#pragma once

#include <map>
#include <memory>
#include <mutex>
#include <optional>
#include <string>
#include <utility>
#include <vector>
#include <Functions/likePatternToRegexp.h>
#include <Common/Exception.h>
#include <Common/OptimizedRegularExpression.h>
#include <Common/ProfileEvents.h>
#include <Common/config.h>
#include <base/StringRef.h>

#include "config_functions.h"

#if USE_VECTORSCAN
#    include <hs.h>
#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<Regexp>;

template <bool like, bool no_capture, bool case_insensitive>
inline Regexp createRegexp(const std::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<Regexp>;

    template <bool like, bool no_capture, bool case_insensitive>
    void getOrSet(const String & pattern, RegexpPtr & regexp)
    {
        StringAndRegexp & bucket = known_regexps[hasher(pattern) % max_regexp_cache_size];

        if (likely(bucket.regexp != nullptr))
        {
            if (pattern == bucket.pattern)
                regexp = bucket.regexp;
            else
            {
                regexp = std::make_shared<Regexp>(createRegexp<like, no_capture, case_insensitive>(pattern));
                bucket = {pattern, regexp};
            }
        }
        else
        {
            regexp = std::make_shared<Regexp>(createRegexp<like, no_capture, case_insensitive>(pattern));
            bucket = {pattern, regexp};
        }
    }

private:
    constexpr static size_t max_regexp_cache_size = 100; // collision probability

    std::hash<std::string> hasher;
    struct StringAndRegexp
    {
        std::string pattern;
        RegexpPtr regexp;
    };
    using CacheTable = std::array<StringAndRegexp, max_regexp_cache_size>;
    CacheTable known_regexps;

};

}

#if USE_VECTORSCAN

namespace MultiRegexps
{
template <typename Deleter, Deleter deleter>
struct HyperscanDeleter
{
    template <typename T>
    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 CompilerError = std::unique_ptr<hs_compile_error_t, HyperscanDeleter<decltype(&hs_free_compile_error), &hs_free_compile_error>>;
using ScratchPtr = std::unique_ptr<hs_scratch_t, HyperscanDeleter<decltype(&hs_free_scratch), &hs_free_scratch>>;
using DataBasePtr = std::unique_ptr<hs_database_t, HyperscanDeleter<decltype(&hs_free_database), &hs_free_database>>;

/// Database is thread safe across multiple threads and 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 RegexpsConstructor
{
public:
    RegexpsConstructor() = default;

    void setConstructor(std::function<Regexps()> constructor_) { constructor = std::move(constructor_); }

    Regexps * operator()()
    {
        std::lock_guard lock(mutex);
        if (regexp)
            return &*regexp;
        regexp = constructor();
        return &*regexp;
    }

private:
    std::function<Regexps()> constructor;
    std::optional<Regexps> regexp;
    std::mutex mutex;
};

struct Pool
{
    /// Mutex for finding in map.
    std::mutex mutex;
    /// Patterns + possible edit_distance to database and scratch.
    std::map<std::pair<std::vector<String>, std::optional<UInt32>>, RegexpsConstructor> storage;
};

template <bool save_indices, bool WithEditDistance>
inline Regexps constructRegexps(const std::vector<String> & str_patterns, [[maybe_unused]] std::optional<UInt32> edit_distance)
{
    /// Common pointers
    std::vector<const char *> patterns;
    std::vector<unsigned int> flags;

    /// Pointer for external edit distance compilation
    std::vector<hs_expr_ext> ext_exprs;
    std::vector<const hs_expr_ext *> ext_exprs_ptrs;

    patterns.reserve(str_patterns.size());
    flags.reserve(str_patterns.size());

    if constexpr (WithEditDistance)
    {
        ext_exprs.reserve(str_patterns.size());
        ext_exprs_ptrs.reserve(str_patterns.size());
    }

    for (const StringRef 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 (WithEditDistance)
        {
            /// 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<unsigned int[]> 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] = i + 1;
    }

    hs_error_t err;
    if constexpr (!WithEditDistance)
        err = hs_compile_multi(
            patterns.data(),
            flags.data(),
            ids.get(),
            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(),
            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.
        CompilerError error(compile_error);

        if (error->expression < 0)
            throw Exception(String(error->message), ErrorCodes::LOGICAL_ERROR);
        else
            throw Exception(
                "Pattern '" + str_patterns[error->expression] + "' failed with error '" + String(error->message),
                ErrorCodes::BAD_ARGUMENTS);
    }

    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("Could not allocate scratch space for hyperscan", ErrorCodes::CANNOT_ALLOCATE_MEMORY);

    return {db, scratch};
}

/// If WithEditDistance 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 <bool save_indices, bool WithEditDistance>
inline Regexps * get(const std::vector<std::string_view> & patterns, std::optional<UInt32> edit_distance)
{
    static Pool known_regexps; /// Different variables for different pattern parameters, thread-safe in C++11

    std::vector<String> str_patterns;
    str_patterns.reserve(patterns.size());
    for (const auto & pattern : patterns)
        str_patterns.emplace_back(std::string(pattern.data(), pattern.size()));

    /// Get the lock for finding database.
    std::unique_lock lock(known_regexps.mutex);

    auto it = known_regexps.storage.find({str_patterns, edit_distance});

    /// If not found, compile and let other threads wait.
    if (known_regexps.storage.end() == it)
    {
        it = known_regexps.storage
                 .emplace(std::piecewise_construct, std::make_tuple(std::move(str_patterns), edit_distance), std::make_tuple())
                 .first;
        it->second.setConstructor([&str_patterns = it->first.first, edit_distance]()
        {
            return constructRegexps<save_indices, WithEditDistance>(str_patterns, edit_distance);
        });
    }

    /// Unlock before possible construction.
    lock.unlock();
    return it->second();
}

}

#endif // USE_VECTORSCAN

}