By Edward Hill, Jr.
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Extra info for A Comparative Study of Very Large Databases
Address algorithm. K. i - - R E A D ( i ). Let address i--h(K), DO the INFO[i] track. ] GET (P)" 1. probing) function set the . h(K) that been the internal read the directory. by used rv+l in [inear the rotation L which 2 .... bucket. Assume has that into I. The on P. first variables and of for records with the track containing key of that Assume = containing address addresses the track of i transformation address a k hashing node )n-k) and addresses. a writing containing the bucket of °.. ~ j=o A key-to--address the is number 1) in time address average size, A'" time calculated is - retrievat ~EAD(P) to iS WRITE(P) to device the of first that Location i a mean F co,taiaing last addresses.
Several ~ DO R O V E R ' - R L I N K [ G S ] , R~ROVER+b, GS~R, m constant we have. assigning stored factor by is chaining to any with of 28 P[X = In the storage device address h(K) nodes List the tend to be to the total total required to List List the of k tota• t k where The mean per k ) LiSt. be address the a the bucket, are aLLowed Length due to short. Items due to to k exactly, list must that the coalescing is number or occupied The be of smaLL to probes . of probes required to address aLL ÷ _l(k 2 - b)(k - b ÷ I ) items item addressed in a '~ i _ k _ - - ~ 2 value of of probes This the number per list of probes divided by per the mean numbem yields N ) = ~ tkP(k) .
B-trees in which binary was introduced by average performance Uzga[is  search in a introduced tree. search of They the atgorittrms approximated binary tree. Again, it is B~-trees. to the atiocate mean number 52 A Binary track Search aLLocation Trees. and measures are caLcuLated fLexibLe and efficient. is device TRIE introduced sequentiaLLy. each for is One store Average structure. parameter to The performance method controls T~EE~ the presented efficiency is which dependent. Knuth from scheme any tree algorithm [ 35] has shown binary tree.