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118 lines
4.1 KiB
118 lines
4.1 KiB
/*
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Copyright (c) 2014, 2017, Oracle and/or its affiliates. All rights reserved.
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This program is free software; you can redistribute it and/or modify
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it under the terms of the GNU General Public License, version 2.0,
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as published by the Free Software Foundation.
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This program is also distributed with certain software (including
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but not limited to OpenSSL) that is licensed under separate terms,
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as designated in a particular file or component or in included license
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documentation. The authors of MySQL hereby grant you an additional
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permission to link the program and your derivative works with the
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separately licensed software that they have included with MySQL.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License, version 2.0, for more details.
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You should have received a copy of the GNU General Public License
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along with this program; if not, write to the Free Software
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Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */
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#include "sql/opt_statistics.h"
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#include <algorithm>
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#include "my_base.h"
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#include "my_dbug.h"
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#include "my_macros.h"
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#include "sql/handler.h"
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#include "sql/key.h" // rec_per_key_t, KEY
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#include "sql/table.h" // TABLE
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using std::max;
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/**
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This code for computing a guestimate for records per key is based on
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code in Optimize_table_order::find_best_ref().
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Assume that the first key part matches 1% of the file and that the
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whole key matches 10 (duplicates) or 1 (unique) records. For small
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tables, ensure there are at least ten different key values. Assume
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also that more key matches proportionally more records. This gives
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the formula:
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records = a - (x-1)/(c-1)*(a-b)
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where
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b = records matched by whole key
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a = records matched by first key part (1% of all records?)
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c = number of key parts in key
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x = used key parts (1 <= x <= c)
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@todo Change Optimize_table_order::find_best_ref() to use this function.
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*/
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rec_per_key_t guess_rec_per_key(const TABLE *const table, const KEY *const key,
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uint used_keyparts) {
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DBUG_ASSERT(used_keyparts >= 1);
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DBUG_ASSERT(used_keyparts <= key->actual_key_parts);
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DBUG_ASSERT(!key->has_records_per_key(used_keyparts - 1));
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const ha_rows table_rows = table->file->stats.records;
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/*
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Make an estimates for how many records the whole key will match.
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If there exists index statistics for the whole key we use this.
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If not, we assume the whole key matches ten records for a non-unique
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index and 1 record for a unique index.
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*/
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rec_per_key_t rec_per_key_all;
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if (key->has_records_per_key(key->user_defined_key_parts - 1))
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rec_per_key_all = key->records_per_key(key->user_defined_key_parts - 1);
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else {
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if (key->actual_flags & HA_NOSAME)
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rec_per_key_all = 1.0f; // Unique index
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else {
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rec_per_key_all = 10.0f; // Non-unique index
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/*
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Assume the index contains at least ten unique values. Need to
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adjust the records per key estimate for small tables. For an
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empty table we assume records per key is 1.
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*/
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set_if_smaller(rec_per_key_all,
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max(rec_per_key_t(table_rows) / 10, 1.0f));
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}
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}
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rec_per_key_t rec_per_key;
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// rec_per_key estimate for first key part (1% of records)
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const rec_per_key_t rec_per_key_first = table_rows * 0.01f;
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if (rec_per_key_first < rec_per_key_all) {
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rec_per_key = rec_per_key_all;
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} else {
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if (key->user_defined_key_parts > 1) {
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// See formula above
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rec_per_key =
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rec_per_key_first - (rec_per_key_t(used_keyparts - 1) /
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(key->user_defined_key_parts - 1)) *
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(rec_per_key_first - rec_per_key_all);
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} else {
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// Single column index
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if (key->actual_flags & HA_NOSAME)
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rec_per_key = 1.0f; // Unique index
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else
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rec_per_key = rec_per_key_first; // Non-unique index
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}
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DBUG_ASSERT(rec_per_key >= rec_per_key_all);
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}
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return rec_per_key;
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}
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