test-example-projects/c++_projects/280w-mysql-8.0.18/sql/hash_join_buffer.h

#ifndef SQL_HASH_JOIN_BUFFER_H_
#define SQL_HASH_JOIN_BUFFER_H_

/* Copyright (c) 2019, Oracle and/or its affiliates. All rights reserved.

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   it under the terms of the GNU General Public License, version 2.0,
   as published by the Free Software Foundation.

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   You should have received a copy of the GNU General Public License
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/// @file
///
/// This file contains the HashJoinRowBuffer class and related
/// functions/classes.
///
/// A HashJoinBuffer is a row buffer that can hold a certain amount of rows.
/// The rows are stored in a hash table, which allows for constant-time lookup.
/// The HashJoinBuffer maintains its own internal MEM_ROOT, where all of the
/// data is allocated.
///
/// The HashJoinBuffer contains an operand with rows from one or more tables,
/// keyed on the value we join on. Consider the following trivial example:
///
///   SELECT t1.data FROM t1 JOIN t2 ON (t1.key = t2.key);
///
/// Let us say that the table "t2" is stored in a HashJoinBuffer. In this case,
/// the hash table key will be the value found in "t2.key", since that is the
/// join condition that belongs to t2. If we have multiple equalities, they
/// will be concatenated together in order to form the hash table key. The hash
/// table key is bascially an std::string_view, and should be replaced when we
/// go to C++17.
///
/// In order to store a row, we use the function StoreFromTableBuffers. See the
/// comments attached to the function for more details.
///
/// The amount of memory a HashJoinBuffer instance can use is limited by the
/// system variable "join_buffer_size". However, note that we check whether we
/// have exceeded the memory limit _after_ we have inserted data into the row
/// buffer. As such, we will probably use a little bit more memory than
/// specified by join_buffer_size.
///
/// Some basic profiling shows that the majority of the time is used on
/// constructing the hash table. It would be a future improvement to replace
/// std::unordered_multimap with a more performant hash table, as the literature
/// suggests that there are better alternatives (see e.g.
/// https://probablydance.com/2017/02/26/i-wrote-the-fastest-hashtable/).
///
/// The primary use case for these classes is, as the name implies,
/// for implementing hash join.

#include <stddef.h>
#include <stdint.h>
#include <memory>
#include <vector>

#include "extra/lz4/my_xxhash.h"
#include "field_types.h"
#include "map_helpers.h"
#include "my_alloc.h"
#include "my_inttypes.h"
#include "my_table_map.h"
#include "prealloced_array.h"
#include "sql/item_cmpfunc.h"
#include "sql/table.h"
#include "sql_string.h"

class Field;
class QEP_TAB;

namespace hash_join_buffer {

/// A class that represents a field, which also holds a cached value of the
/// field's data type.
struct Column {
  explicit Column(Field *field);
  Field *const field;

  // The field type is used frequently, and caching it gains around 30% in some
  // of our microbenchmarks.
  const enum_field_types field_type;
};

/// This struct is primarily used for holding the extracted columns in a hash
/// join. When the hash join iterator is constructed, we extract the columns
/// that are needed to satisfy the SQL query.
struct Table {
  explicit Table(QEP_TAB *qep_tab);
  QEP_TAB *qep_tab;
  Prealloced_array<Column, 8> columns;

  // Whether to copy the NULL flags or not.
  bool copy_null_flags{false};

  // A cached value of QEP_TAB::rowid_status. This determines whether we need to
  // copy/restore the row ID for each row, and how we should retrieve the row ID
  // (i.e., should we call handler::position() or not). See the comment on
  // QEP_TAB::rowid_status for more details.
  rowid_statuses rowid_status;
};

/// A structure that contains a list of tables for the hash join operation,
/// and some pre-computed properties for the tables.
class TableCollection {
 public:
  TableCollection() = default;

  explicit TableCollection(const std::vector<QEP_TAB *> &tables);

  const Prealloced_array<Table, 4> &tables() const { return m_tables; }

  table_map tables_bitmap() const { return m_tables_bitmap; }

  size_t ref_and_null_bytes_size() const { return m_ref_and_null_bytes_size; }

  bool has_blob_column() const { return m_has_blob_column; }

 private:
  Prealloced_array<Table, 4> m_tables{PSI_NOT_INSTRUMENTED};

  // We frequently use the bitmap to determine which side of the join an Item
  // belongs to, so precomputing the bitmap saves quite some time.
  table_map m_tables_bitmap;

  // Sum of the NULL bytes and the row ID for all of the tables.
  size_t m_ref_and_null_bytes_size;

  // Whether any of the tables has a BLOB/TEXT column. This is used to determine
  // whether we need to estimate the row size every time we store a row to the
  // row buffer or to a chunk file on disk. If this is set to false, we can
  // pre-allocate any necessary buffers we need during the hash join, and thus
  // eliminate the need for recalculating the row size every time.
  bool m_has_blob_column;
};

/// Count up how many bytes a single row from the given tables will occupy,
/// in "packed" format. Note that this is an upper bound, so the length after
/// calling Field::pack may very well be shorter than the size returned by this
/// function.
///
/// The value returned from this function will sum up
/// 1) The row-id if that is to be kept.
/// 2) Size of the NULL flags.
/// 3) Size of the buffer returned by pack() on all columns marked in the
///    read_set.
///
/// Note that if any of the tables has a BLOB/TEXT column, this function looks
/// at the data stored in the record buffers. This means that the function can
/// not be called before reading any rows if tables.has_blob_column is true.
size_t ComputeRowSizeUpperBound(const TableCollection &tables);

/// The key type for the hash structure in HashJoinRowBuffer.
///
/// A key consists of the value from one or more columns, taken from the join
/// condition(s) in the query.  E.g., if the join condition is
/// (t1.col1 = t2.col1 AND t1.col2 = t2.col2), the key is (col1, col2), with the
/// two key parts concatenated together.
///
/// What the data actually contains depends on the comparison context for the
/// join condition. For instance, if the join condition is between a string
/// column and an integer column, the comparison will be done in a string
/// context, and thus the integers will be converted to strings before storing.
/// So the data we store in the key are in some cases converted, so that we can
/// hash and compare them byte-by-byte (i.e. decimals), while other types are
/// already comparable byte-by-byte (i.e. integers), and thus stored as-is.
///
/// Note that the key data can come from items as well as fields if the join
/// condition is an expression. E.g. if the join condition is
/// UPPER(t1.col1) = UPPER(t2.col1), the join key data will come from an Item
/// instead of a Field.
///
/// The Key class never takes ownership of the data. As such, the user must
/// ensure that the data has the proper lifetime. When storing rows in the row
/// buffer, the data must have the same lifetime as the row buffer itself.
/// When using the Key class for lookups in the row buffer, the same lifetime is
/// not needed; the key object is only needed when the lookup is done.
///
/// When we move to C++17, this class should most likely be replaced with
/// std::string_view.
class Key {
 public:
  /// Note that data can be nullptr if size is 0.
  Key(const uchar *data, size_t size) : m_data(data), m_size(size) {}

  bool operator==(const Key &other) const {
    if (other.size() != size()) {
      return false;
    } else if (size() == 0) {
      return true;
    }

    return memcmp(other.data(), data(), size()) == 0;
  }

  const uchar *data() const { return m_data; }

  size_t size() const { return m_size; }

 private:
  const uchar *m_data;
  const size_t m_size;
};

// A row in the hash join buffer is generally the same as the Key class. In
// C++17, both of them should most likely be replaced with std::string_view. For
// now, we create an alias to distinguish between Key and a row.
using BufferRow = Key;

/// We rely on xxHash64 to do the hashing of the key. xxHash64 was chosen as it
/// both is very fast _and_ produces reasonably good-quality hashes
/// (see https://github.com/rurban/smhasher).
class KeyHasher {
 public:
  explicit KeyHasher(uint32_t seed) : m_seed(seed) {}

  size_t operator()(hash_join_buffer::Key key) const {
    return MY_XXH64(key.data(), key.size(), m_seed);
  }

 private:
  const uint32_t m_seed;
};

/// Take the data marked for reading in "tables" and store it in the provided
/// buffer. What data to store is determined by the read set of each table.
/// Note that any existing data in "buffer" will be overwritten.
///
/// The output buffer will contain three things:
///
/// 1) NULL flags for each nullable column.
/// 2) The row ID for each row. This is only stored if QEP_TAB::rowid_status !=
///    NO_ROWID_NEEDED.
/// 3) The actual data from the columns.
///
/// @retval true if error, false otherwise
bool StoreFromTableBuffers(const TableCollection &tables, String *buffer);

/// Take the data in "row" and put it back to the tables' record buffers. The
/// tables must be _exactly_ the same as when the BufferRow was created.
/// That is, it must contain the same tables in the same order, and the read set
/// of each table must be identical when storing and restoring the row.
/// If that's not the case, you will end up with undefined and unpredictable
/// behavior.
void LoadIntoTableBuffers(const TableCollection &tables, BufferRow row);

enum class StoreRowResult { ROW_STORED, BUFFER_FULL, FATAL_ERROR };

class HashJoinRowBuffer {
 public:
  // Construct the buffer. Note that Init() must be called before the buffer can
  // be used.
  HashJoinRowBuffer(TableCollection tables,
                    std::vector<HashJoinCondition> join_conditions,
                    size_t max_mem_available_bytes);

  // Initialize the HashJoinRowBuffer so it is ready to store rows. This
  // function can be called multiple times; subsequent calls will only clear the
  // buffer for existing rows.
  bool Init(uint32_t hash_seed);

  /// Store the row that is currently lying in the tables record buffers.
  /// The hash map key is extracted from the join conditions that the row buffer
  /// holds.
  ///
  /// @param thd the thread handler
  ///
  /// @retval ROW_STORED the row was stored.
  /// @retval BUFFER_FULL the row was stored, and the buffer is full.
  /// @retval FATAL_ERROR an unrecoverable error occured (most likely,
  ///         malloc failed). It is the callers responsibility to call
  ///         my_error().
  StoreRowResult StoreRow(THD *thd);

  size_t size() const { return m_hash_map->size(); }

  bool empty() const { return m_hash_map->empty(); }

  using hash_map_type = memroot_unordered_multimap<Key, BufferRow, KeyHasher>;

  using hash_map_iterator = hash_map_type::const_iterator;

  std::pair<hash_map_iterator, hash_map_iterator> equal_range(
      const Key &key) const {
    return m_hash_map->equal_range(key);
  }

  hash_map_iterator begin() const { return m_hash_map->begin(); }

  hash_map_iterator end() const { return m_hash_map->end(); }

 private:
  const std::vector<HashJoinCondition> m_join_conditions;

  // A row can consist of parts from different tables. This structure tells us
  // which tables that are involved.
  const TableCollection m_tables;

  // The MEM_ROOT on which all of the hash table data is allocated.
  MEM_ROOT m_mem_root;

  // The hash table where the rows are stored.
  unique_ptr_destroy_only<hash_map_type> m_hash_map;

  // A buffer we can use when we are constructing a join key from a join
  // condition. In order to avoid reallocating memory, the buffer never shrinks.
  String m_buffer;

  // The maximum size of the buffer, given in bytes.
  const size_t m_max_mem_available;
};

}  // namespace hash_join_buffer

#endif  // SQL_HASH_JOIN_BUFFER_H_