mariadb/mysql-test/main/analyze_engine_stats.result
Sergei Petrunia 0940a96940 MDEV-18478 ANALYZE for statement should show selectivity of ICP, part#2
Part#2, variant 2: Make the printed r_ values in JSON output consistent.
After this patch, ANALYZE output has:

- r_index_rows (NEW) - Observed number of rows before ICP or Rowid Filtering
  checks. This is a per-scan average. like r_rows and "rows" are.

- r_rows (AS BEFORE) - Observed number of rows after ICP and Rowid Filtering.

- r_icp_filtered (NEW) - Observed selectivity of ICP condition.

- (AS BEFORE) observed selectivity of Rowid Filter is in
  $.rowid_filter.r_selectivity_pct

- r_total_filtered - Observed combined selectivity: fraction of rows left
  after applying ICP condition, Rowid Filter, and attached_condition.
  This is now comparable with "filtered" and is printed right after it.

- r_filtered (AS BEFORE) - Observed selectivity of "attached_condition".

Tabular ANALYZE output is not changed. Note that JSON's r_filtered and
r_rows have the same meanings as before and have the same meaning as in
tabular output.
2024-04-23 22:55:22 +03:00

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Text

create table t1 (
pk int not null,
a varchar(64),
b varchar(64),
c varchar(64)
) engine=innodb;
insert into t1 select
seq, seq, seq, seq
from
seq_1_to_10000;
analyze table t1 persistent for all;
Table Op Msg_type Msg_text
test.t1 analyze status Engine-independent statistics collected
test.t1 analyze status OK
# Note the r_engine_stats below. Only non-zero members are printed
select '$out' as X;
X
{
"query_optimization": {
"r_total_time_ms": "REPLACED"
},
"query_block": {
"select_id": 1,
"cost": 1.6664988,
"r_loops": 1,
"r_total_time_ms": "REPLACED",
"nested_loop": [
{
"table": {
"table_name": "t1",
"access_type": "ALL",
"loops": 1,
"r_loops": 1,
"rows": 10000,
"r_rows": 10000,
"cost": 1.6664988,
"r_table_time_ms": "REPLACED",
"r_other_time_ms": "REPLACED",
"r_engine_stats": {
"pages_accessed": "REPLACED"
},
"filtered": 100,
"r_total_filtered": 100,
"attached_condition": "t1.pk < 120000",
"r_filtered": 100
}
}
]
}
}
set @js='$out';
set @out=(select json_extract(@js,'$**.r_engine_stats.pages_accessed'));
select cast(json_extract(@out,'$[0]') as DOUBLE) > 0 as PAGES_ACCESSED_MORE_THAN_ZERO;
PAGES_ACCESSED_MORE_THAN_ZERO
1
#
# Try an UPDATE
#
select '$out' as X;
X
{
"query_optimization": {
"r_total_time_ms": "REPLACED"
},
"query_block": {
"select_id": 1,
"r_total_time_ms": "REPLACED",
"table": {
"update": 1,
"table_name": "t1",
"access_type": "ALL",
"rows": 10000,
"r_rows": 10000,
"r_total_filtered": 100,
"r_total_time_ms": "REPLACED",
"r_engine_stats": {
"pages_accessed": "REPLACED",
"pages_updated": "REPLACED"
},
"attached_condition": "t1.pk < 120000",
"r_filtered": 100
}
}
}
set @js='$out';
set @out=(select json_extract(@js,'$**.r_engine_stats.pages_updated'));
select cast(json_extract(@out,'$[0]') as DOUBLE) > 0 as PAGES_UPDATED_MORE_THAN_ZERO;
PAGES_UPDATED_MORE_THAN_ZERO
1
#
# Try a DELETE
#
select '$out' as X;
X
{
"query_optimization": {
"r_total_time_ms": "REPLACED"
},
"query_block": {
"select_id": 1,
"r_total_time_ms": "REPLACED",
"table": {
"delete": 1,
"table_name": "t1",
"access_type": "ALL",
"rows": 10000,
"r_rows": 10000,
"r_total_filtered": 50,
"r_total_time_ms": "REPLACED",
"r_engine_stats": {
"pages_accessed": "REPLACED",
"pages_updated": "REPLACED"
},
"attached_condition": "t1.pk MOD 2 = 1",
"r_filtered": 50
}
}
}
set @js='$out';
set @out=(select json_extract(@js,'$**.r_engine_stats.pages_updated'));
select cast(json_extract(@out,'$[0]') as DOUBLE) > 0 as PAGES_UPDATED_MORE_THAN_ZERO;
PAGES_UPDATED_MORE_THAN_ZERO
1
drop table t1;
#
# MDEV-31764: ASAN use-after-poison in trace_engine_stats upon ANALYZE FORMAT=JSON
#
ANALYZE FORMAT=JSON SELECT count(*) FROM information_schema.GLOBAL_STATUS;
# Another testcase without I_S:
CREATE TABLE t1 (a INT);
INSERT INTO t1 SELECT seq FROM seq_1_to_100;
CREATE TABLE t2 (s INT);
INSERT INTO t2 SELECT seq FROM seq_1_to_10;
# Must use SJ-Materialization to hit the issue with temp.table:
ANALYZE FORMAT=JSON SELECT * FROM t1 WHERE a IN (SELECT s FROM t2);
ANALYZE
{
"query_optimization": {
"r_total_time_ms": "REPLACED"
},
"query_block": {
"select_id": 1,
"cost": "REPLACED",
"r_loops": 1,
"r_total_time_ms": "REPLACED",
"const_condition": "1",
"nested_loop": [
{
"table": {
"table_name": "t1",
"access_type": "ALL",
"loops": 1,
"r_loops": 1,
"rows": 100,
"r_rows": 100,
"cost": "REPLACED",
"r_table_time_ms": "REPLACED",
"r_other_time_ms": "REPLACED",
"r_engine_stats": REPLACED,
"filtered": 100,
"r_total_filtered": 100,
"r_filtered": 100
}
},
{
"table": {
"table_name": "<subquery2>",
"access_type": "eq_ref",
"possible_keys": ["distinct_key"],
"key": "distinct_key",
"key_length": "4",
"used_key_parts": ["s"],
"ref": ["func"],
"r_loops": 100,
"r_table_loops": 110,
"rows": 1,
"r_rows": 0.1,
"r_table_time_ms": "REPLACED",
"r_other_time_ms": "REPLACED",
"filtered": 100,
"r_total_filtered": 100,
"r_filtered": 100,
"materialized": {
"unique": 1,
"query_block": {
"select_id": 2,
"nested_loop": [
{
"table": {
"table_name": "t2",
"access_type": "ALL",
"loops": 1,
"r_loops": 1,
"rows": 10,
"r_rows": 10,
"cost": "REPLACED",
"r_table_time_ms": "REPLACED",
"r_other_time_ms": "REPLACED",
"r_engine_stats": REPLACED,
"filtered": 100,
"r_total_filtered": 100,
"r_filtered": 100
}
}
]
}
}
}
}
]
}
}
DROP TABLE t1, t2;