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The probability that a partial-match query will specify all attributes is slim It is furthermore expected that, if many search arguments are speci ed, only a few or no records will respond to a query There exists hence a further opportunity for reduction of le cost Certain attribute keys can be placed in a don t care category, and not entered in combined lists When queries are made, the retrieval from the le will fetch some unwanted records The excess can then be pared down on the basis of the actual key values When early binding is used, this again reduces the number of entries in the pointer list; when late binding is used, it provides an opportunity for better use of the pointer list Fewer combinations of attributes need be stored if for some queries a merge of two or more distinct TID lists is permissible Then the attributes can be partitioned into these sets so that frequent queries require only one set Some will need two or more, and an odd partial-match query may need one attribute from each set The number of stored combinations reduces drastically, as was shown in Eq 4-9 Superimposed coding is another traditional technique used to reduce the number of distinct attribute elds In applications where there are typically many attributes of binary (have or have-not) value, one column may be assigned to more than one attribute It is hoped that the number of attributes will be such that a retrieval with many arguments will include few unwanted records (false drops) An attribute can also be assigned redundantly to a combination of several columns to avoid false drops due to a single other attribute The percentage of false drops can, in fact, be statistically predicted, given data on attribute patterns in goal records and queries.

p = x;

The schemes discussed above bring early and late binding multiattribute hashing schemes closer together The handling of false drops is obviously a late-binding procedure; selection of attributes which can be omitted or superimposed is an earlybinding process There is still active research in this area It is always di cult to balance rapid response to complex queries with e cient update and use of storage

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do not support the DISTINCT keyword inside of aggregate functions 9 presents an alternative formulation in Access SQL to compensate for the inability to use the DISTINCT keyword inside the COUNT function Examples 413 and 414 contrast the WHERE and HAVING clauses In Example 413, the WHERE clause selects upper-division students (juniors or seniors) before grouping on major Because the WHERE clause eliminates students before grouping occurs, only upper-division students are grouped In Example 414, a HAVING condition retains groups with an average GPA greater than 31 The HAVING clause applies to groups of rows, whereas the WHERE clause applies to individual rows To use a HAVING clause, there must be a GROUP BY clause

In Sec 3-6 we presented the basic ring-structure organization Implementations of le systems based on this structure o er a number of options which allow better performance at some increase in complexity Such options can be selected to apply to those rings which play a crucial role in the performance of the le We will nd language speci cations for such options in Chaps 8 and 9 when the codasyl database schema language is presented 4-7-1 Prior Pointers In the serial chain and ring structures, pointers may be kept that refer to the preceding record The availability of such a prior pointer simpli es certain search and update operations considerably Prior pointers allow spacing backward through a ring, so that the predecessor record is found using one access rather than using y 1 accesses through the ring If an open-chain structure is used, access to predecessors is impossible unless prior pointers or equivalent mechanisms are available

is wrong That statement assigns the value 10 to the pointer p However, p is supposed to contain an address, not a value To correct the program, write

An example of a query requiring such a predecessor search could be in a factory where the goal is a list of ve machines adequate at a lower level of production for the task now assigned to machine B The search nds machine B according to the task chain, and a predecessor search is needed now since the machine chain is sorted in order of increasing capability

Grouping w i t h R o w Conditions Summarize the average GPA of upper-division (junior or senior) students by major

Update is greatly a ected by the existence of prior pointers Figure 4-38(a) shows a part of a ring structure ( Equipment ) which has been entered from another ring sequence ( Supplier=Earthworm ) at record Cat At this point a successor record is to be inserted In order to add the successor record Cat2 into the ring, the pointer address to record Dozer from the original record Cat is inserted into Cat2, and subsequently a pointer to Cat2 is inserted into Cat No other record accesses are required in this case If, however, a new record Grader2 is to be inserted in the preceding position (Grader2 is to be put in service before Grader) and no prior pointer exists, the update becomes costly All the records of the ring will have to be read, since record Dozer will have to be modi ed to point to the record being inserted The availability of prior pointers, shown in Fig 4-38(b), speeds this update process but adds some complexity to all update processes General use of prior pointers also a ects storage requirements and reduces locality

p = &x;

Sec 4-7

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