Database Reference
In-Depth Information
which intersections are recorded at the smallest scale square possible that still gives enough
samples in the time series segment to be efficient. If a time series involves slow motion, a
very fine grid will be used. If the time series involves faster motion, a coarser grid will be
used. A time series that moves quickly sometimes and more slowly at other times will have a
mix of fine and coarse squares. In a database using a blobbed storage format, a good rule of
thumb is to record intersections at whichever size square roughly corresponds a single blob
of data.
Space-Filling Curves
As a small optimization, you can label the squares in the spatial index according to a pattern
known as a Hilbert curve, as shown in
Figure 7-3
. This labeling is recursively defined so that
finer squares share the prefix of their label with overlapping coarser squares. Another nice
property of Hilbert labeling is that roughly round or square regions will overlap squares with
large runs of sequential labels. This can mean that a database such as Apache HBase that or-
ders items according to their key may need to do fewer disk seeks when finding the content
associated with these squares.
