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Commit bff65a81 authored by Michael Okoko's avatar Michael Okoko Committed by Sergei Petrunia
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Implement point selectivity for JSON histograms 

* Also merges tests relating to JSON statistics into one file
Signed-off-by: default avatarMichael Okoko <okokomichaels@outlook.com>
parent 547f8053
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mysql-test/main/st_play.result deleted 100644 → 0
View file @ 547f8053
create table users (
city varchar(100)
);
insert into users select 'Moscow' from seq_1_to_99;
insert into users select 'Helsinki' from seq_1_to_2;
analyze table users persistent for all;
Table Op Msg_type Msg_text
test.users analyze status Engine-independent statistics collected
test.users analyze status OK
select hex(histogram) from mysql.column_stats where table_name='users';
hex(histogram)
00000000FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF
explain extended select * from users where city = 'Moscow';
id select_type table type possible_keys key key_len ref rows filtered Extra
1 SIMPLE users ALL NULL NULL NULL NULL 101 97.66 Using where
Warnings:
Note 1003 select `test`.`users`.`city` AS `city` from `test`.`users` where `test`.`users`.`city` = 'Moscow'
analyze select * from users where city = 'Moscow';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE users ALL NULL NULL NULL NULL 101 101.00 97.66 98.02 Using where
delete from mysql.column_stats where table_name='users';
set histogram_type=json;
set histogram_size=10;
analyze table users persistent for all;
Table Op Msg_type Msg_text
test.users analyze status Engine-independent statistics collected
test.users analyze status Table is already up to date
select histogram from mysql.column_stats where table_name='users';
histogram
[]
explain extended select * from users where city = 'Moscow';
id select_type table type possible_keys key key_len ref rows filtered Extra
1 SIMPLE users ALL NULL NULL NULL NULL 101 50.00 Using where
Warnings:
Note 1003 select `test`.`users`.`city` AS `city` from `test`.`users` where `test`.`users`.`city` = 'Moscow'
analyze select * from users where city = 'Moscow';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE users ALL NULL NULL NULL NULL 101 101.00 50.00 98.02 Using where
mysql-test/main/st_play.test deleted 100644 → 0
View file @ 547f8053
--source include/have_sequence.inc
create table users (
city varchar(100)
);
insert into users select 'Moscow' from seq_1_to_99;
insert into users select 'Helsinki' from seq_1_to_2;
analyze table users persistent for all;
select hex(histogram) from mysql.column_stats where table_name='users';
explain extended select * from users where city = 'Moscow';
analyze select * from users where city = 'Moscow';
delete from mysql.column_stats where table_name='users';
set histogram_type=json;
set histogram_size=10;
analyze table users persistent for all;
select histogram from mysql.column_stats where table_name='users';
explain extended select * from users where city = 'Moscow';
analyze select * from users where city = 'Moscow';
mysql-test/main/statistics_fetch.result deleted 100644 → 0
View file @ 547f8053
#
# Test to inspect the range_selectivity returned by Histogram_json and Histogram_binary
# todo: should be merged with statistics_json.test
#
set @save_histogram_type=@@histogram_type;
set @save_histogram_size=@@histogram_size;
create table ten(a int primary key);
insert into ten values (0),(1),(2),(3),(4),(5),(6),(7),(8),(9);
create table t1_bin (a varchar(255));
insert into t1_bin select concat('a-', a) from ten;
set histogram_size=100;
analyze table t1_bin persistent for all;
Table Op Msg_type Msg_text
test.t1_bin analyze status Engine-independent statistics collected
test.t1_bin analyze status OK
select hex(histogram) from mysql.column_stats where table_name='t1_bin';
hex(histogram)
00000000000000000000711C711C711C711C711CE338E338E338E338E33855555555555555555555C671C671C671C671C671388E388E388E388E388EAAAAAAAAAAAAAAAAAAAA1BC71BC71BC71BC71BC78DE38DE38DE38DE38DE3FFFFFFFFFFFFFFFFFFFF
explain extended select * from t1_bin where a between 'a-3a' and 'zzzzzzzzz';
id select_type table type possible_keys key key_len ref rows filtered Extra
1 SIMPLE t1_bin ALL NULL NULL NULL NULL 10 58.82 Using where
Warnings:
Note 1003 select `test`.`t1_bin`.`a` AS `a` from `test`.`t1_bin` where `test`.`t1_bin`.`a` between 'a-3a' and 'zzzzzzzzz'
analyze select * from t1_bin 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_bin ALL NULL NULL NULL NULL 10 10.00 58.82 60.00 Using where
create table t1_json (a varchar(255));
insert into t1_json select concat('a-', a) from ten;
set histogram_type=json;
analyze table t1_json persistent for all;
Table Op Msg_type Msg_text
test.t1_json analyze status Engine-independent statistics collected
test.t1_json analyze status OK
select * from mysql.column_stats where table_name='t1_json';
db_name table_name column_name min_value max_value nulls_ratio avg_length avg_frequency hist_size hist_type histogram
test t1_json a a-0 a-9 0.0000 3.0000 1.0000 100 JSON [
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9"
]
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 60.87 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 60.87 60.00 Using where
create table t2_bin(a int);
insert into t2_bin select a*10 from ten;
set histogram_type=@save_histogram_type;
analyze table t2_bin persistent for all;
Table Op Msg_type Msg_text
test.t2_bin analyze status Engine-independent statistics collected
test.t2_bin analyze status OK
explain extended select * from t2_bin where a between '44' and '55';
id select_type table type possible_keys key key_len ref rows filtered Extra
1 SIMPLE t2_bin ALL NULL NULL NULL NULL 10 11.76 Using where
Warnings:
Note 1003 select `test`.`t2_bin`.`a` AS `a` from `test`.`t2_bin` where `test`.`t2_bin`.`a` between '44' and '55'
analyze select * from t2_bin where a between '44' and '55';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE t2_bin ALL NULL NULL NULL NULL 10 10.00 11.76 10.00 Using where
create table t2_json(a int);
insert into t2_json select a*10 from ten;
set histogram_type=json;
analyze table t2_json persistent for all;
Table Op Msg_type Msg_text
test.t2_json analyze status Engine-independent statistics collected
test.t2_json analyze status OK
select * from mysql.column_stats where table_name='t2_json';
db_name table_name column_name min_value max_value nulls_ratio avg_length avg_frequency hist_size hist_type histogram
test t2_json a 0 90 0.0000 4.0000 1.0000 100 JSON [
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"10",
"10",
"10",
"10",
"10",
"10",
"10",
"10",
"10",
"10",
"20",
"20",
"20",
"20",
"20",
"20",
"20",
"20",
"20",
"20",
"30",
"30",
"30",
"30",
"30",
"30",
"30",
"30",
"30",
"30",
"40",
"40",
"40",
"40",
"40",
"40",
"40",
"40",
"40",
"40",
"50",
"50",
"50",
"50",
"50",
"50",
"50",
"50",
"50",
"50",
"60",
"60",
"60",
"60",
"60",
"60",
"60",
"60",
"60",
"60",
"70",
"70",
"70",
"70",
"70",
"70",
"70",
"70",
"70",
"70",
"80",
"80",
"80",
"80",
"80",
"80",
"80",
"80",
"80",
"80",
"90",
"90",
"90",
"90",
"90",
"90",
"90",
"90",
"90",
"90"
]
explain extended select * from t2_json where a between '44' and '55';
id select_type table type possible_keys key key_len ref rows filtered Extra
1 SIMPLE t2_json ALL NULL NULL NULL NULL 10 10.10 Using where
Warnings:
Note 1003 select `test`.`t2_json`.`a` AS `a` from `test`.`t2_json` where `test`.`t2_json`.`a` between '44' and '55'
analyze select * from t2_json where a between '44' and '55';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE t2_json ALL NULL NULL NULL NULL 10 10.00 10.10 10.00 Using where
create table users (
city varchar(100)
);
set histogram_size=50;
insert into users select 'Moscow' from seq_1_to_99;
insert into users select 'Helsinki' from seq_1_to_2;
set histogram_type=json;
analyze table users persistent for all;
Table Op Msg_type Msg_text
test.users analyze status Engine-independent statistics collected
test.users analyze status OK
select histogram from mysql.column_stats where table_name='users';
histogram
[
"Helsinki",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow",
"Moscow"
]
explain extended select * from users where city <= 'Moscow';
id select_type table type possible_keys key key_len ref rows filtered Extra
1 SIMPLE users ALL NULL NULL NULL NULL 101 100.00 Using where
Warnings:
Note 1003 select `test`.`users`.`city` AS `city` from `test`.`users` where `test`.`users`.`city` <= 'Moscow'
analyze select * from users where city <= 'Moscow';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE users ALL NULL NULL NULL NULL 101 101.00 100.00 100.00 Using where
drop table t1_bin;
drop table t1_json;
drop table t2_bin;
drop table t2_json;
drop table users;
mysql-test/main/statistics_fetch.test deleted 100644 → 0
View file @ 547f8053
--echo #
--echo # Test to inspect the range_selectivity returned by Histogram_json and Histogram_binary
--echo # todo: should be merged with statistics_json.test
--echo #
set @save_histogram_type=@@histogram_type;
set @save_histogram_size=@@histogram_size;
create table ten(a int primary key);
insert into ten values (0),(1),(2),(3),(4),(5),(6),(7),(8),(9);
create table t1_bin (a varchar(255));
insert into t1_bin select concat('a-', a) from ten;
set histogram_size=100;
analyze table t1_bin persistent for all;
select hex(histogram) from mysql.column_stats where table_name='t1_bin';
explain extended select * from t1_bin where a between 'a-3a' and 'zzzzzzzzz';
analyze select * from t1_bin where a between 'a-3a' and 'zzzzzzzzz';
create table t1_json (a varchar(255));
insert into t1_json select concat('a-', a) from ten;
set histogram_type=json;
analyze table t1_json persistent for all;
select * from mysql.column_stats where table_name='t1_json';
explain extended select * from t1_json where a between 'a-3a' and 'zzzzzzzzz';
analyze select * from t1_json where a between 'a-3a' and 'zzzzzzzzz';
create table t2_bin(a int);
insert into t2_bin select a*10 from ten;
set histogram_type=@save_histogram_type;
analyze table t2_bin persistent for all;
explain extended select * from t2_bin where a between '44' and '55';
analyze select * from t2_bin where a between '44' and '55';
create table t2_json(a int);
insert into t2_json select a*10 from ten;
set histogram_type=json;
analyze table t2_json persistent for all;
select * from mysql.column_stats where table_name='t2_json';
explain extended select * from t2_json where a between '44' and '55';
analyze select * from t2_json where a between '44' and '55';
--source include/have_sequence.inc
create table users (
city varchar(100)
);
set histogram_size=50;
insert into users select 'Moscow' from seq_1_to_99;
insert into users select 'Helsinki' from seq_1_to_2;
set histogram_type=json;
analyze table users persistent for all;
select histogram from mysql.column_stats where table_name='users';
explain extended select * from users where city <= 'Moscow';
analyze select * from users where city <= 'Moscow';
drop table t1_bin;
drop table t1_json;
drop table t2_bin;
drop table t2_json;
drop table users;
mysql-test/main/statistics_json.result
View file @ bff65a81
......@@ -4,6 +4,175 @@
drop table if exists t1;
set @save_histogram_type=@@histogram_type;
set @save_histogram_size=@@histogram_size;
create table ten(a int primary key);
insert into ten values (0),(1),(2),(3),(4),(5),(6),(7),(8),(9);
create table t1_bin (a varchar(255));
insert into t1_bin select concat('a-', a) from ten;
set histogram_size=100;
analyze table t1_bin persistent for all;
Table Op Msg_type Msg_text
test.t1_bin analyze status Engine-independent statistics collected
test.t1_bin analyze status OK
select hex(histogram) from mysql.column_stats where table_name='t1_bin';
hex(histogram)
00000000000000000000711C711C711C711C711CE338E338E338E338E33855555555555555555555C671C671C671C671C671388E388E388E388E388EAAAAAAAAAAAAAAAAAAAA1BC71BC71BC71BC71BC78DE38DE38DE38DE38DE3FFFFFFFFFFFFFFFFFFFF
explain extended select * from t1_bin where a between 'a-3a' and 'zzzzzzzzz';
id select_type table type possible_keys key key_len ref rows filtered Extra
1 SIMPLE t1_bin ALL NULL NULL NULL NULL 10 58.82 Using where
Warnings:
Note 1003 select `test`.`t1_bin`.`a` AS `a` from `test`.`t1_bin` where `test`.`t1_bin`.`a` between 'a-3a' and 'zzzzzzzzz'
analyze select * from t1_bin 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_bin ALL NULL NULL NULL NULL 10 10.00 58.82 60.00 Using where
create table t1_json (a varchar(255));
insert into t1_json select concat('a-', a) from ten;
set histogram_type=json;
analyze table t1_json persistent for all;
Table Op Msg_type Msg_text
test.t1_json analyze status Engine-independent statistics collected
test.t1_json analyze status OK
select * from mysql.column_stats where table_name='t1_json';
db_name table_name column_name min_value max_value nulls_ratio avg_length avg_frequency hist_size hist_type histogram
test t1_json a a-0 a-9 0.0000 3.0000 1.0000 100 JSON [
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-0",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-1",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-2",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-3",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-4",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-5",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-6",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-7",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-8",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9",
"a-9"
]
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 60.87 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 60.87 60.00 Using where
create table users (
city varchar(100)
);
set histogram_size=50;
insert into users select 'Moscow' from seq_1_to_99;
insert into users select 'Helsinki' from seq_1_to_2;
set histogram_type=json;
analyze table users persistent for all;
Table Op Msg_type Msg_text
test.users analyze status Engine-independent statistics collected
test.users analyze status OK
explain extended select * from users where city = 'Moscow';
id select_type table type possible_keys key key_len ref rows filtered Extra
1 SIMPLE users ALL NULL NULL NULL NULL 101 98.04 Using where
Warnings:
Note 1003 select `test`.`users`.`city` AS `city` from `test`.`users` where `test`.`users`.`city` = 'Moscow'
analyze select * from users where city = 'Moscow';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE users ALL NULL NULL NULL NULL 101 101.00 98.04 98.02 Using where
explain extended select * from users where city = 'Helsinki';
id select_type table type possible_keys key key_len ref rows filtered Extra
1 SIMPLE users ALL NULL NULL NULL NULL 101 50.00 Using where
Warnings:
Note 1003 select `test`.`users`.`city` AS `city` from `test`.`users` where `test`.`users`.`city` = 'Helsinki'
analyze select * from users where city = 'helsinki';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE users ALL NULL NULL NULL NULL 101 101.00 50.00 1.98 Using where
drop table t1_bin;
drop table t1_json;
drop table users;
CREATE TABLE t1 (
a int NOT NULL PRIMARY KEY,
b varchar(32),
......@@ -252,6 +421,10 @@ Note 1003 select `test`.`t1`.`a` AS `a`,`test`.`t1`.`b` AS `b`,`test`.`t1`.`c` A
analyze select * from t1 where a between '20' and '70';
id select_type table type possible_keys key key_len ref rows r_rows filtered r_filtered Extra
1 SIMPLE t1 ALL PRIMARY NULL NULL NULL 40 40.00 57.50 57.50 Using where
UPDATE mysql.column_stats SET histogram='["1", {"a": "b"}, "2"]' WHERE table_name='t1';
FLUSH TABLES;
explain extended select * from t1 where a between '20' and '70';
ERROR HY000: Failed to parse histogram, encountered JSON_TYPE '1'.
DELETE FROM mysql.column_stats;
DROP TABLE t1;
create schema world;
......
mysql-test/main/statistics_json.test
View file @ bff65a81
......@@ -11,6 +11,46 @@ drop table if exists t1;
set @save_histogram_type=@@histogram_type;
set @save_histogram_size=@@histogram_size;
create table ten(a int primary key);
insert into ten values (0),(1),(2),(3),(4),(5),(6),(7),(8),(9);
create table t1_bin (a varchar(255));
insert into t1_bin select concat('a-', a) from ten;
set histogram_size=100;
analyze table t1_bin persistent for all;
select hex(histogram) from mysql.column_stats where table_name='t1_bin';
explain extended select * from t1_bin where a between 'a-3a' and 'zzzzzzzzz';
analyze select * from t1_bin where a between 'a-3a' and 'zzzzzzzzz';
create table t1_json (a varchar(255));
insert into t1_json select concat('a-', a) from ten;
set histogram_type=json;
analyze table t1_json persistent for all;
select * from mysql.column_stats where table_name='t1_json';
explain extended select * from t1_json where a between 'a-3a' and 'zzzzzzzzz';
analyze select * from t1_json where a between 'a-3a' and 'zzzzzzzzz';
--source include/have_sequence.inc
create table users (
city varchar(100)
);
set histogram_size=50;
insert into users select 'Moscow' from seq_1_to_99;
insert into users select 'Helsinki' from seq_1_to_2;
set histogram_type=json;
analyze table users persistent for all;
explain extended select * from users where city = 'Moscow';
analyze select * from users where city = 'Moscow';
explain extended select * from users where city = 'Helsinki';
analyze select * from users where city = 'helsinki';
drop table t1_bin;
drop table t1_json;
drop table users;
CREATE TABLE t1 (
a int NOT NULL PRIMARY KEY,
b varchar(32),
......@@ -81,11 +121,11 @@ SELECT COUNT(*) FROM t1;
explain extended select * from t1 where a between '20' and '70';
analyze select * from t1 where a between '20' and '70';
# todo: test different valid JSON strings that are invalid histograms.
# UPDATE mysql.column_stats SET histogram='["1", {"a": "b"}, "2"]' WHERE table_name='t1';
# FLUSH TABLES;
# --error ER_JSON_HISTOGRAM_PARSE_FAILED
# explain extended select * from t1 where a between '20' and '70';
# test different valid JSON strings that are invalid histograms.
UPDATE mysql.column_stats SET histogram='["1", {"a": "b"}, "2"]' WHERE table_name='t1';
FLUSH TABLES;
--error ER_JSON_HISTOGRAM_PARSE_FAILED
explain extended select * from t1 where a between '20' and '70';
DELETE FROM mysql.column_stats;
DROP TABLE t1;
......
sql/sql_statistics.cc
View file @ bff65a81
......@@ -1452,10 +1452,37 @@ double pos_in_interval_through_strxfrm(Field *field,
}
double Histogram_json::point_selectivity(Field *field, key_range *min_endp,
key_range *max_endp, double avg_sel)
double Histogram_json::point_selectivity(Field *field, key_range *endpoint, double avg_sel)
{
return 0.5;
double sel;
store_key_image_to_rec(field, (uchar *) endpoint->key,
field->key_length());
const uchar *min_key = endpoint->key;
if (field->real_maybe_null())
min_key++;
uint min_idx= find_bucket(field, min_key);
uint max_idx= min_idx;
// find how many buckets this value occupies
while ((max_idx + 1 < get_width() ) &&
(field->key_cmp((uchar *)histogram_bounds[max_idx + 1].data(), min_key) == 0)) {
max_idx++;
}
//todo: do we need to account for zero value-length similarly to binary histograms.
if (max_idx > min_idx)
{
// value spans multiple buckets
double bucket_sel= 1.0/(get_width() + 1);
sel= bucket_sel * (max_idx - min_idx + 1);
} else
{
// the value fits within a single bucket
sel = MIN(avg_sel, get_width());
}
return sel;
}
/*
@param field The table field histogram is for. We don't care about the
......@@ -1572,11 +1599,8 @@ int Histogram_json::find_bucket(Field *field, const uchar *endpoint)
if (res < 0) {
low = mid + 1;
min_bucket_index = mid;
} else if (res > 0) {
} else if (res >= 0) {
high = mid - 1;
} else {
//todo: endpoint is on a bucket boundary
break;
}
}
......@@ -4326,7 +4350,7 @@ double get_column_range_cardinality(Field *field,
if (hist && hist->is_usable(thd))
{
res= col_non_nulls *
hist->point_selectivity(field, min_endp, max_endp,
hist->point_selectivity(field, min_endp,
avg_frequency / col_non_nulls);
}
}
......@@ -4390,8 +4414,7 @@ double get_column_range_cardinality(Field *field,
value.
*/
double Histogram_binary::point_selectivity(Field *field, key_range *min_endp,
key_range *max_endp, double avg_sel)
double Histogram_binary::point_selectivity(Field *field, key_range *min_endp, double avg_sel)
{
double sel;
Column_statistics *col_stats= field->read_stats;
......
sql/sql_statistics.h
View file @ bff65a81
......@@ -169,8 +169,7 @@ class Histogram_base : public Sql_alloc
virtual void set_size(ulonglong sz)=0;
virtual double point_selectivity(Field *field, key_range *min_endp,
key_range *max_endp, double avg_selection)=0;
virtual double point_selectivity(Field *field, key_range *endpoint, double avg_selection)=0;
virtual double range_selectivity(Field *field, key_range *min_endp,
key_range *max_endp)=0;
......@@ -334,8 +333,7 @@ class Histogram_binary : public Histogram_base
/*
Estimate selectivity of "col=const" using a histogram
*/
double point_selectivity(Field *field, key_range *min_endp,
key_range *max_endp, double avg_sel) override;
double point_selectivity(Field *field, key_range *endpoint, double avg_sel) override;
};
class Histogram_json : public Histogram_base
......@@ -399,8 +397,7 @@ class Histogram_json : public Histogram_base
uchar *get_values() override { return (uchar *) values; }
double point_selectivity(Field *field, key_range *min_endp,
key_range *max_endp, double avg_selection) override;
double point_selectivity(Field *field, key_range *endpoint, double avg_selection) override;
double range_selectivity(Field *field, key_range *min_endp,
key_range *max_endp) override;
......
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