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Update the documentation comment

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Mark Rousskov 2020-03-27 18:13:22 -04:00
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//! This implements the core logic of the compression scheme used to compactly
//! encode Unicode properties.
//!
//! We have two primary goals with the encoding: we want to be compact, because
//! these tables often end up in ~every Rust program (especially the
//! grapheme_extend table, used for str debugging), including those for embedded
//! targets (where space is important). We also want to be relatively fast,
//! though this is more of a nice to have rather than a key design constraint.
//! It is expected that libraries/applications which are performance-sensitive
//! to Unicode property lookups are extremely rare, and those that care may find
//! the tradeoff of the raw bitsets worth it. For most applications, a
//! relatively fast but much smaller (and as such less cache-impacting, etc.)
//! data set is likely preferable.
//!
//! We have two separate encoding schemes: a skiplist-like approach, and a
//! compressed bitset. The datasets we consider mostly use the skiplist (it's
//! smaller) but the lowercase and uppercase sets are sufficiently sparse for
//! the bitset to be worthwhile -- for those sets the biset is a 2x size win.
//! Since the bitset is also faster, this seems an obvious choice. (As a
//! historical note, the bitset was also the prior implementation, so its
//! relative complexity had already been paid).
//!
//! ## The bitset
//!
//! The primary idea is that we 'flatten' the Unicode ranges into an enormous
//! bitset. To represent any arbitrary codepoint in a raw bitset, we would need
//! over 17 kilobytes of data per character set -- way too much for our
//! purposes.
//!
//! First, the raw bitset (one bit for every valid `char`, from 0 to 0x10FFFF,
//! not skipping the small 'gap') is associated into words (u64) and
//! deduplicated. On random data, this would be useless; on our data, this is
//! incredibly beneficial -- our data sets have (far) less than 256 unique
//! words.
//!
//! This gives us an array that maps `u8 -> word`; the current algorithm does
//! not handle the case of more than 256 unique words, but we are relatively far
//! from coming that close.
//!
//! With that scheme, we now have a single byte for every 64 codepoints.
//!
//! We further chunk these by some constant N (between 1 and 64 per group,
//! dynamically chosen for smallest size), and again deduplicate and store in an
//! array (u8 -> [u8; N]).
//!
//! The bytes of this array map into the words from the bitset above, but we
//! apply another trick here: some of these words are similar enough that they
//! can be represented by some function of another word. The particular
//! functions chosen are rotation, inversion, and shifting (right).
//!
//! ## The skiplist
//!
//! The skip list arose out of the desire for an even smaller encoding than the
//! bitset -- and was the answer to the question "what is the smallest
//! representation we can imagine?". However, it is not necessarily the
//! smallest, and if you have a better proposal, please do suggest it!
//!
//! This is a relatively straightforward encoding. First, we break up all the
//! ranges in the input data into offsets from each other, essentially a gap
//! encoding. In practice, most gaps are small -- less than u8::MAX -- so we
//! store those directly. We make use of the larger gaps (which are nicely
//! interspersed already) throughout the dataset to index this data set.
//!
//! In particular, each run of small gaps (terminating in a large gap) is
//! indexed in a separate dataset. That data set stores an index into the
//! primary offset list and a prefix sum of that offset list. These are packed
//! into a single u32 (11 bits for the offset, 21 bits for the prefix sum).
//!
//! Lookup proceeds via a binary search in the index and then a straightforward
//! linear scan (adding up the offsets) until we reach the needle, and then the
//! index of that offset is utilized as the answer to whether we're in the set
//! or not.
use std::collections::{BTreeMap, HashMap}; use std::collections::{BTreeMap, HashMap};
use std::ops::Range; use std::ops::Range;
use ucd_parse::Codepoints; use ucd_parse::Codepoints;

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//! This implements the core logic of the compression scheme used to compactly
//! encode the Unicode character classes.
//!
//! The primary idea is that we 'flatten' the Unicode ranges into an enormous
//! bitset. To represent any arbitrary codepoint in a raw bitset, we would need
//! over 17 kilobytes of data per character set -- way too much for our
//! purposes.
//!
//! We have two primary goals with the encoding: we want to be compact, because
//! these tables often end up in ~every Rust program (especially the
//! grapheme_extend table, used for str debugging), including those for embedded
//! targets (where space is important). We also want to be relatively fast,
//! though this is more of a nice to have rather than a key design constraint.
//! In practice, due to modern processor design these two are closely related.
//!
//! The encoding scheme here compresses the bitset by first deduplicating the
//! "words" (64 bits on all platforms). In practice very few words are present
//! in most data sets.
//!
//! This gives us an array that maps `u8 -> word` (if we ever went beyond 256
//! words, we could go to u16 -> word or have some dual compression scheme
//! mapping into two separate sets; currently this is not dealt with).
//!
//! With that scheme, we now have a single byte for every 64 codepoints. We
//! further group these by some constant N (between 1 and 64 per group), and
//! again deduplicate and store in an array (u8 -> [u8; N]). The constant is
//! chosen to be optimal in bytes-in-memory for the given dataset.
//!
//! The indices into this array represent ranges of 64*16 = 1024 codepoints.
//!
//! This already reduces the top-level array to at most 1,086 bytes, but in
//! practice we usually can encode in far fewer (the first couple Unicode planes
//! are dense).
//!
//! The last byte of this top-level array is pulled out to a separate static
//! and trailing zeros are dropped; this is simply because grapheme_extend and
//! case_ignorable have a single entry in the 896th entry, so this shrinks them
//! down considerably.
use crate::fmt_list; use crate::fmt_list;
use std::collections::{BTreeMap, BTreeSet, HashMap}; use std::collections::{BTreeMap, BTreeSet, HashMap};
use std::convert::TryFrom; use std::convert::TryFrom;