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We introduce PaCHash, a hash table that stores its objects contiguously in an array without intervening space, even if the objects have variable size. In particular, each object can be compressed using standard compression techniques. A small search data structure allows locating the objects in constant expected time. PaCHash is most naturally described as a static external hash table where it needs a constant number of bits of internal memory per block of external memory. Here, in some sense, PaCHash beats a lower bound on the space consumption of k-perfect hashing. An implementation for fast SSDs needs about 5 bits of internal memory per block of external memory, requires only one disk access (of variable length) per search operation, and has small internal search overhead compared to the disk access cost. Our experiments show that it has lower space consumption than all previous approaches even when considering objects of identical size.
ddc:004, FOS: Computer and information sciences, DATA processing & computer science, Computer Science - Data Structures and Algorithms, Data Structures and Algorithms (cs.DS), info:eu-repo/classification/ddc/004, 004
ddc:004, FOS: Computer and information sciences, DATA processing & computer science, Computer Science - Data Structures and Algorithms, Data Structures and Algorithms (cs.DS), info:eu-repo/classification/ddc/004, 004
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |