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and change the ring pointers The awkwardness of update may make the batch reorganization technique presented in Sec 3-5, Eq 3-89 appropriate here 4-6-4 Partial-Match Retrieval with Direct Access In basic direct les, access capability is restricted to one attribute If intermediate pointer-lists are used, as described in Sec 4-6-2, then access becomes possible by any of a variety of attributes These pointer-lists can become the source for partialmatch query processing The buckets that are created in the pointer-lists will contain TIDs for speci c attribute-name and value combinations If collision chains are maintained all identical entries will be on one chain; some irrelevant ones may be chained in as well and have to be removed based on their key value The sets of TIDs obtained can be merged for partial-match retrieval, so that selection can be accomplished prior to accessing the goal le The procedure can be visualized using Fig 4-35 and compared with Fig 4-12, where indexes were used We note that ranges of values are not supported unless the complications of additional serial access structures (Sec 4-6-3) are accepted The attribute values are hence made discrete; the Price, for instance, is given here as two distinct truncated values {31 000, 32 000} rather than as {31 000 33 000} in the indexed case of Sec 4-2-5 The information loss from truncation increases the number of collisions The accessing and merging of many buckets can still be costly An obvious approach to rapid direct partial-match access is to develop hash functions and pointer-lists which permit immediate retrieval of records in response to queries which specify multiple attributes in their search argument Any or all combinations of more than one attribute, as were considered for indexes in Sec 42-5, may be de ned and added to the a pointer-lists for the single attributes.

1 Lars Maaseidvaag has been working at the George Group for more than six years focusing on lean process improvement and process simplification His focus areas include: complexity value stream mapping and complexity analysis, queuing theory, discrete event simulation, and mathematical programming Mr Maaseidvaag has earned several advanced degrees including an MBA and MSE in Operations Research from the University of Texas He is also currently pursuing a PhD in Operations Research at The Illinois Institute of Technology 2 Excel is a registered trademark of Microsoft 3 The Complexity Equation is protected by US Patents 5,195,041 and 5,351,195 and patents pending Interested parties may inquire about obtaining the equation in spreadsheet format from wwwgeorgegroupcom 4 In practice, we have had to bring several different analysis tools to bear on the problem of quantifying the PCE destruction within a process The Complexity Equation itself requires no special solvers or software and can be relatively easily modeled in an Excel spreadsheet At times, specific sub-problems have been addressed using a combination of mixed-integer-programming, linear program, and discrete event simulation

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To delete all markers:

Sec 4-6

Providing for all possible (2a 1) or even many partial-match attribute combinations increases the number and hence the redundancy in the access lists greatly The reduction in number of indexes made possible by the sorted ordering within indexes does not apply here When multiattribute hashing techniques are being considered, the design decision has to balance redundancy in the les, leading to high update and storage costs versus the e ort saved at retrieval time This choice is actually equivalent to the familiar problem of binding-time selection, and we will abstract the alternatives using the binding paradigm If fast access is paramount, all possible partial-match attribute combinations for each record can be hashed At each hash address a set of pointers or TIDs will direct the fetch immediately to the goal records All these TIDs must be set when a record is inserted If an average record has a attributes of interest for retrieval, there will be 2a 1 entries per record The entries for the four houses retrieved for the query in example of Fig 4-35 are shown in Fig 4-36 These four houses have 4(2a 1) = 60 TIDs distributed over the 2a + 2a 1 1 = 23 buckets for the a = 4 attributes and the fth value for the extra price

Control-click in the Track Editor Marker Area, then select Delete All Markers from the pop-up (see Fig 8-3c)

Early Binding Entries for all records needed in response to a query will be found in the bucket; all records with identical key combinations cluster in the bucket The bucket may contain further entries because of collisions from the randomization Since the clustering of popular and few-attribute combinations leads to dense usage of some bucket addresses, a chained over ow to external buckets rather than open addressing is called for Combinations which do not correspond to records in the le will not generate entries in the pointer-lists; there may be, for instance, no Condominiums in WuthHeights

(Complexity Analysis Phase 3)

To Import Embedded Markers from a Clip if they don t appear:

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

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