hash_join_iterator.h

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#ifndef SQL_ITERATORS_HASH_JOIN_ITERATOR_H_
#define SQL_ITERATORS_HASH_JOIN_ITERATOR_H_
 
/* Copyright (c) 2019, 2024, Oracle and/or its affiliates.
 
   This program is free software; you can redistribute it and/or modify
   it under the terms of the GNU General Public License, version 2.0,
   as published by the Free Software Foundation.
 
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   permission to link the program and your derivative works with the
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   This program is distributed in the hope that it will be useful,
   but WITHOUT ANY WARRANTY; without even the implied warranty of
   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
   GNU General Public License, version 2.0, for more details.
 
   You should have received a copy of the GNU General Public License
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   Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301  USA */
 
#include <stdio.h>
#include <cassert>
#include <cstdint>
#include <span>
#include <vector>
 
#include "my_alloc.h"
#include "my_base.h"
#include "my_table_map.h"
#include "prealloced_array.h"
#include "sql/immutable_string.h"
#include "sql/item_cmpfunc.h"
#include "sql/iterators/hash_join_buffer.h"
#include "sql/iterators/hash_join_chunk.h"
#include "sql/iterators/row_iterator.h"
#include "sql/join_type.h"
#include "sql/mem_root_array.h"
#include "sql/pack_rows.h"
#include "sql/table.h"
#include "sql_string.h"
 
class Item;
class THD;
struct AccessPath;
 
struct ChunkPair {
  HashJoinChunk probe_chunk;
  HashJoinChunk build_chunk;
};
 
/// @file
///
/// An iterator for joining two inputs by using hashing to match rows from
/// the inputs.
///
/// The iterator starts out by doing everything in-memory. If everything fits
/// into memory, the joining algorithm for inner joins works like this:
///
/// 1) Designate one input as the "build" input and one input as the "probe"
/// input. Ideally, the smallest input measured in total size (not number of
/// rows) should be designated as the build input.
///
/// 2) Read all the rows from the build input into an in-memory hash table.
/// The hash key used in the hash table is calculated from the join attributes,
/// e.g., if we have the following query where "orders" is designated as the
/// build input:
///
///   SELECT * FROM lineitem
///     INNER JOIN orders ON orders.o_orderkey = lineitem.l_orderkey;
///
/// the hash value will be calculated from the values in the column
/// orders.o_orderkey. Note that the optimizer recognizes implicit join
/// conditions, so this also works for SQL statements like:
///
///   SELECT * FROM orders, lineitem
///     WHERE orders.o_orderkey = lineitem.l_orderkey;
///
/// 3) Then, we read the rows from the probe input, one by one. For each row,
/// a hash key is calculated for the other side of the join (the probe input)
/// using the join attribute (lineitem.l_orderkey in the above example) and the
/// same hash function as in step 2. This hash key is used to do a lookup in the
/// hash table, and for each match, an output row is produced. Note that the row
/// from the probe input is already located in the table record buffers, and the
/// matching row stored in the hash table is restored back to the record buffers
/// where it originally came from. For details around how rows are stored and
/// restored, see comments on pack_rows::StoreFromTableBuffers.
///
/// The size of the in-memory hash table is controlled by the system variable
/// join_buffer_size. If we run out of memory during step 2, we degrade into a
/// hybrid hash join. The data already in memory is processed using regular hash
/// join, and the remainder is processed using on-disk hash join. It works like
/// this:
///
/// 1) The rest of the rows in the build input that did not fit into the hash
/// table are partitioned out into a given amount of files, represented by
/// HashJoinChunks. We create an equal number of chunk files for both the probe
/// and build input. We determine which file to put a row in by calculating a
/// hash from the join attribute like in step 2 above, but using a different
/// hash function.
///
/// 2) Then, we read the rows from the probe input, one by one. We look for a
/// match in the hash table as described above, but the row is also written out
/// to the chunk file on disk, since it might match a row from the build input
/// that we've written to disk.
///
/// 3) When the entire probe input is read, we run the "classic" hash join on
/// each of the corresponding chunk file probe/build pairs. Since the rows are
/// partitioned using the same hash function for probe and build inputs, we know
/// that matching rows must be located in the same pair of chunk files.
///
/// The algorithm for semijoin is quite similar to inner joins:
///
/// 1) Designate the inner table (i.e. the IN-side of a semijoin) as the build
/// input. As semijoins only needs the first matching row from the inner table,
/// we do not store duplicate keys in the hash table.
///
/// 2) Output all rows from the probe input where there is at least one matching
/// row in the hash table. In case we have degraded into on-disk hash join, we
/// write the probe row out to chunk file only if we did not find a matching row
/// in the hash table.
///
/// The optimizer may set up semijoins with conditions that are not pure join
/// conditions, but that must be attached to the hash join iterator anyways.
/// Consider the following query and (slightly modified) execution plan:
///
///   SELECT c FROM t WHERE 1 IN (SELECT t.c = col1 FROM t1);
///
///   -> Hash semijoin (no condition), extra conditions: (1 = (t.c = t1.col1))
///       -> Table scan on t
///       -> Hash
///           -> Table scan on t1
///
/// In this query, the optimizer has set up the condition (1 = (t.c = t1.col1))
/// as the semijoin condition. We cannot use this as a join condition, since
/// hash join only supports equi-join conditions. However, we cannot attach this
/// as a filter after the join, as that would cause wrong results. We attach
/// these conditions as "extra" conditions to the hash join iterator, and causes
/// these notable behaviors:
///
/// a. If we have any extra conditions, we cannot reject duplicate keys in the
///    hash table: the first row matching the join condition could fail the
///    extra condition(s).
///
/// b. We can only output rows if all extra conditions pass. If any of the extra
///    conditions fail, we must go to the next matching row in the hash table.
///
/// c. In case of on-disk hash join, we must write the probe row to disk _after_
///    we have checked that there are no rows in the hash table that match any
///    of the extra conditions.
///
/// If we are able to execute the hash join in memory (classic hash join),
/// the output will be sorted the same as the left (probe) input. If we start
/// spilling to disk, we lose any reasonable ordering properties.
///
/// Note that we still might end up in a case where a single chunk file from
/// disk won't fit into memory. This is resolved by reading as much as possible
/// into the hash table, and then reading the entire probe chunk file for each
/// time the hash table is reloaded. This might happen if we have a very skewed
/// data set, for instance.
///
/// When we start spilling to disk, we allocate a maximum of "kMaxChunks"
/// chunk files on disk for each of the two inputs. The reason for having an
/// upper limit is to avoid running out of file descriptors.
///
/// There is also a flag we can set to avoid hash join spilling to disk
/// regardless of the input size. If the flag is set, the join algorithm works
/// like this:
///
/// 1) Read as many rows as possible from the build input into an in-memory hash
/// table.
/// 2) When the hash table is full (we have reached the limit set by the system
/// variable join_buffer_size), start reading from the beginning of the probe
/// input, probing for matches in the hash table. Output a row for each match
/// found.
/// 3) When the probe input is empty, see if there are any remaining rows in the
/// build input. If so, clear the in-memory hash table and go to step 1,
/// continuing from the build input where we stopped the last time. If not, the
/// join is done.
///
/// Doing everything in memory can be beneficial in a few cases. Currently, it
/// is used when we have a LIMIT without sorting or grouping in the query. The
/// gain is that we start producing output rows a lot earlier than if we were to
/// spill both inputs out to disk. It could also be beneficial if the build
/// input _almost_ fits in memory; it would likely be better to read the probe
/// input twice instead of writing both inputs out to disk. However, we do not
/// currently do any such cost based optimization.
///
/// There is a concept called "probe row saving" in the iterator. This is a
/// technique that is enabled in two different scenarios: when a hash join build
/// chunk does not fit entirely in memory and when hash join is not allowed to
/// spill to disk. Common for these two scenarios is that a probe row will be
/// read multiple times. For certain join types (semijoin), we must take care so
/// that the same probe row is not sent to the client multiple times. Probe row
/// saving takes care of this by doing the following:
///
/// - If we realize that we are going to read the same probe row multiple times,
///   we enable probe row saving.
/// - When a probe row is read, we write the row out to a probe row saving write
///   file, given that it matches certain conditions (for semijoin we only save
///   unmatched probe rows).
/// - After the probe input is consumed, we will swap the probe row saving
///   _write_ file and the probe row saving _read_ file, making the write file
///   available for writing again.
/// - When we are to read the probe input again, we read the probe rows from the
///   probe row saving read file. This ensures that we i.e. do not output the
///   same probe row twice for semijoin. Note that if the rows we read from the
///   probe row saving read file will be read again (e.g., we have a big hash
///   join build chunk that is many times bigger than the available hash table
///   memory, causing us to process the chunk file in chunks), we will again
///   write the rows to a new probe row saving write file. This reading from the
///   read file and writing to a new write file continues until we know that we
///   are seeing the probe rows for the last time.
///
/// We use the same methods as on-disk hash join (HashJoinChunk) for reading and
/// writing rows to files. Note that probe row saving is never enabled for inner
/// joins, since we do want to output the same probe row multiple times if it
/// matches muliple rows from the build input. There are some differences
/// regarding when probe row saving is enabled, depending on the hash join type
/// (see enum HashJoinType):
///
/// - IN_MEMORY: Probe row saving is never activated, since the probe input is
///   read only once.
/// - SPILL_TO_DISK: If a build chunk file does not fit in memory (may happen
///   with skewed data set), we will have to read the corresponding probe chunk
///   multiple times. In this case, probe row saving is enabled as soon as we
///   see that the build chunk does not fit in memory, and remains active until
///   the entire build chunk is consumed. After the probe chunk is read once,
///   we swap the probe row saving write file and probe row saving read file so
///   that probe rows will be read from the probe row saving read file. Probe
///   row saving is deactivated once we move to the next pair of chunk files.
/// - IN_MEMORY_WITH_HASH_TABLE_REFILL: Probe row saving is activated when we
///   see that the build input is too large to fit in memory. Once the probe
///   iterator has been consumed once, we swap the probe row saving write file
///   and probe row saving read file so that probe rows will be read from the
///   probe row saving read file. As long as the build input is not fully
///   consumed, we write probe rows from the read file out to a new write file,
///   swapping these files for every hash table refill. Probe row saving is
///   never deactivated in this hash join type.
///
/// Note that we always write the entire row when writing to probe row saving
/// file. It would be possible to only write the match flag, but this is tricky
/// as long as we have the hash join type IN_MEMORY_WITH_HASH_TABLE_REFILL. If
/// we were to write only match flags in this hash join type, we would have to
/// read the probe iterator multiple times. But there is no guarantee that rows
/// will come in the same order when reading an iterator multiple times (e.g.
/// NDB does not guarantee this), so it would require us to store match flags in
/// a lookup structure using a row ID as the key. Due to this, we will
/// reconsider this if the hash join type IN_MEMORY_WITH_HASH_TABLE_REFILL goes
/// away.
 
/// The two inputs that we read from when executing a hash join.
enum class HashJoinInput {
  /// We build the hash table from this input.
  kBuild,
  /// For each row from this input, we try to find a match in the hash table.
  kProbe
};
 
class HashJoinIterator final : public RowIterator {
 public:
  /// Construct a HashJoinIterator.
  ///
  /// @param thd
  ///   the thread handle
  /// @param build_input
  ///   the iterator for the build input
  /// @param build_input_tables
  ///   a list of all the tables in the build input. The tables are needed for
  ///   two things:
  ///   1) Accessing the columns when creating the join key during creation of
  ///   the hash table,
  ///   2) and accessing the column data when creating the row to be stored in
  ///   the hash table and/or the chunk file on disk.
  /// @param estimated_build_rows
  ///   How many rows we assume there will be when reading the build input.
  ///   This is used to choose how many chunks we break it into on disk.
  /// @param probe_input
  ///   the iterator for the probe input
  /// @param probe_input_tables
  ///   the probe input tables. Needed for the same reasons as
  ///   build_input_tables.
  /// @param store_rowids whether we need to make sure row ids are available
  ///   for all tables below us, after Read() has been called. used only if
  ///   we are below a weedout operation.
  /// @param tables_to_get_rowid_for a map of which tables we need to call
  ///   position() for ourselves. tables that are in build_input_tables
  ///   but not in this map, are expected to be handled by some other iterator.
  ///   tables that are in this map but not in build_input_tables will be
  ///   ignored.
  /// @param max_memory_available
  ///   the amount of memory available, in bytes, for this hash join iterator.
  ///   This can be user-controlled by setting the system variable
  ///   join_buffer_size.
  /// @param join_conditions
  ///   a list of all the join conditions between the two inputs
  /// @param allow_spill_to_disk
  ///   whether the hash join can spill to disk. This is set to false in some
  ///   cases where we have a LIMIT in the query
  /// @param join_type
  ///   The join type.
  /// @param extra_conditions
  ///   A list of extra conditions that the iterator will evaluate after a
  ///   lookup in the hash table is done, but before the row is returned. The
  ///   conditions are AND-ed together into a single Item.
  /// @param single_row_index_lookups
  ///   All the single-row index lookups in the build input and probe input.
  /// @param first_input
  ///   The first input (build or probe) to read from. (If this is empty, we
  ///   will not have to read from the other.)
  /// @param probe_input_batch_mode
  ///   Whether we need to enable batch mode on the probe input table.
  ///   Only make sense if it is a single table, and we are not on the
  ///   outer side of any nested loop join.
  /// @param hash_table_generation
  ///   If this is non-nullptr, it is a counter of how many times the query
  ///   block the iterator is a part of has been asked to clear hash tables,
  ///   since outer references may have changed value. It is used to know when
  ///   we need to drop our hash table; when the value changes, we need to drop
  ///   it. If it is nullptr, we _always_ drop it on Init().
  HashJoinIterator(THD *thd, unique_ptr_destroy_only<RowIterator> build_input,
                   const Prealloced_array<TABLE *, 4> &build_input_tables,
                   double estimated_build_rows,
                   unique_ptr_destroy_only<RowIterator> probe_input,
                   const Prealloced_array<TABLE *, 4> &probe_input_tables,
                   bool store_rowids, table_map tables_to_get_rowid_for,
                   size_t max_memory_available,
                   const std::vector<HashJoinCondition> &join_conditions,
                   bool allow_spill_to_disk, JoinType join_type,
                   const Mem_root_array<Item *> &extra_conditions,
                   std::span<AccessPath *> single_row_index_lookups,
                   HashJoinInput first_input, bool probe_input_batch_mode,
                   uint64_t *hash_table_generation);
 
  bool Init() override;
 
  int Read() override;
 
  void SetNullRowFlag(bool is_null_row) override {
    // Don't call this after Init() but before calling Read() for the first
    // time. Init() may have loaded a row that is (partially or fully) a null
    // row, so resetting the null row flags is incorrect.
    assert(!m_probe_row_read || m_state == State::END_OF_ROWS);
    m_build_input->SetNullRowFlag(is_null_row);
    m_probe_input->SetNullRowFlag(is_null_row);
  }
 
  void EndPSIBatchModeIfStarted() override {
    m_build_input->EndPSIBatchModeIfStarted();
    m_probe_input->EndPSIBatchModeIfStarted();
  }
 
  void UnlockRow() override {
    // Since both inputs may have been materialized to disk, we cannot unlock
    // them.
  }
 
  int ChunkCount() { return m_chunk_files_on_disk.size(); }
 
 private:
  /// Read all rows from the build input and store the rows into the in-memory
  /// hash table. If the hash table goes full, the rest of the rows are written
  /// out to chunk files on disk. See the class comment for more details.
  ///
  /// @retval true in case of error
  bool BuildHashTable();
 
  /// Write all the remaining rows from the build table input to chunk files on
  /// disk.
  ///
  /// @return True on error, false on success.
  bool WriteBuildTableToChunkFiles();
 
  /// Read all rows from the next chunk file into the in-memory hash table.
  /// See the class comment for details.
  ///
  /// @retval true in case of error
  bool ReadNextHashJoinChunk();
 
  /// Read a single row from the probe iterator input into the tables' record
  /// buffers. If we have started spilling to disk, the row is written out to a
  /// chunk file on disk as well.
  ///
  /// The end condition is that either:
  /// a) a row is ready in the tables' record buffers, and the state will be set
  ///    to READING_FIRST_ROW_FROM_HASH_TABLE.
  /// b) There are no more rows to process from the probe input, so the iterator
  ///    state will be LOADING_NEXT_CHUNK_PAIR.
  ///
  /// @retval true in case of error
  bool ReadRowFromProbeIterator();
 
  /// Read a single row from the current probe chunk file into the tables'
  /// record buffers. The end conditions are the same as for
  /// ReadRowFromProbeIterator().
  ///
  /// @retval true in case of error
  bool ReadRowFromProbeChunkFile();
 
  /// Read a single row from the probe row saving file into the tables' record
  /// buffers.
  ///
  /// @retval true in case of error
  bool ReadRowFromProbeRowSavingFile();
 
  // Do a lookup in the hash table for matching rows from the build input.
  // The lookup is done by computing the join key from the probe input, and
  // using that join key for doing a lookup in the hash table. If the join key
  // contains one or more SQL NULLs, the row cannot match anything and will be
  // skipped, and the iterator state will be READING_ROW_FROM_PROBE_INPUT. If
  // not, the iterator state will be READING_FIRST_ROW_FROM_HASH_TABLE.
  //
  // After this function is called, ReadJoinedRow() will return false until
  // there are no more matching rows for the computed join key.
  void LookupProbeRowInHashTable();
 
  /// Take the next matching row from the hash table, and put the row into the
  /// build tables' record buffers. The function expects that
  /// LookupProbeRowInHashTable() has been called up-front. The user must
  /// call ReadJoinedRow() as long as it returns false, as there may be
  /// multiple matching rows from the hash table. It is up to the caller to set
  /// a new state in case of EOF.
  ///
  /// @retval 0 if a match was found and the row is put in the build tables'
  ///         record buffers
  /// @retval -1 if there are no more matching rows in the hash table
  int ReadJoinedRow();
 
  // Have we degraded into on-disk hash join?
  bool on_disk_hash_join() const { return !m_chunk_files_on_disk.empty(); }
 
  /// Write the last row read from the probe input out to chunk files on disk,
  /// if applicable.
  ///
  /// For inner joins, we must write all probe rows to chunk files, since we
  /// need to match the row against rows from the build input that are written
  /// out to chunk files. For semijoin, we can only write probe rows that do not
  /// match any of the rows in the hash table. Writing a probe row with a
  /// matching row in the hash table could cause the row to be returned multiple
  /// times.
  ///
  /// @retval true in case of errors.
  bool WriteProbeRowToDiskIfApplicable();
 
  /// @retval true if the last joined row passes all of the extra conditions.
  bool JoinedRowPassesExtraConditions() const;
 
  /// If true, reject duplicate keys in the hash table.
  ///
  /// Semijoins/antijoins are only interested in the first matching row from the
  /// hash table, so we can avoid storing duplicate keys in order to save some
  /// memory. However, this cannot be applied if we have any "extra" conditions:
  /// the first matching row in the hash table may fail the extra condition(s).
  ///
  /// @retval true if we can reject duplicate keys in the hash table.
  bool RejectDuplicateKeys() const {
    return m_extra_condition == nullptr &&
           (m_join_type == JoinType::SEMI || m_join_type == JoinType::ANTI);
  }
 
  /// Clear the row buffer and reset all iterators pointing to it. This may be
  /// called multiple times to re-init the row buffer.
  ///
  /// @retval true in case of error. my_error has been called
  bool InitRowBuffer();
 
  /// Prepare to read the probe iterator from the beginning, and enable batch
  /// mode if applicable. The iterator state will remain unchanged.
  ///
  /// @retval true in case of error. my_error has been called.
  bool InitProbeIterator();
 
  /// Mark that probe row saving is enabled, and prepare the probe row saving
  /// file for writing.
  /// @see m_write_to_probe_row_saving
  ///
  /// @retval true in case of error. my_error has been called.
  bool InitWritingToProbeRowSavingFile();
 
  /// Mark that we should read from the probe row saving file. The probe row
  /// saving file is rewinded to the beginning.
  /// @see m_read_from_probe_row_saving
  ///
  /// @retval true in case of error. my_error has been called.
  bool InitReadingFromProbeRowSavingFile();
 
  /// Set the iterator state to the correct READING_ROW_FROM_PROBE_*-state.
  /// Which state we end up in depends on which hash join type we are executing
  /// (in-memory, on-disk or in-memory with hash table refill).
  void SetReadingProbeRowState();
 
  /// Read a joined row from the hash table, and see if it passes any extra
  /// conditions. The last probe row read will also be written do disk if needed
  /// (see WriteProbeRowToDiskIfApplicable).
  ///
  /// @retval -1 There are no more matching rows in the hash table.
  /// @retval 0 A joined row is ready.
  /// @retval 1 An error occurred.
  int ReadNextJoinedRowFromHashTable();
 
  enum class State {
    // We are reading a row from the probe input, where the row comes from
    // the iterator.
    READING_ROW_FROM_PROBE_ITERATOR,
    // We are reading a row from the probe input, where the row comes from a
    // chunk file.
    READING_ROW_FROM_PROBE_CHUNK_FILE,
    // We are reading a row from the probe input, where the row comes from a
    // probe row saving file.
    READING_ROW_FROM_PROBE_ROW_SAVING_FILE,
    // The iterator is moving to the next pair of chunk files, where the chunk
    // file from the build input will be loaded into the hash table.
    LOADING_NEXT_CHUNK_PAIR,
    // We are reading the first row returned from the hash table lookup that
    // also passes extra conditions.
    READING_FIRST_ROW_FROM_HASH_TABLE,
    // We are reading the remaining rows returned from the hash table lookup.
    READING_FROM_HASH_TABLE,
    // No more rows, both inputs are empty.
    END_OF_ROWS
  };
 
  State m_state;
  uint64_t *m_hash_table_generation;
  uint64_t m_last_hash_table_generation;
 
  const unique_ptr_destroy_only<RowIterator> m_build_input;
  const unique_ptr_destroy_only<RowIterator> m_probe_input;
 
  // The last row that was read from the hash table, or nullptr if none.
  // All rows under the same key are linked together (see the documentation
  // for LinkedImmutableString), so this allows iterating through the rows
  // until the end.
  LinkedImmutableString m_current_row{nullptr};
 
  // These structures holds the tables and columns that are needed for the hash
  // join. Rows/columns that are not needed are filtered out in the constructor.
  // We need to know which tables that belong to each iterator, so that we can
  // compute the join key when needed.
  pack_rows::TableCollection m_probe_input_tables;
  pack_rows::TableCollection m_build_input_tables;
 
  // An in-memory hash table that holds rows from the build input (directly from
  // the build input iterator, or from a chunk file). See the class comment for
  // details on how and when this is used.
  hash_join_buffer::HashJoinRowBuffer m_row_buffer;
 
  // A list of the join conditions (all of them are equi-join conditions).
  Prealloced_array<HashJoinCondition, 4> m_join_conditions;
 
  // Array to hold the list of chunk files on disk in case we degrade into
  // on-disk hash join.
  Mem_root_array<ChunkPair> m_chunk_files_on_disk;
 
  // Which HashJoinChunk, if any, we are currently reading from, in both
  // LOADING_NEXT_CHUNK_PAIR and READING_ROW_FROM_PROBE_CHUNK_FILE.
  // It is incremented during the state LOADING_NEXT_CHUNK_PAIR.
  int m_current_chunk{-1};
 
  // Which row we currently are reading from each of the hash join chunk file.
  ha_rows m_build_chunk_current_row = 0;
  ha_rows m_probe_chunk_current_row = 0;
 
  // How many rows we assume there will be when reading the build input.
  // This is used to choose how many chunks we break it into on disk.
  const double m_estimated_build_rows;
 
 public:
  // The seed that is by xxHash64 when calculating the hash from a join
  // key. We use xxHash64 when calculating the hash that is used for
  // determining which chunk file a row should be placed in (in case of
  // on-disk hash join); if we used the same hash function (and seed) for
  // both operation, we would get a really bad hash table when loading
  // a chunk file to the hash table. The number is chosen randomly and have
  // no special meaning.
  static constexpr uint32_t kChunkPartitioningHashSeed{899339};
 
  // The maximum number of HashJoinChunks that is allocated for each of the
  // inputs in case we spill to disk. We might very well end up with an amount
  // less than this number, but we keep an upper limit so we don't risk running
  // out of file descriptors. We always use a power of two number of files,
  // which allows us to do some optimizations when calculating which chunk a row
  // should be placed in.
  static constexpr size_t kMaxChunks = 128;
 
 private:
  // A buffer that is used during two phases:
  // 1) when constructing a join key from join conditions.
  // 2) when moving a row between tables' record buffers and the hash table.
  //
  // There are two functions that needs this buffer; ConstructJoinKey() and
  // StoreFromTableBuffers(). After calling one of these functions, the user
  // must take responsibility of the data if it is needed for a longer lifetime.
  //
  // If there are no BLOB/TEXT column in the join, we calculate an upper bound
  // of the row size that is used to preallocate this buffer. In the case of
  // BLOB/TEXT columns, we cannot calculate a reasonable upper bound, and the
  // row size is calculated per row. The allocated memory is kept for the
  // duration of the iterator, so that we (most likely) avoid reallocations.
  String m_temporary_row_and_join_key_buffer;
 
  /// The first input (build or probe) to read from. (If this is empty, we will
  /// not have to read from the other.)
  HashJoinInput m_first_input;
 
  // Whether we should turn on batch mode for the probe input. Batch mode is
  // enabled if the probe input consists of exactly one table, and said table
  // can return more than one row and has no associated subquery condition.
  // (See ShouldEnableBatchMode().)
  bool m_probe_input_batch_mode{false};
 
  // Whether we are allowed to spill to disk.
  bool m_allow_spill_to_disk{true};
 
  // Whether the build iterator has more rows. This is used to stop the hash
  // join iterator asking for more rows when we know for sure that the entire
  // build input is consumed. The variable is only used if m_allow_spill_to_disk
  // is false, as we have to see if there are more rows in the build input after
  // the probe input is consumed.
  bool m_build_iterator_has_more_rows{true};
 
  // What kind of join the iterator should execute.
  const JoinType m_join_type;
 
  // If not nullptr, an extra condition that the iterator will evaluate after a
  // lookup in the hash table is done, but before the row is returned. This is
  // needed in case we have a semijoin condition that is not an equi-join
  // condition (i.e. 't1.col1 < t2.col1').
  Item *m_extra_condition{nullptr};
 
  // Whether we should write rows from the probe input to the probe row saving
  // write file. See the class comment on HashJoinIterator for details around
  // probe row saving.
  bool m_write_to_probe_row_saving{false};
 
  // Whether we should read rows from the probe row saving read file. See the
  // class comment on HashJoinIterator for details around probe row saving.
  bool m_read_from_probe_row_saving{false};
 
  // The probe row saving files where unmatched probe rows are written to and
  // read from.
  HashJoinChunk m_probe_row_saving_write_file;
  HashJoinChunk m_probe_row_saving_read_file;
 
  // Which row we currently are reading from in the probe row saving read file.
  // Used to know whether we have reached the end of the file. How many files
  // the probe row saving read file contains is contained in the HashJoinChunk
  // (see m_probe_row_saving_read_file).
  ha_rows m_probe_row_saving_read_file_current_row{0};
 
  // All the single-row index lookups that provide rows to this iterator.
  std::span<AccessPath *> m_single_row_index_lookups;
 
  // The "type" of hash join we are executing. We currently have three different
  // types of hash join:
  // - In memory: We do everything in memory without any refills of the hash
  //   table. Each input is read only once, and nothing is written to disk.
  // - Spill to disk: If the build input does not fit in memory, we write both
  //   inputs out to a set of chunk files. Both inputs are partitioned using a
  //   hash function over the join attribute, ensuring that matching rows can be
  //   found in the same set of chunk files. Each pair of chunk file is then
  //   processed as an in-memory hash join.
  // - In memory with hash table refill: This is enabled if we are not allowed
  //   to spill to disk, and the build input does not fit in memory. We read as
  //   much as possible from the build input into the hash table. We then read
  //   the entire probe input, probing for matching rows in the hash table.
  //   When the probe input returns EOF, the hash table is refilled with the
  //   rows that did not fit the first time. The entire probe input is read
  //   again, and this is repeated until the entire build input is consumed.
  enum class HashJoinType {
    IN_MEMORY,
    SPILL_TO_DISK,
    IN_MEMORY_WITH_HASH_TABLE_REFILL
  };
  HashJoinType m_hash_join_type{HashJoinType::IN_MEMORY};
 
  // The match flag for the last probe row read from chunk file.
  //
  // This is needed if a outer join spills to disk; a probe row can match a row
  // from the build input we haven't seen yet (it's been written out to disk
  // because the hash table was full). So when reading a probe row from a chunk
  // file, this variable holds the match flag. This flag must be a class member,
  // since one probe row may match multiple rows from the hash table; the
  // execution will go out of HashJoinIterator::Read() between each matching
  // row, causing any local match flag to lose the match flag info from the last
  // probe row read.
  bool m_probe_row_match_flag{false};
 
  /// If true, a row was already read from the probe input, in order to check if
  /// that input was empty. If so, we should process that row before reading
  /// another.
  bool m_probe_row_read{false};
 
  /// Helper function for Init(). Read the first row from m_probe_input.
  /// @returns 'true' if there was an error.
  bool ReadFirstProbeRow();
 
  /// Helper function for Init(). Build the hash table and check for empty query
  /// results (empty build input or non-empty build input in case of degenerate
  /// antijoin.)
  /// @returns 'true' in case of error.
  bool InitHashTable();
};
 
#endif  // SQL_ITERATORS_HASH_JOIN_ITERATOR_H_