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Rarely can we a ord to allocate in advance pointers for every possible query In Fig 4-37 we show an alternative design with composed pointers When some attributes do not appear in the query the records to be fetched will be in multiple buckets

Late Binding The hash address is constructed by catenating the hash addresses for all attributes a The size of the hash address is based on the number of buckets If one bucket can hold one record, an appropriate length for the hash address is log2 n This means that to each of the a attributes log2 n/a bits can be allocated For a le with a million records and 10 attributes the log2 (106 ) = 20-bit address would allow 20/10 = 2 bits per attribute

SELECT OffYear, COUNT(*) AS NumOfferings, COUNT(DISTINCT CourseNo) AS NumCourses FROM Offering GROUP BY OffYear

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Using this scheme, the attributes partition the search space only grossly A retrieval based on only one argument will specify 1/a or two bits out of the twenty, and one could expect that one-fourth of the le is to be retrieved The situation improves quickly as more attributes are speci ed in the query When all attributes are speci ed, the expectation becomes close to one Figure 4-37 illustrates the case for a nine-attribute query

The partial-match indexing and hashing schemes presented are not very e ective at extreme ranges We can take advantage of these conditions and modify these schemes, so that the update e ort is greatly reduced while much of the bene t is retained

Meaning and Comments Computes the number of rows Counts the non-null values in column; DISTINCT can be used to count the unique column values Computes the average of a numeric column or expression excluding null values; DISTINCT can be used to compute the average of unique column values Computes the sum of a numeric column or expression excluding null values; DISTINCT can be used to compute the average of unique column values Computes the smallest value For string columns, the collating sequence is used to compare strings Computes the largest value For string columns, the collating sequence is used to compare strings

int x, *p; x = 10; p = x; printf("%d", *p); return 0; }

Small Number of Arguments There seems to be little point in supporting rapid access for queries which lead to retrieval of a large fraction of the le A heuristic which states: Search sequentially when looking for more than 20% of the records remains a valid guideline In the early binding cases with many access lists (Fig 4-36) or combined indexes (Fig 4-12), update time and storage space can be saved by only entering combinations of several, say, > 3 attributes into the access lists In the late binding case illustrated in Fig 4-37 the retrieval algorithm might as well search sequentially when near exhaustive requests are made In an interactive environment it is well to have the system respond to a poorly partitioned query with a counter question as: Do you really want 13117 references on the topic: system

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The call to printf( ) does not print the value of x, which is 10, on the screen It prints some unknown value because the assignment

4 WHERE vs HAVING use the WHERE clause for conditions that can be tested on individual rows Use the HAVING clause for conditions that can be tested only on groups Conditions in the HAVING clause should involve aggregate functions, whereas conditions in the WHERE clause cannot involve aggregate functions

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