sql/sql_planner.cc (1,692 lines of code) (raw):
/* Copyright (c) 2000, 2016, Oracle and/or its affiliates. All rights reserved.
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; version 2 of the License.
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 for more details.
You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */
/**
@file
@brief
Create plan for a single select.
@defgroup Query_Planner Query Planner
@{
*/
#include "sql_planner.h"
#include "sql_optimizer.h"
#include "opt_range.h"
#include "opt_trace.h"
#include "sql_executor.h"
#include "merge_sort.h"
#include <my_bit.h>
#include <algorithm>
using std::max;
using std::min;
static double prev_record_reads(JOIN *join, uint idx, table_map found_ref);
static void trace_plan_prefix(JOIN *join, uint idx,
table_map excluded_tables);
/*
This is a class for considering possible loose index scan optimizations.
It's usage pattern is as follows:
best_access_path()
{
Loose_scan_opt opt;
opt.init()
for each index we can do ref access with
{
opt.next_ref_key();
for each keyuse
opt.add_keyuse();
opt.check_ref_access_part1();
opt.check_ref_access_part2();
}
if (some criteria for range scans)
opt.check_range_access();
opt.save_to_position();
}
*/
class Loose_scan_opt
{
private:
/* All methods must check this before doing anything else */
bool try_loosescan;
/*
If we consider (oe1, .. oeN) IN (SELECT ie1, .. ieN) then ieK=oeK is
called sj-equality. If oeK depends only on preceding tables then such
equality is called 'bound'.
*/
ulonglong bound_sj_equalities;
/* Accumulated properties of ref access we're now considering: */
ulonglong handled_sj_equalities;
key_part_map loose_scan_keyparts;
/**
Biggest index (starting at 0) of keyparts used for the "handled", not
"bound", equalities.
*/
uint max_loose_keypart;
bool part1_conds_met;
/*
Use of quick select is a special case. Some of its properties:
*/
uint quick_uses_applicable_index;
uint quick_max_loose_keypart;
/* Best loose scan method so far */
uint best_loose_scan_key;
double best_loose_scan_cost;
double best_loose_scan_records;
Key_use *best_loose_scan_start_key;
uint best_max_loose_keypart;
public:
Loose_scan_opt() :
try_loosescan(FALSE),
quick_uses_applicable_index(FALSE)
{
/*
We needn't initialize:
bound_sj_equalities - protected by try_loosescan
quick_max_loose_keypart - protected by quick_uses_applicable_index
best_loose_scan_key - protected by best_loose_scan_cost != DBL_MAX
best_loose_scan_records - same
best_max_loose_keypart - same
best_loose_scan_start_key - same
Not initializing them causes compiler warnings with g++ at -O1 or higher,
but initializing them would cause a 2% CPU time loss in a 20-table plan
search. So we initialize only if warnings would stop the build.
*/
#ifdef COMPILE_FLAG_WERROR
bound_sj_equalities= 0;
quick_max_loose_keypart= 0;
best_loose_scan_key= 0;
best_loose_scan_records= 0;
best_max_loose_keypart= 0;
best_loose_scan_start_key= NULL;
#endif
}
void init(JOIN_TAB *s, table_map remaining_tables,
bool in_dups_producing_range, bool is_sjm_nest)
{
/*
We may consider the LooseScan strategy if
1. The next table is an SJ-inner table, and
2, We have no more than 64 IN expressions (must fit in bitmap), and
3. It is the first table from that semijoin, and
4. We're not within a semi-join range (i.e. all semi-joins either have
all or none of their tables in join_table_map), except
s->emb_sj_nest (which we've just entered, see #2), and
5. All non-IN-equality correlation references from this sj-nest are
bound, and
6. But some of the IN-equalities aren't (so this can't be handled by
FirstMatch strategy), and
7. LooseScan is not disabled, and
8. Not a derived table/view. (a temporary restriction)
*/
best_loose_scan_cost= DBL_MAX;
if (s->emb_sj_nest && !is_sjm_nest && // (1)
s->emb_sj_nest->nested_join->sj_inner_exprs.elements <= 64 && // (2)
((remaining_tables & s->emb_sj_nest->sj_inner_tables) == // (3)
s->emb_sj_nest->sj_inner_tables) && // (3)
!in_dups_producing_range && // (4)
!(remaining_tables &
s->emb_sj_nest->nested_join->sj_corr_tables) && // (5)
(remaining_tables & s->emb_sj_nest->nested_join->sj_depends_on) && //(6)
s->join->thd->optimizer_switch_flag(OPTIMIZER_SWITCH_LOOSE_SCAN) &&//(7)
!s->table->pos_in_table_list->uses_materialization()) // (8)
{
try_loosescan= true; // This table is a LooseScan scan candidate
bound_sj_equalities= 0; // These equalities are populated later
DBUG_PRINT("info", ("Will try LooseScan scan"));
}
}
void next_ref_key()
{
handled_sj_equalities=0;
loose_scan_keyparts= 0;
max_loose_keypart= 0;
part1_conds_met= FALSE;
}
void add_keyuse(table_map remaining_tables, Key_use *keyuse)
{
if (try_loosescan && keyuse->sj_pred_no != UINT_MAX)
{
if (!(remaining_tables & keyuse->used_tables))
{
/*
This allows to use equality propagation to infer that some
sj-equalities are bound.
*/
bound_sj_equalities |= 1ULL << keyuse->sj_pred_no;
}
else
{
handled_sj_equalities |= 1ULL << keyuse->sj_pred_no;
loose_scan_keyparts |= ((key_part_map)1) << keyuse->keypart;
set_if_bigger(max_loose_keypart, keyuse->keypart);
}
}
}
bool have_a_case() { return MY_TEST(handled_sj_equalities); }
/**
Check if an index can be used for LooseScan, part 1
@param s The join_tab we are checking
@param key The key being checked for the associated table
@param start_key First applicable keyuse for this key.
@param bound_keyparts The key columns determined for this index, ie.
found in earlier tables in plan.
*/
void check_ref_access_part1(JOIN_TAB *s, uint key, Key_use *start_key,
key_part_map bound_keyparts)
{
/*
Check if we can use LooseScan semi-join strategy. We can if
1. This is the right table at right location
2. All IN-equalities are either
- "bound", ie. the outer_expr part refers to the preceding tables
- "handled", ie. covered by the index we're considering
3. Index order allows to enumerate subquery's duplicate groups in
order. This happens when the index columns are defined in an order
that matches this pattern:
(handled_col|bound_col)* (other_col|bound_col)
4. No keys are defined over a partial column
*/
if (try_loosescan && // (1)
(handled_sj_equalities | bound_sj_equalities) == // (2)
LOWER_BITS(ulonglong,
s->emb_sj_nest->nested_join->sj_inner_exprs.elements) && // (2)
(LOWER_BITS(key_part_map, max_loose_keypart+1) & // (3)
~(bound_keyparts | loose_scan_keyparts)) == 0 && // (3)
!key_uses_partial_cols(s->table, key)) // (4)
{
/* Ok, can use the strategy */
part1_conds_met= TRUE;
if (s->quick && s->quick->index == key &&
s->quick->get_type() == QUICK_SELECT_I::QS_TYPE_RANGE)
{
quick_uses_applicable_index= TRUE;
quick_max_loose_keypart= max_loose_keypart;
}
DBUG_PRINT("info", ("Can use LooseScan scan"));
/*
Check if this is a confluent where there are no usable bound
IN-equalities, e.g. we have
outer_expr IN (SELECT innertbl.key FROM ...)
and outer_expr cannot be evaluated yet, so it's actually full
index scan and not a ref access
*/
if (!(bound_keyparts & 1 ) && /* no usable ref access for 1st key part */
s->table->covering_keys.is_set(key))
{
DBUG_PRINT("info", ("Can use full index scan for LooseScan"));
/* Calculate the cost of complete loose index scan. */
double records= rows2double(s->table->file->stats.records);
/* The cost is entire index scan cost (divided by 2) */
double read_time= s->table->file->index_only_read_time(key, records);
/*
Now find out how many different keys we will get (for now we
ignore the fact that we have "keypart_i=const" restriction for
some key components, that may make us think think that loose
scan will produce more distinct records than it actually will)
*/
ulong rpc;
if ((rpc= s->table->key_info[key].rec_per_key[max_loose_keypart]))
records= records / rpc;
// TODO: previous version also did /2
if (read_time < best_loose_scan_cost)
{
best_loose_scan_key= key;
best_loose_scan_cost= read_time;
best_loose_scan_records= records;
best_max_loose_keypart= max_loose_keypart;
best_loose_scan_start_key= start_key;
}
}
}
}
/**
Check if ref access can be used for LooseScan, part 2
Record this LooseScan index if it is cheaper than the currently
cheapest LooseScan index.
@note Actually ref access is not used by LooseScan:
JOIN::set_access_methods() always sets up a index/range scan.
@param key The key being checked for the associated table
@param start_key First applicable keyuse for this key.
@param records Row count estimate for this index access
@param read_time Cost of access using this index
*/
void check_ref_access_part2(uint key, Key_use *start_key, double records,
double read_time)
{
if (part1_conds_met && read_time < best_loose_scan_cost)
{
/* TODO use rec-per-key-based fanout calculations */
best_loose_scan_key= key;
best_loose_scan_cost= read_time;
best_loose_scan_records= records;
best_max_loose_keypart= max_loose_keypart;
best_loose_scan_start_key= start_key;
}
}
void check_range_access(JOIN *join, uint idx, QUICK_SELECT_I *quick)
{
/* TODO: this the right part restriction: */
if (quick_uses_applicable_index && idx == join->const_tables &&
quick->read_time < best_loose_scan_cost)
{
best_loose_scan_key= quick->index;
best_loose_scan_cost= quick->read_time;
/* this is ok because idx == join->const_tables */
best_loose_scan_records= rows2double(quick->records);
best_max_loose_keypart= quick_max_loose_keypart;
best_loose_scan_start_key= NULL;
}
}
void save_to_position(JOIN_TAB *tab, POSITION *pos)
{
pos->read_time= best_loose_scan_cost;
if (best_loose_scan_cost != DBL_MAX)
{
pos->records_read= best_loose_scan_records;
pos->key= best_loose_scan_start_key;
pos->loosescan_key= best_loose_scan_key;
pos->loosescan_parts= best_max_loose_keypart + 1;
pos->use_join_buffer= FALSE;
pos->table= tab;
// todo need ref_depend_map ?
DBUG_PRINT("info", ("Produced a LooseScan plan, key %s, %s",
tab->table->key_info[best_loose_scan_key].name,
best_loose_scan_start_key? "(ref access)":
"(range/index access)"));
}
}
};
static uint
max_part_bit(key_part_map bits)
{
uint found;
for (found=0; bits & 1 ; found++,bits>>=1) ;
return found;
}
static uint
cache_record_length(JOIN *join,uint idx)
{
uint length=0;
JOIN_TAB **pos,**end;
THD *thd=join->thd;
for (pos=join->best_ref+join->const_tables,end=join->best_ref+idx ;
pos != end ;
pos++)
{
JOIN_TAB *join_tab= *pos;
if (!join_tab->used_fieldlength) /* Not calced yet */
calc_used_field_length(thd, join_tab);
length+=join_tab->used_fieldlength;
}
return length;
}
/**
Find the best access path for an extension of a partial execution
plan and add this path to the plan.
The function finds the best access path to table 's' from the passed
partial plan where an access path is the general term for any means to
access the data in 's'. An access path may use either an index or a scan,
whichever is cheaper. The input partial plan is passed via the array
'join->positions' of length 'idx'. The chosen access method for 's' and its
cost are stored in 'join->positions[idx]'.
@param s the table to be joined by the function
@param thd thread for the connection that submitted the query
@param remaining_tables set of tables not included in the partial plan yet.
@param idx the length of the partial plan
@param disable_jbuf TRUE<=> Don't use join buffering
@param record_count estimate for the number of records returned by the
partial plan
@param[out] pos Table access plan
@param[out] loose_scan_pos Table plan that uses loosescan, or set cost to
DBL_MAX if not possible.
*/
void Optimize_table_order::best_access_path(
JOIN_TAB *s,
table_map remaining_tables,
uint idx,
bool disable_jbuf,
double record_count,
POSITION *pos,
POSITION *loose_scan_pos)
{
Key_use *best_key= NULL;
uint best_max_key_part= 0;
bool found_constraint= false;
double best= DBL_MAX;
double best_time= DBL_MAX;
double records= DBL_MAX;
table_map best_ref_depends_map= 0;
double tmp;
bool best_uses_jbuf= false;
Opt_trace_context * const trace= &thd->opt_trace;
status_var_increment(thd->status_var.last_query_partial_plans);
/*
Cannot use join buffering if either
1. This is the first table in the join sequence, or
2. Join buffering is not enabled
(Only Block Nested Loop is considered in this context)
*/
disable_jbuf= disable_jbuf ||
idx == join->const_tables || // 1
!thd->optimizer_switch_flag(OPTIMIZER_SWITCH_BNL); // 2
Loose_scan_opt loose_scan_opt;
DBUG_ENTER("Optimize_table_order::best_access_path");
Opt_trace_object trace_wrapper(trace, "best_access_path");
Opt_trace_array trace_paths(trace, "considered_access_paths");
{
/*
Loose-scan specific-logic:
- we must decide whether this is within the dups_producing range.
- if 'pos' is within the JOIN::positions array, then decide this
by using the pos[-1] entry.
- if 'pos' is not in the JOIN::position array then
in_dups_producing_range must be false (this case may occur in
semijoin_*_access_paths() which calls best_access_path() with 'pos'
allocated on the stack).
@todo One day Loose-scan will be considered in advance_sj_state() only,
outside best_access_path(), so this complicated logic will not be
needed.
*/
const bool in_dups_producing_range=
(idx == join->const_tables) ?
false :
(pos == (join->positions + idx) ?
(pos[-1].dups_producing_tables != 0) :
false);
loose_scan_opt.init(s, remaining_tables, in_dups_producing_range,
emb_sjm_nest != NULL);
}
/*
This isn't unlikely at all, but unlikely() cuts 6% CPU time on a 20-table
search when s->keyuse==0, and has no cost when s->keyuse!=0.
*/
if (unlikely(s->keyuse != NULL))
{ /* Use key if possible */
TABLE *const table= s->table;
double best_records= DBL_MAX;
/* Test how we can use keys */
ha_rows rec=
s->records/MATCHING_ROWS_IN_OTHER_TABLE; // Assumed records/key
for (Key_use *keyuse=s->keyuse; keyuse->table == table; )
{
key_part_map found_part= 0;
table_map found_ref= 0;
const uint key= keyuse->key;
uint max_key_part= 0;
KEY *const keyinfo= table->key_info+key;
const bool ft_key= (keyuse->keypart == FT_KEYPART);
/* Bitmap of keyparts where the ref access is over 'keypart=const': */
key_part_map const_part= 0;
/* The or-null keypart in ref-or-null access: */
key_part_map ref_or_null_part= 0;
/// Set dodgy_ref_cost only if that index is chosen for ref access.
bool is_dodgy= false;
/* Calculate how many key segments of the current key we can use */
Key_use *const start_key= keyuse;
loose_scan_opt.next_ref_key();
DBUG_PRINT("info", ("Considering ref access on key %s",
keyuse->table->key_info[keyuse->key].name));
Opt_trace_object trace_access_idx(trace);
trace_access_idx.add_alnum("access_type", "ref").
add_utf8("index", keyinfo->name);
// For each keypart
while (keyuse->table == table && keyuse->key == key)
{
const uint keypart= keyuse->keypart;
table_map best_part_found_ref= 0;
double best_prev_record_reads= DBL_MAX;
// For each way to access the keypart
for ( ; keyuse->table == table && keyuse->key == key &&
keyuse->keypart == keypart ; ++keyuse)
{
/*
When calculating a plan for a materialized semijoin nest,
we must not consider key references between tables inside the
semijoin nest and those outside of it. The same applies to a
materialized subquery.
*/
if ((excluded_tables & keyuse->used_tables))
continue;
/*
if 1. expression doesn't refer to forward tables
2. we won't get two ref-or-null's
*/
if (!(remaining_tables & keyuse->used_tables) &&
!(ref_or_null_part && (keyuse->optimize &
KEY_OPTIMIZE_REF_OR_NULL)))
{
found_part|= keyuse->keypart_map;
if (!(keyuse->used_tables & ~join->const_table_map))
const_part|= keyuse->keypart_map;
double tmp2= prev_record_reads(join, idx, (found_ref |
keyuse->used_tables));
if (tmp2 < best_prev_record_reads)
{
best_part_found_ref= keyuse->used_tables & ~join->const_table_map;
best_prev_record_reads= tmp2;
}
if (rec > keyuse->ref_table_rows)
rec= keyuse->ref_table_rows;
/*
If there is one 'key_column IS NULL' expression, we can
use this ref_or_null optimisation of this field
*/
if (keyuse->optimize & KEY_OPTIMIZE_REF_OR_NULL)
ref_or_null_part |= keyuse->keypart_map;
}
loose_scan_opt.add_keyuse(remaining_tables, keyuse);
}
found_ref|= best_part_found_ref;
}
/*
Assume that that each key matches a proportional part of table.
*/
if (!found_part && !ft_key && !loose_scan_opt.have_a_case())
{
trace_access_idx.add("usable", false);
goto done_with_index; // Nothing usable found
}
if (rec < MATCHING_ROWS_IN_OTHER_TABLE)
rec= MATCHING_ROWS_IN_OTHER_TABLE; // Fix for small tables
/*
ft-keys require special treatment
*/
if (ft_key)
{
/*
Really, there should be records=0.0 (yes!)
but 1.0 would be probably safer
*/
tmp= prev_record_reads(join, idx, found_ref);
records= 1.0;
}
else
{
found_constraint= MY_TEST(found_part);
loose_scan_opt.check_ref_access_part1(s, key, start_key, found_part);
/* Check if we found full key */
if (found_part == LOWER_BITS(key_part_map, actual_key_parts(keyinfo)) &&
!ref_or_null_part)
{ /* use eq key */
max_key_part= (uint) ~0;
if ((keyinfo->flags & (HA_NOSAME | HA_NULL_PART_KEY)) == HA_NOSAME)
{
tmp = prev_record_reads(join, idx, found_ref);
records=1.0;
}
else
{
if (!found_ref)
{ /* We found a const key */
/*
ReuseRangeEstimateForRef-1:
We get here if we've found a ref(const) (c_i are constants):
"(keypart1=c1) AND ... AND (keypartN=cN)" [ref_const_cond]
If range optimizer was able to construct a "range"
access on this index, then its condition "quick_cond" was
eqivalent to ref_const_cond (*), and we can re-use E(#rows)
from the range optimizer.
Proof of (*): By properties of range and ref optimizers
quick_cond will be equal or tighther than ref_const_cond.
ref_const_cond already covers "smallest" possible interval -
a singlepoint interval over all keyparts. Therefore,
quick_cond is equivalent to ref_const_cond (if it was an
empty interval we wouldn't have got here).
*/
if (table->quick_keys.is_set(key))
records= (double) table->quick_rows[key];
else
{
/* quick_range couldn't use key! */
records= (double) s->records/rec;
}
}
else
{
if (!(records= keyinfo->rec_per_key[actual_key_parts(keyinfo)-1]))
{ /* Prefer longer keys */
records=
((double) s->records / (double) rec *
(1.0 +
((double) (table->s->max_key_length-keyinfo->key_length) /
(double) table->s->max_key_length)));
if (records < 2.0)
records=2.0; /* Can't be as good as a unique */
}
/*
ReuseRangeEstimateForRef-2: We get here if we could not reuse
E(#rows) from range optimizer. Make another try:
If range optimizer produced E(#rows) for a prefix of the ref
access we're considering, and that E(#rows) is lower then our
current estimate, make an adjustment. The criteria of when we
can make an adjustment is a special case of the criteria used
in ReuseRangeEstimateForRef-3.
*/
if (table->quick_keys.is_set(key) &&
(const_part &
(((key_part_map)1 << table->quick_key_parts[key])-1)) ==
(((key_part_map)1 << table->quick_key_parts[key])-1) &&
table->quick_n_ranges[key] == 1 &&
records > (double) table->quick_rows[key])
{
records= (double) table->quick_rows[key];
}
}
/* Limit the number of matched rows */
tmp= records;
set_if_smaller(tmp, (double) thd->variables.max_seeks_for_key);
if (table->covering_keys.is_set(key))
{
/* we can use only index tree */
tmp= record_count * table->file->index_only_read_time(key, tmp);
}
else
tmp= record_count*min(tmp,s->worst_seeks);
}
}
else
{
/*
Use as much key-parts as possible and a uniq key is better
than a not unique key
Set tmp to (previous record count) * (records / combination)
*/
if ((found_part & 1) &&
(!(table->file->index_flags(key, 0, 0) & HA_ONLY_WHOLE_INDEX) ||
found_part == LOWER_BITS(key_part_map,
actual_key_parts(keyinfo))))
{
max_key_part= max_part_bit(found_part);
/*
ReuseRangeEstimateForRef-3:
We're now considering a ref[or_null] access via
(t.keypart1=e1 AND ... AND t.keypartK=eK) [ OR
(same-as-above but with one cond replaced
with "t.keypart_i IS NULL")] (**)
Try re-using E(#rows) from "range" optimizer:
We can do so if "range" optimizer used the same intervals as
in (**). The intervals used by range optimizer may be not
available at this point (as "range" access might have choosen to
create quick select over another index), so we can't compare
them to (**). We'll make indirect judgements instead.
The sufficient conditions for re-use are:
(C1) All e_i in (**) are constants, i.e. found_ref==FALSE. (if
this is not satisfied we have no way to know which ranges
will be actually scanned by 'ref' until we execute the
join)
(C2) max #key parts in 'range' access == K == max_key_part (this
is apparently a necessary requirement)
We also have a property that "range optimizer produces equal or
tighter set of scan intervals than ref(const) optimizer". Each
of the intervals in (**) are "tightest possible" intervals when
one limits itself to using keyparts 1..K (which we do in #2).
From here it follows that range access used either one, or
both of the (I1) and (I2) intervals:
(t.keypart1=c1 AND ... AND t.keypartK=eK) (I1)
(same-as-above but with one cond replaced
with "t.keypart_i IS NULL") (I2)
The remaining part is to exclude the situation where range
optimizer used one interval while we're considering
ref-or-null and looking for estimate for two intervals. This
is done by last limitation:
(C3) "range optimizer used (have ref_or_null?2:1) intervals"
*/
if (table->quick_keys.is_set(key) && !found_ref && //(C1)
table->quick_key_parts[key] == max_key_part && //(C2)
table->quick_n_ranges[key] == 1+MY_TEST(ref_or_null_part)) //(C3)
{
tmp= records= (double) table->quick_rows[key];
}
else
{
/* Check if we have statistic about the distribution */
if ((records= keyinfo->rec_per_key[max_key_part-1]))
{
/*
Fix for the case where the index statistics is too
optimistic: If
(1) We're considering ref(const) and there is quick select
on the same index,
(2) and that quick select uses more keyparts (i.e. it will
scan equal/smaller interval then this ref(const))
(3) and E(#rows) for quick select is higher then our
estimate,
Then
We'll use E(#rows) from quick select.
One observation is that when there are multiple
indexes with a common prefix (eg (b) and (b, c)) we
are not always selecting (b, c) even when this can
use more keyparts. Inaccuracies in statistics from
the storage engines can cause the record estimate
for the quick object for (b) to be lower than the
record estimate for the quick object for (b,c).
Q: Why do we choose to use 'ref'? Won't quick select be
cheaper in some cases ?
TODO: figure this out and adjust the plan choice if needed.
*/
if (!found_ref && table->quick_keys.is_set(key) && // (1)
table->quick_key_parts[key] > max_key_part && // (2)
records < (double)table->quick_rows[key]) // (3)
{
records= (double)table->quick_rows[key];
is_dodgy= true;
}
tmp= records;
}
else
{
/*
Assume that the first key part matches 1% of the file
and that the whole key matches 10 (duplicates) or 1
(unique) records.
Assume also that more key matches proportionally more
records
This gives the formula:
records = (x * (b-a) + a*c-b)/(c-1)
b = records matched by whole key
a = records matched by first key part (1% of all records?)
c = number of key parts in key
x = used key parts (1 <= x <= c)
*/
double rec_per_key;
if (!(rec_per_key=(double)
keyinfo->rec_per_key[keyinfo->user_defined_key_parts-1]))
rec_per_key=(double) s->records/rec+1;
if (!s->records)
tmp = 0;
else if (rec_per_key/(double) s->records >= 0.01)
tmp = rec_per_key;
else
{
double a=s->records*0.01;
if (keyinfo->user_defined_key_parts > 1)
tmp= (max_key_part * (rec_per_key - a) +
a * keyinfo->user_defined_key_parts - rec_per_key) /
(keyinfo->user_defined_key_parts - 1);
else
tmp= a;
set_if_bigger(tmp,1.0);
}
records = (ulong) tmp;
}
if (ref_or_null_part)
{
/* We need to do two key searches to find key */
tmp *= 2.0;
records *= 2.0;
}
/*
ReuseRangeEstimateForRef-4: We get here if we could not reuse
E(#rows) from range optimizer. Make another try:
If range optimizer produced E(#rows) for a prefix of the ref
access we're considering, and that E(#rows) is lower then our
current estimate, make the adjustment.
The decision whether we can re-use the estimate from the range
optimizer is the same as in ReuseRangeEstimateForRef-3,
applied to first table->quick_key_parts[key] key parts.
*/
if (table->quick_keys.is_set(key) &&
table->quick_key_parts[key] <= max_key_part &&
const_part &
((key_part_map)1 << table->quick_key_parts[key]) &&
table->quick_n_ranges[key] == 1 + MY_TEST(ref_or_null_part &
const_part) &&
records > (double) table->quick_rows[key])
{
tmp= records= (double) table->quick_rows[key];
}
}
/* Limit the number of matched rows */
set_if_smaller(tmp, (double) thd->variables.max_seeks_for_key);
if (table->covering_keys.is_set(key))
{
/* we can use only index tree */
tmp= record_count * table->file->index_only_read_time(key, tmp);
}
else
tmp= record_count * min(tmp,s->worst_seeks);
}
else
tmp= best_time; // Do nothing
}
// {semijoin LooseScan + ref} is disabled
#if 0
loose_scan_opt.check_ref_access_part2(key, start_key, records, tmp);
#endif
} /* not ft_key */
{
const double idx_time= tmp + records * ROW_EVALUATE_COST;
trace_access_idx.add("rows", records).add("cost", idx_time);
if (idx_time < best_time)
{
best_time= idx_time;
best= tmp;
best_records= records;
best_key= start_key;
best_max_key_part= max_key_part;
best_ref_depends_map= found_ref;
}
}
done_with_index:
bool chosen= (best_key == start_key);
trace_access_idx.add("chosen", chosen);
if (chosen)
s->dodgy_ref_cost= is_dodgy;
} /* for each key */
records= best_records;
}
Opt_trace_object trace_access_scan(trace);
/*
Don't test table scan if it can't be better.
Prefer key lookup if we would use the same key for scanning.
Don't do a table scan on InnoDB tables, if we can read the used
parts of the row from any of the used index.
This is because table scans uses index and we would not win
anything by using a table scan. The only exception is INDEX_MERGE
quick select. We can not say for sure that INDEX_MERGE quick select
is always faster than ref access. So it's necessary to check if
ref access is more expensive.
A word for word translation of the below if-statement in sergefp's
understanding: we check if we should use table scan if:
(1) The found 'ref' access produces more records than a table scan
(or index scan, or quick select), or 'ref' is more expensive than
any of them.
(2) The best way to perform table or index scan is to use 'range' access
using index IDX. If it is a 'tight range' scan (i.e not a loose index
scan' or 'index merge'), then ref access on the same index will
perform equal or better if ref access can use the same or more number
of key parts.
(3) See above note about InnoDB.
(4) NOT ("FORCE INDEX(...)" is used for table and there is 'ref' access
path, but there is no quick select)
If the condition in the above brackets holds, then the only possible
"table scan" access method is ALL/index (there is no quick select).
Since we have a 'ref' access path, and FORCE INDEX instructs us to
choose it over ALL/index, there is no need to consider a full table
scan.
*/
if (!(records >= s->found_records || best > s->read_time)) // (1)
{
// "scan" means (full) index scan or (full) table scan.
trace_access_scan.add_alnum("access_type", s->quick ? "range" : "scan").
add("cost", s->read_time + s->found_records * ROW_EVALUATE_COST).
add("rows", s->found_records).
add_alnum("cause", "cost");
goto skip_table_scan;
}
if ((s->quick && best_key && s->quick->index == best_key->key && // (2)
best_max_key_part >= s->table->quick_key_parts[best_key->key]) && // (2)
(s->quick->get_type() !=
QUICK_SELECT_I::QS_TYPE_GROUP_MIN_MAX) && // (2)
(s->quick->get_type() !=
QUICK_SELECT_I::QS_TYPE_SKIP_SCAN)) // (2)
{
trace_access_scan.add_alnum("access_type", "range").
add_alnum("cause", "heuristic_index_cheaper");
goto skip_table_scan;
}
if ((s->table->file->ha_table_flags() & HA_TABLE_SCAN_ON_INDEX) && //(3)
best_key && //(3)
(!s->table->covering_keys.is_clear_all() ||
(s->table->file->primary_key_is_clustered() &&
s->table->s->primary_key == best_key->key)) && //(3)
(!s->quick || //(3)
(s->quick->get_type() == QUICK_SELECT_I::QS_TYPE_ROR_INTERSECT &&//(3)
best < s->quick->read_time))) //(3)
{
trace_access_scan.add_alnum("access_type", s->quick ? "range" : "scan").
add_alnum("cause", "covering_index_better_than_full_scan");
goto skip_table_scan;
}
if ((s->table->force_index && best_key && !s->quick)) // (4)
{
trace_access_scan.add_alnum("access_type", "scan").
add_alnum("cause", "force_index");
goto skip_table_scan;
}
{ // Check full join
ha_rows rnd_records= s->found_records;
/*
If there is a filtering condition on the table (i.e. ref analyzer found
at least one "table.keyXpartY= exprZ", where exprZ refers only to tables
preceding this table in the join order we're now considering), then
assume that 25% of the rows will be filtered out by this condition.
This heuristic is supposed to force tables used in exprZ to be before
this table in join order.
*/
if (found_constraint)
rnd_records-= rnd_records/4;
/*
If applicable, get a more accurate estimate. Don't use the two
heuristics at once.
*/
if (s->table->quick_condition_rows != s->found_records)
rnd_records= s->table->quick_condition_rows;
/*
Range optimizer never proposes a RANGE if it isn't better
than FULL: so if RANGE is present, it's always preferred to FULL.
Here we estimate its cost.
*/
if (s->quick)
{
trace_access_scan.add_alnum("access_type", "range");
/*
For each record we:
- read record range through 'quick'
- skip rows which does not satisfy WHERE constraints
TODO:
We take into account possible use of join cache for ALL/index
access (see first else-branch below), but we don't take it into
account here for range/index_merge access. Find out why this is so.
*/
tmp= record_count *
(s->quick->read_time +
(s->found_records - rnd_records) * ROW_EVALUATE_COST);
loose_scan_opt.check_range_access(join, idx, s->quick);
}
else
{
trace_access_scan.add_alnum("access_type", "scan");
/* Estimate cost of reading table. */
if (s->table->force_index && !best_key) // index scan
tmp= s->table->file->read_time(s->ref.key, 1, s->records);
else // table scan
tmp= s->table->file->scan_time();
if (disable_jbuf)
{
/*
For each record we have to:
- read the whole table record
- skip rows which does not satisfy join condition
*/
tmp= record_count *
(tmp + (s->records - rnd_records) * ROW_EVALUATE_COST);
}
else
{
trace_access_scan.add("using_join_cache", true);
/*
We read the table as many times as join buffer becomes full.
It would be more exact to round the result of the division with
floor(), but that takes 5% of time in a 20-table query plan search.
*/
tmp*= (1.0 + ((double) cache_record_length(join,idx) *
record_count /
(double) thd->variables.join_buff_size));
/*
We don't make full cartesian product between rows in the scanned
table and existing records because we skip all rows from the
scanned table, which does not satisfy join condition when
we read the table (see flush_cached_records for details). Here we
take into account cost to read and skip these records.
*/
tmp+= (s->records - rnd_records) * ROW_EVALUATE_COST;
}
}
const double scan_cost=
tmp + (record_count * ROW_EVALUATE_COST * rnd_records);
trace_access_scan.add("rows", rows2double(rnd_records)).
add("cost", scan_cost);
/*
We estimate the cost of evaluating WHERE clause for found records
as record_count * rnd_records * ROW_EVALUATE_COST. This cost plus
tmp give us total cost of using TABLE SCAN
*/
if (best == DBL_MAX ||
(scan_cost < best + (record_count * ROW_EVALUATE_COST * records)))
{
/*
If the table has a range (s->quick is set) make_join_select()
will ensure that this will be used
*/
best= tmp;
records= rows2double(rnd_records);
best_key= 0;
/* range/index_merge/ALL/index access method are "independent", so: */
best_ref_depends_map= 0;
best_uses_jbuf= MY_TEST(!disable_jbuf);
}
}
skip_table_scan:
trace_access_scan.add("chosen", best_key == NULL);
/* Update the cost information for the current partial plan */
pos->records_read= records;
pos->read_time= best;
pos->key= best_key;
pos->table= s;
pos->ref_depend_map= best_ref_depends_map;
pos->loosescan_key= MAX_KEY;
pos->use_join_buffer= best_uses_jbuf;
loose_scan_opt.save_to_position(s, loose_scan_pos);
if (!best_key &&
idx == join->const_tables &&
s->table == join->sort_by_table &&
join->unit->select_limit_cnt >= records)
{
trace_access_scan.add("use_tmp_table", true);
join->sort_by_table= (TABLE*) 1; // Must use temporary table
}
DBUG_VOID_RETURN;
}
/**
Selects and invokes a search strategy for an optimal query join order.
The function checks user-configurable parameters that control the search
strategy for an optimal plan, selects the search method and then invokes
it. Each specific optimization procedure stores the final optimal plan in
the array 'join->best_positions', and the cost of the plan in
'join->best_read'.
The function can be invoked to produce a plan for all tables in the query
(in this case, the const tables are usually filtered out), or it can be
invoked to produce a plan for a materialization of a semijoin nest.
Set a non-NULL emb_sjm_nest pointer when producing a plan for a semijoin
nest to be materialized and a NULL pointer when producing a full query plan.
@return false if successful, true if error
*/
bool Optimize_table_order::choose_table_order()
{
DBUG_ENTER("Optimize_table_order::choose_table_order");
/* Are there any tables to optimize? */
if (join->const_tables == join->tables)
{
memcpy(join->best_positions, join->positions,
sizeof(POSITION) * join->const_tables);
join->best_read= 1.0;
join->best_rowcount= 1;
DBUG_RETURN(false);
}
reset_nj_counters(join->join_list);
const bool straight_join= MY_TEST(join->select_options & SELECT_STRAIGHT_JOIN);
table_map join_tables; ///< The tables involved in order selection
if (emb_sjm_nest)
{
/* We're optimizing semi-join materialization nest, so put the
tables from this semi-join as first
*/
merge_sort(join->best_ref + join->const_tables,
join->best_ref + join->tables,
Join_tab_compare_embedded_first(emb_sjm_nest));
join_tables= emb_sjm_nest->sj_inner_tables;
}
else
{
/*
if (SELECT_STRAIGHT_JOIN option is set)
reorder tables so dependent tables come after tables they depend
on, otherwise keep tables in the order they were specified in the query
else
Apply heuristic: pre-sort all access plans with respect to the number of
records accessed.
*/
if (straight_join)
merge_sort(join->best_ref + join->const_tables,
join->best_ref + join->tables,
Join_tab_compare_straight());
else
merge_sort(join->best_ref + join->const_tables,
join->best_ref + join->tables,
Join_tab_compare_default());
join_tables= join->all_table_map & ~join->const_table_map;
}
Opt_trace_object wrapper(&join->thd->opt_trace);
Opt_trace_array
trace_plan(&join->thd->opt_trace, "considered_execution_plans",
Opt_trace_context::GREEDY_SEARCH);
if (straight_join)
optimize_straight_join(join_tables);
else
{
if (greedy_search(join_tables))
DBUG_RETURN(true);
}
// Remaining part of this function not needed when processing semi-join nests.
if (emb_sjm_nest)
DBUG_RETURN(false);
// Fix semi-join strategies and perform final cost calculation.
if (fix_semijoin_strategies())
DBUG_RETURN(true);
DBUG_RETURN(false);
}
/**
Heuristic procedure to automatically guess a reasonable degree of
exhaustiveness for the greedy search procedure.
The procedure estimates the optimization time and selects a search depth
big enough to result in a near-optimal QEP, that doesn't take too long to
find. If the number of tables in the query exceeds some constant, then
search_depth is set to this constant.
@param search_depth Search depth value specified.
If zero, calculate a default value.
@param table_count Number of tables to be optimized (excludes const tables)
@note
This is an extremely simplistic implementation that serves as a stub for a
more advanced analysis of the join. Ideally the search depth should be
determined by learning from previous query optimizations, because it will
depend on the CPU power (and other factors).
@todo
this value should be determined dynamically, based on statistics:
uint max_tables_for_exhaustive_opt= 7;
@todo
this value could be determined by some mapping of the form:
depth : table_count -> [max_tables_for_exhaustive_opt..MAX_EXHAUSTIVE]
@return
A positive integer that specifies the search depth (and thus the
exhaustiveness) of the depth-first search algorithm used by
'greedy_search'.
*/
uint Optimize_table_order::determine_search_depth(uint search_depth,
uint table_count)
{
if (search_depth > 0)
return search_depth;
/* TODO: this value should be determined dynamically, based on statistics: */
const uint max_tables_for_exhaustive_opt= 7;
if (table_count <= max_tables_for_exhaustive_opt)
search_depth= table_count+1; // use exhaustive for small number of tables
else
/*
TODO: this value could be determined by some mapping of the form:
depth : table_count -> [max_tables_for_exhaustive_opt..MAX_EXHAUSTIVE]
*/
search_depth= max_tables_for_exhaustive_opt; // use greedy search
return search_depth;
}
/**
Select the best ways to access the tables in a query without reordering them.
Find the best access paths for each query table and compute their costs
according to their order in the array 'join->best_ref' (thus without
reordering the join tables). The function calls sequentially
'best_access_path' for each table in the query to select the best table
access method. The final optimal plan is stored in the array
'join->best_positions', and the corresponding cost in 'join->best_read'.
@param join_tables set of the tables in the query
@note
This function can be applied to:
- queries with STRAIGHT_JOIN
- internally to compute the cost of an arbitrary QEP
@par
Thus 'optimize_straight_join' can be used at any stage of the query
optimization process to finalize a QEP as it is.
*/
void Optimize_table_order::optimize_straight_join(table_map join_tables)
{
JOIN_TAB *s;
uint idx= join->const_tables;
double record_count= 1.0;
double read_time= 0.0;
Opt_trace_context * const trace= &join->thd->opt_trace;
for (JOIN_TAB **pos= join->best_ref + idx ; (s= *pos) ; pos++)
{
POSITION * const position= join->positions + idx;
Opt_trace_object trace_table(trace);
if (unlikely(trace->is_started()))
{
trace_plan_prefix(join, idx, excluded_tables);
trace_table.add_utf8_table(s->table);
}
/*
Dependency computation (make_join_statistics()) and proper ordering
based on them (join_tab_cmp*) guarantee that this order is compatible
with execution, check it:
*/
DBUG_ASSERT(!check_interleaving_with_nj(s));
/* Find the best access method from 's' to the current partial plan */
POSITION loose_scan_pos;
best_access_path(s, join_tables, idx, false, record_count,
position, &loose_scan_pos);
/* compute the cost of the new plan extended with 's' */
record_count*= position->records_read;
read_time+= position->read_time;
read_time+= record_count * ROW_EVALUATE_COST;
position->set_prefix_costs(read_time, record_count);
// see similar if() in best_extension_by_limited_search
if (!join->select_lex->sj_nests.is_empty())
advance_sj_state(join_tables, s, idx, &record_count, &read_time,
&loose_scan_pos);
else
position->no_semijoin();
trace_table.add("cost_for_plan", read_time).
add("rows_for_plan", record_count);
join_tables&= ~(s->table->map);
++idx;
}
if (join->sort_by_table &&
join->sort_by_table != join->positions[join->const_tables].table->table)
read_time+= record_count; // We have to make a temp table
memcpy(join->best_positions, join->positions, sizeof(POSITION)*idx);
/**
* If many plans have identical cost, which one will be used
* depends on how compiler optimizes floating-point calculations.
* this fix adds repeatability to the optimizer.
* (Similar code in best_extension_by_li...)
*/
join->best_read= read_time - 0.001;
join->best_rowcount= (ha_rows)record_count;
}
/**
Check whether a semijoin materialization strategy is allowed for
the current (semi)join table order.
@param join Join object
@param remaining_tables Tables that have not yet been added to the join plan
@param tab Join tab of the table being considered
@param idx Index of table with join tab "tab"
@retval SJ_OPT_NONE - Materialization not applicable
@retval SJ_OPT_MATERIALIZE_LOOKUP - Materialization with lookup applicable
@retval SJ_OPT_MATERIALIZE_SCAN - Materialization with scan applicable
@details
The function checks applicability of both MaterializeLookup and
MaterializeScan strategies.
No checking is made until "tab" is pointing to the last inner table
of a semijoin nest that can be executed using materialization -
for all other cases SJ_OPT_NONE is returned.
MaterializeLookup and MaterializeScan are both applicable in the following
two cases:
1. There are no correlated outer tables, or
2. There are correlated outer tables within the prefix only.
In this case, MaterializeLookup is returned based on a heuristic decision.
*/
static int
semijoin_order_allows_materialization(const JOIN *join,
table_map remaining_tables,
const JOIN_TAB *tab, uint idx)
{
DBUG_ASSERT(!(remaining_tables & tab->table->map));
/*
Check if
1. We're in a semi-join nest that can be run with SJ-materialization
2. All the tables from the subquery are in the prefix
*/
const TABLE_LIST *emb_sj_nest= tab->emb_sj_nest;
if (!emb_sj_nest ||
!emb_sj_nest->nested_join->sjm.positions ||
(remaining_tables & emb_sj_nest->sj_inner_tables))
return SJ_OPT_NONE;
/*
Walk back and check if all immediately preceding tables are from
this semi-join.
*/
const uint n_tables= my_count_bits(emb_sj_nest->sj_inner_tables);
for (uint i= 1; i < n_tables ; i++)
{
if (join->positions[idx - i].table->emb_sj_nest != emb_sj_nest)
return SJ_OPT_NONE;
}
/*
Must use MaterializeScan strategy if there are outer correlated tables
among the remaining tables, otherwise, if possible, use MaterializeLookup.
*/
if ((remaining_tables & emb_sj_nest->nested_join->sj_depends_on) ||
!emb_sj_nest->nested_join->sjm.lookup_allowed)
{
if (emb_sj_nest->nested_join->sjm.scan_allowed)
return SJ_OPT_MATERIALIZE_SCAN;
return SJ_OPT_NONE;
}
return SJ_OPT_MATERIALIZE_LOOKUP;
}
/**
Find a good, possibly optimal, query execution plan (QEP) by a greedy search.
The search procedure uses a hybrid greedy/exhaustive search with controlled
exhaustiveness. The search is performed in N = card(remaining_tables)
steps. Each step evaluates how promising is each of the unoptimized tables,
selects the most promising table, and extends the current partial QEP with
that table. Currenly the most 'promising' table is the one with least
expensive extension.\
There are two extreme cases:
-# When (card(remaining_tables) < search_depth), the estimate finds the
best complete continuation of the partial QEP. This continuation can be
used directly as a result of the search.
-# When (search_depth == 1) the 'best_extension_by_limited_search'
consideres the extension of the current QEP with each of the remaining
unoptimized tables.
All other cases are in-between these two extremes. Thus the parameter
'search_depth' controlls the exhaustiveness of the search. The higher the
value, the longer the optimizaton time and possibly the better the
resulting plan. The lower the value, the fewer alternative plans are
estimated, but the more likely to get a bad QEP.
All intermediate and final results of the procedure are stored in 'join':
- join->positions : modified for every partial QEP that is explored
- join->best_positions: modified for the current best complete QEP
- join->best_read : modified for the current best complete QEP
- join->best_ref : might be partially reordered
The final optimal plan is stored in 'join->best_positions', and its
corresponding cost in 'join->best_read'.
@note
The following pseudocode describes the algorithm of 'greedy_search':
@code
procedure greedy_search
input: remaining_tables
output: pplan;
{
pplan = <>;
do {
(t, a) = best_extension(pplan, remaining_tables);
pplan = concat(pplan, (t, a));
remaining_tables = remaining_tables - t;
} while (remaining_tables != {})
return pplan;
}
@endcode
where 'best_extension' is a placeholder for a procedure that selects the
most "promising" of all tables in 'remaining_tables'.
Currently this estimate is performed by calling
'best_extension_by_limited_search' to evaluate all extensions of the
current QEP of size 'search_depth', thus the complexity of 'greedy_search'
mainly depends on that of 'best_extension_by_limited_search'.
@par
If 'best_extension()' == 'best_extension_by_limited_search()', then the
worst-case complexity of this algorithm is <=
O(N*N^search_depth/search_depth). When serch_depth >= N, then the
complexity of greedy_search is O(N!).
'N' is the number of 'non eq_ref' tables + 'eq_ref groups' which normally
are considerable less than total numbers of tables in the query.
@par
In the future, 'greedy_search' might be extended to support other
implementations of 'best_extension'.
@par
@c search_depth from Optimize_table_order controls the exhaustiveness
of the search, and @c prune_level controls the pruning heuristics that
should be applied during search.
@param remaining_tables set of tables not included into the partial plan yet
@return false if successful, true if error
*/
bool Optimize_table_order::greedy_search(table_map remaining_tables)
{
double record_count= 1.0;
double read_time= 0.0;
uint idx= join->const_tables; // index into 'join->best_ref'
uint best_idx;
POSITION best_pos;
JOIN_TAB *best_table; // the next plan node to be added to the curr QEP
DBUG_ENTER("Optimize_table_order::greedy_search");
/* Number of tables that we are optimizing */
const uint n_tables= my_count_bits(remaining_tables);
/* Number of tables remaining to be optimized */
uint size_remain= n_tables;
do {
/* Find the extension of the current QEP with the lowest cost */
join->best_read= DBL_MAX;
join->best_rowcount= HA_POS_ERROR;
if (best_extension_by_limited_search(remaining_tables, idx,
record_count, read_time,
search_depth))
DBUG_RETURN(true);
/*
'best_read < DBL_MAX' means that optimizer managed to find
some plan and updated 'best_positions' array accordingly.
*/
DBUG_ASSERT(join->best_read < DBL_MAX);
if (size_remain <= search_depth)
{
/*
'join->best_positions' contains a complete optimal extension of the
current partial QEP.
*/
DBUG_EXECUTE("opt", print_plan(join, n_tables, record_count, read_time,
read_time, "optimal"););
DBUG_RETURN(false);
}
/* select the first table in the optimal extension as most promising */
best_pos= join->best_positions[idx];
best_table= best_pos.table;
/*
Each subsequent loop of 'best_extension_by_limited_search' uses
'join->positions' for cost estimates, therefore we have to update its
value.
*/
join->positions[idx]= best_pos;
/*
Search depth is smaller than the number of remaining tables to join.
- Update the interleaving state after extending the current partial plan
with a new table. We are doing this here because
best_extension_by_limited_search reverts the interleaving state to the
one of the non-extended partial plan on exit.
- The semi join state is entirely in POSITION, so it is transferred fine
when we copy POSITION objects (no special handling needed).
- After we have chosen the final plan covering all tables, the nested
join state will not be reverted back to its initial state because we
don't "pop" tables already present in the partial plan.
*/
bool is_interleave_error MY_ATTRIBUTE((unused))=
check_interleaving_with_nj (best_table);
/* This has been already checked by best_extension_by_limited_search */
DBUG_ASSERT(!is_interleave_error);
/* find the position of 'best_table' in 'join->best_ref' */
best_idx= idx;
JOIN_TAB *pos= join->best_ref[best_idx];
while (pos && best_table != pos)
pos= join->best_ref[++best_idx];
DBUG_ASSERT((pos != NULL)); // should always find 'best_table'
/*
Maintain '#rows-sorted' order of 'best_ref[]':
- Shift 'best_ref[]' to make first position free.
- Insert 'best_table' at the first free position in the array of joins.
*/
memmove(join->best_ref + idx + 1, join->best_ref + idx,
sizeof(JOIN_TAB*) * (best_idx - idx));
join->best_ref[idx]= best_table;
/* compute the cost of the new plan extended with 'best_table' */
record_count*= join->positions[idx].records_read;
read_time+= join->positions[idx].read_time
+ record_count * ROW_EVALUATE_COST;
remaining_tables&= ~(best_table->table->map);
--size_remain;
++idx;
DBUG_EXECUTE("opt", print_plan(join, idx, record_count, read_time,
read_time, "extended"););
} while (true);
}
/*
Calculate a cost of given partial join order
SYNOPSIS
get_partial_join_cost()
join IN Join to use. join->positions holds the
partial join order
n_tables IN # tables in the partial join order
read_time_arg OUT Store read time here
record_count_arg OUT Store record count here
DESCRIPTION
This is needed for semi-join materialization code. The idea is that
we detect sj-materialization after we've put all sj-inner tables into
the join prefix
prefix-tables semi-join-inner-tables tN
^--we're here
and we'll need to get the cost of prefix-tables prefix again.
*/
void get_partial_join_cost(JOIN *join, uint n_tables, double *read_time_arg,
double *record_count_arg)
{
double record_count= 1;
double read_time= 0.0;
for (uint i= join->const_tables; i < n_tables + join->const_tables ; i++)
{
if (join->best_positions[i].records_read)
{
record_count *= join->best_positions[i].records_read;
read_time += join->best_positions[i].read_time
+ record_count * ROW_EVALUATE_COST;
}
}
*read_time_arg= read_time;
*record_count_arg= record_count;
}
/**
Cost calculation of another (partial-)QEP has been completed.
If this is our 'best' plan explored so far, we record this
query plan and its cost.
@param idx length of the partial QEP in 'join->positions';
also corresponds to the current depth of the search tree;
also an index in the array 'join->best_ref';
@param record_count estimate for the number of records returned by the
best partial plan
@param read_time the cost of the best partial plan
@param trace_obj trace object where information is to be added
*/
void Optimize_table_order::consider_plan(uint idx,
double record_count,
double read_time,
Opt_trace_object *trace_obj)
{
/*
We may have to make a temp table, note that this is only a
heuristic since we cannot know for sure at this point.
Hence it may be too pesimistic.
*/
if (join->sort_by_table &&
join->sort_by_table !=
join->positions[join->const_tables].table->table)
{
read_time+= record_count;
trace_obj->add("sort_cost", record_count).
add("new_cost_for_plan", read_time);
}
const bool chosen= read_time < join->best_read;
trace_obj->add("chosen", chosen);
if (chosen)
{
memcpy((uchar*) join->best_positions, (uchar*) join->positions,
sizeof(POSITION) * (idx + 1));
/*
If many plans have identical cost, which one will be used
depends on how compiler optimizes floating-point calculations.
this fix adds repeatability to the optimizer.
(Similar code in best_extension_by_li...)
*/
join->best_read= read_time - 0.001;
join->best_rowcount= (ha_rows)record_count;
}
DBUG_EXECUTE("opt", print_plan(join, idx+1,
record_count,
read_time,
read_time,
"full_plan"););
}
/**
Find a good, possibly optimal, query execution plan (QEP) by a possibly
exhaustive search.
The procedure searches for the optimal ordering of the query tables in set
'remaining_tables' of size N, and the corresponding optimal access paths to
each table. The choice of a table order and an access path for each table
constitutes a query execution plan (QEP) that fully specifies how to
execute the query.
The maximal size of the found plan is controlled by the parameter
'search_depth'. When search_depth == N, the resulting plan is complete and
can be used directly as a QEP. If search_depth < N, the found plan consists
of only some of the query tables. Such "partial" optimal plans are useful
only as input to query optimization procedures, and cannot be used directly
to execute a query.
The algorithm begins with an empty partial plan stored in 'join->positions'
and a set of N tables - 'remaining_tables'. Each step of the algorithm
evaluates the cost of the partial plan extended by all access plans for
each of the relations in 'remaining_tables', expands the current partial
plan with the access plan that results in lowest cost of the expanded
partial plan, and removes the corresponding relation from
'remaining_tables'. The algorithm continues until it either constructs a
complete optimal plan, or constructs an optimal plartial plan with size =
search_depth.
The final optimal plan is stored in 'join->best_positions'. The
corresponding cost of the optimal plan is in 'join->best_read'.
@note
The procedure uses a recursive depth-first search where the depth of the
recursion (and thus the exhaustiveness of the search) is controlled by the
parameter 'search_depth'.
@note
The pseudocode below describes the algorithm of
'best_extension_by_limited_search'. The worst-case complexity of this
algorithm is O(N*N^search_depth/search_depth). When serch_depth >= N, then
the complexity of greedy_search is O(N!).
@note
::best_extension_by_limited_search() & ::eq_ref_extension_by_limited_search()
are closely related to each other and intentially implemented using the
same pattern wherever possible. If a change/bug fix is done to either of
these also consider if it is relevant for the other.
@code
procedure best_extension_by_limited_search(
pplan in, // in, partial plan of tables-joined-so-far
pplan_cost, // in, cost of pplan
remaining_tables, // in, set of tables not referenced in pplan
best_plan_so_far, // in/out, best plan found so far
best_plan_so_far_cost,// in/out, cost of best_plan_so_far
search_depth) // in, maximum size of the plans being considered
{
for each table T from remaining_tables
{
// Calculate the cost of using table T as above
cost = complex-series-of-calculations;
// Add the cost to the cost so far.
pplan_cost+= cost;
if (pplan_cost >= best_plan_so_far_cost)
// pplan_cost already too great, stop search
continue;
pplan= expand pplan by best_access_method;
remaining_tables= remaining_tables - table T;
if (remaining_tables is not an empty set
and
search_depth > 1)
{
if (table T is EQ_REF-joined)
eq_ref_eq_ref_extension_by_limited_search(
pplan, pplan_cost,
remaining_tables,
best_plan_so_far,
best_plan_so_far_cost,
search_depth - 1);
else
best_extension_by_limited_search(pplan, pplan_cost,
remaining_tables,
best_plan_so_far,
best_plan_so_far_cost,
search_depth - 1);
}
else
{
best_plan_so_far_cost= pplan_cost;
best_plan_so_far= pplan;
}
}
}
@endcode
@note
When 'best_extension_by_limited_search' is called for the first time,
'join->best_read' must be set to the largest possible value (e.g. DBL_MAX).
The actual implementation provides a way to optionally use pruning
heuristic (controlled by the parameter 'prune_level') to reduce the search
space by skipping some partial plans.
@note
The parameter 'search_depth' provides control over the recursion
depth, and thus the size of the resulting optimal plan.
@param remaining_tables set of tables not included into the partial plan yet
@param idx length of the partial QEP in 'join->positions';
since a depth-first search is used, also corresponds
to the current depth of the search tree;
also an index in the array 'join->best_ref';
@param record_count estimate for the number of records returned by the
best partial plan
@param read_time the cost of the best partial plan
@param current_search_depth maximum depth of recursion and thus size of the
found optimal plan
(0 < current_search_depth <= join->tables+1).
@return false if successful, true if error
*/
bool Optimize_table_order::best_extension_by_limited_search(
table_map remaining_tables,
uint idx,
double record_count,
double read_time,
uint current_search_depth)
{
DBUG_ENTER("Optimize_table_order::best_extension_by_limited_search");
DBUG_EXECUTE_IF("bug13820776_2", thd->killed= THD::KILL_QUERY;);
if (thd->killed) // Abort
DBUG_RETURN(true);
Opt_trace_context * const trace= &thd->opt_trace;
/*
'join' is a partial plan with lower cost than the best plan so far,
so continue expanding it further with the tables in 'remaining_tables'.
*/
double best_record_count= DBL_MAX;
double best_read_time= DBL_MAX;
DBUG_EXECUTE("opt", print_plan(join, idx, record_count, read_time, read_time,
"part_plan"););
/*
No need to call advance_sj_state() when
1) there are no semijoin nests or
2) we are optimizing a materialized semijoin nest.
*/
const bool has_sj= !(join->select_lex->sj_nests.is_empty() || emb_sjm_nest);
/*
'eq_ref_extended' are the 'remaining_tables' which has already been
involved in an partial query plan extension if this QEP. These
will not be considered in further EQ_REF extensions based
on current (partial) QEP.
*/
table_map eq_ref_extended(0);
JOIN_TAB *saved_refs[MAX_TABLES];
// Save 'best_ref[]' as we has to restore before return.
memcpy(saved_refs, join->best_ref + idx,
sizeof(JOIN_TAB*) * (join->tables - idx));
for (JOIN_TAB **pos= join->best_ref + idx; *pos; pos++)
{
JOIN_TAB *const s= *pos;
const table_map real_table_bit= s->table->map;
/*
Don't move swap inside conditional code: All items should
be uncond. swapped to maintain '#rows-ordered' best_ref[].
This is critical for early pruning of bad plans.
*/
swap_variables(JOIN_TAB*, join->best_ref[idx], *pos);
if ((remaining_tables & real_table_bit) &&
!(eq_ref_extended & real_table_bit) &&
!(remaining_tables & s->dependent) &&
(!idx || !check_interleaving_with_nj(s)))
{
double current_record_count, current_read_time;
Opt_trace_object trace_one_table(trace);
if (unlikely(trace->is_started()))
{
trace_plan_prefix(join, idx, excluded_tables);
trace_one_table.add_utf8_table(s->table);
}
POSITION *const position= join->positions + idx;
// If optimizing a sj-mat nest, tables in this plan must be in nest:
DBUG_ASSERT(emb_sjm_nest == NULL || emb_sjm_nest == s->emb_sj_nest);
/* Find the best access method from 's' to the current partial plan */
POSITION loose_scan_pos;
best_access_path(s, remaining_tables, idx, false, record_count,
position, &loose_scan_pos);
/* Compute the cost of extending the plan with 's' */
current_record_count= record_count * position->records_read;
current_read_time= read_time
+ position->read_time
+ current_record_count * ROW_EVALUATE_COST;
position->set_prefix_costs(current_read_time, current_record_count);
trace_one_table.add("cost_for_plan", current_read_time).
add("rows_for_plan", current_record_count);
if (has_sj)
{
/*
Even if there are no semijoins, advance_sj_state() has a significant
cost (takes 9% of time in a 20-table plan search), hence the if()
above, which is also more efficient than the same if() inside
advance_sj_state() would be.
Besides, never call advance_sj_state() when calculating the plan
for a materialized semi-join nest.
*/
advance_sj_state(remaining_tables, s, idx,
¤t_record_count, ¤t_read_time,
&loose_scan_pos);
}
else
position->no_semijoin();
/* Expand only partial plans with lower cost than the best QEP so far */
if (current_read_time >= join->best_read)
{
DBUG_EXECUTE("opt", print_plan(join, idx+1,
current_record_count,
read_time,
current_read_time,
"prune_by_cost"););
trace_one_table.add("pruned_by_cost", true);
backout_nj_state(remaining_tables, s);
continue;
}
/*
Prune some less promising partial plans. This heuristic may miss
the optimal QEPs, thus it results in a non-exhaustive search.
*/
if (prune_level == 1)
{
if (best_record_count > current_record_count ||
best_read_time > current_read_time ||
(idx == join->const_tables && // 's' is the first table in the QEP
s->table == join->sort_by_table))
{
if (best_record_count >= current_record_count &&
best_read_time >= current_read_time &&
/* TODO: What is the reasoning behind this condition? */
(!(s->key_dependent & remaining_tables) ||
position->records_read < 2.0))
{
best_record_count= current_record_count;
best_read_time= current_read_time;
}
}
else
{
DBUG_EXECUTE("opt", print_plan(join, idx+1,
current_record_count,
read_time,
current_read_time,
"pruned_by_heuristic"););
trace_one_table.add("pruned_by_heuristic", true);
backout_nj_state(remaining_tables, s);
continue;
}
}
const table_map remaining_tables_after=
(remaining_tables & ~real_table_bit);
if ((current_search_depth > 1) && remaining_tables_after)
{
/*
Explore more extensions of plan:
If possible, use heuristic to avoid a full expansion of partial QEP.
Evaluate a simplified EQ_REF extension of QEP if:
1) Pruning is enabled.
2) and, There are tables joined by (EQ_)REF key.
3) and, There is a 1::1 relation between those tables
*/
if (prune_level == 1 && // 1)
position->key != NULL && // 2)
position->records_read <= 1.0) // 3)
{
/*
Join in this 'position' is an EQ_REF-joined table, append more EQ_REFs.
We do this only for the first EQ_REF we encounter which will then
include other EQ_REFs from 'remaining_tables' and inform about which
tables was 'eq_ref_extended'. These are later 'pruned' as they was
processed here.
*/
if (eq_ref_extended == (table_map)0)
{
/* Try an EQ_REF-joined expansion of the partial plan */
Opt_trace_array trace_rest(trace, "rest_of_plan");
eq_ref_extended= real_table_bit |
eq_ref_extension_by_limited_search(
remaining_tables_after,
idx + 1,
current_record_count,
current_read_time,
current_search_depth - 1);
if (eq_ref_extended == ~(table_map)0)
DBUG_RETURN(true); // Failed
backout_nj_state(remaining_tables, s);
if (eq_ref_extended == remaining_tables)
goto done;
continue;
}
else // Skip, as described above
{
DBUG_EXECUTE("opt", print_plan(join, idx+1,
current_record_count,
read_time,
current_read_time,
"pruned_by_eq_ref_heuristic"););
trace_one_table.add("pruned_by_eq_ref_heuristic", true);
backout_nj_state(remaining_tables, s);
continue;
}
} // if (prunable...)
/* Fallthrough: Explore more best extensions of plan */
Opt_trace_array trace_rest(trace, "rest_of_plan");
if (best_extension_by_limited_search(remaining_tables_after,
idx + 1,
current_record_count,
current_read_time,
current_search_depth - 1))
DBUG_RETURN(true);
}
else //if ((current_search_depth > 1) && ...
{
consider_plan(idx, current_record_count, current_read_time,
&trace_one_table);
/*
If plan is complete, there should be no "open" outer join nest, and
all semi join nests should be handled by a strategy:
*/
DBUG_ASSERT((remaining_tables_after != 0) ||
((cur_embedding_map == 0) &&
(join->positions[idx].dups_producing_tables == 0)));
}
backout_nj_state(remaining_tables, s);
}
}
done:
// Restore previous #rows sorted best_ref[]
memcpy(join->best_ref + idx, saved_refs,
sizeof(JOIN_TAB*) * (join->tables-idx));
DBUG_RETURN(false);
}
/**
Heuristic utility used by best_extension_by_limited_search().
Adds EQ_REF-joined tables to the partial plan without
extensive 'greedy' cost calculation.
When a table is joined by an unique key there is a
1::1 relation between the rows being joined. Assuming we
have multiple such 1::1 (star-)joined relations in a
sequence, without other join types inbetween. Then all of
these 'eq_ref-joins' will be estimated to return the excact
same #rows and having identical 'cost' (or 'read_time').
This leads to that we can append such a contigous sequence
of eq_ref-joins to a partial plan in any order without
affecting the total cost of the query plan. Exploring the
different permutations of these eq_refs in the 'greedy'
optimizations will simply be a waste of precious CPU cycles.
Once we have appended a single eq_ref-join to a partial
plan, we may use eq_ref_extension_by_limited_search() to search
'remaining_tables' for more eq_refs which will form a contigous
set of eq_refs in the QEP.
Effectively, this chain of eq_refs will be handled as a single
entity wrt. the full 'greedy' exploration of the possible
join plans. This will reduce the 'N' in the O(N!) complexity
of the full greedy search.
The algorithm start by already having a eq_ref joined table
in position[idx-1] when called. It then search for more
eq_ref-joinable 'remaining_tables' which are added directly
to the partial QEP without further cost analysis. The algorithm
continues until it either has constructed a complete plan,
constructed a partial plan with size = search_depth, or could not
find more eq_refs to append.
In the later case the algorithm continues into
'best_extension_by_limited_search' which does a 'greedy'
search for the next table to add - Possibly with later
eq_ref_extensions.
The final optimal plan is stored in 'join->best_positions'. The
corresponding cost of the optimal plan is in 'join->best_read'.
@note
::best_extension_by_limited_search() & ::eq_ref_extension_by_limited_search()
are closely related to each other and intentially implemented using the
same pattern wherever possible. If a change/bug fix is done to either of
these also consider if it is relevant for the other.
@code
procedure eq_ref_extension_by_limited_search(
pplan in, // in, partial plan of tables-joined-so-far
pplan_cost, // in, cost of pplan
remaining_tables, // in, set of tables not referenced in pplan
best_plan_so_far, // in/out, best plan found so far
best_plan_so_far_cost,// in/out, cost of best_plan_so_far
search_depth) // in, maximum size of the plans being considered
{
if find 'eq_ref' table T from remaining_tables
{
// Calculate the cost of using table T as above
cost = complex-series-of-calculations;
// Add the cost to the cost so far.
pplan_cost+= cost;
if (pplan_cost >= best_plan_so_far_cost)
// pplan_cost already too great, stop search
continue;
pplan= expand pplan by best_access_method;
remaining_tables= remaining_tables - table T;
eq_ref_extension_by_limited_search(pplan, pplan_cost,
remaining_tables,
best_plan_so_far,
best_plan_so_far_cost,
search_depth - 1);
}
else
{
best_extension_by_limited_search(pplan, pplan_cost,
remaining_tables,
best_plan_so_far,
best_plan_so_far_cost,
search_depth - 1);
}
}
@endcode
@note
The parameter 'search_depth' provides control over the recursion
depth, and thus the size of the resulting optimal plan.
@param remaining_tables set of tables not included into the partial plan yet
@param idx length of the partial QEP in 'join->positions';
since a depth-first search is used, also corresponds
to the current depth of the search tree;
also an index in the array 'join->best_ref';
@param record_count estimate for the number of records returned by the
best partial plan
@param read_time the cost of the best partial plan
@param current_search_depth
maximum depth of recursion and thus size of the
found optimal plan
(0 < current_search_depth <= join->tables+1).
@retval
'table_map' Map of those tables appended to the EQ_REF-joined sequence
@retval
~(table_map)0 Fatal error
*/
table_map Optimize_table_order::eq_ref_extension_by_limited_search(
table_map remaining_tables,
uint idx,
double record_count,
double read_time,
uint current_search_depth)
{
DBUG_ENTER("Optimize_table_order::eq_ref_extension_by_limited_search");
if (remaining_tables == 0)
DBUG_RETURN(0);
const bool has_sj= !(join->select_lex->sj_nests.is_empty() || emb_sjm_nest);
/*
The section below adds 'eq_ref' joinable tables to the QEP in the order
they are found in the 'remaining_tables' set.
See above description for why we can add these without greedy
cost analysis.
*/
Opt_trace_context * const trace= &thd->opt_trace;
table_map eq_ref_ext(0);
JOIN_TAB *s;
JOIN_TAB *saved_refs[MAX_TABLES];
// Save 'best_ref[]' as we has to restore before return.
memcpy(saved_refs, join->best_ref + idx,
sizeof(JOIN_TAB*) * (join->tables-idx));
for (JOIN_TAB **pos= join->best_ref + idx ; (s= *pos) ; pos++)
{
const table_map real_table_bit= s->table->map;
/*
Don't move swap inside conditional code: All items
should be swapped to maintain '#rows' ordered tables.
This is critical for early pruning of bad plans.
*/
swap_variables(JOIN_TAB*, join->best_ref[idx], *pos);
/*
Consider table for 'eq_ref' heuristic if:
1) It might use a keyref for best_access_path
2) and, Table remains to be handled.
3) and, It is independent of those not yet in partial plan.
4) and, It passed the interleaving check.
*/
if (s->keyuse && // 1)
(remaining_tables & real_table_bit) && // 2)
!(remaining_tables & s->dependent) && // 3)
(!idx || !check_interleaving_with_nj(s))) // 4)
{
Opt_trace_object trace_one_table(trace);
if (unlikely(trace->is_started()))
{
trace_plan_prefix(join, idx, excluded_tables);
trace_one_table.add_utf8_table(s->table);
}
POSITION *const position= join->positions + idx;
POSITION loose_scan_pos;
DBUG_ASSERT(emb_sjm_nest == NULL || emb_sjm_nest == s->emb_sj_nest);
/* Find the best access method from 's' to the current partial plan */
best_access_path(s, remaining_tables, idx, false, record_count,
position, &loose_scan_pos);
/*
EQ_REF prune logic is based on that all joins
in the ref_extension has the same #rows and cost.
-> The total cost of the QEP is independent of the order
of joins within this 'ref_extension'.
Expand QEP with all 'identical' REFs in
'join->positions' order.
*/
const bool added_to_eq_ref_extension=
position->key &&
position->read_time == (position-1)->read_time &&
position->records_read == (position-1)->records_read;
trace_one_table.add("added_to_eq_ref_extension",
added_to_eq_ref_extension);
if (added_to_eq_ref_extension)
{
double current_record_count, current_read_time;
/* Add the cost of extending the plan with 's' */
current_record_count= record_count * position->records_read;
current_read_time= read_time
+ position->read_time
+ current_record_count * ROW_EVALUATE_COST;
position->set_prefix_costs(current_read_time, current_record_count);
trace_one_table.add("cost_for_plan", current_read_time).
add("rows_for_plan", current_record_count);
if (has_sj)
{
/*
Even if there are no semijoins, advance_sj_state() has a
significant cost (takes 9% of time in a 20-table plan search),
hence the if() above, which is also more efficient than the
same if() inside advance_sj_state() would be.
*/
advance_sj_state(remaining_tables, s, idx,
¤t_record_count, ¤t_read_time,
&loose_scan_pos);
}
else
position->no_semijoin();
// Expand only partial plans with lower cost than the best QEP so far
if (current_read_time >= join->best_read)
{
DBUG_EXECUTE("opt", print_plan(join, idx+1,
current_record_count,
read_time,
current_read_time,
"prune_by_cost"););
trace_one_table.add("pruned_by_cost", true);
backout_nj_state(remaining_tables, s);
continue;
}
eq_ref_ext= real_table_bit;
const table_map remaining_tables_after=
(remaining_tables & ~real_table_bit);
if ((current_search_depth > 1) && remaining_tables_after)
{
DBUG_EXECUTE("opt", print_plan(join, idx + 1,
current_record_count,
read_time,
current_read_time,
"EQ_REF_extension"););
/* Recursively EQ_REF-extend the current partial plan */
Opt_trace_array trace_rest(trace, "rest_of_plan");
eq_ref_ext|=
eq_ref_extension_by_limited_search(remaining_tables_after,
idx + 1,
current_record_count,
current_read_time,
current_search_depth - 1);
}
else
{
consider_plan(idx, current_record_count, current_read_time,
&trace_one_table);
DBUG_ASSERT((remaining_tables_after != 0) ||
((cur_embedding_map == 0) &&
(join->positions[idx].dups_producing_tables == 0)));
}
backout_nj_state(remaining_tables, s);
memcpy(join->best_ref + idx, saved_refs,
sizeof(JOIN_TAB*) * (join->tables - idx));
DBUG_RETURN(eq_ref_ext);
} // if (added_to_eq_ref_extension)
backout_nj_state(remaining_tables, s);
} // if (... !check_interleaving_with_nj() ...)
} // for (JOIN_TAB **pos= ...)
memcpy(join->best_ref + idx, saved_refs, sizeof(JOIN_TAB*) * (join->tables-idx));
/*
'eq_ref' heuristc didn't find a table to be appended to
the query plan. We need to use the greedy search
for finding the next table to be added.
*/
DBUG_ASSERT(!eq_ref_ext);
if (best_extension_by_limited_search(remaining_tables,
idx,
record_count,
read_time,
current_search_depth))
DBUG_RETURN(~(table_map)0);
DBUG_RETURN(eq_ref_ext);
}
/*
Get the number of different row combinations for subset of partial join
SYNOPSIS
prev_record_reads()
join The join structure
idx Number of tables in the partial join order (i.e. the
partial join order is in join->positions[0..idx-1])
found_ref Bitmap of tables for which we need to find # of distinct
row combinations.
DESCRIPTION
Given a partial join order (in join->positions[0..idx-1]) and a subset of
tables within that join order (specified in found_ref), find out how many
distinct row combinations of subset tables will be in the result of the
partial join order.
This is used as follows: Suppose we have a table accessed with a ref-based
method. The ref access depends on current rows of tables in found_ref.
We want to count # of different ref accesses. We assume two ref accesses
will be different if at least one of access parameters is different.
Example: consider a query
SELECT * FROM t1, t2, t3 WHERE t1.key=c1 AND t2.key=c2 AND t3.key=t1.field
and a join order:
t1, ref access on t1.key=c1
t2, ref access on t2.key=c2
t3, ref access on t3.key=t1.field
For t1: n_ref_scans = 1, n_distinct_ref_scans = 1
For t2: n_ref_scans = records_read(t1), n_distinct_ref_scans=1
For t3: n_ref_scans = records_read(t1)*records_read(t2)
n_distinct_ref_scans = #records_read(t1)
The reason for having this function (at least the latest version of it)
is that we need to account for buffering in join execution.
An edge-case example: if we have a non-first table in join accessed via
ref(const) or ref(param) where there is a small number of different
values of param, then the access will likely hit the disk cache and will
not require any disk seeks.
The proper solution would be to assume an LRU disk cache of some size,
calculate probability of cache hits, etc. For now we just count
identical ref accesses as one.
RETURN
Expected number of row combinations
*/
static double
prev_record_reads(JOIN *join, uint idx, table_map found_ref)
{
double found=1.0;
POSITION *pos_end= join->positions - 1;
for (POSITION *pos= join->positions + idx - 1; pos != pos_end; pos--)
{
if (pos->table->table->map & found_ref)
{
found_ref|= pos->ref_depend_map;
/*
For the case of "t1 LEFT JOIN t2 ON ..." where t2 is a const table
with no matching row we will get position[t2].records_read==0.
Actually the size of output is one null-complemented row, therefore
we will use value of 1 whenever we get records_read==0.
Note
- the above case can't occur if inner part of outer join has more
than one table: table with no matches will not be marked as const.
- Ideally we should add 1 to records_read for every possible null-
complemented row. We're not doing it because: 1. it will require
non-trivial code and add overhead. 2. The value of records_read
is an inprecise estimate and adding 1 (or, in the worst case,
#max_nested_outer_joins=64-1) will not make it any more precise.
*/
if (pos->records_read > DBL_EPSILON)
found*= pos->records_read;
}
}
return found;
}
/**
@brief Fix semi-join strategies for the picked join order
@return FALSE if success, TRUE if error
@details
Fix semi-join strategies for the picked join order. This is a step that
needs to be done right after we have fixed the join order. What we do
here is switch join's semi-join strategy description from backward-based
to forwards based.
When join optimization is in progress, we re-consider semi-join
strategies after we've added another table. Here's an illustration.
Suppose the join optimization is underway:
1) ot1 it1 it2
sjX -- looking at (ot1, it1, it2) join prefix, we decide
to use semi-join strategy sjX.
2) ot1 it1 it2 ot2
sjX sjY -- Having added table ot2, we now may consider
another semi-join strategy and decide to use a
different strategy sjY. Note that the record
of sjX has remained under it2. That is
necessary because we need to be able to get
back to (ot1, it1, it2) join prefix.
what makes things even worse is that there are cases where the choice
of sjY changes the way we should access it2.
3) [ot1 it1 it2 ot2 ot3]
sjX sjY -- This means that after join optimization is
finished, semi-join info should be read
right-to-left (while nearly all plan refinement
functions, EXPLAIN, etc proceed from left to
right)
This function does the needed reversal, making it possible to read the
join and semi-join order from left to right.
*/
bool Optimize_table_order::fix_semijoin_strategies()
{
table_map remaining_tables= 0;
table_map handled_tables= 0;
DBUG_ENTER("Optimize_table_order::fix_semijoin_strategies");
if (join->select_lex->sj_nests.is_empty())
DBUG_RETURN(false);
Opt_trace_context *const trace= &thd->opt_trace;
for (uint tableno= join->tables - 1;
tableno != join->const_tables - 1;
tableno--)
{
POSITION *const pos= join->best_positions + tableno;
if ((handled_tables & pos->table->table->map) ||
pos->sj_strategy == SJ_OPT_NONE)
{
remaining_tables|= pos->table->table->map;
continue;
}
uint first;
LINT_INIT(first);
if (pos->sj_strategy == SJ_OPT_MATERIALIZE_LOOKUP)
{
TABLE_LIST *const sjm_nest= pos->table->emb_sj_nest;
const uint table_count= my_count_bits(sjm_nest->sj_inner_tables);
/*
This memcpy() copies a partial QEP produced by
optimize_semijoin_nests_for_materialization() (source) into the final
top-level QEP (target), in order to re-use the source plan for
to-be-materialized inner tables.
It is however possible that the source QEP had picked
some semijoin strategy (noted SJY), different from
materialization. The target QEP rules (it has seen more tables), but
this memcpy() is going to copy the source stale strategy SJY,
wrongly. Which is why sj_strategy of each table of the
duplicate-generating range then becomes temporarily unreliable. It is
fixed for the first table of that range right after the memcpy(), and
fixed for the rest of that range at the end of this iteration by
setting it to SJ_OPT_NONE). But until then, pos->sj_strategy should
not be read.
*/
memcpy(pos - table_count + 1, sjm_nest->nested_join->sjm.positions,
sizeof(POSITION) * table_count);
first= tableno - table_count + 1;
join->best_positions[first].n_sj_tables= table_count;
join->best_positions[first].sj_strategy= SJ_OPT_MATERIALIZE_LOOKUP;
Opt_trace_object trace_final_strategy(trace);
trace_final_strategy.add_alnum("final_semijoin_strategy",
"MaterializeLookup");
}
else if (pos->sj_strategy == SJ_OPT_MATERIALIZE_SCAN)
{
const uint last_inner= pos->sjm_scan_last_inner;
TABLE_LIST *const sjm_nest=
(join->best_positions + last_inner)->table->emb_sj_nest;
const uint table_count= my_count_bits(sjm_nest->sj_inner_tables);
first= last_inner - table_count + 1;
DBUG_ASSERT((join->best_positions + first)->table->emb_sj_nest ==
sjm_nest);
memcpy(join->best_positions + first, // stale semijoin strategy here too
sjm_nest->nested_join->sjm.positions,
sizeof(POSITION) * table_count);
join->best_positions[first].sj_strategy= SJ_OPT_MATERIALIZE_SCAN;
join->best_positions[first].n_sj_tables= table_count;
Opt_trace_object trace_final_strategy(trace);
trace_final_strategy.add_alnum("final_semijoin_strategy",
"MaterializeScan");
// Recalculate final access paths for this semi-join strategy
double rowcount, cost;
semijoin_mat_scan_access_paths(last_inner, tableno,
remaining_tables, sjm_nest, true,
&rowcount, &cost);
}
else if (pos->sj_strategy == SJ_OPT_FIRST_MATCH)
{
first= pos->first_firstmatch_table;
join->best_positions[first].sj_strategy= SJ_OPT_FIRST_MATCH;
join->best_positions[first].n_sj_tables= tableno - first + 1;
Opt_trace_object trace_final_strategy(trace);
trace_final_strategy.add_alnum("final_semijoin_strategy", "FirstMatch");
// Recalculate final access paths for this semi-join strategy
double rowcount, cost;
(void)semijoin_firstmatch_loosescan_access_paths(first, tableno,
remaining_tables, false, true,
&rowcount, &cost);
}
else if (pos->sj_strategy == SJ_OPT_LOOSE_SCAN)
{
first= pos->first_loosescan_table;
Opt_trace_object trace_final_strategy(trace);
trace_final_strategy.add_alnum("final_semijoin_strategy", "LooseScan");
// Recalculate final access paths for this semi-join strategy
double rowcount, cost;
(void)semijoin_firstmatch_loosescan_access_paths(first, tableno,
remaining_tables, true, true,
&rowcount, &cost);
POSITION *const first_pos= join->best_positions + first;
first_pos->sj_strategy= SJ_OPT_LOOSE_SCAN;
first_pos->n_sj_tables=
my_count_bits(first_pos->table->emb_sj_nest->sj_inner_tables);
}
else if (pos->sj_strategy == SJ_OPT_DUPS_WEEDOUT)
{
/*
Duplicate Weedout starting at pos->first_dupsweedout_table, ending at
this table.
*/
first= pos->first_dupsweedout_table;
join->best_positions[first].sj_strategy= SJ_OPT_DUPS_WEEDOUT;
join->best_positions[first].n_sj_tables= tableno - first + 1;
Opt_trace_object trace_final_strategy(trace);
trace_final_strategy.add_alnum("final_semijoin_strategy",
"DuplicateWeedout");
}
for (uint i= first; i <= tableno; i++)
{
/*
Eliminate stale strategies. See comment in the
SJ_OPT_MATERIALIZE_LOOKUP case above.
*/
if (i != first)
join->best_positions[i].sj_strategy= SJ_OPT_NONE;
handled_tables|= join->best_positions[i].table->table->map;
}
remaining_tables |= pos->table->table->map;
}
DBUG_ASSERT(remaining_tables == (join->all_table_map&~join->const_table_map));
DBUG_RETURN(FALSE);
}
/**
Check interleaving with an inner tables of an outer join for
extension table.
Check if table tab can be added to current partial join order, and
if yes, record that it has been added. This recording can be rolled back
with backout_nj_state().
The function assumes that both current partial join order and its
extension with tab are valid wrt table dependencies.
@verbatim
IMPLEMENTATION
LIMITATIONS ON JOIN ORDER
The nested [outer] joins executioner algorithm imposes these limitations
on join order:
1. "Outer tables first" - any "outer" table must be before any
corresponding "inner" table.
2. "No interleaving" - tables inside a nested join must form a continuous
sequence in join order (i.e. the sequence must not be interrupted by
tables that are outside of this nested join).
#1 is checked elsewhere, this function checks #2 provided that #1 has
been already checked.
WHY NEED NON-INTERLEAVING
Consider an example:
select * from t0 join t1 left join (t2 join t3) on cond1
The join order "t1 t2 t0 t3" is invalid:
table t0 is outside of the nested join, so WHERE condition for t0 is
attached directly to t0 (without triggers, and it may be used to access
t0). Applying WHERE(t0) to (t2,t0,t3) record is invalid as we may miss
combinations of (t1, t2, t3) that satisfy condition cond1, and produce a
null-complemented (t1, t2.NULLs, t3.NULLs) row, which should not have
been produced.
If table t0 is not between t2 and t3, the problem doesn't exist:
If t0 is located after (t2,t3), WHERE(t0) is applied after nested join
processing has finished.
If t0 is located before (t2,t3), predicates like WHERE_cond(t0, t2) are
wrapped into condition triggers, which takes care of correct nested
join processing.
HOW IT IS IMPLEMENTED
The limitations on join order can be rephrased as follows: for valid
join order one must be able to:
1. write down the used tables in the join order on one line.
2. for each nested join, put one '(' and one ')' on the said line
3. write "LEFT JOIN" and "ON (...)" where appropriate
4. get a query equivalent to the query we're trying to execute.
Calls to check_interleaving_with_nj() are equivalent to writing the
above described line from left to right.
A single check_interleaving_with_nj(A,B) call is equivalent to writing
table B and appropriate brackets on condition that table A and
appropriate brackets is the last what was written. Graphically the
transition is as follows:
+---- current position
|
... last_tab ))) | ( tab ) )..) | ...
X Y Z |
+- need to move to this
position.
Notes about the position:
The caller guarantees that there is no more then one X-bracket by
checking "!(remaining_tables & s->dependent)" before calling this
function. X-bracket may have a pair in Y-bracket.
When "writing" we store/update this auxilary info about the current
position:
1. cur_embedding_map - bitmap of pairs of brackets (aka nested
joins) we've opened but didn't close.
2. {each NESTED_JOIN structure not simplified away}->counter - number
of this nested join's children that have already been added to to
the partial join order.
@endverbatim
@param tab Table we're going to extend the current partial join with
@retval
FALSE Join order extended, nested joins info about current join
order (see NOTE section) updated.
@retval
TRUE Requested join order extension not allowed.
*/
bool Optimize_table_order::check_interleaving_with_nj(JOIN_TAB *tab)
{
if (cur_embedding_map & ~tab->embedding_map)
{
/*
tab is outside of the "pair of brackets" we're currently in.
Cannot add it.
*/
return true;
}
const TABLE_LIST *next_emb= tab->table->pos_in_table_list->embedding;
/*
Do update counters for "pairs of brackets" that we've left (marked as
X,Y,Z in the above picture)
*/
for (; next_emb != emb_sjm_nest; next_emb= next_emb->embedding)
{
// Ignore join nests that are not outer joins.
if (!next_emb->join_cond())
continue;
next_emb->nested_join->nj_counter++;
cur_embedding_map |= next_emb->nested_join->nj_map;
if (next_emb->nested_join->nj_total != next_emb->nested_join->nj_counter)
break;
/*
We're currently at Y or Z-bracket as depicted in the above picture.
Mark that we've left it and continue walking up the brackets hierarchy.
*/
cur_embedding_map &= ~next_emb->nested_join->nj_map;
}
return false;
}
/**
Find best access paths for semi-join FirstMatch or LooseScan strategy
and calculate rowcount and cost based on these.
@param first_tab The first tab to calculate access paths for,
this is always a semi-join inner table.
@param last_tab The last tab to calculate access paths for,
always a semi-join inner table for FirstMatch,
may be inner or outer for LooseScan.
@param remaining_tables Bitmap of tables that are not in the
[0...last_tab] join prefix
@param loosescan If true, use LooseScan strategy, otherwise FirstMatch
@param final If true, use and update access path data in
join->best_positions, otherwise use join->positions
and update a local buffer.
@param[out] rowcount New output row count
@param[out] newcost New join prefix cost
@return True if strategy selection successful, false otherwise.
@details
Calculate best access paths for the tables of a semi-join FirstMatch or
LooseScan strategy, given the order of tables provided in join->positions
(or join->best_positions when calculating the cost of a final plan).
Calculate estimated cost and rowcount for this plan.
Given a join prefix [0; ... first_tab-1], change the access to the tables
in the range [first_tab; last_tab] according to the constraints set by the
relevant semi-join strategy. Those constraints are:
- For the LooseScan strategy, join buffering can be used for the outer
tables following the last inner table.
- For the FirstMatch strategy, join buffering can be used if there is a
single inner table in the semi-join nest.
For FirstMatch, the handled range of tables may be a mix of inner tables
and non-dependent outer tables. The first and last table in the handled
range are always inner tables.
For LooseScan, the handled range can be a mix of inner tables and
dependent and non-dependent outer tables. The first table is always an
inner table.
*/
bool Optimize_table_order::semijoin_firstmatch_loosescan_access_paths(
uint first_tab, uint last_tab, table_map remaining_tables,
bool loosescan, bool final,
double *newcount, double *newcost)
{
DBUG_ENTER(
"Optimize_table_order::semijoin_firstmatch_loosescan_access_paths");
double cost; // Contains running estimate of calculated cost.
double rowcount; // Rowcount of join prefix (ie before first_tab).
double outer_fanout= 1.0; // Fanout contributed by outer tables in range.
double inner_fanout= 1.0; // Fanout contributed by inner tables in range.
Opt_trace_context *const trace= &thd->opt_trace;
Opt_trace_object recalculate(trace, "recalculate_access_paths_and_cost");
Opt_trace_array trace_tables(trace, "tables");
POSITION *const positions= final ? join->best_positions : join->positions;
if (first_tab == join->const_tables)
{
cost= 0.0;
rowcount= 1.0;
}
else
{
cost= positions[first_tab - 1].prefix_cost.total_cost();
rowcount= positions[first_tab - 1].prefix_record_count;
}
uint table_count= 0;
uint no_jbuf_before;
for (uint i= first_tab; i <= last_tab; i++)
{
remaining_tables|= positions[i].table->table->map;
if (positions[i].table->emb_sj_nest)
table_count++;
}
if (loosescan)
{
// LooseScan: May use join buffering for all tables after last inner table.
for (no_jbuf_before= last_tab; no_jbuf_before > first_tab; no_jbuf_before--)
{
if (positions[no_jbuf_before].table->emb_sj_nest != NULL)
break; // Encountered the last inner table.
}
no_jbuf_before++;
}
else
{
// FirstMatch: May use join buffering if there is only one inner table.
no_jbuf_before= (table_count > 1) ? last_tab + 1 : first_tab;
}
for (uint i= first_tab; i <= last_tab; i++)
{
JOIN_TAB *const tab= positions[i].table;
POSITION regular_pos, loose_scan_pos;
POSITION *const dst_pos= final ? positions + i : ®ular_pos;
POSITION *pos; // Position for later calculations
/*
We always need a new calculation for the first inner table in
the LooseScan strategy. Notice the use of loose_scan_pos.
*/
if ((i == first_tab && loosescan) || positions[i].use_join_buffer)
{
Opt_trace_object trace_one_table(trace);
trace_one_table.add_utf8_table(tab->table);
// Find the best access method with specified join buffering strategy.
best_access_path(tab, remaining_tables, i,
i < no_jbuf_before,
rowcount * inner_fanout * outer_fanout,
dst_pos, &loose_scan_pos);
if (i == first_tab && loosescan) // Use loose scan position
{
*dst_pos= loose_scan_pos;
const double rows= rowcount * dst_pos->records_read;
dst_pos->set_prefix_costs(cost + dst_pos->read_time +
rows * ROW_EVALUATE_COST,
rows);
}
pos= dst_pos;
}
else
pos= positions + i; // Use result from prior calculation
/*
Terminate search if best_access_path found no possible plan.
Otherwise we will be getting infinite cost when summing up below.
*/
if (pos->read_time == DBL_MAX)
{
DBUG_ASSERT(loosescan && !final);
DBUG_RETURN(false);
}
remaining_tables&= ~tab->table->map;
if (tab->emb_sj_nest)
inner_fanout*= pos->records_read;
else
outer_fanout*= pos->records_read;
cost+= pos->read_time +
rowcount * inner_fanout * outer_fanout * ROW_EVALUATE_COST;
}
*newcount= rowcount * outer_fanout;
*newcost= cost;
DBUG_RETURN(true);
}
/**
Find best access paths for semi-join MaterializeScan strategy
and calculate rowcount and cost based on these.
@param last_inner_tab The last tab in the set of inner tables
@param last_outer_tab The last tab in the set of outer tables
@param remaining_tables Bitmap of tables that are not in the join prefix
including the inner and outer tables processed here.
@param sjm_nest Pointer to semi-join nest for inner tables
@param final If true, use and update access path data in
join->best_positions, otherwise use join->positions
and update a local buffer.
@param[out] rowcount New output row count
@param[out] newcost New join prefix cost
@details
Calculate best access paths for the outer tables of the MaterializeScan
semi-join strategy. All outer tables may use join buffering.
The prefix row count is adjusted with the estimated number of rows in
the materialized tables, before taking into consideration the rows
contributed by the outer tables.
*/
void Optimize_table_order::semijoin_mat_scan_access_paths(
uint last_inner_tab, uint last_outer_tab,
table_map remaining_tables, TABLE_LIST *sjm_nest, bool final,
double *newcount, double *newcost)
{
DBUG_ENTER("Optimize_table_order::semijoin_mat_scan_access_paths");
Opt_trace_context *const trace= &thd->opt_trace;
Opt_trace_object recalculate(trace, "recalculate_access_paths_and_cost");
Opt_trace_array trace_tables(trace, "tables");
double cost; // Calculated running cost of operation
double rowcount; // Rowcount of join prefix (ie before first_inner).
POSITION *const positions= final ? join->best_positions : join->positions;
const uint inner_count= my_count_bits(sjm_nest->sj_inner_tables);
// Get the prefix cost.
const uint first_inner= last_inner_tab + 1 - inner_count;
if (first_inner == join->const_tables)
{
rowcount= 1.0;
cost= 0.0;
}
else
{
rowcount= positions[first_inner - 1].prefix_record_count;
cost= positions[first_inner - 1].prefix_cost.total_cost();
}
// Add materialization cost.
cost+= sjm_nest->nested_join->sjm.materialization_cost.total_cost() +
rowcount * sjm_nest->nested_join->sjm.scan_cost.total_cost();
for (uint i= last_inner_tab + 1; i <= last_outer_tab; i++)
remaining_tables|= positions[i].table->table->map;
/*
Materialization removes duplicates from the materialized table, so
number of rows to scan is probably less than the number of rows
from a full join, on which the access paths of outer tables are currently
based. Rerun best_access_path to adjust for reduced rowcount.
*/
const double inner_fanout= sjm_nest->nested_join->sjm.expected_rowcount;
double outer_fanout= 1.0;
for (uint i= last_inner_tab + 1; i <= last_outer_tab; i++)
{
Opt_trace_object trace_one_table(trace);
JOIN_TAB *const tab= positions[i].table;
trace_one_table.add_utf8_table(tab->table);
POSITION regular_pos, dummy;
POSITION *const dst_pos= final ? positions + i : ®ular_pos;
best_access_path(tab, remaining_tables, i, false,
rowcount * inner_fanout * outer_fanout, dst_pos, &dummy);
remaining_tables&= ~tab->table->map;
outer_fanout*= dst_pos->records_read;
cost+= dst_pos->read_time +
rowcount * inner_fanout * outer_fanout * ROW_EVALUATE_COST;
}
*newcount= rowcount * outer_fanout;
*newcost= cost;
DBUG_VOID_RETURN;
}
/**
Find best access paths for semi-join MaterializeLookup strategy.
and calculate rowcount and cost based on these.
@param last_inner Index of the last inner table
@param sjm_nest Pointer to semi-join nest for inner tables
@param[out] rowcount New output row count
@param[out] newcost New join prefix cost
@details
All outer tables may use join buffering, so there is no need to recalculate
access paths nor costs for these.
Add cost of materialization and scanning the materialized table to the
costs of accessing the outer tables.
*/
void Optimize_table_order::semijoin_mat_lookup_access_paths(
uint last_inner, TABLE_LIST *sjm_nest,
double *newcount, double *newcost)
{
DBUG_ENTER("Optimize_table_order::semijoin_mat_lookup_access_paths");
const uint inner_count= my_count_bits(sjm_nest->sj_inner_tables);
double rowcount, cost;
const uint first_inner= last_inner + 1 - inner_count;
if (first_inner == join->const_tables)
{
cost= 0.0;
rowcount= 1.0;
}
else
{
cost= join->positions[first_inner - 1].prefix_cost.total_cost();
rowcount= join->positions[first_inner - 1].prefix_record_count;
}
cost+= sjm_nest->nested_join->sjm.materialization_cost.total_cost() +
rowcount * sjm_nest->nested_join->sjm.lookup_cost.total_cost();
*newcount= rowcount;
*newcost= cost;
DBUG_VOID_RETURN;
}
/**
Find best access paths for semi-join DuplicateWeedout strategy
and calculate rowcount and cost based on these.
@param first_tab The first tab to calculate access paths for
@param last_tab The last tab to calculate access paths for
@param remaining_tables Bitmap of tables that are not in the
[0...last_tab] join prefix
@param[out] newcount New output row count
@param[out] newcost New join prefix cost
@return True if strategy selection successful, false otherwise.
@details
Notice that new best access paths need not be calculated.
The proper access path information is already in join->positions,
because DuplicateWeedout can handle any join buffering strategy.
The only action performed by this function is to calculate
output rowcount, and an updated cost estimate.
The cost estimate is based on performing a join over the involved
tables, but we must also add the cost of creating and populating
the temporary table used for duplicate removal, and the cost of
doing lookups against this table.
*/
void Optimize_table_order::semijoin_dupsweedout_access_paths(
uint first_tab, uint last_tab,
table_map remaining_tables,
double *newcount, double *newcost)
{
DBUG_ENTER("Optimize_table_order::semijoin_dupsweedout_access_paths");
double cost, rowcount;
double inner_fanout= 1.0;
double outer_fanout= 1.0;
double max_outer_fanout= 1.0;
uint rowsize; // Row size of the temporary table
if (first_tab == join->const_tables)
{
cost= 0.0;
rowcount= 1.0;
rowsize= 0;
}
else
{
cost= join->positions[first_tab - 1].prefix_cost.total_cost();
rowcount= join->positions[first_tab - 1].prefix_record_count;
rowsize= 8; // This is not true but we'll make it so
}
/**
Some times, some outer fanout is "absorbed" into the inner fanout.
In this case, we should make a better estimate for outer_fanout that
is used to calculate the output rowcount.
If we have inner table(s) before an outer table and if there are
dependencies between these tables, the fanout for the outer table is not
a good estimate for the final number of rows from the weedout execution,
therefore we convert some of the inner fanout into an outer fanout,
limited to the number of possible rows in the outer table.
*/
for (uint j= first_tab; j <= last_tab; j++)
{
const POSITION *const p= join->positions + j;
if (p->table->emb_sj_nest)
inner_fanout*= p->records_read;
else
{
/*
max_outer_fanout is the cardinality of the cross product of the
outer tables.
@note: We do not consider dependencies between these tables here.
*/
max_outer_fanout*= p->table->table->quick_condition_rows;
if (inner_fanout > 1.0)
{
// Absorb inner fanout into the outer fanout:
outer_fanout*= inner_fanout * p->records_read;
inner_fanout= 1.0;
}
else
outer_fanout*= p->records_read;
rowsize+= p->table->table->file->ref_length;
}
cost+= p->read_time +
rowcount * inner_fanout * outer_fanout * ROW_EVALUATE_COST;
}
if (max_outer_fanout < outer_fanout)
{
/*
The calculated fanout for the outer tables is bigger than the
cardinality of the cross product of the outer tables. Adjust outer
fanout to the max value, but also adjust inner fanout so that
inner_fanout * outer_fanout is still the same (dups weedout runs
a complete join internally).
*/
if (max_outer_fanout > 0.0)
inner_fanout*= outer_fanout / max_outer_fanout;
outer_fanout= max_outer_fanout;
}
/*
Add the cost of temptable use. The table will have outer_fanout rows,
and we will make
- rowcount * outer_fanout writes
- rowcount * inner_fanout * outer_fanout lookups.
We assume here that a lookup and a write has the same cost.
*/
double one_lookup_cost, create_cost;
if (outer_fanout * rowsize > thd->variables.max_heap_table_size)
{
one_lookup_cost= DISK_TEMPTABLE_ROW_COST;
create_cost= DISK_TEMPTABLE_CREATE_COST;
}
else
{
one_lookup_cost= HEAP_TEMPTABLE_ROW_COST;
create_cost= HEAP_TEMPTABLE_CREATE_COST;
}
const double write_cost= rowcount * outer_fanout * one_lookup_cost;
const double full_lookup_cost= write_cost * inner_fanout;
cost+= create_cost + write_cost + full_lookup_cost;
*newcount= rowcount * outer_fanout;
*newcost= cost;
DBUG_VOID_RETURN;
}
/**
Do semi-join optimization step after we've added a new tab to join prefix
@param remaining_tables Tables not in the join prefix
@param new_join_tab Join tab that we are adding to the join prefix
@param idx Index of this join tab (i.e. number of tables
in the prefix)
@param[in,out] current_rowcount Estimate of #rows in join prefix's output
@param[in,out] current_cost Cost to execute the join prefix
@param loose_scan_pos A POSITION with LooseScan plan to access table
new_join_tab (produced by last best_access_path call)
@details
Update semi-join optimization state after we've added another tab (table
and access method) to the join prefix.
The state is maintained in join->positions[#prefix_size]. Each of the
available strategies has its own state variables.
for each semi-join strategy
{
update strategy's state variables;
if (join prefix has all the tables that are needed to consider
using this strategy for the semi-join(s))
{
calculate cost of using the strategy
if ((this is the first strategy to handle the semi-join nest(s) ||
the cost is less than other strategies))
{
// Pick this strategy
pos->sj_strategy= ..
..
}
}
Most of the new state is saved in join->positions[idx] (and hence no undo
is necessary).
See setup_semijoin_dups_elimination() for a description of what kinds of
join prefixes each strategy can handle.
A note on access path, rowcount and cost estimates:
- best_extension_by_limited_search() performs *initial calculations*
of access paths, rowcount and cost based on the operation being
an inner join or an outer join operation. These estimates are saved
in join->positions.
- advance_sj_state() performs *intermediate calculations* based on the
same table information, but for the supported semi-join strategies.
The access path part of these calculations are not saved anywhere,
but the rowcount and cost of the best semi-join strategy are saved
in join->positions.
- Because the semi-join access path information was not saved previously,
fix_semijoin_strategies() must perform *final calculations* of
access paths, rowcount and cost when saving the selected table order
in join->best_positions. The results of the final calculations will be
the same as the results of the "best" intermediate calculations.
*/
void Optimize_table_order::advance_sj_state(
table_map remaining_tables,
const JOIN_TAB *new_join_tab, uint idx,
double *current_rowcount, double *current_cost,
POSITION *loose_scan_pos)
{
Opt_trace_context * const trace= &thd->opt_trace;
TABLE_LIST *const emb_sj_nest= new_join_tab->emb_sj_nest;
POSITION *const pos= join->positions + idx;
uint sj_strategy= SJ_OPT_NONE; // Initially: No chosen strategy
/*
Semi-join nests cannot be nested, hence we never need to advance the
semi-join state of a materialized semi-join query.
In fact, doing this may cause undesirable effects because all tables
within a semi-join nest have emb_sj_nest != NULL, which triggers several
of the actions inside this function.
*/
DBUG_ASSERT(emb_sjm_nest == NULL);
/* Add this table to the join prefix */
remaining_tables &= ~new_join_tab->table->map;
DBUG_ENTER("Optimize_table_order::advance_sj_state");
Opt_trace_array trace_choices(trace, "semijoin_strategy_choice");
/* Initialize the state or copy it from prev. tables */
if (idx == join->const_tables)
{
pos->dups_producing_tables= 0;
pos->first_firstmatch_table= MAX_TABLES;
pos->first_loosescan_table= MAX_TABLES;
pos->dupsweedout_tables= 0;
pos->sjm_scan_need_tables= 0;
LINT_INIT(pos->sjm_scan_last_inner);
}
else
{
pos->dups_producing_tables= pos[-1].dups_producing_tables;
// FirstMatch
pos->first_firstmatch_table= pos[-1].first_firstmatch_table;
pos->first_firstmatch_rtbl= pos[-1].first_firstmatch_rtbl;
pos->firstmatch_need_tables= pos[-1].firstmatch_need_tables;
// LooseScan
pos->first_loosescan_table=
(pos[-1].sj_strategy == SJ_OPT_LOOSE_SCAN) ?
MAX_TABLES : pos[-1].first_loosescan_table;
pos->loosescan_need_tables= pos[-1].loosescan_need_tables;
// MaterializeScan
pos->sjm_scan_need_tables=
(pos[-1].sj_strategy == SJ_OPT_MATERIALIZE_SCAN) ?
0 : pos[-1].sjm_scan_need_tables;
pos->sjm_scan_last_inner= pos[-1].sjm_scan_last_inner;
// Duplicate Weedout
pos->dupsweedout_tables= pos[-1].dupsweedout_tables;
pos->first_dupsweedout_table= pos[-1].first_dupsweedout_table;
}
table_map handled_by_fm_or_ls= 0;
/*
FirstMatch Strategy
===================
FirstMatch requires that all dependent outer tables are in the join prefix.
(see "FirstMatch strategy" above setup_semijoin_dups_elimination()).
The execution strategy will handle multiple semi-join nests correctly,
and the optimizer will pick execution strategy according to these rules:
- If tables from multiple semi-join nests are intertwined, they will
be processed as one FirstMatch evaluation.
- If tables from each semi-join nest are grouped together, each semi-join
nest is processed as one FirstMatch evaluation.
Example: Let's say we have an outer table ot and two semi-join nests with
two tables each: it11 and it12, and it21 and it22.
Intertwined tables: ot - FM(it11 - it21 - it12 - it22)
Grouped tables: ot - FM(it11 - it12) - FM(it21 - it22)
*/
if (emb_sj_nest &&
thd->optimizer_switch_flag(OPTIMIZER_SWITCH_FIRSTMATCH))
{
const table_map outer_corr_tables= emb_sj_nest->nested_join->sj_depends_on;
const table_map sj_inner_tables= emb_sj_nest->sj_inner_tables;
/*
Enter condition:
1. The next join tab belongs to semi-join nest
(verified for the encompassing code block above).
2. We're not in a duplicate producer range yet
3. All outer tables that
- the subquery is correlated with, or
- referred to from the outer_expr
are in the join prefix
*/
if (pos->dups_producing_tables == 0 && // (2)
!(remaining_tables & outer_corr_tables)) // (3)
{
/* Start tracking potential FirstMatch range */
pos->first_firstmatch_table= idx;
pos->firstmatch_need_tables= 0;
pos->first_firstmatch_rtbl= remaining_tables;
// All inner tables should still be part of remaining_tables.
DBUG_ASSERT(sj_inner_tables ==
((remaining_tables | new_join_tab->table->map) &
sj_inner_tables));
}
if (pos->first_firstmatch_table != MAX_TABLES)
{
/* Record that we need all of this semi-join's inner tables */
pos->firstmatch_need_tables|= sj_inner_tables;
if (outer_corr_tables & pos->first_firstmatch_rtbl)
{
/*
Trying to add an sj-inner table whose sj-nest has an outer correlated
table that was not in the prefix. This means FirstMatch can't be used.
*/
pos->first_firstmatch_table= MAX_TABLES;
}
else if (!(pos->firstmatch_need_tables & remaining_tables))
{
// Got a complete FirstMatch range. Calculate access paths and cost
double cost, rowcount;
/* We use the same FirstLetterUpcase as in EXPLAIN */
Opt_trace_object trace_one_strategy(trace);
trace_one_strategy.add_alnum("strategy", "FirstMatch");
(void)semijoin_firstmatch_loosescan_access_paths(
pos->first_firstmatch_table, idx,
remaining_tables, false, false,
&rowcount, &cost);
/*
We don't yet know what are the other strategies, so pick FirstMatch.
We ought to save the alternate POSITIONs produced by
semijoin_firstmatch_loosescan_access_paths() but the problem is that
providing save space uses too much space.
Instead, we will re-calculate the alternate POSITIONs after we've
picked the best QEP.
*/
sj_strategy= SJ_OPT_FIRST_MATCH;
*current_cost= cost;
*current_rowcount= rowcount;
trace_one_strategy.add("cost", *current_cost).
add("rows", *current_rowcount);
handled_by_fm_or_ls= pos->firstmatch_need_tables;
trace_one_strategy.add("chosen", true);
}
}
}
/*
LooseScan Strategy
==================
LooseScan requires that all dependent outer tables are not in the join
prefix. (see "LooseScan strategy" above setup_semijoin_dups_elimination()).
The tables must come in a rather strictly defined order:
1. The LooseScan driving table (which is a subquery inner table).
2. The remaining tables from the same semi-join nest as the above table.
3. The outer dependent tables, possibly mixed with outer non-dependent
tables.
Notice that any other semi-joined tables must be outside this table range.
*/
if (thd->optimizer_switch_flag(OPTIMIZER_SWITCH_LOOSE_SCAN))
{
POSITION *const first= join->positions+pos->first_loosescan_table;
/*
LooseScan strategy can't handle interleaving between tables from the
semi-join that LooseScan is handling and any other tables.
*/
if (pos->first_loosescan_table != MAX_TABLES)
{
if (first->table->emb_sj_nest->sj_inner_tables &
(remaining_tables | new_join_tab->table->map))
{
// Stage 2: Accept remaining tables from the semi-join nest:
if (emb_sj_nest != first->table->emb_sj_nest)
pos->first_loosescan_table= MAX_TABLES;
}
else
{
// Stage 3: Accept outer dependent and non-dependent tables:
DBUG_ASSERT(emb_sj_nest != first->table->emb_sj_nest);
if (emb_sj_nest != NULL)
pos->first_loosescan_table= MAX_TABLES;
}
}
/*
If we got an option to use LooseScan for the current table, start
considering using LooseScan strategy
*/
if (loose_scan_pos->read_time != DBL_MAX)
{
pos->first_loosescan_table= idx;
pos->loosescan_need_tables= emb_sj_nest->sj_inner_tables |
emb_sj_nest->nested_join->sj_depends_on;
}
if ((pos->first_loosescan_table != MAX_TABLES) &&
!(remaining_tables & pos->loosescan_need_tables))
{
/*
Ok we have LooseScan plan and also have all LooseScan sj-nest's
inner tables and outer correlated tables into the prefix.
*/
// Got a complete LooseScan range. Calculate access paths and cost
double cost, rowcount;
Opt_trace_object trace_one_strategy(trace);
trace_one_strategy.add_alnum("strategy", "LooseScan");
/*
The same problem as with FirstMatch - we need to save POSITIONs
somewhere but reserving space for all cases would require too
much space. We will re-calculate POSITION structures later on.
*/
if (semijoin_firstmatch_loosescan_access_paths(
pos->first_loosescan_table, idx,
remaining_tables, true, false,
&rowcount, &cost))
{
/*
We don't yet have any other strategies that could handle this
semi-join nest (the other options are Duplicate Elimination or
Materialization, which need at least the same set of tables in
the join prefix to be considered) so unconditionally pick the
LooseScan.
*/
sj_strategy= SJ_OPT_LOOSE_SCAN;
*current_cost= cost;
*current_rowcount= rowcount;
trace_one_strategy.add("cost", *current_cost).
add("rows", *current_rowcount);
handled_by_fm_or_ls= first->table->emb_sj_nest->sj_inner_tables;
}
trace_one_strategy.add("chosen", sj_strategy == SJ_OPT_LOOSE_SCAN);
}
}
if (emb_sj_nest)
pos->dups_producing_tables |= emb_sj_nest->sj_inner_tables;
pos->dups_producing_tables &= ~handled_by_fm_or_ls;
/* MaterializeLookup and MaterializeScan strategy handler */
const int sjm_strategy=
semijoin_order_allows_materialization(join, remaining_tables,
new_join_tab, idx);
if (sjm_strategy == SJ_OPT_MATERIALIZE_SCAN)
{
/*
We cannot evaluate this option now. This is because we cannot
account for fanout of sj-inner tables yet:
ntX SJM-SCAN(it1 ... itN) | ot1 ... otN |
^(1) ^(2)
we're now at position (1). SJM temptable in general has multiple
records, so at point (1) we'll get the fanout from sj-inner tables (ie
there will be multiple record combinations).
The final join result will not contain any semi-join produced
fanout, i.e. tables within SJM-SCAN(...) will not contribute to
the cardinality of the join output. Extra fanout produced by
SJM-SCAN(...) will be 'absorbed' into fanout produced by ot1 ... otN.
The simple way to model this is to remove SJM-SCAN(...) fanout once
we reach the point #2.
*/
pos->sjm_scan_need_tables=
emb_sj_nest->sj_inner_tables |
emb_sj_nest->nested_join->sj_depends_on;
pos->sjm_scan_last_inner= idx;
Opt_trace_object(trace).add_alnum("strategy", "MaterializeScan").
add_alnum("choice", "deferred");
}
else if (sjm_strategy == SJ_OPT_MATERIALIZE_LOOKUP)
{
// Calculate access paths and cost for MaterializeLookup strategy
double cost, rowcount;
semijoin_mat_lookup_access_paths(idx, emb_sj_nest, &rowcount, &cost);
Opt_trace_object trace_one_strategy(trace);
trace_one_strategy.add_alnum("strategy", "MaterializeLookup").
add("cost", cost).add("rows", rowcount).
add("duplicate_tables_left", pos->dups_producing_tables != 0);
if (cost < *current_cost || pos->dups_producing_tables)
{
/*
NOTE: When we pick to use SJM[-Scan] we don't memcpy its POSITION
elements to join->positions as that makes it hard to return things
back when making one step back in join optimization. That's done
after the QEP has been chosen.
*/
sj_strategy= SJ_OPT_MATERIALIZE_LOOKUP;
*current_cost= cost;
*current_rowcount= rowcount;
pos->dups_producing_tables &= ~emb_sj_nest->sj_inner_tables;
}
trace_one_strategy.add("chosen", sj_strategy == SJ_OPT_MATERIALIZE_LOOKUP);
}
/* MaterializeScan second phase check */
/*
The optimizer does not support that we have inner tables from more
than one semi-join nest within the table range.
*/
if (pos->sjm_scan_need_tables &&
emb_sj_nest != NULL &&
emb_sj_nest !=
join->positions[pos->sjm_scan_last_inner].table->emb_sj_nest)
pos->sjm_scan_need_tables= 0;
if (pos->sjm_scan_need_tables && /* Have SJM-Scan prefix */
!(pos->sjm_scan_need_tables & remaining_tables))
{
TABLE_LIST *const sjm_nest=
join->positions[pos->sjm_scan_last_inner].table->emb_sj_nest;
double cost, rowcount;
Opt_trace_object trace_one_strategy(trace);
trace_one_strategy.add_alnum("strategy", "MaterializeScan");
semijoin_mat_scan_access_paths(pos->sjm_scan_last_inner, idx,
remaining_tables, sjm_nest, false,
&rowcount, &cost);
trace_one_strategy.add("cost", cost).
add("rows", rowcount).
add("duplicate_tables_left", pos->dups_producing_tables != 0);
/*
Use the strategy if
* it is cheaper then what we've had, or
* we haven't picked any other semi-join strategy yet
In the second case, we pick this strategy unconditionally because
comparing cost without semi-join duplicate removal with cost with
duplicate removal is not an apples-to-apples comparison.
*/
if (cost < *current_cost || pos->dups_producing_tables)
{
sj_strategy= SJ_OPT_MATERIALIZE_SCAN;
*current_cost= cost;
*current_rowcount= rowcount;
pos->dups_producing_tables &= ~sjm_nest->sj_inner_tables;
}
trace_one_strategy.add("chosen", sj_strategy == SJ_OPT_MATERIALIZE_SCAN);
}
/* Duplicate Weedout strategy handler */
{
/*
Duplicate weedout can be applied after all ON-correlated and
correlated
*/
if (emb_sj_nest)
{
if (!pos->dupsweedout_tables)
pos->first_dupsweedout_table= idx;
pos->dupsweedout_tables|= emb_sj_nest->sj_inner_tables |
emb_sj_nest->nested_join->sj_depends_on;
}
if (pos->dupsweedout_tables &&
!(remaining_tables & pos->dupsweedout_tables))
{
Opt_trace_object trace_one_strategy(trace);
trace_one_strategy.add_alnum("strategy", "DuplicatesWeedout");
/*
Ok, reached a state where we could put a dups weedout point.
Walk back and calculate
- the join cost (this is needed as the accumulated cost may assume
some other duplicate elimination method)
- extra fanout that will be removed by duplicate elimination
- duplicate elimination cost
There are two cases:
1. We have other strategy/ies to remove all of the duplicates.
2. We don't.
We need to calculate the cost in case #2 also because we need to make
choice between this join order and others.
*/
double rowcount, cost;
semijoin_dupsweedout_access_paths(pos->first_dupsweedout_table, idx,
remaining_tables, &rowcount, &cost);
/*
Use the strategy if
* it is cheaper then what we've had, or
* we haven't picked any other semi-join strategy yet
The second part is necessary because this strategy is the last one
to consider (it needs "the most" tables in the prefix) and we can't
leave duplicate-producing tables not handled by any strategy.
*/
trace_one_strategy.
add("cost", cost).
add("rows", rowcount).
add("duplicate_tables_left", pos->dups_producing_tables != 0);
if (cost < *current_cost || pos->dups_producing_tables)
{
sj_strategy= SJ_OPT_DUPS_WEEDOUT;
*current_cost= cost;
*current_rowcount= rowcount;
/*
Note, dupsweedout_tables contains inner and outer tables, even though
"dups_producing_tables" are always inner table. Ok for this use.
*/
pos->dups_producing_tables &= ~pos->dupsweedout_tables;
}
trace_one_strategy.add("chosen", sj_strategy == SJ_OPT_DUPS_WEEDOUT);
}
}
pos->sj_strategy= sj_strategy;
/*
If a semi-join strategy is chosen, update cost and rowcount in positions
as well. These values may be used as prefix cost and rowcount for later
semi-join calculations, e.g for plans like "ot1 - it1 - it2 - ot2",
where we have two semi-join nests containing it1 and it2, respectively,
and we have a dependency between ot1 and it1, and between ot2 and it2.
When looking at a semi-join plan for "it2 - ot2", the correct prefix cost
(located in the join_tab for it1) must be filled in properly.
Tables in a semijoin range, except the last in range, won't have their
prefix_costs changed below; this is normal: when we process them, this is
a regular join so regular costs calculated in best_ext...() are ok;
duplicates elimination happens only at the last table in range, so it
makes sense to correct prefix_costs of that last table.
*/
if (sj_strategy != SJ_OPT_NONE)
pos->set_prefix_costs(*current_cost, *current_rowcount);
DBUG_VOID_RETURN;
}
/**
Nested joins perspective: Remove the last table from the join order.
@details
Remove the last table from the partial join order and update the nested
joins counters and cur_embedding_map. It is ok to call this
function for the first table in join order (for which
check_interleaving_with_nj has not been called)
This function rolls back changes done by:
- check_interleaving_with_nj(): removes the last table from the partial join
order and update the nested joins counters and cur_embedding_map. It
is ok to call this for the first table in join order (for which
check_interleaving_with_nj() has not been called).
The algorithm is the reciprocal of check_interleaving_with_nj(), hence
parent join nest nodes are updated only when the last table in its child
node is removed. The ASCII graphic below will clarify.
%A table nesting such as <tt> t1 x [ ( t2 x t3 ) x ( t4 x t5 ) ] </tt>is
represented by the below join nest tree.
@verbatim
NJ1
_/ / \
_/ / NJ2
_/ / / \
/ / / \
t1 x [ (t2 x t3) x (t4 x t5) ]
@endverbatim
At the point in time when check_interleaving_with_nj() adds the table t5 to
the query execution plan, QEP, it also directs the node named NJ2 to mark
the table as covered. NJ2 does so by incrementing its @c counter
member. Since all of NJ2's tables are now covered by the QEP, the algorithm
proceeds up the tree to NJ1, incrementing its counter as well. All join
nests are now completely covered by the QEP.
backout_nj_state() does the above in reverse. As seen above, the node
NJ1 contains the nodes t2, t3, and NJ2. Its counter being equal to 3 means
that the plan covers t2, t3, and NJ2, @e and that the sub-plan (t4 x t5)
completely covers NJ2. The removal of t5 from the partial plan will first
decrement NJ2's counter to 1. It will then detect that NJ2 went from being
completely to partially covered, and hence the algorithm must continue
upwards to NJ1 and decrement its counter to 2. A subsequent removal of t4
will however not influence NJ1 since it did not un-cover the last table in
NJ2.
@param remaining_tables remaining tables to optimize, must contain 'tab'
@param tab join table to remove, assumed to be the last in
current partial join order.
*/
void Optimize_table_order::backout_nj_state(const table_map remaining_tables,
const JOIN_TAB *tab)
{
DBUG_ASSERT(remaining_tables & tab->table->map);
/* Restore the nested join state */
TABLE_LIST *last_emb= tab->table->pos_in_table_list->embedding;
for (; last_emb != emb_sjm_nest; last_emb= last_emb->embedding)
{
// Ignore join nests that are not outer joins.
if (!last_emb->join_cond())
continue;
NESTED_JOIN *const nest= last_emb->nested_join;
DBUG_ASSERT(nest->nj_counter > 0);
cur_embedding_map|= nest->nj_map;
bool was_fully_covered= nest->nj_total == nest->nj_counter;
if (--nest->nj_counter == 0)
cur_embedding_map&= ~nest->nj_map;
if (!was_fully_covered)
break;
}
}
/**
Helper function to write the current plan's prefix to the optimizer trace.
*/
static void trace_plan_prefix(JOIN *join, uint idx,
table_map excluded_tables)
{
#ifdef OPTIMIZER_TRACE
THD * const thd= join->thd;
Opt_trace_array plan_prefix(&thd->opt_trace, "plan_prefix");
for (uint i= 0; i < idx; i++)
{
const TABLE * const table= join->positions[i].table->table;
if (!(table->map & excluded_tables))
{
TABLE_LIST * const tl= table->pos_in_table_list;
if (tl != NULL)
{
StringBuffer<32> str;
tl->print(thd, &str, enum_query_type(QT_TO_SYSTEM_CHARSET |
QT_SHOW_SELECT_NUMBER |
QT_NO_DEFAULT_DB |
QT_DERIVED_TABLE_ONLY_ALIAS));
plan_prefix.add_utf8(str.ptr(), str.length());
}
}
}
#endif
}
/**
@} (end of group Query_Planner)
*/