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Merge branch '10.9' into 10.10

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This commit is contained in:
Oleksandr Byelkin
2023-05-04 11:50:34 +02:00
parent 13a294a2c9 d7fae797f4
commit 16e5bc4cbc
17 changed files with 1638 additions and 357 deletions
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537
mysql-test/main/derived_split_innodb.result
View File

@ -287,4 +287,541 @@ id select_type table type possible_keys key key_len ref rows Extra
2 DERIVED t4 ALL NULL NULL NULL NULL 40 Using filesort 2 DERIVED t4 ALL NULL NULL NULL NULL 40 Using filesort
drop table t3, t4; drop table t3, t4;
# End of 10.3 tests # End of 10.3 tests
#
# MDEV-26301: Split optimization refills temporary table too many times
#
create table t1(a int, b int);
insert into t1 select seq,seq from seq_1_to_5;
create table t2(a int, b int, key(a));
insert into t2
select A.seq,B.seq from seq_1_to_25 A, seq_1_to_2 B;
create table t3(a int, b int, key(a));
insert into t3
select A.seq,B.seq from seq_1_to_5 A, seq_1_to_3 B;
analyze table t1,t2,t3 persistent for all;
Table Op Msg_type Msg_text
test.t1 analyze status Engine-independent statistics collected
test.t1 analyze status OK
test.t2 analyze status Engine-independent statistics collected
test.t2 analyze status Table is already up to date
test.t3 analyze status Engine-independent statistics collected
test.t3 analyze status Table is already up to date
explain
select * from
(t1 left join t2 on t2.a=t1.b) left join t3 on t3.a=t1.b;
id select_type table type possible_keys key key_len ref rows Extra
1 SIMPLE t1 ALL NULL NULL NULL NULL 5
1 SIMPLE t2 ref a a 5 test.t1.b 2 Using where
1 SIMPLE t3 ref a a 5 test.t1.b 3 Using where
create table t10 (
grp_id int,
col1 int,
key(grp_id)
);
insert into t10
select
A.seq,
B.seq
from
seq_1_to_100 A,
seq_1_to_100 B;
create table t11 (
col1 int,
col2 int
);
insert into t11
select A.seq, A.seq from seq_1_to_10 A;
analyze table t10,t11 persistent for all;
Table Op Msg_type Msg_text
test.t10 analyze status Engine-independent statistics collected
test.t10 analyze status Table is already up to date
test.t11 analyze status Engine-independent statistics collected
test.t11 analyze status OK
explain select * from
(
(t1 left join t2 on t2.a=t1.b)
left join t3 on t3.a=t1.b
) left join (select grp_id, count(*)
from t10 left join t11 on t11.col1=t10.col1
group by grp_id) T on T.grp_id=t1.b;
id select_type table type possible_keys key key_len ref rows Extra
1 PRIMARY t1 ALL NULL NULL NULL NULL 5
1 PRIMARY t2 ref a a 5 test.t1.b 2 Using where
1 PRIMARY t3 ref a a 5 test.t1.b 3 Using where
1 PRIMARY <derived2> ref key0 key0 5 test.t1.b 10 Using where
2 LATERAL DERIVED t10 ref grp_id grp_id 5 test.t1.b 100
2 LATERAL DERIVED t11 ALL NULL NULL NULL NULL 10 Using where; Using join buffer (flat, BNL join)
# The important part in the below output is:
# "lateral": 1,
# "query_block": {
# "select_id": 2,
# "r_loops": 5, <-- must be 5, not 30.
analyze format=json select * from
(
(t1 left join t2 on t2.a=t1.b)
left join t3 on t3.a=t1.b
) left join (select grp_id, count(*)
from t10 left join t11 on t11.col1=t10.col1
group by grp_id) T on T.grp_id=t1.b;
ANALYZE
{
"query_block": {
"select_id": 1,
"r_loops": 1,
"r_total_time_ms": "REPLACED",
"const_condition": "1",
"nested_loop": [
{
"table": {
"table_name": "t1",
"access_type": "ALL",
"r_loops": 1,
"rows": 5,
"r_rows": 5,
"r_table_time_ms": "REPLACED",
"r_other_time_ms": "REPLACED",
"filtered": 100,
"r_filtered": 100
}
},
{
"table": {
"table_name": "t2",
"access_type": "ref",
"possible_keys": ["a"],
"key": "a",
"key_length": "5",
"used_key_parts": ["a"],
"ref": ["test.t1.b"],
"r_loops": 5,
"rows": 2,
"r_rows": 2,
"r_table_time_ms": "REPLACED",
"r_other_time_ms": "REPLACED",
"filtered": 100,
"r_filtered": 100,
"attached_condition": "trigcond(trigcond(t1.b is not null))"
}
},
{
"table": {
"table_name": "t3",
"access_type": "ref",
"possible_keys": ["a"],
"key": "a",
"key_length": "5",
"used_key_parts": ["a"],
"ref": ["test.t1.b"],
"r_loops": 10,
"rows": 3,
"r_rows": 3,
"r_table_time_ms": "REPLACED",
"r_other_time_ms": "REPLACED",
"filtered": 100,
"r_filtered": 100,
"attached_condition": "trigcond(trigcond(t1.b is not null))"
}
},
{
"table": {
"table_name": "<derived2>",
"access_type": "ref",
"possible_keys": ["key0"],
"key": "key0",
"key_length": "5",
"used_key_parts": ["grp_id"],
"ref": ["test.t1.b"],
"r_loops": 30,
"rows": 10,
"r_rows": 1,
"r_table_time_ms": "REPLACED",
"r_other_time_ms": "REPLACED",
"filtered": 100,
"r_filtered": 100,
"attached_condition": "trigcond(trigcond(t1.b is not null))",
"materialized": {
"lateral": 1,
"query_block": {
"select_id": 2,
"r_loops": 5,
"r_total_time_ms": "REPLACED",
"outer_ref_condition": "t1.b is not null",
"nested_loop": [
{
"table": {
"table_name": "t10",
"access_type": "ref",
"possible_keys": ["grp_id"],
"key": "grp_id",
"key_length": "5",
"used_key_parts": ["grp_id"],
"ref": ["test.t1.b"],
"r_loops": 5,
"rows": 100,
"r_rows": 100,
"r_table_time_ms": "REPLACED",
"r_other_time_ms": "REPLACED",
"filtered": 100,
"r_filtered": 100
}
},
{
"block-nl-join": {
"table": {
"table_name": "t11",
"access_type": "ALL",
"r_loops": 5,
"rows": 10,
"r_rows": 10,
"r_table_time_ms": "REPLACED",
"r_other_time_ms": "REPLACED",
"filtered": 100,
"r_filtered": 100
},
"buffer_type": "flat",
"buffer_size": "1Kb",
"join_type": "BNL",
"attached_condition": "trigcond(t11.col1 = t10.col1)",
"r_loops": 500,
"r_filtered": 10,
"r_unpack_time_ms": "REPLACED",
"r_other_time_ms": "REPLACED",
"r_effective_rows": 10
}
}
]
}
}
}
}
]
}
}
create table t21 (pk int primary key);
insert into t21 values (1),(2),(3);
create table t22 (pk int primary key);
insert into t22 values (1),(2),(3);
explain
select * from
t21, t22,
(
(t1 left join t2 on t2.a=t1.b)
left join t3 on t3.a=t1.b
) left join (select grp_id, count(*)
from t10 left join t11 on t11.col1=t10.col1
group by grp_id) T on T.grp_id=t1.b
where
t21.pk=1 and t22.pk=2;
id select_type table type possible_keys key key_len ref rows Extra
1 PRIMARY t21 const PRIMARY PRIMARY 4 const 1 Using index
1 PRIMARY t22 const PRIMARY PRIMARY 4 const 1 Using index
1 PRIMARY t1 ALL NULL NULL NULL NULL 5
1 PRIMARY t2 ref a a 5 test.t1.b 2 Using where
1 PRIMARY t3 ref a a 5 test.t1.b 3 Using where
1 PRIMARY <derived2> ref key0 key0 5 test.t1.b 10 Using where
2 LATERAL DERIVED t10 ref grp_id grp_id 5 test.t1.b 100
2 LATERAL DERIVED t11 ALL NULL NULL NULL NULL 10 Using where; Using join buffer (flat, BNL join)
explain
select * from
t21,
(
(t1 left join t2 on t2.a=t1.b)
left join t3 on t3.a=t1.b
) left join (select grp_id, count(*)
from
t22 join t10 left join t11 on t11.col1=t10.col1
where
t22.pk=1
group by grp_id) T on T.grp_id=t1.b
where
t21.pk=1;
id select_type table type possible_keys key key_len ref rows Extra
1 PRIMARY t21 const PRIMARY PRIMARY 4 const 1 Using index
1 PRIMARY t1 ALL NULL NULL NULL NULL 5
1 PRIMARY t2 ref a a 5 test.t1.b 2 Using where
1 PRIMARY t3 ref a a 5 test.t1.b 3 Using where
1 PRIMARY <derived2> ref key0 key0 5 test.t1.b 10 Using where
2 LATERAL DERIVED t22 const PRIMARY PRIMARY 4 const 1 Using index
2 LATERAL DERIVED t10 ref grp_id grp_id 5 test.t1.b 100
2 LATERAL DERIVED t11 ALL NULL NULL NULL NULL 10 Using where; Using join buffer (flat, BNL join)
create table t5 (
pk int primary key
);
insert into t5 select seq from seq_1_to_1000;
explain
select * from
t21,
(
(((t1 join t5 on t5.pk=t1.b)) left join t2 on t2.a=t1.b)
left join t3 on t3.a=t1.b
) left join (select grp_id, count(*)
from
t22 join t10 left join t11 on t11.col1=t10.col1
where
t22.pk=1
group by grp_id) T on T.grp_id=t1.b
where
t21.pk=1;
id select_type table type possible_keys key key_len ref rows Extra
1 PRIMARY t21 const PRIMARY PRIMARY 4 const 1 Using index
1 PRIMARY t1 ALL NULL NULL NULL NULL 5 Using where
1 PRIMARY t5 eq_ref PRIMARY PRIMARY 4 test.t1.b 1 Using index
1 PRIMARY t2 ref a a 5 test.t1.b 2
1 PRIMARY t3 ref a a 5 test.t1.b 3
1 PRIMARY <derived2> ref key0 key0 5 test.t1.b 10 Using where
2 LATERAL DERIVED t22 const PRIMARY PRIMARY 4 const 1 Using index
2 LATERAL DERIVED t10 ref grp_id grp_id 5 test.t5.pk 100 Using index condition
2 LATERAL DERIVED t11 ALL NULL NULL NULL NULL 10 Using where; Using join buffer (flat, BNL join)
drop table t1,t2,t3,t5, t10, t11, t21, t22;
create table t1(a int, b int);
insert into t1 select seq,seq from seq_1_to_5;
create table t2(a int, b int, key(a));
insert into t2
select A.seq,B.seq from seq_1_to_25 A, seq_1_to_2 B;
create table t3(a int, b int, key(a));
insert into t3
select A.seq,B.seq from seq_1_to_5 A, seq_1_to_3 B;
analyze table t1,t2,t3 persistent for all;
Table Op Msg_type Msg_text
test.t1 analyze status Engine-independent statistics collected
test.t1 analyze status OK
test.t2 analyze status Engine-independent statistics collected
test.t2 analyze status Table is already up to date
test.t3 analyze status Engine-independent statistics collected
test.t3 analyze status Table is already up to date
create table t10 (
grp_id int,
col1 int,
key(grp_id)
);
insert into t10
select
A.seq,
B.seq
from
seq_1_to_100 A,
seq_1_to_100 B;
create table t11 (
col1 int,
col2 int
);
insert into t11
select A.seq, A.seq from seq_1_to_10 A;
analyze table t10,t11 persistent for all;
Table Op Msg_type Msg_text
test.t10 analyze status Engine-independent statistics collected
test.t10 analyze status Table is already up to date
test.t11 analyze status Engine-independent statistics collected
test.t11 analyze status OK
explain select *
from
(
(t1 left join t2 on t2.a=t1.b)
left join
t3
on t3.a=t1.b
)
left join
(
select grp_id, count(*)
from t10 left join t11 on t11.col1=t10.col1
group by grp_id
)dt
on dt.grp_id=t1.b;
id select_type table type possible_keys key key_len ref rows Extra
1 PRIMARY t1 ALL NULL NULL NULL NULL 5
1 PRIMARY t2 ref a a 5 test.t1.b 2 Using where
1 PRIMARY t3 ref a a 5 test.t1.b 3 Using where
1 PRIMARY <derived2> ref key0 key0 5 test.t1.b 10 Using where
2 LATERAL DERIVED t10 ref grp_id grp_id 5 test.t1.b 100
2 LATERAL DERIVED t11 ALL NULL NULL NULL NULL 10 Using where; Using join buffer (flat, BNL join)
select *
from
(
(t1 left join t2 on t2.a=t1.b)
left join
t3
on t3.a=t1.b
)
left join
(
select grp_id, count(*)
from t10 left join t11 on t11.col1=t10.col1
group by grp_id
)dt
on dt.grp_id=t1.b;
a b a b a b grp_id count(*)
1 1 1 1 1 1 1 100
1 1 1 1 1 2 1 100
1 1 1 1 1 3 1 100
1 1 1 2 1 1 1 100
1 1 1 2 1 2 1 100
1 1 1 2 1 3 1 100
2 2 2 1 2 1 2 100
2 2 2 1 2 2 2 100
2 2 2 1 2 3 2 100
2 2 2 2 2 1 2 100
2 2 2 2 2 2 2 100
2 2 2 2 2 3 2 100
3 3 3 1 3 1 3 100
3 3 3 1 3 2 3 100
3 3 3 1 3 3 3 100
3 3 3 2 3 1 3 100
3 3 3 2 3 2 3 100
3 3 3 2 3 3 3 100
4 4 4 1 4 1 4 100
4 4 4 1 4 2 4 100
4 4 4 1 4 3 4 100
4 4 4 2 4 1 4 100
4 4 4 2 4 2 4 100
4 4 4 2 4 3 4 100
5 5 5 1 5 1 5 100
5 5 5 1 5 2 5 100
5 5 5 1 5 3 5 100
5 5 5 2 5 1 5 100
5 5 5 2 5 2 5 100
5 5 5 2 5 3 5 100
set join_cache_level=4;
explain select *
from
(
(t1 left join t2 on t2.a=t1.b)
left join
t3
on t3.a=t1.b
)
left join
(
select grp_id, count(*)
from t10 left join t11 on t11.col1=t10.col1
group by grp_id
)dt
on dt.grp_id=t1.b;
id select_type table type possible_keys key key_len ref rows Extra
1 PRIMARY t1 ALL NULL NULL NULL NULL 5
1 PRIMARY t2 ref a a 5 test.t1.b 2 Using where
1 PRIMARY t3 ref a a 5 test.t1.b 3 Using where
1 PRIMARY <derived2> ref key0 key0 5 test.t1.b 10 Using where
2 LATERAL DERIVED t10 ref grp_id grp_id 5 test.t1.b 100
2 LATERAL DERIVED t11 hash_ALL NULL #hash#$hj 5 test.t10.col1 10 Using where; Using join buffer (flat, BNLH join)
select *
from
(
(t1 left join t2 on t2.a=t1.b)
left join
t3
on t3.a=t1.b
)
left join
(
select grp_id, count(*)
from t10 left join t11 on t11.col1=t10.col1
group by grp_id
)dt
on dt.grp_id=t1.b;
a b a b a b grp_id count(*)
1 1 1 1 1 1 1 100
1 1 1 1 1 2 1 100
1 1 1 1 1 3 1 100
1 1 1 2 1 1 1 100
1 1 1 2 1 2 1 100
1 1 1 2 1 3 1 100
2 2 2 1 2 1 2 100
2 2 2 1 2 2 2 100
2 2 2 1 2 3 2 100
2 2 2 2 2 1 2 100
2 2 2 2 2 2 2 100
2 2 2 2 2 3 2 100
3 3 3 1 3 1 3 100
3 3 3 1 3 2 3 100
3 3 3 1 3 3 3 100
3 3 3 2 3 1 3 100
3 3 3 2 3 2 3 100
3 3 3 2 3 3 3 100
4 4 4 1 4 1 4 100
4 4 4 1 4 2 4 100
4 4 4 1 4 3 4 100
4 4 4 2 4 1 4 100
4 4 4 2 4 2 4 100
4 4 4 2 4 3 4 100
5 5 5 1 5 1 5 100
5 5 5 1 5 2 5 100
5 5 5 1 5 3 5 100
5 5 5 2 5 1 5 100
5 5 5 2 5 2 5 100
5 5 5 2 5 3 5 100
set join_cache_level=default;
drop index a on t2;
drop index a on t3;
explain select *
from
(
(t1 left join t2 on t2.a=t1.b)
left join
t3
on t3.a=t1.b
)
left join
(
select grp_id, count(*)
from t10 left join t11 on t11.col1=t10.col1
group by grp_id
)dt
on dt.grp_id=t1.b;
id select_type table type possible_keys key key_len ref rows Extra
1 PRIMARY t1 ALL NULL NULL NULL NULL 5
1 PRIMARY t2 ALL NULL NULL NULL NULL 50 Using where; Using join buffer (flat, BNL join)
1 PRIMARY t3 ALL NULL NULL NULL NULL 15 Using where; Using join buffer (incremental, BNL join)
1 PRIMARY <derived2> ref key0 key0 5 test.t1.b 1000 Using where
2 DERIVED t10 ALL grp_id NULL NULL NULL 10000 Using temporary; Using filesort
2 DERIVED t11 ALL NULL NULL NULL NULL 10 Using where; Using join buffer (flat, BNL join)
select *
from
(
(t1 left join t2 on t2.a=t1.b)
left join
t3
on t3.a=t1.b
)
left join
(
select grp_id, count(*)
from t10 left join t11 on t11.col1=t10.col1
group by grp_id
)dt
on dt.grp_id=t1.b;
a b a b a b grp_id count(*)
1 1 1 1 1 1 1 100
1 1 1 2 1 1 1 100
1 1 1 1 1 2 1 100
1 1 1 2 1 2 1 100
1 1 1 1 1 3 1 100
1 1 1 2 1 3 1 100
2 2 2 1 2 1 2 100
2 2 2 2 2 1 2 100
2 2 2 1 2 2 2 100
2 2 2 2 2 2 2 100
2 2 2 1 2 3 2 100
2 2 2 2 2 3 2 100
3 3 3 1 3 1 3 100
3 3 3 2 3 1 3 100
3 3 3 1 3 2 3 100
3 3 3 2 3 2 3 100
3 3 3 1 3 3 3 100
3 3 3 2 3 3 3 100
4 4 4 1 4 1 4 100
4 4 4 2 4 1 4 100
4 4 4 1 4 2 4 100
4 4 4 2 4 2 4 100
4 4 4 1 4 3 4 100
4 4 4 2 4 3 4 100
5 5 5 1 5 1 5 100
5 5 5 2 5 1 5 100
5 5 5 1 5 2 5 100
5 5 5 2 5 2 5 100
5 5 5 1 5 3 5 100
5 5 5 2 5 3 5 100
drop table t1,t2,t3;
drop table t10, t11;
# End of 10.4 tests
SET GLOBAL innodb_stats_persistent=@save_innodb_stats_persistent; SET GLOBAL innodb_stats_persistent=@save_innodb_stats_persistent;

212
mysql-test/main/derived_split_innodb.test
View File

@ -233,4 +233,216 @@ drop table t3, t4;
--echo # End of 10.3 tests --echo # End of 10.3 tests
--echo #
--echo # MDEV-26301: Split optimization refills temporary table too many times
--echo #
# 5 values
create table t1(a int, b int);
insert into t1 select seq,seq from seq_1_to_5;
# 5 value groups of size 2 each
create table t2(a int, b int, key(a));
insert into t2
select A.seq,B.seq from seq_1_to_25 A, seq_1_to_2 B;
# 5 value groups of size 3 each
create table t3(a int, b int, key(a));
insert into t3
select A.seq,B.seq from seq_1_to_5 A, seq_1_to_3 B;
analyze table t1,t2,t3 persistent for all;
explain
select * from
(t1 left join t2 on t2.a=t1.b) left join t3 on t3.a=t1.b;
# Now, create tables for Groups.
create table t10 (
grp_id int,
col1 int,
key(grp_id)
);
# 100 groups of 100 values each
insert into t10
select
A.seq,
B.seq
from
seq_1_to_100 A,
seq_1_to_100 B;
# and X10 multiplier
create table t11 (
col1 int,
col2 int
);
insert into t11
select A.seq, A.seq from seq_1_to_10 A;
analyze table t10,t11 persistent for all;
let $q1=
select * from
(
(t1 left join t2 on t2.a=t1.b)
left join t3 on t3.a=t1.b
) left join (select grp_id, count(*)
from t10 left join t11 on t11.col1=t10.col1
group by grp_id) T on T.grp_id=t1.b;
eval
explain $q1;
--echo # The important part in the below output is:
--echo # "lateral": 1,
--echo # "query_block": {
--echo # "select_id": 2,
--echo # "r_loops": 5, <-- must be 5, not 30.
--source include/analyze-format.inc
eval
analyze format=json $q1;
create table t21 (pk int primary key);
insert into t21 values (1),(2),(3);
create table t22 (pk int primary key);
insert into t22 values (1),(2),(3);
# Same as above but throw in a couple of const tables.
explain
select * from
t21, t22,
(
(t1 left join t2 on t2.a=t1.b)
left join t3 on t3.a=t1.b
) left join (select grp_id, count(*)
from t10 left join t11 on t11.col1=t10.col1
group by grp_id) T on T.grp_id=t1.b
where
t21.pk=1 and t22.pk=2;
explain
select * from
t21,
(
(t1 left join t2 on t2.a=t1.b)
left join t3 on t3.a=t1.b
) left join (select grp_id, count(*)
from
t22 join t10 left join t11 on t11.col1=t10.col1
where
t22.pk=1
group by grp_id) T on T.grp_id=t1.b
where
t21.pk=1;
# And also add a non-const table
create table t5 (
pk int primary key
);
insert into t5 select seq from seq_1_to_1000;
explain
select * from
t21,
(
(((t1 join t5 on t5.pk=t1.b)) left join t2 on t2.a=t1.b)
left join t3 on t3.a=t1.b
) left join (select grp_id, count(*)
from
t22 join t10 left join t11 on t11.col1=t10.col1
where
t22.pk=1
group by grp_id) T on T.grp_id=t1.b
where
t21.pk=1;
drop table t1,t2,t3,t5, t10, t11, t21, t22;
# 5 values
create table t1(a int, b int);
insert into t1 select seq,seq from seq_1_to_5;
# 5 value groups of size 2 each
create table t2(a int, b int, key(a));
insert into t2
select A.seq,B.seq from seq_1_to_25 A, seq_1_to_2 B;
# 5 value groups of size 3 each
create table t3(a int, b int, key(a));
insert into t3
select A.seq,B.seq from seq_1_to_5 A, seq_1_to_3 B;
analyze table t1,t2,t3 persistent for all;
create table t10 (
grp_id int,
col1 int,
key(grp_id)
);
# 100 groups of 100 values each
insert into t10
select
A.seq,
B.seq
from
seq_1_to_100 A,
seq_1_to_100 B;
# and X10 multiplier
create table t11 (
col1 int,
col2 int
);
insert into t11
select A.seq, A.seq from seq_1_to_10 A;
analyze table t10,t11 persistent for all;
let $q=
select *
from
(
(t1 left join t2 on t2.a=t1.b)
left join
t3
on t3.a=t1.b
)
left join
(
select grp_id, count(*)
from t10 left join t11 on t11.col1=t10.col1
group by grp_id
)dt
on dt.grp_id=t1.b;
eval explain $q;
eval $q;
set join_cache_level=4;
eval explain $q;
eval $q;
set join_cache_level=default;
drop index a on t2;
drop index a on t3;
eval explain $q;
eval $q;
drop table t1,t2,t3;
drop table t10, t11;
--echo # End of 10.4 tests
SET GLOBAL innodb_stats_persistent=@save_innodb_stats_persistent; SET GLOBAL innodb_stats_persistent=@save_innodb_stats_persistent;

18
mysql-test/main/explain_innodb.result
View File

@ -18,3 +18,21 @@ id select_type table type possible_keys key key_len ref rows Extra
2 DERIVED t1 range NULL id 53 NULL 2 Using index for group-by 2 DERIVED t1 range NULL id 53 NULL 2 Using index for group-by
SET GLOBAL slow_query_log = @sql_tmp; SET GLOBAL slow_query_log = @sql_tmp;
drop table t1; drop table t1;
#
# MDEV-31181: Server crash in subselect_uniquesubquery_engine::print
# upon EXPLAIN EXTENDED DELETE
#
CREATE TABLE t1 (a INT);
INSERT INTO t1 VALUES (1),(2);
CREATE TABLE t2 (pk INT PRIMARY KEY);
INSERT INTO t2 VALUES (1),(2);
EXPLAIN EXTENDED DELETE FROM t1 WHERE a IN (SELECT pk FROM t2);
id select_type table type possible_keys key key_len ref rows filtered Extra
1 PRIMARY t1 ALL NULL NULL NULL NULL 2 100.00 Using where
2 DEPENDENT SUBQUERY t2 unique_subquery PRIMARY PRIMARY 4 func 1 100.00 Using index
Warnings:
Note 1003 /* select#1 */ delete from `test`.`t1` where <in_optimizer>(`test`.`t1`.`a`,<exists>(<primary_index_lookup>(<cache>(`test`.`t1`.`a`))))
drop table t1, t2;
#
# End of 10.4 tests
#

19
mysql-test/main/explain_innodb.test
View File

@ -18,3 +18,22 @@ SELECT * FROM (SELECT id FROM t1 GROUP BY id) dt WHERE 1=0;
SET GLOBAL slow_query_log = @sql_tmp; SET GLOBAL slow_query_log = @sql_tmp;
drop table t1; drop table t1;
--echo #
--echo # MDEV-31181: Server crash in subselect_uniquesubquery_engine::print
--echo # upon EXPLAIN EXTENDED DELETE
--echo #
CREATE TABLE t1 (a INT);
INSERT INTO t1 VALUES (1),(2);
CREATE TABLE t2 (pk INT PRIMARY KEY);
INSERT INTO t2 VALUES (1),(2);
EXPLAIN EXTENDED DELETE FROM t1 WHERE a IN (SELECT pk FROM t2);
drop table t1, t2;
--echo #
--echo # End of 10.4 tests
--echo #

254
mysql-test/main/opt_trace.result
View File

@ -480,6 +480,11 @@ select * from v2 {
} }
] ]
}, },
{
"check_split_materialized": {
"not_applicable": "no candidate field can be accessed through ref"
}
},
{ {
"best_join_order": ["t1"] "best_join_order": ["t1"]
}, },
@ -827,6 +832,11 @@ explain select * from v1 {
} }
] ]
}, },
{
"check_split_materialized": {
"not_applicable": "group list has no candidates"
}
},
{ {
"best_join_order": ["t1"] "best_join_order": ["t1"]
}, },
@ -10343,6 +10353,110 @@ SET optimizer_trace=DEFAULT;
DROP VIEW v; DROP VIEW v;
DROP TABLE t; DROP TABLE t;
# #
# MDEV-26301: Split optimization improvements: Optimizer Trace coverage
#
create table t1(a int, b int);
insert into t1 select seq,seq from seq_1_to_5;
create table t2(a int, b int, key(a));
insert into t2
select A.seq,B.seq from seq_1_to_25 A, seq_1_to_2 B;
create table t3(a int, b int, key(a));
insert into t3
select A.seq,B.seq from seq_1_to_5 A, seq_1_to_3 B;
analyze table t1,t2,t3 persistent for all;
Table Op Msg_type Msg_text
test.t1 analyze status Engine-independent statistics collected
test.t1 analyze status OK
test.t2 analyze status Engine-independent statistics collected
test.t2 analyze status Table is already up to date
test.t3 analyze status Engine-independent statistics collected
test.t3 analyze status Table is already up to date
create table t10 (
grp_id int,
col1 int,
key(grp_id)
);
insert into t10
select
A.seq,
B.seq
from
seq_1_to_100 A,
seq_1_to_100 B;
create table t11 (
col1 int,
col2 int
);
insert into t11
select A.seq, A.seq from seq_1_to_10 A;
analyze table t10,t11 persistent for all;
Table Op Msg_type Msg_text
test.t10 analyze status Engine-independent statistics collected
test.t10 analyze status Table is already up to date
test.t11 analyze status Engine-independent statistics collected
test.t11 analyze status OK
set optimizer_trace=1;
explain
select * from
(
(t1 left join t2 on t2.a=t1.b)
left join t3 on t3.a=t1.b
) left join (select grp_id, count(*)
from t10 left join t11 on t11.col1=t10.col1
group by grp_id) T on T.grp_id=t1.b;
id select_type table type possible_keys key key_len ref rows Extra
1 PRIMARY t1 ALL NULL NULL NULL NULL 5
1 PRIMARY t2 ref a a 5 test.t1.b 2 Using where
1 PRIMARY t3 ref a a 5 test.t1.b 3 Using where
1 PRIMARY <derived2> ref key0 key0 5 test.t1.b 10 Using where
2 LATERAL DERIVED t10 ref grp_id grp_id 5 test.t1.b 100
2 LATERAL DERIVED t11 ALL NULL NULL NULL NULL 10 Using where; Using join buffer (flat, BNL join)
select json_detailed(json_extract(trace, '$**.check_split_materialized')) as JS
from information_schema.optimizer_trace;
JS
[
{
"split_candidates":
["t10.grp_id"]
}
]
select
json_detailed(
json_remove(
json_extract(trace, '$**.choose_best_splitting')
, '$[0].split_plan_search[0]'
)
) as JS
from information_schema.optimizer_trace;
JS
[
{
"considered_keys":
[
{
"table_name": "t10",
"index": "grp_id",
"rec_per_key": 100,
"param_tables": 1
}
],
"refills": 5,
"spl_pd_boundary": 2,
"split_plan_search":
[],
"lead_table": "t10",
"index": "grp_id",
"parts": 1,
"split_sel": 0.001,
"cost": 2535.968504,
"unsplit_cost": 253440.0075,
"records": 100,
"chosen": true
}
]
drop table t1,t2,t3,t10,t11;
set optimizer_trace=DEFAULT;
#
# End of 10.4 tests # End of 10.4 tests
# #
set optimizer_trace='enabled=on'; set optimizer_trace='enabled=on';
@ -10763,79 +10877,83 @@ from
information_schema.optimizer_trace; information_schema.optimizer_trace;
json_detailed(json_extract(trace, '$**.choose_best_splitting')) json_detailed(json_extract(trace, '$**.choose_best_splitting'))
[ [
[ {
{ "considered_keys":
"considered_execution_plans": []
[ },
{ {
"plan_prefix": "considered_keys":
[], [
"get_costs_for_tables": {
[ "table_name": "t2",
{ "index": "idx_a",
"best_access_path": "rec_per_key": 1.8367,
"param_tables": 1
}
],
"refills": 4,
"spl_pd_boundary": 2,
"split_plan_search":
[
{
"considered_execution_plans":
[
{
"plan_prefix":
[],
"get_costs_for_tables":
[
{ {
"table": "t2", "best_access_path":
"considered_access_paths":
[
{
"access_type": "ref",
"index": "idx_a",
"used_range_estimates": false,
"reason": "not available",
"rows": 1.8367,
"cost": 2.000585794,
"chosen": true
},
{
"type": "scan",
"chosen": false,
"cause": "cost"
}
],
"chosen_access_method":
{ {
"type": "ref", "table": "t2",
"records": 1.8367, "considered_access_paths":
"cost": 2.000585794, [
"uses_join_buffering": false {
"access_type": "ref",
"index": "idx_a",
"used_range_estimates": false,
"reason": "not available",
"rows": 1.8367,
"cost": 2.000585794,
"chosen": true
},
{
"type": "scan",
"chosen": false,
"cause": "cost"
}
],
"chosen_access_method":
{
"type": "ref",
"records": 1.8367,
"cost": 2.000585794,
"uses_join_buffering": false
}
} }
} }
} ]
] },
}, {
{ "plan_prefix":
"plan_prefix": [],
[], "table": "t2",
"table": "t2", "rows_for_plan": 1.8367,
"rows_for_plan": 1.8367, "cost_for_plan": 2.367925794,
"cost_for_plan": 2.367925794, "cost_for_sorting": 1.8367
"cost_for_sorting": 1.8367 }
} ]
]
},
{
"best_splitting":
{
"table": "t2",
"key": "idx_a",
"record_count": 4,
"cost": 2.488945919,
"unsplit_cost": 25.72361682
} }
} ],
] "lead_table": "t2",
] "index": "idx_a",
select "parts": 1,
json_detailed(json_extract(trace, '$**.lateral_derived')) "split_sel": 0.020407778,
from "cost": 2.488945919,
information_schema.optimizer_trace; "unsplit_cost": 25.72361682,
json_detailed(json_extract(trace, '$**.lateral_derived')) "records": 1,
[ "chosen": true
{
"startup_cost": 9.955783677,
"splitting_cost": 2.488945919,
"records": 1
} }
] ]
drop table t1,t2; drop table t1,t2;

77
mysql-test/main/opt_trace.test
View File

@ -701,6 +701,76 @@ SET optimizer_trace=DEFAULT;
DROP VIEW v; DROP VIEW v;
DROP TABLE t; DROP TABLE t;
--echo #
--echo # MDEV-26301: Split optimization improvements: Optimizer Trace coverage
--echo #
# 5 values
create table t1(a int, b int);
insert into t1 select seq,seq from seq_1_to_5;
# 5 value groups of size 2 each
create table t2(a int, b int, key(a));
insert into t2
select A.seq,B.seq from seq_1_to_25 A, seq_1_to_2 B;
# 5 value groups of size 3 each
create table t3(a int, b int, key(a));
insert into t3
select A.seq,B.seq from seq_1_to_5 A, seq_1_to_3 B;
analyze table t1,t2,t3 persistent for all;
create table t10 (
grp_id int,
col1 int,
key(grp_id)
);
# 100 groups of 100 values each
insert into t10
select
A.seq,
B.seq
from
seq_1_to_100 A,
seq_1_to_100 B;
# and X10 multiplier
create table t11 (
col1 int,
col2 int
);
insert into t11
select A.seq, A.seq from seq_1_to_10 A;
analyze table t10,t11 persistent for all;
set optimizer_trace=1;
explain
select * from
(
(t1 left join t2 on t2.a=t1.b)
left join t3 on t3.a=t1.b
) left join (select grp_id, count(*)
from t10 left join t11 on t11.col1=t10.col1
group by grp_id) T on T.grp_id=t1.b;
select json_detailed(json_extract(trace, '$**.check_split_materialized')) as JS
from information_schema.optimizer_trace;
select
json_detailed(
json_remove(
json_extract(trace, '$**.choose_best_splitting')
, '$[0].split_plan_search[0]'
)
) as JS
from information_schema.optimizer_trace;
drop table t1,t2,t3,t10,t11;
set optimizer_trace=DEFAULT;
--echo # --echo #
--echo # End of 10.4 tests --echo # End of 10.4 tests
--echo # --echo #
@ -909,13 +979,6 @@ from
information_schema.optimizer_trace; information_schema.optimizer_trace;
--enable_view_protocol --enable_view_protocol
# Same as above. just to show that splitting plan has some coverage in the
# trace.
select
json_detailed(json_extract(trace, '$**.lateral_derived'))
from
information_schema.optimizer_trace;
drop table t1,t2; drop table t1,t2;
--echo # --echo #

69
mysql-test/main/selectivity.result
View File

@ -1943,75 +1943,6 @@ Warnings:
Note 1003 select `test`.`t1`.`a` AS `a` from `test`.`t1` where `test`.`t1`.`a` = 2 Note 1003 select `test`.`t1`.`a` AS `a` from `test`.`t1` where `test`.`t1`.`a` = 2
DROP TABLE t1; DROP TABLE t1;
# End of 10.2 tests # End of 10.2 tests
#
# MDEV-31067: selectivity_from_histogram >1.0 for a DOUBLE_PREC_HB histogram
#
create table t0(a int);
insert into t0 select 1 from seq_1_to_78;
create table t1(a int);
insert into t1 select 1 from seq_1_to_26;
create table t10 (a int);
insert into t10 select 0 from t0, seq_1_to_4;
insert into t10 select 8693 from t1;
insert into t10 select 8694 from t1;
insert into t10 select 8695 from t1;
insert into t10 select 34783 from t1;
insert into t10 select 34784 from t1;
insert into t10 select 34785 from t1;
insert into t10 select 34785 from t0, seq_1_to_8;
insert into t10 select 65214 from t1;
insert into t10 select 65215 from t1;
insert into t10 select 65216 from t1;
insert into t10 select 65216 from t0, seq_1_to_52;
insert into t10 select 65217 from t1;
insert into t10 select 65218 from t1;
insert into t10 select 65219 from t1;
insert into t10 select 65219 from t0;
insert into t10 select 73913 from t1;
insert into t10 select 73914 from t1;
insert into t10 select 73915 from t1;
insert into t10 select 73915 from t0, seq_1_to_40;
insert into t10 select 78257 from t1;
insert into t10 select 78258 from t1;
insert into t10 select 78259 from t1;
insert into t10 select 91300 from t1;
insert into t10 select 91301 from t1;
insert into t10 select 91302 from t1;
insert into t10 select 91302 from t0, seq_1_to_6;
insert into t10 select 91303 from t1;
insert into t10 select 91304 from t1;
insert into t10 select 91305 from t1;
insert into t10 select 91305 from t0, seq_1_to_8;
insert into t10 select 99998 from t1;
insert into t10 select 99999 from t1;
insert into t10 select 100000 from t1;
set use_stat_tables=preferably;
analyze table t10 persistent for all;
Table Op Msg_type Msg_text
test.t10 analyze status Engine-independent statistics collected
test.t10 analyze status OK
flush tables;
set @tmp=@@optimizer_trace;
set optimizer_trace=1;
explain select * from t10 where a in (91303);
id select_type table type possible_keys key key_len ref rows Extra
1 SIMPLE t10 ALL NULL NULL NULL NULL 9984 Using where
# Must have selectivity_from_histogram <= 1.0:
select json_detailed(json_extract(trace, '$**.selectivity_for_columns'))
from information_schema.optimizer_trace;
json_detailed(json_extract(trace, '$**.selectivity_for_columns'))
[
[
{
"column_name": "a",
"ranges":
["91303 <= a <= 91303"],
"selectivity_from_histogram": 0.035714283
}
]
]
set optimizer_trace=@tmp;
drop table t0,t1,t10;
set optimizer_use_condition_selectivity= @save_optimizer_use_condition_selectivity; set optimizer_use_condition_selectivity= @save_optimizer_use_condition_selectivity;
set histogram_size=@save_histogram_size; set histogram_size=@save_histogram_size;
set use_stat_tables= @save_use_stat_tables; set use_stat_tables= @save_use_stat_tables;

84
mysql-test/main/selectivity.test
View File

@ -1326,90 +1326,12 @@ DROP TABLE t1;
--echo # End of 10.2 tests --echo # End of 10.2 tests
--echo #
--echo # MDEV-31067: selectivity_from_histogram >1.0 for a DOUBLE_PREC_HB histogram
--echo #
create table t0(a int); # This holds how many rows we hold in a bucket.
insert into t0 select 1 from seq_1_to_78;
create table t1(a int); # one-third of a bucket
insert into t1 select 1 from seq_1_to_26;
create table t10 (a int);
insert into t10 select 0 from t0, seq_1_to_4;
insert into t10 select 8693 from t1;
insert into t10 select 8694 from t1;
insert into t10 select 8695 from t1;
insert into t10 select 34783 from t1;
insert into t10 select 34784 from t1;
insert into t10 select 34785 from t1;
insert into t10 select 34785 from t0, seq_1_to_8;
insert into t10 select 65214 from t1;
insert into t10 select 65215 from t1;
insert into t10 select 65216 from t1;
insert into t10 select 65216 from t0, seq_1_to_52;
insert into t10 select 65217 from t1;
insert into t10 select 65218 from t1;
insert into t10 select 65219 from t1;
insert into t10 select 65219 from t0;
insert into t10 select 73913 from t1;
insert into t10 select 73914 from t1;
insert into t10 select 73915 from t1;
insert into t10 select 73915 from t0, seq_1_to_40;
insert into t10 select 78257 from t1;
insert into t10 select 78258 from t1;
insert into t10 select 78259 from t1;
insert into t10 select 91300 from t1;
insert into t10 select 91301 from t1;
insert into t10 select 91302 from t1;
insert into t10 select 91302 from t0, seq_1_to_6;
insert into t10 select 91303 from t1; # Only 1/3rd of bucket matches the search tuple
insert into t10 select 91304 from t1;
insert into t10 select 91305 from t1;
insert into t10 select 91305 from t0, seq_1_to_8;
insert into t10 select 99998 from t1;
insert into t10 select 99999 from t1;
insert into t10 select 100000 from t1;
set use_stat_tables=preferably;
analyze table t10 persistent for all;
flush tables;
set @tmp=@@optimizer_trace;
set optimizer_trace=1;
explain select * from t10 where a in (91303);
--echo # Must have selectivity_from_histogram <= 1.0:
select json_detailed(json_extract(trace, '$**.selectivity_for_columns'))
from information_schema.optimizer_trace;
set optimizer_trace=@tmp;
drop table t0,t1,t10;
set optimizer_use_condition_selectivity= @save_optimizer_use_condition_selectivity;
set histogram_size=@save_histogram_size;
set use_stat_tables= @save_use_stat_tables;
# #
# Clean up # Clean up
# #
set optimizer_use_condition_selectivity= @save_optimizer_use_condition_selectivity;
set histogram_size=@save_histogram_size;
set use_stat_tables= @save_use_stat_tables;
--source include/restore_charset.inc --source include/restore_charset.inc
set @@global.histogram_size=@save_histogram_size; set @@global.histogram_size=@save_histogram_size;

69
mysql-test/main/selectivity_innodb.result
View File

@ -1955,75 +1955,6 @@ Warnings:
Note 1003 select `test`.`t1`.`a` AS `a` from `test`.`t1` where `test`.`t1`.`a` = 2 Note 1003 select `test`.`t1`.`a` AS `a` from `test`.`t1` where `test`.`t1`.`a` = 2
DROP TABLE t1; DROP TABLE t1;
# End of 10.2 tests # End of 10.2 tests
#
# MDEV-31067: selectivity_from_histogram >1.0 for a DOUBLE_PREC_HB histogram
#
create table t0(a int);
insert into t0 select 1 from seq_1_to_78;
create table t1(a int);
insert into t1 select 1 from seq_1_to_26;
create table t10 (a int);
insert into t10 select 0 from t0, seq_1_to_4;
insert into t10 select 8693 from t1;
insert into t10 select 8694 from t1;
insert into t10 select 8695 from t1;
insert into t10 select 34783 from t1;
insert into t10 select 34784 from t1;
insert into t10 select 34785 from t1;
insert into t10 select 34785 from t0, seq_1_to_8;
insert into t10 select 65214 from t1;
insert into t10 select 65215 from t1;
insert into t10 select 65216 from t1;
insert into t10 select 65216 from t0, seq_1_to_52;
insert into t10 select 65217 from t1;
insert into t10 select 65218 from t1;
insert into t10 select 65219 from t1;
insert into t10 select 65219 from t0;
insert into t10 select 73913 from t1;
insert into t10 select 73914 from t1;
insert into t10 select 73915 from t1;
insert into t10 select 73915 from t0, seq_1_to_40;
insert into t10 select 78257 from t1;
insert into t10 select 78258 from t1;
insert into t10 select 78259 from t1;
insert into t10 select 91300 from t1;
insert into t10 select 91301 from t1;
insert into t10 select 91302 from t1;
insert into t10 select 91302 from t0, seq_1_to_6;
insert into t10 select 91303 from t1;
insert into t10 select 91304 from t1;
insert into t10 select 91305 from t1;
insert into t10 select 91305 from t0, seq_1_to_8;
insert into t10 select 99998 from t1;
insert into t10 select 99999 from t1;
insert into t10 select 100000 from t1;
set use_stat_tables=preferably;
analyze table t10 persistent for all;
Table Op Msg_type Msg_text
test.t10 analyze status Engine-independent statistics collected
test.t10 analyze status OK
flush tables;
set @tmp=@@optimizer_trace;
set optimizer_trace=1;
explain select * from t10 where a in (91303);
id select_type table type possible_keys key key_len ref rows Extra
1 SIMPLE t10 ALL NULL NULL NULL NULL 9984 Using where
# Must have selectivity_from_histogram <= 1.0:
select json_detailed(json_extract(trace, '$**.selectivity_for_columns'))
from information_schema.optimizer_trace;
json_detailed(json_extract(trace, '$**.selectivity_for_columns'))
[
[
{
"column_name": "a",
"ranges":
["91303 <= a <= 91303"],
"selectivity_from_histogram": 0.035714283
}
]
]
set optimizer_trace=@tmp;
drop table t0,t1,t10;
set optimizer_use_condition_selectivity= @save_optimizer_use_condition_selectivity; set optimizer_use_condition_selectivity= @save_optimizer_use_condition_selectivity;
set histogram_size=@save_histogram_size; set histogram_size=@save_histogram_size;
set use_stat_tables= @save_use_stat_tables; set use_stat_tables= @save_use_stat_tables;

104
mysql-test/main/selectivity_innodb_notembedded.result Normal file
View File

@ -0,0 +1,104 @@
SET SESSION STORAGE_ENGINE='InnoDB';
Warnings:
Warning 1287 '@@storage_engine' is deprecated and will be removed in a future release. Please use '@@default_storage_engine' instead
set @save_optimizer_switch_for_selectivity_test=@@optimizer_switch;
set optimizer_switch='extended_keys=on';
drop table if exists t0,t1,t2,t3;
select @@global.use_stat_tables;
@@global.use_stat_tables
COMPLEMENTARY
select @@session.use_stat_tables;
@@session.use_stat_tables
COMPLEMENTARY
set @save_use_stat_tables=@@use_stat_tables;
set use_stat_tables='preferably';
set @save_optimizer_use_condition_selectivity=@@optimizer_use_condition_selectivity;
set @save_histogram_size=@@histogram_size;
set @save_histogram_type=@@histogram_type;
set join_cache_level=2;
set @@global.histogram_size=0,@@local.histogram_size=0;
set histogram_type='single_prec_hb';
set optimizer_use_condition_selectivity=3;
#
# MDEV-31067: selectivity_from_histogram >1.0 for a DOUBLE_PREC_HB histogram
#
create table t0(a int);
insert into t0 select 1 from seq_1_to_78;
create table t1(a int);
insert into t1 select 1 from seq_1_to_26;
create table t10 (a int);
insert into t10 select 0 from t0, seq_1_to_4;
insert into t10 select 8693 from t1;
insert into t10 select 8694 from t1;
insert into t10 select 8695 from t1;
insert into t10 select 34783 from t1;
insert into t10 select 34784 from t1;
insert into t10 select 34785 from t1;
insert into t10 select 34785 from t0, seq_1_to_8;
insert into t10 select 65214 from t1;
insert into t10 select 65215 from t1;
insert into t10 select 65216 from t1;
insert into t10 select 65216 from t0, seq_1_to_52;
insert into t10 select 65217 from t1;
insert into t10 select 65218 from t1;
insert into t10 select 65219 from t1;
insert into t10 select 65219 from t0;
insert into t10 select 73913 from t1;
insert into t10 select 73914 from t1;
insert into t10 select 73915 from t1;
insert into t10 select 73915 from t0, seq_1_to_40;
insert into t10 select 78257 from t1;
insert into t10 select 78258 from t1;
insert into t10 select 78259 from t1;
insert into t10 select 91300 from t1;
insert into t10 select 91301 from t1;
insert into t10 select 91302 from t1;
insert into t10 select 91302 from t0, seq_1_to_6;
insert into t10 select 91303 from t1;
insert into t10 select 91304 from t1;
insert into t10 select 91305 from t1;
insert into t10 select 91305 from t0, seq_1_to_8;
insert into t10 select 99998 from t1;
insert into t10 select 99999 from t1;
insert into t10 select 100000 from t1;
set use_stat_tables=preferably;
analyze table t10 persistent for all;
Table Op Msg_type Msg_text
test.t10 analyze status Engine-independent statistics collected
test.t10 analyze status OK
flush tables;
set @tmp=@@optimizer_trace;
set optimizer_trace=1;
explain select * from t10 where a in (91303);
id select_type table type possible_keys key key_len ref rows Extra
1 SIMPLE t10 ALL NULL NULL NULL NULL 9984 Using where
# Must have selectivity_from_histogram <= 1.0:
select json_detailed(json_extract(trace, '$**.selectivity_for_columns')) as sel
from information_schema.optimizer_trace;
sel
[
[
{
"column_name": "a",
"ranges":
["91303 <= a <= 91303"],
"selectivity_from_histogram": 0.035714283
}
]
]
set optimizer_trace=@tmp;
drop table t0,t1,t10;
set optimizer_use_condition_selectivity= @save_optimizer_use_condition_selectivity;
set histogram_size=@save_histogram_size;
set use_stat_tables= @save_use_stat_tables;
#
# End of 10.4 tests
#
#
# Clean up
#
set @@global.histogram_size=@save_histogram_size;
set optimizer_switch=@save_optimizer_switch_for_selectivity_test;
SET SESSION STORAGE_ENGINE=DEFAULT;
Warnings:
Warning 1287 '@@storage_engine' is deprecated and will be removed in a future release. Please use '@@default_storage_engine' instead

16
mysql-test/main/selectivity_innodb_notembedded.test Normal file
View File

@ -0,0 +1,16 @@
--source include/have_innodb.inc
# This test is slow on buildbot.
--source include/big_test.inc
--source include/default_optimizer_switch.inc
--source include/not_embedded.inc
SET SESSION STORAGE_ENGINE='InnoDB';
set @save_optimizer_switch_for_selectivity_test=@@optimizer_switch;
set optimizer_switch='extended_keys=on';
--source selectivity_notembedded.test
set optimizer_switch=@save_optimizer_switch_for_selectivity_test;
SET SESSION STORAGE_ENGINE=DEFAULT;

95
mysql-test/main/selectivity_notembedded.result Normal file
View File

@ -0,0 +1,95 @@
drop table if exists t0,t1,t2,t3;
select @@global.use_stat_tables;
@@global.use_stat_tables
COMPLEMENTARY
select @@session.use_stat_tables;
@@session.use_stat_tables
COMPLEMENTARY
set @save_use_stat_tables=@@use_stat_tables;
set use_stat_tables='preferably';
set @save_optimizer_use_condition_selectivity=@@optimizer_use_condition_selectivity;
set @save_histogram_size=@@histogram_size;
set @save_histogram_type=@@histogram_type;
set join_cache_level=2;
set @@global.histogram_size=0,@@local.histogram_size=0;
set histogram_type='single_prec_hb';
set optimizer_use_condition_selectivity=3;
#
# MDEV-31067: selectivity_from_histogram >1.0 for a DOUBLE_PREC_HB histogram
#
create table t0(a int);
insert into t0 select 1 from seq_1_to_78;
create table t1(a int);
insert into t1 select 1 from seq_1_to_26;
create table t10 (a int);
insert into t10 select 0 from t0, seq_1_to_4;
insert into t10 select 8693 from t1;
insert into t10 select 8694 from t1;
insert into t10 select 8695 from t1;
insert into t10 select 34783 from t1;
insert into t10 select 34784 from t1;
insert into t10 select 34785 from t1;
insert into t10 select 34785 from t0, seq_1_to_8;
insert into t10 select 65214 from t1;
insert into t10 select 65215 from t1;
insert into t10 select 65216 from t1;
insert into t10 select 65216 from t0, seq_1_to_52;
insert into t10 select 65217 from t1;
insert into t10 select 65218 from t1;
insert into t10 select 65219 from t1;
insert into t10 select 65219 from t0;
insert into t10 select 73913 from t1;
insert into t10 select 73914 from t1;
insert into t10 select 73915 from t1;
insert into t10 select 73915 from t0, seq_1_to_40;
insert into t10 select 78257 from t1;
insert into t10 select 78258 from t1;
insert into t10 select 78259 from t1;
insert into t10 select 91300 from t1;
insert into t10 select 91301 from t1;
insert into t10 select 91302 from t1;
insert into t10 select 91302 from t0, seq_1_to_6;
insert into t10 select 91303 from t1;
insert into t10 select 91304 from t1;
insert into t10 select 91305 from t1;
insert into t10 select 91305 from t0, seq_1_to_8;
insert into t10 select 99998 from t1;
insert into t10 select 99999 from t1;
insert into t10 select 100000 from t1;
set use_stat_tables=preferably;
analyze table t10 persistent for all;
Table Op Msg_type Msg_text
test.t10 analyze status Engine-independent statistics collected
test.t10 analyze status OK
flush tables;
set @tmp=@@optimizer_trace;
set optimizer_trace=1;
explain select * from t10 where a in (91303);
id select_type table type possible_keys key key_len ref rows Extra
1 SIMPLE t10 ALL NULL NULL NULL NULL 9984 Using where
# Must have selectivity_from_histogram <= 1.0:
select json_detailed(json_extract(trace, '$**.selectivity_for_columns')) as sel
from information_schema.optimizer_trace;
sel
[
[
{
"column_name": "a",
"ranges":
["91303 <= a <= 91303"],
"selectivity_from_histogram": 0.035714283
}
]
]
set optimizer_trace=@tmp;
drop table t0,t1,t10;
set optimizer_use_condition_selectivity= @save_optimizer_use_condition_selectivity;
set histogram_size=@save_histogram_size;
set use_stat_tables= @save_use_stat_tables;
#
# End of 10.4 tests
#
#
# Clean up
#
set @@global.histogram_size=@save_histogram_size;

121
mysql-test/main/selectivity_notembedded.test Normal file
View File

@ -0,0 +1,121 @@
--source include/no_valgrind_without_big.inc
--source include/have_stat_tables.inc
--source include/have_sequence.inc
--source include/default_charset.inc
--source include/not_embedded.inc
--disable_warnings
drop table if exists t0,t1,t2,t3;
--enable_warnings
select @@global.use_stat_tables;
select @@session.use_stat_tables;
set @save_use_stat_tables=@@use_stat_tables;
set use_stat_tables='preferably';
--source include/default_optimizer_switch.inc
set @save_optimizer_use_condition_selectivity=@@optimizer_use_condition_selectivity;
set @save_histogram_size=@@histogram_size;
set @save_histogram_type=@@histogram_type;
set join_cache_level=2;
set @@global.histogram_size=0,@@local.histogram_size=0;
set histogram_type='single_prec_hb';
# check that statistics on nulls is used
set optimizer_use_condition_selectivity=3;
--echo #
--echo # MDEV-31067: selectivity_from_histogram >1.0 for a DOUBLE_PREC_HB histogram
--echo #
create table t0(a int); # This holds how many rows we hold in a bucket.
insert into t0 select 1 from seq_1_to_78;
create table t1(a int); # one-third of a bucket
insert into t1 select 1 from seq_1_to_26;
create table t10 (a int);
insert into t10 select 0 from t0, seq_1_to_4;
insert into t10 select 8693 from t1;
insert into t10 select 8694 from t1;
insert into t10 select 8695 from t1;
insert into t10 select 34783 from t1;
insert into t10 select 34784 from t1;
insert into t10 select 34785 from t1;
insert into t10 select 34785 from t0, seq_1_to_8;
insert into t10 select 65214 from t1;
insert into t10 select 65215 from t1;
insert into t10 select 65216 from t1;
insert into t10 select 65216 from t0, seq_1_to_52;
insert into t10 select 65217 from t1;
insert into t10 select 65218 from t1;
insert into t10 select 65219 from t1;
insert into t10 select 65219 from t0;
insert into t10 select 73913 from t1;
insert into t10 select 73914 from t1;
insert into t10 select 73915 from t1;
insert into t10 select 73915 from t0, seq_1_to_40;
insert into t10 select 78257 from t1;
insert into t10 select 78258 from t1;
insert into t10 select 78259 from t1;
insert into t10 select 91300 from t1;
insert into t10 select 91301 from t1;
insert into t10 select 91302 from t1;
insert into t10 select 91302 from t0, seq_1_to_6;
insert into t10 select 91303 from t1; # Only 1/3rd of bucket matches the search tuple
insert into t10 select 91304 from t1;
insert into t10 select 91305 from t1;
insert into t10 select 91305 from t0, seq_1_to_8;
insert into t10 select 99998 from t1;
insert into t10 select 99999 from t1;
insert into t10 select 100000 from t1;
set use_stat_tables=preferably;
analyze table t10 persistent for all;
flush tables;
set @tmp=@@optimizer_trace;
set optimizer_trace=1;
explain select * from t10 where a in (91303);
--echo # Must have selectivity_from_histogram <= 1.0:
select json_detailed(json_extract(trace, '$**.selectivity_for_columns')) as sel
from information_schema.optimizer_trace;
set optimizer_trace=@tmp;
drop table t0,t1,t10;
set optimizer_use_condition_selectivity= @save_optimizer_use_condition_selectivity;
set histogram_size=@save_histogram_size;
set use_stat_tables= @save_use_stat_tables;
--echo #
--echo # End of 10.4 tests
--echo #
--echo #
--echo # Clean up
--echo #
--source include/restore_charset.inc
set @@global.histogram_size=@save_histogram_size;

6
sql/item_subselect.cc
View File

@ -4624,6 +4624,12 @@ void subselect_uniquesubquery_engine::print(String *str,
{ {
str->append(STRING_WITH_LEN("<primary_index_lookup>(")); str->append(STRING_WITH_LEN("<primary_index_lookup>("));
tab->ref.items[0]->print(str, query_type); tab->ref.items[0]->print(str, query_type);
if (!tab->table)
{
// table is not opened so unknown
str->append(')');
return;
}
str->append(STRING_WITH_LEN(" in ")); str->append(STRING_WITH_LEN(" in "));
if (tab->table->s->table_category == TABLE_CATEGORY_TEMPORARY) if (tab->table->s->table_category == TABLE_CATEGORY_TEMPORARY)
{ {

240
sql/opt_split.cc
View File

@ -65,7 +65,7 @@
If we have only one equi-join condition then we either push it as If we have only one equi-join condition then we either push it as
for Q1R or we don't. In a general case we may have much more options. for Q1R or we don't. In a general case we may have much more options.
Consider the query (Q3) Consider the query (Q3)
SELECT SELECT *
FROM t1,t2 (SELECT t3.a, t3.b, MIN(t3.c) as min FROM t1,t2 (SELECT t3.a, t3.b, MIN(t3.c) as min
FROM t3 GROUP BY a,b) t FROM t3 GROUP BY a,b) t
WHERE t.a = t1.a AND t.b = t2.b WHERE t.a = t1.a AND t.b = t2.b
@ -102,6 +102,47 @@
If we just drop the index on t3(a,b) the chances that the splitting If we just drop the index on t3(a,b) the chances that the splitting
will be used becomes much lower but they still exists providing that will be used becomes much lower but they still exists providing that
the fanout of the partial join of t1 and t2 is small enough. the fanout of the partial join of t1 and t2 is small enough.
The lateral derived table LT formed as a result of SM optimization applied
to a materialized derived table DT must be joined after all parameters
of splitting has been evaluated, i.e. after all expressions used in the
equalities pushed into DT that make the employed splitting effective
could be evaluated. With the chosen join order all the parameters can be
evaluated after the last table LPT that contains any columns referenced in
the parameters has been joined and the table APT following LPT in the chosen
join order is accessed.
Usually the formed lateral derived table LT is accessed right after the table
LPT. As in such cases table LT must be refilled for each combination of
splitting parameters this table must be populated before each access to LT
and the estimate of the expected number of refills that could be suggested in
such cases is the number of rows in the partial join ending with table LPT.
However in other cases the chosen join order may contain tables between LPT
and LT.
Consider the query (Q4)
SELECT *
FROM t1 JOIN t2 ON t1.b = t2.b
LEFT JOIN (SELECT t3.a, t3.b, MIN(t3.c) as min
FROM t3 GROUP BY a,b) t
ON t.a = t1.a AND t.c > 0
[WHERE P(t1,t2)];
Let's assume that the join order t1,t2,t was chosen for this query and
SP optimization was applied to t with splitting over t3.a using the index
on column t3.a. Here the table t1 serves as LPT, t2 as APT while t with
pushed condition t.a = t1.a serves as LT. Note that here LT is accessed
after t2, not right after t1. Here the number of refills of the lateral
derived is not more that the number of key values of t1.a that might be
less than the cardinality of the partial join (t1,t2). That's why it makes
sense to signal that t3 has to be refilled just before t2 is accessed.
However if the cardinality of the partial join (t1,t2) happens to be less
than the cardinality of the partial join (t1) due to additional selective
condition P(t1,t2) then the flag informing about necessity of a new refill
can be set either when accessing t2 or right after it has been joined.
The current code sets such flag right after generating a record of the
partial join with minimal cardinality for all those partial joins that
end between APT and LT. It allows sometimes to push extra conditions
into the lateral derived without any increase of the number of refills.
However this flag can be set only after the last join table between
APT and LT using join buffer has been joined.
*/ */
/* /*
@ -249,6 +290,7 @@ public:
double unsplit_card; double unsplit_card;
/* Lastly evaluated execution plan for 'join' with pushed equalities */ /* Lastly evaluated execution plan for 'join' with pushed equalities */
SplM_plan_info *last_plan; SplM_plan_info *last_plan;
double last_refills;
SplM_plan_info *find_plan(TABLE *table, uint key, uint parts); SplM_plan_info *find_plan(TABLE *table, uint key, uint parts);
}; };
@ -346,6 +388,9 @@ bool JOIN::check_for_splittable_materialized()
if (!partition_list) if (!partition_list)
return false; return false;
Json_writer_object trace_wrapper(thd);
Json_writer_object trace_split(thd, "check_split_materialized");
ORDER *ord; ORDER *ord;
Dynamic_array<SplM_field_ext_info> candidates(PSI_INSTRUMENT_MEM); Dynamic_array<SplM_field_ext_info> candidates(PSI_INSTRUMENT_MEM);
@ -391,7 +436,10 @@ bool JOIN::check_for_splittable_materialized()
} }
} }
if (candidates.elements() == 0) // no candidates satisfying (8.1) && (8.2) if (candidates.elements() == 0) // no candidates satisfying (8.1) && (8.2)
{
trace_split.add("not_applicable", "group list has no candidates");
return false; return false;
}
/* /*
For each table from this join find the keys that can be used for ref access For each table from this join find the keys that can be used for ref access
@ -450,7 +498,11 @@ bool JOIN::check_for_splittable_materialized()
} }
if (!spl_field_cnt) // No candidate field can be accessed by ref => !(9) if (!spl_field_cnt) // No candidate field can be accessed by ref => !(9)
{
trace_split.add("not_applicable",
"no candidate field can be accessed through ref");
return false; return false;
}
/* /*
Create a structure of the type SplM_opt_info and fill it with Create a structure of the type SplM_opt_info and fill it with
@ -468,16 +520,22 @@ bool JOIN::check_for_splittable_materialized()
spl_opt_info->tables_usable_for_splitting= 0; spl_opt_info->tables_usable_for_splitting= 0;
spl_opt_info->spl_field_cnt= spl_field_cnt; spl_opt_info->spl_field_cnt= spl_field_cnt;
spl_opt_info->spl_fields= spl_field; spl_opt_info->spl_fields= spl_field;
for (cand= cand_start; cand < cand_end; cand++)
{ {
if (!cand->is_usable_for_ref_access) Json_writer_array trace_range(thd, "split_candidates");
continue; for (cand= cand_start; cand < cand_end; cand++)
spl_field->producing_item= cand->producing_item; {
spl_field->underlying_field= cand->underlying_field; if (!cand->is_usable_for_ref_access)
spl_field->mat_field= cand->mat_field; continue;
spl_opt_info->tables_usable_for_splitting|= trace_range.add(cand->producing_item);
cand->underlying_field->table->map;
spl_field++; spl_field->producing_item= cand->producing_item;
spl_field->underlying_field= cand->underlying_field;
spl_field->mat_field= cand->mat_field;
spl_opt_info->tables_usable_for_splitting|=
cand->underlying_field->table->map;
spl_field++;
}
} }
/* Attach this info to the table T */ /* Attach this info to the table T */
@ -732,7 +790,7 @@ void JOIN::add_keyuses_for_splitting()
bzero((char*) &keyuse_ext_end, sizeof(keyuse_ext_end)); bzero((char*) &keyuse_ext_end, sizeof(keyuse_ext_end));
if (ext_keyuses_for_splitting->push(keyuse_ext_end)) if (ext_keyuses_for_splitting->push(keyuse_ext_end))
goto err; goto err;
// psergey-todo: trace anything here?
spl_opt_info->unsplit_card= join_record_count; spl_opt_info->unsplit_card= join_record_count;
rec_len= table->s->rec_buff_length; rec_len= table->s->rec_buff_length;
@ -830,13 +888,13 @@ SplM_plan_info *SplM_opt_info::find_plan(TABLE *table, uint key, uint parts)
static static
void reset_validity_vars_for_keyuses(KEYUSE_EXT *key_keyuse_ext_start, void reset_validity_vars_for_keyuses(KEYUSE_EXT *key_keyuse_ext_start,
TABLE *table, uint key, TABLE *table, uint key,
table_map remaining_tables, table_map excluded_tables,
bool validity_val) bool validity_val)
{ {
KEYUSE_EXT *keyuse_ext= key_keyuse_ext_start; KEYUSE_EXT *keyuse_ext= key_keyuse_ext_start;
do do
{ {
if (!(keyuse_ext->needed_in_prefix & remaining_tables)) if (!(keyuse_ext->needed_in_prefix & excluded_tables))
{ {
/* /*
The enabling/disabling flags are set just in KEYUSE_EXT structures. The enabling/disabling flags are set just in KEYUSE_EXT structures.
@ -856,8 +914,11 @@ void reset_validity_vars_for_keyuses(KEYUSE_EXT *key_keyuse_ext_start,
Choose the best splitting to extend the evaluated partial join Choose the best splitting to extend the evaluated partial join
@param @param
record_count estimated cardinality of the extended partial join idx index for joined table T in current partial join P
remaining_tables tables not joined yet remaining_tables tables not joined yet
spl_pd_boundary OUT bitmap of the table from P extended by T that
starts the sub-sequence of tables S from which
no conditions are allowed to be pushed into T.
@details @details
This function is called during the search for the best execution This function is called during the search for the best execution
@ -872,17 +933,19 @@ void reset_validity_vars_for_keyuses(KEYUSE_EXT *key_keyuse_ext_start,
splitting the function set it as the true plan of materialization splitting the function set it as the true plan of materialization
of the table T. of the table T.
The function caches the found plans for materialization of table T The function caches the found plans for materialization of table T
together if the info what key was used for splitting. Next time when together with the info what key was used for splitting. Next time when
the optimizer prefers to use the same key the plan is taken from the optimizer prefers to use the same key the plan is taken from
the cache of plans the cache of plans
@retval @retval
Pointer to the info on the found plan that employs the pushed equalities Pointer to the info on the found plan that employs the pushed equalities
if the plan has been chosen, NULL - otherwise. if the plan has been chosen, NULL - otherwise.
If the function returns NULL the value of spl_param_tables is set to 0.
*/ */
SplM_plan_info * JOIN_TAB::choose_best_splitting(double record_count, SplM_plan_info * JOIN_TAB::choose_best_splitting(uint idx,
table_map remaining_tables) table_map remaining_tables,
table_map *spl_pd_boundary)
{ {
SplM_opt_info *spl_opt_info= table->spl_opt_info; SplM_opt_info *spl_opt_info= table->spl_opt_info;
DBUG_ASSERT(spl_opt_info != NULL); DBUG_ASSERT(spl_opt_info != NULL);
@ -897,7 +960,9 @@ SplM_plan_info * JOIN_TAB::choose_best_splitting(double record_count,
SplM_plan_info *spl_plan= 0; SplM_plan_info *spl_plan= 0;
uint best_key= 0; uint best_key= 0;
uint best_key_parts= 0; uint best_key_parts= 0;
table_map best_param_tables;
Json_writer_object trace_obj(thd, "choose_best_splitting");
Json_writer_array trace_arr(thd, "considered_keys");
/* /*
Check whether there are keys that can be used to join T employing splitting Check whether there are keys that can be used to join T employing splitting
and if so, select the best out of such keys and if so, select the best out of such keys
@ -915,6 +980,7 @@ SplM_plan_info * JOIN_TAB::choose_best_splitting(double record_count,
uint key= keyuse_ext->key; uint key= keyuse_ext->key;
KEYUSE_EXT *key_keyuse_ext_start= keyuse_ext; KEYUSE_EXT *key_keyuse_ext_start= keyuse_ext;
key_part_map found_parts= 0; key_part_map found_parts= 0;
table_map needed_in_prefix= 0;
do do
{ {
if (keyuse_ext->needed_in_prefix & remaining_tables) if (keyuse_ext->needed_in_prefix & remaining_tables)
@ -940,6 +1006,7 @@ SplM_plan_info * JOIN_TAB::choose_best_splitting(double record_count,
KEY *key_info= table->key_info + key; KEY *key_info= table->key_info + key;
double rec_per_key= double rec_per_key=
key_info->actual_rec_per_key(keyuse_ext->keypart); key_info->actual_rec_per_key(keyuse_ext->keypart);
needed_in_prefix|= keyuse_ext->needed_in_prefix;
if (rec_per_key < best_rec_per_key) if (rec_per_key < best_rec_per_key)
{ {
best_table= keyuse_ext->table; best_table= keyuse_ext->table;
@ -947,6 +1014,14 @@ SplM_plan_info * JOIN_TAB::choose_best_splitting(double record_count,
best_key_parts= keyuse_ext->keypart + 1; best_key_parts= keyuse_ext->keypart + 1;
best_rec_per_key= rec_per_key; best_rec_per_key= rec_per_key;
best_key_keyuse_ext_start= key_keyuse_ext_start; best_key_keyuse_ext_start= key_keyuse_ext_start;
best_param_tables= needed_in_prefix;
// trace table, key_name, parts, needed_tables.
Json_writer_object cur_index(thd);
cur_index.
add("table_name", best_table->alias.ptr()).
add("index", best_table->key_info[best_key].name).
add("rec_per_key", best_rec_per_key).
add("param_tables", best_param_tables);
} }
keyuse_ext++; keyuse_ext++;
} }
@ -954,14 +1029,41 @@ SplM_plan_info * JOIN_TAB::choose_best_splitting(double record_count,
} }
while (keyuse_ext->table == table); while (keyuse_ext->table == table);
} }
trace_arr.end();
spl_opt_info->last_plan= 0; spl_opt_info->last_plan= 0;
double refills= DBL_MAX;
table_map excluded_tables= remaining_tables | this->join->sjm_lookup_tables;
if (best_table) if (best_table)
{ {
*spl_pd_boundary= this->table->map;
if (!best_param_tables)
refills= 1;
else
{
table_map last_found= this->table->map;
for (POSITION *pos= &this->join->positions[idx - 1]; ; pos--)
{
if (pos->table->table->map & excluded_tables)
continue;
if (pos->partial_join_cardinality < refills)
{
*spl_pd_boundary= last_found;
refills= pos->partial_join_cardinality;
}
last_found= pos->table->table->map;
if ((last_found & best_param_tables) || pos->use_join_buffer)
break;
}
}
trace_obj.add("refills", refills).
add("spl_pd_boundary", *spl_pd_boundary);
/* /*
The key for splitting was chosen, look for the plan for this key The key for splitting was chosen, look for the plan for this key
in the cache in the cache
*/ */
Json_writer_array spl_trace(thd, "choose_best_splitting");
spl_plan= spl_opt_info->find_plan(best_table, best_key, best_key_parts); spl_plan= spl_opt_info->find_plan(best_table, best_key, best_key_parts);
if (!spl_plan) if (!spl_plan)
{ {
@ -969,11 +1071,13 @@ SplM_plan_info * JOIN_TAB::choose_best_splitting(double record_count,
The plan for the chosen key has not been found in the cache. The plan for the chosen key has not been found in the cache.
Build a new plan and save info on it in the cache Build a new plan and save info on it in the cache
*/ */
Json_writer_array wrapper(thd, "split_plan_search");
table_map all_table_map= (((table_map) 1) << join->table_count) - 1; table_map all_table_map= (((table_map) 1) << join->table_count) - 1;
reset_validity_vars_for_keyuses(best_key_keyuse_ext_start, best_table, reset_validity_vars_for_keyuses(best_key_keyuse_ext_start, best_table,
best_key, remaining_tables, true); best_key, excluded_tables, true);
choose_plan(join, all_table_map & ~join->const_table_map); choose_plan(join, all_table_map & ~join->const_table_map);
wrapper.end();
/* /*
Check that the chosen plan is really a splitting plan. Check that the chosen plan is really a splitting plan.
If not or if there is not enough memory to save the plan in the cache If not or if there is not enough memory to save the plan in the cache
@ -990,7 +1094,8 @@ SplM_plan_info * JOIN_TAB::choose_best_splitting(double record_count,
spl_opt_info->plan_cache.push_back(spl_plan)) spl_opt_info->plan_cache.push_back(spl_plan))
{ {
reset_validity_vars_for_keyuses(best_key_keyuse_ext_start, best_table, reset_validity_vars_for_keyuses(best_key_keyuse_ext_start, best_table,
best_key, remaining_tables, false); best_key, excluded_tables, false);
trace_obj.add("split_plan_discarded", "constructed unapplicable query plan");
return 0; return 0;
} }
@ -1010,32 +1115,41 @@ SplM_plan_info * JOIN_TAB::choose_best_splitting(double record_count,
spl_plan->cost= join->best_positions[join->table_count-1].read_time + spl_plan->cost= join->best_positions[join->table_count-1].read_time +
+ oper_cost; + oper_cost;
if (unlikely(thd->trace_started()))
{
Json_writer_object wrapper(thd);
Json_writer_object find_trace(thd, "best_splitting");
find_trace.add("table", best_table->alias.c_ptr());
find_trace.add("key", best_table->key_info[best_key].name);
find_trace.add("record_count", record_count);
find_trace.add("cost", spl_plan->cost);
find_trace.add("unsplit_cost", spl_opt_info->unsplit_cost);
}
memcpy((char *) spl_plan->best_positions, memcpy((char *) spl_plan->best_positions,
(char *) join->best_positions, (char *) join->best_positions,
sizeof(POSITION) * join->table_count); sizeof(POSITION) * join->table_count);
reset_validity_vars_for_keyuses(best_key_keyuse_ext_start, best_table, reset_validity_vars_for_keyuses(best_key_keyuse_ext_start, best_table,
best_key, remaining_tables, false); best_key, excluded_tables, false);
} }
else
trace_obj.add("cached_plan_found", 1);
if (spl_plan) if (spl_plan)
{ {
if(record_count * spl_plan->cost < spl_opt_info->unsplit_cost - 0.01) if (unlikely(thd->trace_started()))
{
trace_obj.
add("lead_table", spl_plan->table->alias.ptr()).
add("index", spl_plan->table->key_info[spl_plan->key].name).
add("parts", spl_plan->parts).
add("split_sel", spl_plan->split_sel).
add("cost", spl_plan->cost).
add("unsplit_cost", spl_opt_info->unsplit_cost).
add("records", (ha_rows) (records * spl_plan->split_sel));
}
if (refills * spl_plan->cost < spl_opt_info->unsplit_cost - 0.01)
{ {
/* /*
The best plan that employs splitting is cheaper than The best plan that employs splitting is cheaper than
the plan without splitting the plan without splitting
*/ */
spl_opt_info->last_plan= spl_plan; spl_opt_info->last_plan= spl_plan;
spl_opt_info->last_refills= refills;
trace_obj.add("chosen", true);
} }
else
trace_obj.add("chosen", false);
} }
} }
@ -1044,16 +1158,14 @@ SplM_plan_info * JOIN_TAB::choose_best_splitting(double record_count,
spl_plan= spl_opt_info->last_plan; spl_plan= spl_opt_info->last_plan;
if (spl_plan) if (spl_plan)
{ {
startup_cost= record_count * spl_plan->cost; startup_cost= spl_opt_info->last_refills * spl_plan->cost;
records= (ha_rows) (records * spl_plan->split_sel); records= (ha_rows) (records * spl_plan->split_sel);
Json_writer_object trace(thd, "lateral_derived");
trace.add("startup_cost", startup_cost);
trace.add("splitting_cost", spl_plan->cost);
trace.add("records", records);
} }
else else
{
startup_cost= spl_opt_info->unsplit_cost; startup_cost= spl_opt_info->unsplit_cost;
*spl_pd_boundary= 0;
}
return spl_plan; return spl_plan;
} }
@ -1063,13 +1175,13 @@ SplM_plan_info * JOIN_TAB::choose_best_splitting(double record_count,
Inject equalities for splitting used by the materialization join Inject equalities for splitting used by the materialization join
@param @param
excluded_tables used to filter out the equalities that cannot excluded_tables used to filter out the equalities that are not
be pushed. to be pushed.
@details @details
This function injects equalities pushed into a derived table T for which This function injects equalities pushed into a derived table T for which
the split optimization has been chosen by the optimizer. The function the split optimization has been chosen by the optimizer. The function
is called by JOIN::inject_splitting_cond_for_all_tables_with_split_op(). is called by JOIN::inject_splitting_cond_for_all_tables_with_split_opt().
All equalities usable for splitting T whose right parts do not depend on All equalities usable for splitting T whose right parts do not depend on
any of the 'excluded_tables' can be pushed into the where clause of the any of the 'excluded_tables' can be pushed into the where clause of the
derived table T. derived table T.
@ -1157,7 +1269,7 @@ bool is_eq_cond_injected_for_split_opt(Item_func_eq *eq_item)
@param @param
spl_plan info on the splitting plan chosen for the splittable table T spl_plan info on the splitting plan chosen for the splittable table T
remaining_tables the table T is joined just before these tables excluded_tables tables that cannot be used in equalities pushed into T
is_const_table the table T is a constant table is_const_table the table T is a constant table
@details @details
@ -1172,7 +1284,7 @@ bool is_eq_cond_injected_for_split_opt(Item_func_eq *eq_item)
*/ */
bool JOIN_TAB::fix_splitting(SplM_plan_info *spl_plan, bool JOIN_TAB::fix_splitting(SplM_plan_info *spl_plan,
table_map remaining_tables, table_map excluded_tables,
bool is_const_table) bool is_const_table)
{ {
SplM_opt_info *spl_opt_info= table->spl_opt_info; SplM_opt_info *spl_opt_info= table->spl_opt_info;
@ -1180,6 +1292,7 @@ bool JOIN_TAB::fix_splitting(SplM_plan_info *spl_plan,
JOIN *md_join= spl_opt_info->join; JOIN *md_join= spl_opt_info->join;
if (spl_plan && !is_const_table) if (spl_plan && !is_const_table)
{ {
is_split_derived= true;
memcpy((char *) md_join->best_positions, memcpy((char *) md_join->best_positions,
(char *) spl_plan->best_positions, (char *) spl_plan->best_positions,
sizeof(POSITION) * md_join->table_count); sizeof(POSITION) * md_join->table_count);
@ -1190,7 +1303,7 @@ bool JOIN_TAB::fix_splitting(SplM_plan_info *spl_plan,
reset_validity_vars_for_keyuses(spl_plan->keyuse_ext_start, reset_validity_vars_for_keyuses(spl_plan->keyuse_ext_start,
spl_plan->table, spl_plan->table,
spl_plan->key, spl_plan->key,
remaining_tables, excluded_tables,
true); true);
} }
else if (md_join->save_qep) else if (md_join->save_qep)
@ -1226,8 +1339,21 @@ bool JOIN::fix_all_splittings_in_plan()
if (tab->table->is_splittable()) if (tab->table->is_splittable())
{ {
SplM_plan_info *spl_plan= cur_pos->spl_plan; SplM_plan_info *spl_plan= cur_pos->spl_plan;
table_map excluded_tables= (all_tables & ~prev_tables) |
sjm_lookup_tables;
;
if (spl_plan)
{
POSITION *pos= cur_pos;
table_map spl_pd_boundary= pos->spl_pd_boundary;
do
{
excluded_tables|= pos->table->table->map;
}
while (!((pos--)->table->table->map & spl_pd_boundary));
}
if (tab->fix_splitting(spl_plan, if (tab->fix_splitting(spl_plan,
all_tables & ~prev_tables, excluded_tables,
tablenr < const_tables )) tablenr < const_tables ))
return true; return true;
} }
@ -1266,13 +1392,21 @@ bool JOIN::inject_splitting_cond_for_all_tables_with_split_opt()
continue; continue;
SplM_opt_info *spl_opt_info= tab->table->spl_opt_info; SplM_opt_info *spl_opt_info= tab->table->spl_opt_info;
JOIN *join= spl_opt_info->join; JOIN *join= spl_opt_info->join;
/* table_map excluded_tables= (all_tables & ~prev_tables) | sjm_lookup_tables;
Currently the equalities referencing columns of SJM tables with table_map spl_pd_boundary= cur_pos->spl_pd_boundary;
look-up access cannot be pushed into materialized derived. for (POSITION *pos= cur_pos; ; pos--)
*/ {
if (join->inject_best_splitting_cond((all_tables & ~prev_tables) | excluded_tables|= pos->table->table->map;
sjm_lookup_tables)) pos->table->no_forced_join_cache= true;
return true; if (pos->table->table->map & spl_pd_boundary)
{
pos->table->split_derived_to_update|= tab->table->map;
break;
}
}
if (join->inject_best_splitting_cond(excluded_tables))
return true;
} }
return false; return false;
} }

43
sql/sql_select.cc
View File

@ -7684,6 +7684,7 @@ void set_position(JOIN *join,uint idx,JOIN_TAB *table,KEYUSE *key)
join->positions[idx].records_read=1.0; /* This is a const table */ join->positions[idx].records_read=1.0; /* This is a const table */
join->positions[idx].cond_selectivity= 1.0; join->positions[idx].cond_selectivity= 1.0;
join->positions[idx].ref_depend_map= 0; join->positions[idx].ref_depend_map= 0;
join->positions[idx].partial_join_cardinality= 1;
// join->positions[idx].loosescan_key= MAX_KEY; /* Not a LooseScan */ // join->positions[idx].loosescan_key= MAX_KEY; /* Not a LooseScan */
join->positions[idx].sj_strategy= SJ_OPT_NONE; join->positions[idx].sj_strategy= SJ_OPT_NONE;
@ -7701,6 +7702,7 @@ void set_position(JOIN *join,uint idx,JOIN_TAB *table,KEYUSE *key)
} }
join->best_ref[idx]=table; join->best_ref[idx]=table;
join->positions[idx].spl_plan= 0; join->positions[idx].spl_plan= 0;
join->positions[idx].spl_pd_boundary= 0;
} }
@ -7987,6 +7989,7 @@ best_access_path(JOIN *join,
MY_BITMAP *eq_join_set= &s->table->eq_join_set; MY_BITMAP *eq_join_set= &s->table->eq_join_set;
KEYUSE *hj_start_key= 0; KEYUSE *hj_start_key= 0;
SplM_plan_info *spl_plan= 0; SplM_plan_info *spl_plan= 0;
table_map spl_pd_boundary= 0;
Range_rowid_filter_cost_info *filter= 0; Range_rowid_filter_cost_info *filter= 0;
const char* cause= NULL; const char* cause= NULL;
enum join_type best_type= JT_UNKNOWN, type= JT_UNKNOWN; enum join_type best_type= JT_UNKNOWN, type= JT_UNKNOWN;
@ -8005,9 +8008,11 @@ best_access_path(JOIN *join,
loose_scan_opt.init(join, s, remaining_tables); loose_scan_opt.init(join, s, remaining_tables);
if (s->table->is_splittable()) if (s->table->is_splittable())
spl_plan= s->choose_best_splitting(record_count, remaining_tables); spl_plan= s->choose_best_splitting(idx,
Json_writer_array trace_paths(thd, "considered_access_paths"); remaining_tables,
&spl_pd_boundary);
Json_writer_array trace_paths(thd, "considered_access_paths");
if (s->keyuse) if (s->keyuse)
{ /* Use key if possible */ { /* Use key if possible */
KEYUSE *keyuse; KEYUSE *keyuse;
@ -8892,8 +8897,9 @@ best_access_path(JOIN *join,
best_filter= filter; best_filter= filter;
/* range/index_merge/ALL/index access method are "independent", so: */ /* range/index_merge/ALL/index access method are "independent", so: */
best_ref_depends_map= 0; best_ref_depends_map= 0;
best_uses_jbuf= MY_TEST(!disable_jbuf && !((s->table->map & best_uses_jbuf= MY_TEST(!disable_jbuf &&
join->outer_join))); (join->allowed_outer_join_with_cache ||
!(s->table->map & join->outer_join)));
spl_plan= 0; spl_plan= 0;
best_type= type; best_type= type;
} }
@ -8916,6 +8922,7 @@ best_access_path(JOIN *join,
pos->loosescan_picker.loosescan_key= MAX_KEY; pos->loosescan_picker.loosescan_key= MAX_KEY;
pos->use_join_buffer= best_uses_jbuf; pos->use_join_buffer= best_uses_jbuf;
pos->spl_plan= spl_plan; pos->spl_plan= spl_plan;
pos->spl_pd_boundary= !spl_plan ? 0 : spl_pd_boundary;
pos->range_rowid_filter_info= best_filter; pos->range_rowid_filter_info= best_filter;
pos->key_dependent= (best_type == JT_EQ_REF ? (table_map) 0 : pos->key_dependent= (best_type == JT_EQ_REF ? (table_map) 0 :
key_dependent & remaining_tables); key_dependent & remaining_tables);
@ -9449,6 +9456,9 @@ optimize_straight_join(JOIN *join, table_map remaining_tables)
pushdown_cond_selectivity= table_cond_selectivity(join, idx, s, pushdown_cond_selectivity= table_cond_selectivity(join, idx, s,
remaining_tables); remaining_tables);
position->cond_selectivity= pushdown_cond_selectivity; position->cond_selectivity= pushdown_cond_selectivity;
double partial_join_cardinality= record_count *
pushdown_cond_selectivity;
join->positions[idx].partial_join_cardinality= partial_join_cardinality;
++idx; ++idx;
} }
@ -10784,8 +10794,10 @@ best_extension_by_limited_search(JOIN *join,
} }
} }
if ((search_depth > 1) && join->positions[idx].partial_join_cardinality= partial_join_cardinality;
((remaining_tables & ~real_table_bit) & allowed_tables))
if ((search_depth > 1) && (remaining_tables & ~real_table_bit) &
allowed_tables)
{ {
/* Recursively expand the current partial plan */ /* Recursively expand the current partial plan */
Json_writer_array trace_rest(thd, "rest_of_plan"); Json_writer_array trace_rest(thd, "rest_of_plan");
@ -13850,6 +13862,9 @@ uint check_join_cache_usage(JOIN_TAB *tab,
join->return_tab= 0; join->return_tab= 0;
if (tab->no_forced_join_cache)
return 0;
/* /*
Don't use join cache if @@join_cache_level==0 or this table is the first Don't use join cache if @@join_cache_level==0 or this table is the first
one join suborder (either at top level or inside a bush) one join suborder (either at top level or inside a bush)
@ -14818,7 +14833,8 @@ bool JOIN_TAB::preread_init()
DBUG_RETURN(TRUE); DBUG_RETURN(TRUE);
if (!(derived->get_unit()->uncacheable & UNCACHEABLE_DEPENDENT) || if (!(derived->get_unit()->uncacheable & UNCACHEABLE_DEPENDENT) ||
derived->is_nonrecursive_derived_with_rec_ref()) derived->is_nonrecursive_derived_with_rec_ref() ||
is_split_derived)
preread_init_done= TRUE; preread_init_done= TRUE;
if (select && select->quick) if (select && select->quick)
select->quick->replace_handler(table->file); select->quick->replace_handler(table->file);
@ -18396,6 +18412,9 @@ void optimize_wo_join_buffering(JOIN *join, uint first_tab, uint last_tab,
reopt_remaining_tables & reopt_remaining_tables &
~real_table_bit); ~real_table_bit);
} }
double partial_join_cardinality= rec_count *
pushdown_cond_selectivity;
join->positions[i].partial_join_cardinality= partial_join_cardinality;
(*outer_rec_count) *= pushdown_cond_selectivity; (*outer_rec_count) *= pushdown_cond_selectivity;
if (!rs->emb_sj_nest) if (!rs->emb_sj_nest)
*outer_rec_count= COST_MULT(*outer_rec_count, pos.records_read); *outer_rec_count= COST_MULT(*outer_rec_count, pos.records_read);
@ -22010,6 +22029,16 @@ sub_select(JOIN *join,JOIN_TAB *join_tab,bool end_of_records)
{ {
DBUG_ENTER("sub_select"); DBUG_ENTER("sub_select");
if (join_tab->split_derived_to_update && !end_of_records)
{
table_map tab_map= join_tab->split_derived_to_update;
for (uint i= 0; tab_map; i++, tab_map>>= 1)
{
if (tab_map & 1)
join->map2table[i]->preread_init_done= false;
}
}
if (join_tab->last_inner) if (join_tab->last_inner)
{ {
JOIN_TAB *last_inner_tab= join_tab->last_inner; JOIN_TAB *last_inner_tab= join_tab->last_inner;

31
sql/sql_select.h
View File

@ -405,6 +405,8 @@ typedef struct st_join_table {
*/ */
bool idx_cond_fact_out; bool idx_cond_fact_out;
bool use_join_cache; bool use_join_cache;
/* TRUE <=> it is prohibited to join this table using join buffer */
bool no_forced_join_cache;
uint used_join_cache_level; uint used_join_cache_level;
ulong join_buffer_size_limit; ulong join_buffer_size_limit;
JOIN_CACHE *cache; JOIN_CACHE *cache;
@ -531,6 +533,16 @@ typedef struct st_join_table {
bool preread_init_done; bool preread_init_done;
/* true <=> split optimization has been applied to this materialized table */
bool is_split_derived;
/*
Bitmap of split materialized derived tables that can be filled just before
this join table is to be joined. All parameters of the split derived tables
belong to tables preceding this join table.
*/
table_map split_derived_to_update;
/* /*
Cost info to the range filter used when joining this join table Cost info to the range filter used when joining this join table
(Defined when the best join order has been already chosen) (Defined when the best join order has been already chosen)
@ -693,9 +705,10 @@ typedef struct st_join_table {
void partial_cleanup(); void partial_cleanup();
void add_keyuses_for_splitting(); void add_keyuses_for_splitting();
SplM_plan_info *choose_best_splitting(double record_count, SplM_plan_info *choose_best_splitting(uint idx,
table_map remaining_tables); table_map remaining_tables,
bool fix_splitting(SplM_plan_info *spl_plan, table_map remaining_tables, table_map *spl_pd_boundary);
bool fix_splitting(SplM_plan_info *spl_plan, table_map excluded_tables,
bool is_const_table); bool is_const_table);
} JOIN_TAB; } JOIN_TAB;
@ -963,9 +976,21 @@ public:
*/ */
KEYUSE *key; KEYUSE *key;
/* Cardinality of current partial join ending with this position */
double partial_join_cardinality;
/* Info on splitting plan used at this position */ /* Info on splitting plan used at this position */
SplM_plan_info *spl_plan; SplM_plan_info *spl_plan;
/*
If spl_plan is NULL the value of spl_pd_boundary is 0. Otherwise
spl_pd_boundary contains the bitmap of the table from the current
partial join ending at this position that starts the sub-sequence of
tables S from which no conditions are allowed to be used in the plan
spl_plan for the split table joined at this position.
*/
table_map spl_pd_boundary;
/* Cost info for the range filter used at this position */ /* Cost info for the range filter used at this position */
Range_rowid_filter_cost_info *range_rowid_filter_info; Range_rowid_filter_cost_info *range_rowid_filter_info;