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キーワード:
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要旨:
Time-travel queries that couple temporal constraints with keyword
queries are useful in searching large-scale archives of time-evolving
content such as the Web, document collections, wikis, and so
on. Typical approaches for efficient evaluation of these queries
involve \emph{slicing} along the time-axis either the entire
collection~\cite{253349}, or individual index
lists~\cite{kberberi:sigir2007}. Both these methods are not
satisfactory since they sacrifice compactness of index for processing
efficiency making them either too big or, otherwise, too slow.
We present a novel index organization scheme that \emph{shards} the
index with \emph{zero increase in index size}, still minimizing the
cost of reading index index entries during query processing. Based on
the optimal sharding thus obtained, we develop practically efficient
sharding that takes into account the different costs of random and
sequential accesses. Our algorithm merges shards from the optimal
solution carefully to allow for few extra sequential accesses while
gaining significantly by reducing the random accesses. Finally, we
empirically establish the effectiveness of our novel sharding scheme
via detailed experiments over the edit history of the English version
of Wikipedia between 2001-2005 ($\approx$ 700 GB) and an archive of
the UK governmental web sites ($\approx$ 400 GB). Our results
demonstrate the feasibility of faster time-travel query processing
with no space overhead.
