| /*! |
| Provides an architecture independent implementation of the "packed pair" |
| algorithm. |
| |
| The "packed pair" algorithm is based on the [generic SIMD] algorithm. The main |
| difference is that it (by default) uses a background distribution of byte |
| frequencies to heuristically select the pair of bytes to search for. Note that |
| this module provides an architecture independent version that doesn't do as |
| good of a job keeping the search for candidates inside a SIMD hot path. It |
| however can be good enough in many circumstances. |
| |
| [generic SIMD]: http://0x80.pl/articles/simd-strfind.html#first-and-last |
| */ |
| |
| use crate::memchr; |
| |
| mod default_rank; |
| |
| /// An architecture independent "packed pair" finder. |
| /// |
| /// This finder picks two bytes that it believes have high predictive power for |
| /// indicating an overall match of a needle. At search time, it reports offsets |
| /// where the needle could match based on whether the pair of bytes it chose |
| /// match. |
| /// |
| /// This is architecture independent because it utilizes `memchr` to find the |
| /// occurrence of one of the bytes in the pair, and then checks whether the |
| /// second byte matches. If it does, in the case of [`Finder::find_prefilter`], |
| /// the location at which the needle could match is returned. |
| /// |
| /// It is generally preferred to use architecture specific routines for a |
| /// "packed pair" prefilter, but this can be a useful fallback when the |
| /// architecture independent routines are unavailable. |
| #[derive(Clone, Copy, Debug)] |
| pub struct Finder { |
| pair: Pair, |
| byte1: u8, |
| byte2: u8, |
| } |
| |
| impl Finder { |
| /// Create a new prefilter that reports possible locations where the given |
| /// needle matches. |
| #[inline] |
| pub fn new(needle: &[u8]) -> Option<Finder> { |
| Finder::with_pair(needle, Pair::new(needle)?) |
| } |
| |
| /// Create a new prefilter using the pair given. |
| /// |
| /// If the prefilter could not be constructed, then `None` is returned. |
| /// |
| /// This constructor permits callers to control precisely which pair of |
| /// bytes is used as a predicate. |
| #[inline] |
| pub fn with_pair(needle: &[u8], pair: Pair) -> Option<Finder> { |
| let byte1 = needle[usize::from(pair.index1())]; |
| let byte2 = needle[usize::from(pair.index2())]; |
| // Currently this can never fail so we could just return a Finder, |
| // but it's conceivable this could change. |
| Some(Finder { pair, byte1, byte2 }) |
| } |
| |
| /// Run this finder on the given haystack as a prefilter. |
| /// |
| /// If a candidate match is found, then an offset where the needle *could* |
| /// begin in the haystack is returned. |
| #[inline] |
| pub fn find_prefilter(&self, haystack: &[u8]) -> Option<usize> { |
| let mut i = 0; |
| let index1 = usize::from(self.pair.index1()); |
| let index2 = usize::from(self.pair.index2()); |
| loop { |
| // Use a fast vectorized implementation to skip to the next |
| // occurrence of the rarest byte (heuristically chosen) in the |
| // needle. |
| i += memchr(self.byte1, &haystack[i..])?; |
| let found = i; |
| i += 1; |
| |
| // If we can't align our first byte match with the haystack, then a |
| // match is impossible. |
| let aligned1 = match found.checked_sub(index1) { |
| None => continue, |
| Some(aligned1) => aligned1, |
| }; |
| |
| // Now align the second byte match with the haystack. A mismatch |
| // means that a match is impossible. |
| let aligned2 = match aligned1.checked_add(index2) { |
| None => continue, |
| Some(aligned_index2) => aligned_index2, |
| }; |
| if haystack.get(aligned2).map_or(true, |&b| b != self.byte2) { |
| continue; |
| } |
| |
| // We've done what we can. There might be a match here. |
| return Some(aligned1); |
| } |
| } |
| |
| /// Returns the pair of offsets (into the needle) used to check as a |
| /// predicate before confirming whether a needle exists at a particular |
| /// position. |
| #[inline] |
| pub fn pair(&self) -> &Pair { |
| &self.pair |
| } |
| } |
| |
| /// A pair of byte offsets into a needle to use as a predicate. |
| /// |
| /// This pair is used as a predicate to quickly filter out positions in a |
| /// haystack in which a needle cannot match. In some cases, this pair can even |
| /// be used in vector algorithms such that the vector algorithm only switches |
| /// over to scalar code once this pair has been found. |
| /// |
| /// A pair of offsets can be used in both substring search implementations and |
| /// in prefilters. The former will report matches of a needle in a haystack |
| /// where as the latter will only report possible matches of a needle. |
| /// |
| /// The offsets are limited each to a maximum of 255 to keep memory usage low. |
| /// Moreover, it's rarely advantageous to create a predicate using offsets |
| /// greater than 255 anyway. |
| /// |
| /// The only guarantee enforced on the pair of offsets is that they are not |
| /// equivalent. It is not necessarily the case that `index1 < index2` for |
| /// example. By convention, `index1` corresponds to the byte in the needle |
| /// that is believed to be most the predictive. Note also that because of the |
| /// requirement that the indices be both valid for the needle used to build |
| /// the pair and not equal, it follows that a pair can only be constructed for |
| /// needles with length at least 2. |
| #[derive(Clone, Copy, Debug)] |
| pub struct Pair { |
| index1: u8, |
| index2: u8, |
| } |
| |
| impl Pair { |
| /// Create a new pair of offsets from the given needle. |
| /// |
| /// If a pair could not be created (for example, if the needle is too |
| /// short), then `None` is returned. |
| /// |
| /// This chooses the pair in the needle that is believed to be as |
| /// predictive of an overall match of the needle as possible. |
| #[inline] |
| pub fn new(needle: &[u8]) -> Option<Pair> { |
| Pair::with_ranker(needle, DefaultFrequencyRank) |
| } |
| |
| /// Create a new pair of offsets from the given needle and ranker. |
| /// |
| /// This permits the caller to choose a background frequency distribution |
| /// with which bytes are selected. The idea is to select a pair of bytes |
| /// that is believed to strongly predict a match in the haystack. This |
| /// usually means selecting bytes that occur rarely in a haystack. |
| /// |
| /// If a pair could not be created (for example, if the needle is too |
| /// short), then `None` is returned. |
| #[inline] |
| pub fn with_ranker<R: HeuristicFrequencyRank>( |
| needle: &[u8], |
| ranker: R, |
| ) -> Option<Pair> { |
| if needle.len() <= 1 { |
| return None; |
| } |
| // Find the rarest two bytes. We make them distinct indices by |
| // construction. (The actual byte value may be the same in degenerate |
| // cases, but that's OK.) |
| let (mut rare1, mut index1) = (needle[0], 0); |
| let (mut rare2, mut index2) = (needle[1], 1); |
| if ranker.rank(rare2) < ranker.rank(rare1) { |
| core::mem::swap(&mut rare1, &mut rare2); |
| core::mem::swap(&mut index1, &mut index2); |
| } |
| let max = usize::from(core::u8::MAX); |
| for (i, &b) in needle.iter().enumerate().take(max).skip(2) { |
| if ranker.rank(b) < ranker.rank(rare1) { |
| rare2 = rare1; |
| index2 = index1; |
| rare1 = b; |
| index1 = u8::try_from(i).unwrap(); |
| } else if b != rare1 && ranker.rank(b) < ranker.rank(rare2) { |
| rare2 = b; |
| index2 = u8::try_from(i).unwrap(); |
| } |
| } |
| // While not strictly required for how a Pair is normally used, we |
| // really don't want these to be equivalent. If they were, it would |
| // reduce the effectiveness of candidate searching using these rare |
| // bytes by increasing the rate of false positives. |
| assert_ne!(index1, index2); |
| Some(Pair { index1, index2 }) |
| } |
| |
| /// Create a new pair using the offsets given for the needle given. |
| /// |
| /// This bypasses any sort of heuristic process for choosing the offsets |
| /// and permits the caller to choose the offsets themselves. |
| /// |
| /// Indices are limited to valid `u8` values so that a `Pair` uses less |
| /// memory. It is not possible to create a `Pair` with offsets bigger than |
| /// `u8::MAX`. It's likely that such a thing is not needed, but if it is, |
| /// it's suggested to build your own bespoke algorithm because you're |
| /// likely working on a very niche case. (File an issue if this suggestion |
| /// does not make sense to you.) |
| /// |
| /// If a pair could not be created (for example, if the needle is too |
| /// short), then `None` is returned. |
| #[inline] |
| pub fn with_indices( |
| needle: &[u8], |
| index1: u8, |
| index2: u8, |
| ) -> Option<Pair> { |
| // While not strictly required for how a Pair is normally used, we |
| // really don't want these to be equivalent. If they were, it would |
| // reduce the effectiveness of candidate searching using these rare |
| // bytes by increasing the rate of false positives. |
| if index1 == index2 { |
| return None; |
| } |
| // Similarly, invalid indices means the Pair is invalid too. |
| if usize::from(index1) >= needle.len() { |
| return None; |
| } |
| if usize::from(index2) >= needle.len() { |
| return None; |
| } |
| Some(Pair { index1, index2 }) |
| } |
| |
| /// Returns the first offset of the pair. |
| #[inline] |
| pub fn index1(&self) -> u8 { |
| self.index1 |
| } |
| |
| /// Returns the second offset of the pair. |
| #[inline] |
| pub fn index2(&self) -> u8 { |
| self.index2 |
| } |
| } |
| |
| /// This trait allows the user to customize the heuristic used to determine the |
| /// relative frequency of a given byte in the dataset being searched. |
| /// |
| /// The use of this trait can have a dramatic impact on performance depending |
| /// on the type of data being searched. The details of why are explained in the |
| /// docs of [`crate::memmem::Prefilter`]. To summarize, the core algorithm uses |
| /// a prefilter to quickly identify candidate matches that are later verified |
| /// more slowly. This prefilter is implemented in terms of trying to find |
| /// `rare` bytes at specific offsets that will occur less frequently in the |
| /// dataset. While the concept of a `rare` byte is similar for most datasets, |
| /// there are some specific datasets (like binary executables) that have |
| /// dramatically different byte distributions. For these datasets customizing |
| /// the byte frequency heuristic can have a massive impact on performance, and |
| /// might even need to be done at runtime. |
| /// |
| /// The default implementation of `HeuristicFrequencyRank` reads from the |
| /// static frequency table defined in `src/memmem/byte_frequencies.rs`. This |
| /// is optimal for most inputs, so if you are unsure of the impact of using a |
| /// custom `HeuristicFrequencyRank` you should probably just use the default. |
| /// |
| /// # Example |
| /// |
| /// ``` |
| /// use memchr::{ |
| /// arch::all::packedpair::HeuristicFrequencyRank, |
| /// memmem::FinderBuilder, |
| /// }; |
| /// |
| /// /// A byte-frequency table that is good for scanning binary executables. |
| /// struct Binary; |
| /// |
| /// impl HeuristicFrequencyRank for Binary { |
| /// fn rank(&self, byte: u8) -> u8 { |
| /// const TABLE: [u8; 256] = [ |
| /// 255, 128, 61, 43, 50, 41, 27, 28, 57, 15, 21, 13, 24, 17, 17, |
| /// 89, 58, 16, 11, 7, 14, 23, 7, 6, 24, 9, 6, 5, 9, 4, 7, 16, |
| /// 68, 11, 9, 6, 88, 7, 4, 4, 23, 9, 4, 8, 8, 5, 10, 4, 30, 11, |
| /// 9, 24, 11, 5, 5, 5, 19, 11, 6, 17, 9, 9, 6, 8, |
| /// 48, 58, 11, 14, 53, 40, 9, 9, 254, 35, 3, 6, 52, 23, 6, 6, 27, |
| /// 4, 7, 11, 14, 13, 10, 11, 11, 5, 2, 10, 16, 12, 6, 19, |
| /// 19, 20, 5, 14, 16, 31, 19, 7, 14, 20, 4, 4, 19, 8, 18, 20, 24, |
| /// 1, 25, 19, 58, 29, 10, 5, 15, 20, 2, 2, 9, 4, 3, 5, |
| /// 51, 11, 4, 53, 23, 39, 6, 4, 13, 81, 4, 186, 5, 67, 3, 2, 15, |
| /// 0, 0, 1, 3, 2, 0, 0, 5, 0, 0, 0, 2, 0, 0, 0, |
| /// 12, 2, 1, 1, 3, 1, 1, 1, 6, 1, 2, 1, 3, 1, 1, 2, 9, 1, 1, 0, |
| /// 2, 2, 4, 4, 11, 6, 7, 3, 6, 9, 4, 5, |
| /// 46, 18, 8, 18, 17, 3, 8, 20, 16, 10, 3, 7, 175, 4, 6, 7, 13, |
| /// 3, 7, 3, 3, 1, 3, 3, 10, 3, 1, 5, 2, 0, 1, 2, |
| /// 16, 3, 5, 1, 6, 1, 1, 2, 58, 20, 3, 14, 12, 2, 1, 3, 16, 3, 5, |
| /// 8, 3, 1, 8, 6, 17, 6, 5, 3, 8, 6, 13, 175, |
| /// ]; |
| /// TABLE[byte as usize] |
| /// } |
| /// } |
| /// // Create a new finder with the custom heuristic. |
| /// let finder = FinderBuilder::new() |
| /// .build_forward_with_ranker(Binary, b"\x00\x00\xdd\xdd"); |
| /// // Find needle with custom heuristic. |
| /// assert!(finder.find(b"\x00\x00\x00\xdd\xdd").is_some()); |
| /// ``` |
| pub trait HeuristicFrequencyRank { |
| /// Return the heuristic frequency rank of the given byte. A lower rank |
| /// means the byte is believed to occur less frequently in the haystack. |
| /// |
| /// Some uses of this heuristic may treat arbitrary absolute rank values as |
| /// significant. For example, an implementation detail in this crate may |
| /// determine that heuristic prefilters are inappropriate if every byte in |
| /// the needle has a "high" rank. |
| fn rank(&self, byte: u8) -> u8; |
| } |
| |
| /// The default byte frequency heuristic that is good for most haystacks. |
| pub(crate) struct DefaultFrequencyRank; |
| |
| impl HeuristicFrequencyRank for DefaultFrequencyRank { |
| fn rank(&self, byte: u8) -> u8 { |
| self::default_rank::RANK[usize::from(byte)] |
| } |
| } |
| |
| /// This permits passing any implementation of `HeuristicFrequencyRank` as a |
| /// borrowed version of itself. |
| impl<'a, R> HeuristicFrequencyRank for &'a R |
| where |
| R: HeuristicFrequencyRank, |
| { |
| fn rank(&self, byte: u8) -> u8 { |
| (**self).rank(byte) |
| } |
| } |
| |
| #[cfg(test)] |
| mod tests { |
| use super::*; |
| |
| #[test] |
| fn forward_packedpair() { |
| fn find( |
| haystack: &[u8], |
| needle: &[u8], |
| _index1: u8, |
| _index2: u8, |
| ) -> Option<Option<usize>> { |
| // We ignore the index positions requested since it winds up making |
| // this test too slow overall. |
| let f = Finder::new(needle)?; |
| Some(f.find_prefilter(haystack)) |
| } |
| crate::tests::packedpair::Runner::new().fwd(find).run() |
| } |
| } |