10000000000000000000011100000000000000000000000??¦??¦??¦??¦??¦??¦.0000000000000001111111111111111111111111
a) Input bitmap with 5456 bits
01000
Bit 0 indicates ???tail??? word
100??¦010101110 001??¦11
b) Group bits into 176 31-bit groups
d) E ncode each group us ing one word
31 bits 174*31 bits 31 bits
31 bits 31 bits ??¦ 31 bits
c) Merge neighboring groups with identical bits
31 literal bits
run length is 174
Run 1 Run 2
Bit 0 indicates ???tail??? word
31 literal bits Fill bit 0
68 Stockinger & Wu
Copyright ?© 2007, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of
Idea Group Inc. is prohibited.
In theoretical analysis, the query response time on one-dimensional range queries
using WAH compressed indices was shown to grow linearly in the number of hits.
This time complexity is optimal for any searching algorithm since one has to return
at least the hits, which takes ?©(h) time (where h is the number of hits). A variety of
well-known indexing methods such as B+-trees and B*-trees have the same optimal
scaling property. However, compressed bitmap indices have the unique advantage
that they can be easily combined to answer multidimensional ad hoc range queries,
while B+-trees or B*-trees cannot be combined nearly as efficiently.
In general, the query response time can be broken into I/O time and CPU time.
Pages:
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332