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Commit 531dd708 authored by Sergei Petrunia's avatar Sergei Petrunia Committed by Sergei Petrunia
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MDEV-27229: Estimation for filtered rows less precise ... #5 

Fix special handling for values that are right next to buckets with ndv=1.
parent 67d4d042
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Showing with 148 additions and 55 deletions
mysql-test/main/statistics_json.result
View file @ 531dd708
......@@ -4631,12 +4631,12 @@ test t1_json a a-0 a-9 0.0000 3.0000 1.0000 10 JSON_HB {
}
explain extended select * from t1_json where a between 'a-3a' and 'zzzzzzzzz';
id select_type table type possible_keys key key_len ref rows filtered Extra
1 SIMPLE t1_json ALL NULL NULL NULL NULL 10 68.71 Using where
1 SIMPLE t1_json ALL NULL NULL NULL NULL 10 60.00 Using where
Warnings:
Note 1003 select `test`.`t1_json`.`a` AS `a` from `test`.`t1_json` where `test`.`t1_json`.`a` between 'a-3a' and 'zzzzzzzzz'
analyze select * from t1_json where a between 'a-3a' and 'zzzzzzzzz';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE t1_json ALL NULL NULL NULL NULL 10 10.00 68.71 60.00 Using where
1 SIMPLE t1_json ALL NULL NULL NULL NULL 10 10.00 60.00 60.00 Using where
explain extended select * from t1_json where a < 'b-1a';
id select_type table type possible_keys key key_len ref rows filtered Extra
1 SIMPLE t1_json ALL NULL NULL NULL NULL 10 100.00 Using where
......@@ -8014,7 +8014,7 @@ test.t1 analyze status OK
analyze
select c from t1 where c > '1';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE t1 ALL NULL NULL NULL NULL 16 16.00 80.47 75.00 Using where
1 SIMPLE t1 ALL NULL NULL NULL NULL 16 16.00 75.00 75.00 Using where
drop table t1;
#
# MDEV-26849: JSON Histograms: point selectivity estimates are off for non-existent values
......@@ -8211,3 +8211,33 @@ analyze select COUNT(*) FROM t1 WHERE a < 'a';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE t1 ALL NULL NULL NULL NULL 100 100.00 50.00 50.00 Using where
drop table t1;
#
# MDEV-27229: Estimation for filtered rows less precise ... #5
#
create table t1 (id int, a varchar(8));
insert into t1 select seq, 'bar' from seq_1_to_100;
insert into t1 select id, 'qux' from t1;
set histogram_type=JSON_HB;
analyze table t1 persistent for all;
Table Op Msg_type Msg_text
test.t1 analyze status Engine-independent statistics collected
test.t1 analyze status OK
analyze select COUNT(*) FROM t1 WHERE a > 'foo';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE t1 ALL NULL NULL NULL NULL 200 200.00 50.00 50.00 Using where
analyze select COUNT(*) FROM t1 WHERE a > 'aaa';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE t1 ALL NULL NULL NULL NULL 200 200.00 100.00 100.00 Using where
analyze select COUNT(*) FROM t1 WHERE a >='aaa';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE t1 ALL NULL NULL NULL NULL 200 200.00 100.00 100.00 Using where
analyze select COUNT(*) FROM t1 WHERE a > 'bar';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE t1 ALL NULL NULL NULL NULL 200 200.00 50.00 50.00 Using where
analyze select COUNT(*) FROM t1 WHERE a >='bar';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE t1 ALL NULL NULL NULL NULL 200 200.00 100.00 100.00 Using where
analyze select COUNT(*) FROM t1 WHERE a <='bar';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE t1 ALL NULL NULL NULL NULL 200 200.00 50.00 50.00 Using where
drop table t1;
mysql-test/main/statistics_json.test
View file @ 531dd708
......@@ -390,3 +390,29 @@ analyze table t1 persistent for all;
analyze select COUNT(*) FROM t1 WHERE a <> 'a';
analyze select COUNT(*) FROM t1 WHERE a < 'a';
drop table t1;
--echo #
--echo # MDEV-27229: Estimation for filtered rows less precise ... #5
--echo #
create table t1 (id int, a varchar(8));
insert into t1 select seq, 'bar' from seq_1_to_100;
insert into t1 select id, 'qux' from t1;
set histogram_type=JSON_HB;
analyze table t1 persistent for all;
analyze select COUNT(*) FROM t1 WHERE a > 'foo';
analyze select COUNT(*) FROM t1 WHERE a > 'aaa';
analyze select COUNT(*) FROM t1 WHERE a >='aaa';
analyze select COUNT(*) FROM t1 WHERE a > 'bar';
analyze select COUNT(*) FROM t1 WHERE a >='bar';
# Can enable these after get_avg_frequency issue is resolved:
# analyze select COUNT(*) FROM t1 WHERE a < 'aaa';
# analyze select COUNT(*) FROM t1 WHERE a <='aaa';
# analyze select COUNT(*) FROM t1 WHERE a < 'bar';
analyze select COUNT(*) FROM t1 WHERE a <='bar';
drop table t1;
sql/opt_histogram_json.cc
View file @ 531dd708
......@@ -910,12 +910,12 @@ double Histogram_json_hb::point_selectivity(Field *field, key_range *endpoint,
// If the value is outside of the histogram's range, this will "clip" it to
// first or last bucket.
bool equal;
int idx= find_bucket(field, key, &equal);
int endp_cmp;
int idx= find_bucket(field, key, &endp_cmp);
double sel;
if (buckets[idx].ndv == 1 && !equal)
if (buckets[idx].ndv == 1 && (endp_cmp!=0))
{
/*
The bucket has a single value and it doesn't match! Return a very
......@@ -979,22 +979,27 @@ double Histogram_json_hb::range_selectivity(Field *field, key_range *min_endp,
// Find the leftmost bucket that contains the lookup value.
// (If the lookup value is to the left of all buckets, find bucket #0)
bool equal;
int idx= find_bucket(field, min_key, &equal);
if (equal && exclusive_endp && buckets[idx].ndv==1 &&
idx < (int)buckets.size()-1)
int endp_cmp;
int idx= find_bucket(field, min_key, &endp_cmp);
double sel;
// Special handling for buckets with ndv=1:
if (buckets[idx].ndv == 1)
{
/*
The range is "col > $CONST" and we've found a bucket that contains
only the value $CONST. Move to the next bucket.
*/
idx++;
if (endp_cmp < 0)
sel= 0.0;
else if (endp_cmp > 0)
sel= 1.0;
else // endp_cmp == 0.0
sel= (exclusive_endp)? 1.0 : 0.0;
}
else
{
sel= position_in_interval(field, min_key, min_key_len,
buckets[idx].start_value,
get_end_value(idx));
}
double left_fract= get_left_fract(idx);
double sel= position_in_interval(field, min_key, min_key_len,
buckets[idx].start_value,
get_end_value(idx));
min= left_fract + sel * (buckets[idx].cum_fract - left_fract);
}
else
......@@ -1012,28 +1017,35 @@ double Histogram_json_hb::range_selectivity(Field *field, key_range *min_endp,
max_key++;
max_key_len--;
}
bool equal;
int idx= find_bucket(field, max_key, &equal);
int endp_cmp;
int idx= find_bucket(field, max_key, &endp_cmp);
if (equal && !inclusive_endp && idx > 0)
if ((endp_cmp == 0) && !inclusive_endp)
{
/*
The range is "col < $CONST" and we've found a bucket starting with
$CONST. Move to the previous bucket.
$CONST.
*/
idx--;
equal= false;
if (idx > 0)
{
// Move to the previous bucket
endp_cmp= 1;
idx--;
}
else
endp_cmp= -1;
}
double left_fract= get_left_fract(idx);
double sel;
/* Special handling for singleton buckets */
if (buckets[idx].ndv == 1 && equal)
// Special handling for buckets with ndv=1:
if (buckets[idx].ndv == 1)
{
if (inclusive_endp)
sel= 1.0;
else
if (endp_cmp < 0)
sel= 0.0;
else if (endp_cmp > 0)
sel= 1.0;
else // endp_cmp == 0.0
sel= inclusive_endp? 1.0 : 0.0;
}
else
{
......@@ -1041,13 +1053,13 @@ double Histogram_json_hb::range_selectivity(Field *field, key_range *min_endp,
buckets[idx].start_value,
get_end_value(idx));
}
double left_fract= get_left_fract(idx);
max= left_fract + sel * (buckets[idx].cum_fract - left_fract);
}
else
max= 1.0;
double sel = max - min;
return sel;
return max - min;
}
......@@ -1057,25 +1069,37 @@ void Histogram_json_hb::serialize(Field *field)
}
static int SGN(int x)
{
if (!x)
return 0;
return (x < 0)? -1 : 1;
}
/*
@brief
Find the leftmost histogram bucket such that "lookup_val >= start_value".
@param field Field object (used to do value comparisons)
@param lookup_val The lookup value in KeyTupleFormat.
@param equal OUT TRUE<=> the found bucket has left_bound=lookup_val
@param cmp OUT How the lookup_val compares to found_bucket.left_bound:
0 - lookup_val == bucket.left_bound
>0 - lookup_val > bucket.left_bound (the most typical)
<0 - lookup_val < bucket.left_bound. This can only happen
for the first bucket, for all other buckets we would just
pick the previous bucket and have cmp>=0.
@return
The bucket index
*/
int Histogram_json_hb::find_bucket(const Field *field, const uchar *lookup_val,
bool *equal)
int *cmp)
{
int res;
int low= 0;
int high= (int)buckets.size() - 1;
*equal= false;
*cmp= 1; // By default, (bucket[retval].start_value < *lookup_val)
while (low + 1 < high)
{
......@@ -1083,7 +1107,7 @@ int Histogram_json_hb::find_bucket(const Field *field, const uchar *lookup_val,
res= field->key_cmp((uchar*)buckets[middle].start_value.data(), lookup_val);
if (!res)
{
*equal= true;
*cmp= res;
low= middle;
goto end;
}
......@@ -1104,31 +1128,44 @@ int Histogram_json_hb::find_bucket(const Field *field, const uchar *lookup_val,
*/
if (low == 0)
{
res= field->key_cmp((uchar*)buckets[0].start_value.data(), lookup_val);
if (!res)
*equal= true;
else if (res < 0) // buckets[0] < lookup_val
res= field->key_cmp(lookup_val, (uchar*)buckets[0].start_value.data());
if (res <= 0)
*cmp= res;
else // res>0, lookup_val > buckets[0].start_value
{
res= field->key_cmp((uchar*)buckets[high].start_value.data(), lookup_val);
if (!res)
*equal= true;
if (res <= 0) // buckets[high] <= lookup_val
res= field->key_cmp(lookup_val, (uchar*)buckets[high].start_value.data());
if (res >= 0) // lookup_val >= buckets[high].start_value
{
// Move to that bucket
low= high;
*cmp= res;
}
else
*cmp= 1;
}
}
else if (high == (int)buckets.size() - 1)
{
res= field->key_cmp((uchar*)buckets[high].start_value.data(), lookup_val);
if (!res)
*equal= true;
if (res <= 0)
res= field->key_cmp(lookup_val, (uchar*)buckets[high].start_value.data());
if (res >= 0)
{
// Ok the value is in the last bucket.
*cmp= res;
low= high;
}
else
{
// The value is in the 'low' bucket.
res= field->key_cmp(lookup_val, (uchar*)buckets[low].start_value.data());
*cmp= res;
}
}
end:
// Verification: *equal==TRUE <=> lookup value is equal to the found bucket.
DBUG_ASSERT(*equal == !(field->key_cmp((uchar*)buckets[low].start_value.data(),
lookup_val)));
// Verification: *cmp has correct value
DBUG_ASSERT(SGN(*cmp) ==
SGN(field->key_cmp(lookup_val,
(uchar*)buckets[low].start_value.data())));
// buckets[low] <= lookup_val, with one exception of the first bucket.
DBUG_ASSERT(low == 0 ||
field->key_cmp((uchar*)buckets[low].start_value.data(), lookup_val)<= 0);
......
sql/opt_histogram_json.h
View file @ 531dd708
......@@ -144,6 +144,6 @@ class Histogram_json_hb : public Histogram_base
double get_left_fract(int idx);
std::string& get_end_value(int idx);
int find_bucket(const Field *field, const uchar *lookup_val, bool *equal);
int find_bucket(const Field *field, const uchar *lookup_val, int *cmp);
};
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