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0940a96940
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 $.rowid_filter.r_selectivity_pct - r_total_filtered - Observed combined selectivity: fraction of rows left after applying ICP condition, Rowid Filter, and attached_condition. This is now comparable with "filtered" and is printed right after it. - r_filtered (AS BEFORE) - Observed selectivity of "attached_condition". Tabular ANALYZE output is not changed. Note that JSON's r_filtered and r_rows have the same meanings as before and have the same meaning as in tabular output.
213 lines
5.3 KiB
Text
213 lines
5.3 KiB
Text
create table t1 (
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pk int not null,
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a varchar(64),
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b varchar(64),
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c varchar(64)
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) engine=innodb;
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insert into t1 select
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seq, seq, seq, seq
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from
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seq_1_to_10000;
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analyze table t1 persistent for all;
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Table Op Msg_type Msg_text
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test.t1 analyze status Engine-independent statistics collected
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test.t1 analyze status OK
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# Note the r_engine_stats below. Only non-zero members are printed
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select '$out' as X;
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X
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{
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"query_optimization": {
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"r_total_time_ms": "REPLACED"
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},
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"query_block": {
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"select_id": 1,
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"cost": 1.6664988,
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"r_loops": 1,
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"r_total_time_ms": "REPLACED",
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"nested_loop": [
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{
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"table": {
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"table_name": "t1",
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"access_type": "ALL",
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"loops": 1,
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"r_loops": 1,
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"rows": 10000,
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"r_rows": 10000,
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"cost": 1.6664988,
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"r_table_time_ms": "REPLACED",
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"r_other_time_ms": "REPLACED",
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"r_engine_stats": {
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"pages_accessed": "REPLACED"
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},
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"filtered": 100,
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"r_total_filtered": 100,
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"attached_condition": "t1.pk < 120000",
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"r_filtered": 100
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}
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}
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]
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}
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}
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set @js='$out';
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set @out=(select json_extract(@js,'$**.r_engine_stats.pages_accessed'));
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select cast(json_extract(@out,'$[0]') as DOUBLE) > 0 as PAGES_ACCESSED_MORE_THAN_ZERO;
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PAGES_ACCESSED_MORE_THAN_ZERO
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1
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#
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# Try an UPDATE
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#
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select '$out' as X;
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X
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{
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"query_optimization": {
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"r_total_time_ms": "REPLACED"
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},
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"query_block": {
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"select_id": 1,
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"r_total_time_ms": "REPLACED",
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"table": {
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"update": 1,
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"table_name": "t1",
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"access_type": "ALL",
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"rows": 10000,
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"r_rows": 10000,
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"r_total_filtered": 100,
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"r_total_time_ms": "REPLACED",
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"r_engine_stats": {
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"pages_accessed": "REPLACED",
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"pages_updated": "REPLACED"
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},
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"attached_condition": "t1.pk < 120000",
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"r_filtered": 100
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}
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}
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}
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set @js='$out';
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set @out=(select json_extract(@js,'$**.r_engine_stats.pages_updated'));
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select cast(json_extract(@out,'$[0]') as DOUBLE) > 0 as PAGES_UPDATED_MORE_THAN_ZERO;
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PAGES_UPDATED_MORE_THAN_ZERO
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1
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#
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# Try a DELETE
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#
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select '$out' as X;
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X
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{
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"query_optimization": {
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"r_total_time_ms": "REPLACED"
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},
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"query_block": {
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"select_id": 1,
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"r_total_time_ms": "REPLACED",
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"table": {
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"delete": 1,
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"table_name": "t1",
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"access_type": "ALL",
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"rows": 10000,
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"r_rows": 10000,
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"r_total_filtered": 50,
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"r_total_time_ms": "REPLACED",
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"r_engine_stats": {
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"pages_accessed": "REPLACED",
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"pages_updated": "REPLACED"
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},
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"attached_condition": "t1.pk MOD 2 = 1",
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"r_filtered": 50
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}
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}
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}
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set @js='$out';
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set @out=(select json_extract(@js,'$**.r_engine_stats.pages_updated'));
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select cast(json_extract(@out,'$[0]') as DOUBLE) > 0 as PAGES_UPDATED_MORE_THAN_ZERO;
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PAGES_UPDATED_MORE_THAN_ZERO
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1
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drop table t1;
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#
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# MDEV-31764: ASAN use-after-poison in trace_engine_stats upon ANALYZE FORMAT=JSON
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#
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ANALYZE FORMAT=JSON SELECT count(*) FROM information_schema.GLOBAL_STATUS;
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# Another testcase without I_S:
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CREATE TABLE t1 (a INT);
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INSERT INTO t1 SELECT seq FROM seq_1_to_100;
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CREATE TABLE t2 (s INT);
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INSERT INTO t2 SELECT seq FROM seq_1_to_10;
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# Must use SJ-Materialization to hit the issue with temp.table:
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ANALYZE FORMAT=JSON SELECT * FROM t1 WHERE a IN (SELECT s FROM t2);
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ANALYZE
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{
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"query_optimization": {
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"r_total_time_ms": "REPLACED"
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},
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"query_block": {
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"select_id": 1,
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"cost": "REPLACED",
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"r_loops": 1,
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"r_total_time_ms": "REPLACED",
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"const_condition": "1",
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"nested_loop": [
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{
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"table": {
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"table_name": "t1",
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"access_type": "ALL",
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"loops": 1,
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"r_loops": 1,
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"rows": 100,
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"r_rows": 100,
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"cost": "REPLACED",
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"r_table_time_ms": "REPLACED",
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"r_other_time_ms": "REPLACED",
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"r_engine_stats": REPLACED,
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"filtered": 100,
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"r_total_filtered": 100,
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"r_filtered": 100
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}
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},
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{
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"table": {
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"table_name": "<subquery2>",
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"access_type": "eq_ref",
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"possible_keys": ["distinct_key"],
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"key": "distinct_key",
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"key_length": "4",
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"used_key_parts": ["s"],
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"ref": ["func"],
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"r_loops": 100,
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"r_table_loops": 110,
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"rows": 1,
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"r_rows": 0.1,
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"r_table_time_ms": "REPLACED",
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"r_other_time_ms": "REPLACED",
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"filtered": 100,
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"r_total_filtered": 100,
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"r_filtered": 100,
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"materialized": {
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"unique": 1,
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"query_block": {
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"select_id": 2,
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"nested_loop": [
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{
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"table": {
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"table_name": "t2",
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"access_type": "ALL",
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"loops": 1,
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"r_loops": 1,
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"rows": 10,
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"r_rows": 10,
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"cost": "REPLACED",
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"r_table_time_ms": "REPLACED",
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"r_other_time_ms": "REPLACED",
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"r_engine_stats": REPLACED,
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"filtered": 100,
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"r_total_filtered": 100,
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"r_filtered": 100
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}
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}
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]
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}
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}
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}
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}
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]
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}
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}
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DROP TABLE t1, t2;
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