally, you should be thinking about realistic distribution of session start times, session duration, and so on. However, people often take the most obvious approach, which is to duplicate the data from the small source table many times; in our case, such an approach would drastically skew the performance compared to a more realistic representation of production environments. Now run the following code to generate the BigSessions table by duplicating the data from the Sessions table many times. You will get 1,000,000 rows in the BigSessions table:

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IF OBJECT_ID('dbo.BigSessions', 'U') IS NOT NULL DROP TABLE dbo.BigSessions; SELECT ROW_NUMBER() OVER(ORDER BY (SELECT 0)) AS keycol, app, usr, host, starttime, endtime INTO dbo.BigSessions FROM dbo.Sessions AS S CROSS JOIN Nums WHERE n <= 62500;

Although this query plan is much more complex, it will usually outperform the simpler plan by a large margin . The query above finds out which of the 49,146 ZIP codes intersects a given point . We tested the two plans, and the non-indexed plan averaged 5,092 milliseconds whereas the indexed plan averaged only 4 .6 milliseconds . This is not a bad return for a 9-second index build time . Although the query optimizer tries to pick the optimal plan, you may occasionally find that the spatial index is not chosen even though the indexed plan would be better . In these cases, the spatial index can be used in an index hint just like any other index . For example, to force the use of the GEOMETRY index in our query, we would write:

CREATE UNIQUE CLUSTERED INDEX idx_ucl_keycol ON dbo.BigSessions(keycol); CREATE INDEX idx_nc_app_st_et ON dbo.BigSessions(app, starttime, endtime);

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