The t-digest construction algorithm uses a variant of 1-dimensional
k-means clustering to product a data structure that is related to the
Q-digest. This t-digest data structure can be used to estimate
quantiles or compute other rank statistics. The advantage of the
t-digest over the Q-digest is that the t-digest can handle floating
point values while the Q-digest is limited to integers. With small
changes, the t-digest can handle any values from any ordered set that
has something akin to a mean. The accuracy of quantile estimates
produced by t-digests can be orders of magnitude more accurate than
those produced by Q-digests in spite of the fact that t-digests are
more compact when stored on disk.
Installed Size: 71.7 kB
Architectures: all