code 39 barcode font excel Accessing data blocks in Software

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The pointers we obtain from processing of index entries can be e ectively used to reduce the number of block accesses to the data le By putting the pointers in order by block number we can assure that each block will be accessed only once; if possible, we will fetch multiple goal records out of one block This technique becomes especially important when processing multiattribute queries, as will be shown in Sec 4-2-5 We need to know the number of block fetches bG required to retrieve nG goal records in TID order from a large le of nf ile records with Bfr records per block The le uses hence bf ile = nf ile /Bfr blocks We will rst consider the extreme nf ile ) the value of bG = nG since one block fetch cases For small results (nG will fetch one result record For large numbers of nG the value of bG bf ile , if the retrieval is carried out in TID order, since nearly every block will be accessed once; at nG > nf ile Bfr this is absolutely true In the important intermediate region, where many but much less than all records are selected from the goal le, some blocks will yield multiple records and others will not be needed at all An estimate of the number of block fetches required to retrieve nG records in TID order from a le of n records with Bfr records per block, for the cases nG nf ile Bfr, is computable as [Whang81 ] n Bfr 1 1 bG = Bfr n + 15 n3 Bfr G
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This formula is a good approximation in the range of values seen in databases of the computationally di cult function required to produce an exact result [Yao77 ] To a retrieval time computed on the basis of this technique the computation time c, required for sorting of the TIDs in core prior to le access, has to be added
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For the indexed-sequential le, examined in Sec 3-4, serial access according to a single attribute was established through the location of the data records themselves and through a linkage for any over ow records Files with multiple indexes establish multiple serial access paths within the indexes themselves The optional extra linkage between blocks at the same level, presented above, increases update costs when new blocks are allocated but simpli es serial access Serial access remains indirect, and data records are fetched according to the pointers found in index entries The alternative, multiple direct linkages of data records themselves, is used in the design of the multiring le Since indexes are small, it is easier to achieve a high degree of locality for indexes than for data records If few records are to be obtained per serial retrieval, multiple indexes with linkages will perform better than multiring structures For retrieval of subsets the indirection of access makes use of an index costlier than following a ring 4-2-4 The Interaction of Block Size and Index Processing Up to this point we have used the block size as a given parameter in the design of indexes In many cases this is a valid assumption, but it is instructive to see how changes in block size a ect the performance of an index The size of an index entry will be denoted below as Rix, and the number of index entries by nix The positive e ect of large block sizes is a high fanout ratio (y = B/Rix, from Eq 326), which reduces the number of levels required The number of levels x is again determined by x = logy nix (Eq 3-27) The detrimental e ects of large block sizes are the increased block transfer time btt = B/t, the increased computational e ort c to locate the appropriate index entry in a block, and the cost of core-storage occupancy The computation is a function of the number of records which have to be searched in core nix, the method used, and the time for a single comparison c1 Figure 4-11 shows the combined e ect of these factors (except for core-storage) for a fairly large index The fetch time within the index is computed as TF ix = logy n (cix c1 + s + r + y Rix ) t 4-7 linear search binary search (Eq 4-5) jump search (Eq 4-4)
where cix = 1 y 2 and cix = log2 y Fig 4-11 does not show cix = y which is in between, but close to the binary search
The optimum length for index blocks in the case shown, a 2314-type disk, is 4000 bytes The steps in the function are an e ect of the discrete assignment of index levels The lower, continuous curve represents use of optimal index processing; approaches were described in Sec 4-2-2 The time needed to inspect one index entry c1 is taken to be 40 microseconds( s) Abbreviated entries will take longer to process and will raise the left side of the curve, especially if linear searches are made through the index blocks, but their use will also decrease the size of an average index entry, so that the same fanout will correspond to a smaller block size Devices with a shorter seek time will favor shorter block sizes, while devices with a higher transfer rate will cause minimal values of the fetch time to occur with larger blocks
Sec 4-2
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