14.20 Suppose there is a relation r(A, B, C), with a B+-tree index with search key (A, B). 14.21 a. b. What is the worst-case cost of finding records satisfying 10 < A < 50 using this index, in terms of the number of records retrieved n, and the heighth of the tree? C. What is the worst-case cost of finding records satisfying 10

Database System Concepts
7th Edition
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Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
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14.20 Suppose there is a relation r(A, B, C), with a B+-tree index with search key
(A, B).
a.
b.
C.
What is the worst-case cost of finding records satisfying 10 <A < 50
using this index, in terms of the number of records retrieved n, and the
heighth of the tree?
What is the worst-case cost of finding records satisfying 10 <A < 50 A
5 < B < 10 using this index, in terms of the number of records n, that
satisfy this selection, as well as n₁ and h defined above?
Under what conditions on n, and no would the index be an efficient way
of finding records satisfying 10 <A <50 A5 < B < 10?
14.21 Suppose you have to create a B+-tree index on a large number of names, where
the maximum size of a name may be quite large (say 40 characters) and the av-
erage name is itself large (say 10 characters). Explain how prefix compression
can be used to maximize the average fanout of nonleaf nodes.
Transcribed Image Text:14.20 Suppose there is a relation r(A, B, C), with a B+-tree index with search key (A, B). a. b. C. What is the worst-case cost of finding records satisfying 10 <A < 50 using this index, in terms of the number of records retrieved n, and the heighth of the tree? What is the worst-case cost of finding records satisfying 10 <A < 50 A 5 < B < 10 using this index, in terms of the number of records n, that satisfy this selection, as well as n₁ and h defined above? Under what conditions on n, and no would the index be an efficient way of finding records satisfying 10 <A <50 A5 < B < 10? 14.21 Suppose you have to create a B+-tree index on a large number of names, where the maximum size of a name may be quite large (say 40 characters) and the av- erage name is itself large (say 10 characters). Explain how prefix compression can be used to maximize the average fanout of nonleaf nodes.
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