#pragma once #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include "config.h" #if USE_VECTORSCAN # include #endif namespace ProfileEvents { extern const Event RegexpCreated; } namespace DB { namespace ErrorCodes { extern const int CANNOT_ALLOCATE_MEMORY; extern const int LOGICAL_ERROR; extern const int BAD_ARGUMENTS; } namespace Regexps { using Regexp = OptimizedRegularExpressionSingleThreaded; using RegexpPtr = std::shared_ptr; template inline Regexp createRegexp(const String & pattern) { int flags = OptimizedRegularExpression::RE_DOT_NL; if constexpr (no_capture) flags |= OptimizedRegularExpression::RE_NO_CAPTURE; if constexpr (case_insensitive) flags |= OptimizedRegularExpression::RE_CASELESS; if constexpr (like) return {likePatternToRegexp(pattern), flags}; else return {pattern, flags}; } /// Caches compiled re2 objects for given string patterns. Intended to support the common situation of a small set of patterns which are /// evaluated over and over within the same query. In these situations, usage of the cache will save unnecessary pattern re-compilation. /// However, we must be careful that caching does not add too much static overhead to overall pattern evaluation. Therefore, the cache is /// intentionally very lightweight: a) no thread-safety/mutexes, b) small & fixed capacity, c) no collision list, d) but also no open /// addressing, instead collisions simply replace the existing element. class LocalCacheTable { public: using RegexpPtr = std::shared_ptr; template RegexpPtr getOrSet(const String & pattern) { Bucket & bucket = known_regexps[hasher(pattern) % CACHE_SIZE]; if (bucket.regexp == nullptr) [[unlikely]] /// insert new entry bucket = {pattern, std::make_shared(createRegexp(pattern))}; else if (pattern != bucket.pattern) /// replace existing entry bucket = {pattern, std::make_shared(createRegexp(pattern))}; return bucket.regexp; } private: constexpr static size_t CACHE_SIZE = 100; /// collision probability std::hash hasher; struct Bucket { String pattern; /// key RegexpPtr regexp; /// value }; using CacheTable = std::array; CacheTable known_regexps; }; } #if USE_VECTORSCAN namespace MultiRegexps { template struct HyperscanDeleter { template void operator()(T * ptr) const { deleter(ptr); } }; /// Helper unique pointers to correctly delete the allocated space when hyperscan cannot compile something and we throw an exception. using CompilerErrorPtr = std::unique_ptr>; using ScratchPtr = std::unique_ptr>; using DataBasePtr = std::unique_ptr>; /// Database is immutable/thread-safe across multiple threads. Scratch is not but we can copy it whenever we use it in the searcher. class Regexps { public: Regexps(hs_database_t * db_, hs_scratch_t * scratch_) : db{db_}, scratch{scratch_} { } hs_database_t * getDB() const { return db.get(); } hs_scratch_t * getScratch() const { return scratch.get(); } private: DataBasePtr db; ScratchPtr scratch; }; class DeferredConstructedRegexps { public: explicit DeferredConstructedRegexps(std::function constructor_) : constructor(std::move(constructor_)) {} Regexps * get() { std::lock_guard lock(mutex); if (regexps) return &*regexps; regexps = constructor(); return &*regexps; } private: std::function constructor TSA_GUARDED_BY(mutex); std::optional regexps TSA_GUARDED_BY(mutex); std::mutex mutex; }; using DeferredConstructedRegexpsPtr = std::shared_ptr; template inline Regexps constructRegexps(const std::vector & str_patterns, [[maybe_unused]] std::optional edit_distance) { /// Common pointers std::vector patterns; std::vector flags; /// Pointer for external edit distance compilation std::vector ext_exprs; std::vector ext_exprs_ptrs; patterns.reserve(str_patterns.size()); flags.reserve(str_patterns.size()); if constexpr (with_edit_distance) { ext_exprs.reserve(str_patterns.size()); ext_exprs_ptrs.reserve(str_patterns.size()); } for (std::string_view ref : str_patterns) { patterns.push_back(ref.data()); /* Flags below are the pattern matching flags. * HS_FLAG_DOTALL is a compile flag where matching a . will not exclude newlines. This is a good * performance practice according to Hyperscan API. https://intel.github.io/hyperscan/dev-reference/performance.html#dot-all-mode * HS_FLAG_ALLOWEMPTY is a compile flag where empty strings are allowed to match. * HS_FLAG_UTF8 is a flag where UTF8 literals are matched. * HS_FLAG_SINGLEMATCH is a compile flag where each pattern match will be returned only once. it is a good performance practice * as it is said in the Hyperscan documentation. https://intel.github.io/hyperscan/dev-reference/performance.html#single-match-flag */ flags.push_back(HS_FLAG_DOTALL | HS_FLAG_SINGLEMATCH | HS_FLAG_ALLOWEMPTY | HS_FLAG_UTF8); if constexpr (with_edit_distance) { /// Hyperscan currently does not support UTF8 matching with edit distance. flags.back() &= ~HS_FLAG_UTF8; ext_exprs.emplace_back(); /// HS_EXT_FLAG_EDIT_DISTANCE is a compile flag responsible for Levenstein distance. ext_exprs.back().flags = HS_EXT_FLAG_EDIT_DISTANCE; ext_exprs.back().edit_distance = edit_distance.value(); ext_exprs_ptrs.push_back(&ext_exprs.back()); } } hs_database_t * db = nullptr; hs_compile_error_t * compile_error; std::unique_ptr ids; /// We mark the patterns to provide the callback results. if constexpr (save_indices) { ids.reset(new unsigned int[patterns.size()]); for (size_t i = 0; i < patterns.size(); ++i) ids[i] = static_cast(i + 1); } hs_error_t err; if constexpr (!with_edit_distance) err = hs_compile_multi( patterns.data(), flags.data(), ids.get(), static_cast(patterns.size()), HS_MODE_BLOCK, nullptr, &db, &compile_error); else err = hs_compile_ext_multi( patterns.data(), flags.data(), ids.get(), ext_exprs_ptrs.data(), static_cast(patterns.size()), HS_MODE_BLOCK, nullptr, &db, &compile_error); if (err != HS_SUCCESS) { /// CompilerError is a unique_ptr, so correct memory free after the exception is thrown. CompilerErrorPtr error(compile_error); if (error->expression < 0) throw Exception::createRuntime(ErrorCodes::LOGICAL_ERROR, String(error->message)); else throw Exception(ErrorCodes::BAD_ARGUMENTS, "Pattern '{}' failed with error '{}'", str_patterns[error->expression], String(error->message)); } ProfileEvents::increment(ProfileEvents::RegexpCreated); /// We allocate the scratch space only once, then copy it across multiple threads with hs_clone_scratch /// function which is faster than allocating scratch space each time in each thread. hs_scratch_t * scratch = nullptr; err = hs_alloc_scratch(db, &scratch); /// If not HS_SUCCESS, it is guaranteed that the memory would not be allocated for scratch. if (err != HS_SUCCESS) throw Exception(ErrorCodes::CANNOT_ALLOCATE_MEMORY, "Could not allocate scratch space for vectorscan"); return {db, scratch}; } /// Maps string pattern vectors + edit distance to compiled vectorscan regexps. Uses the same eviction mechanism as the LocalCacheTable for /// re2 patterns. Because vectorscan regexes are overall more heavy-weight (more expensive compilation, regexes can grow up to multiple /// MBs, usage of scratch space), 1. GlobalCacheTable is a global singleton and, as a result, needs locking 2. the pattern compilation is /// done outside GlobalCacheTable's lock, at the cost of another level of locking. struct GlobalCacheTable { constexpr static size_t CACHE_SIZE = 500; /// collision probability struct Bucket { std::vector patterns; /// key std::optional edit_distance; /// key /// The compiled patterns and their state (vectorscan 'database' + scratch space) are wrapped in a shared_ptr. Refcounting guarantees /// that eviction of a pattern does not affect parallel threads still using the pattern. DeferredConstructedRegexpsPtr regexps; /// value }; std::array known_regexps TSA_GUARDED_BY(mutex); std::mutex mutex; static size_t getBucketIndexFor(const std::vector patterns, std::optional edit_distance) { size_t hash = 0; for (const auto & pattern : patterns) boost::hash_combine(hash, pattern); boost::hash_combine(hash, edit_distance); return hash % CACHE_SIZE; } }; /// If with_edit_distance is False, edit_distance must be nullopt. Also, we use templates here because each instantiation of function template /// has its own copy of local static variables which must not be the same for different hyperscan compilations. template inline DeferredConstructedRegexpsPtr getOrSet(const std::vector & patterns, std::optional edit_distance) { static GlobalCacheTable pool; /// Different variables for different pattern parameters, thread-safe in C++11 std::vector str_patterns; str_patterns.reserve(patterns.size()); for (const auto & pattern : patterns) str_patterns.emplace_back(String(pattern)); size_t bucket_idx = GlobalCacheTable::getBucketIndexFor(str_patterns, edit_distance); /// Lock cache to find compiled regexp for given pattern vector + edit distance. std::lock_guard lock(pool.mutex); GlobalCacheTable::Bucket & bucket = pool.known_regexps[bucket_idx]; /// Pattern compilation is expensive and we don't want to block other threads reading from / inserting into the cache while we hold the /// cache lock during pattern compilation. Therefore, when a cache entry is created or replaced, only set the regexp constructor method /// and compile outside the cache lock. /// Note that the string patterns and the edit distance is passed into the constructor lambda by value, i.e. copied - it is not an /// option to reference the corresponding string patterns / edit distance key in the cache table bucket because the cache entry may /// already be evicted at the time the compilation starts. if (bucket.regexps == nullptr) [[unlikely]] { /// insert new entry auto deferred_constructed_regexps = std::make_shared( [str_patterns, edit_distance]() { return constructRegexps(str_patterns, edit_distance); }); bucket = {std::move(str_patterns), edit_distance, deferred_constructed_regexps}; } else if (bucket.patterns != str_patterns || bucket.edit_distance != edit_distance) { /// replace existing entry auto deferred_constructed_regexps = std::make_shared( [str_patterns, edit_distance]() { return constructRegexps(str_patterns, edit_distance); }); bucket = {std::move(str_patterns), edit_distance, deferred_constructed_regexps}; } return bucket.regexps; } } #endif // USE_VECTORSCAN }