MDEV-4362: {division by zero when lookup constant is outside the value table}
- Fix Histogram::point_selectivity() to work in the case where the passed value_pos=0 (or 1) and the first (or the last) bucket in the histogram has zero value-range (i.e one value).
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@ -1356,6 +1356,37 @@ id select_type table type possible_keys key key_len ref rows filtered Extra
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Warnings:
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Warnings:
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Note 1003 select `test`.`t1`.`a` AS `a` from `test`.`t1` where (`test`.`t1`.`a` = <cache>(-(1)))
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Note 1003 select `test`.`t1`.`a` AS `a` from `test`.`t1` where (`test`.`t1`.`a` = <cache>(-(1)))
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drop table t0, t1;
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drop table t0, t1;
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#
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# MDEV-4362: Selectivity estimates for IN (...) do not depend on whether the values are in range
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#
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create table t1 (col1 int);
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set @a=-1;
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create table t2 (a int) select (@a:=@a+1) as a from information_schema.session_variables A limit 100;
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insert into t1 select A.a from t2 A, t2 B where A.a < 100 and B.a < 100;
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select min(col1), max(col1), count(*) from t1;
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min(col1) max(col1) count(*)
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0 99 10000
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set histogram_size=100;
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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 OK
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explain extended select * from t1 where col1 in (1,2,3);
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id select_type table type possible_keys key key_len ref rows filtered Extra
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1 SIMPLE t1 ALL NULL NULL NULL NULL 10000 3.37 Using where
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Warnings:
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Note 1003 select `test`.`t1`.`col1` AS `col1` from `test`.`t1` where (`test`.`t1`.`col1` in (1,2,3))
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# Must not cause fp division by zero, or produce nonsense numbers:
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explain extended select * from t1 where col1 in (-1,-2,-3);
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id select_type table type possible_keys key key_len ref rows filtered Extra
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1 SIMPLE t1 ALL NULL NULL NULL NULL 10000 3.00 Using where
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Warnings:
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Note 1003 select `test`.`t1`.`col1` AS `col1` from `test`.`t1` where (`test`.`t1`.`col1` in (<cache>(-(1)),<cache>(-(2)),<cache>(-(3))))
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explain extended select * from t1 where col1<=-1;
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id select_type table type possible_keys key key_len ref rows filtered Extra
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1 SIMPLE t1 ALL NULL NULL NULL NULL 10000 1.00 Using where
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Warnings:
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Note 1003 select `test`.`t1`.`col1` AS `col1` from `test`.`t1` where (`test`.`t1`.`col1` <= <cache>(-(1)))
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drop table t1, t2;
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set histogram_type=@save_histogram_type;
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set histogram_type=@save_histogram_type;
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set histogram_size=@save_histogram_size;
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set histogram_size=@save_histogram_size;
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set optimizer_use_condition_selectivity=@save_optimizer_use_condition_selectivity;
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set optimizer_use_condition_selectivity=@save_optimizer_use_condition_selectivity;
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@ -1366,6 +1366,37 @@ id select_type table type possible_keys key key_len ref rows filtered Extra
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Warnings:
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Warnings:
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Note 1003 select `test`.`t1`.`a` AS `a` from `test`.`t1` where (`test`.`t1`.`a` = <cache>(-(1)))
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Note 1003 select `test`.`t1`.`a` AS `a` from `test`.`t1` where (`test`.`t1`.`a` = <cache>(-(1)))
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drop table t0, t1;
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drop table t0, t1;
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#
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# MDEV-4362: Selectivity estimates for IN (...) do not depend on whether the values are in range
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#
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create table t1 (col1 int);
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set @a=-1;
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create table t2 (a int) select (@a:=@a+1) as a from information_schema.session_variables A limit 100;
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insert into t1 select A.a from t2 A, t2 B where A.a < 100 and B.a < 100;
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select min(col1), max(col1), count(*) from t1;
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min(col1) max(col1) count(*)
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0 99 10000
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set histogram_size=100;
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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 OK
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explain extended select * from t1 where col1 in (1,2,3);
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id select_type table type possible_keys key key_len ref rows filtered Extra
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1 SIMPLE t1 ALL NULL NULL NULL NULL 10000 3.37 Using where
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Warnings:
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Note 1003 select `test`.`t1`.`col1` AS `col1` from `test`.`t1` where (`test`.`t1`.`col1` in (1,2,3))
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# Must not cause fp division by zero, or produce nonsense numbers:
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explain extended select * from t1 where col1 in (-1,-2,-3);
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id select_type table type possible_keys key key_len ref rows filtered Extra
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1 SIMPLE t1 ALL NULL NULL NULL NULL 10000 3.00 Using where
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Warnings:
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Note 1003 select `test`.`t1`.`col1` AS `col1` from `test`.`t1` where (`test`.`t1`.`col1` in (<cache>(-(1)),<cache>(-(2)),<cache>(-(3))))
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explain extended select * from t1 where col1<=-1;
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id select_type table type possible_keys key key_len ref rows filtered Extra
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1 SIMPLE t1 ALL NULL NULL NULL NULL 10000 1.00 Using where
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Warnings:
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Note 1003 select `test`.`t1`.`col1` AS `col1` from `test`.`t1` where (`test`.`t1`.`col1` <= <cache>(-(1)))
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drop table t1, t2;
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set histogram_type=@save_histogram_type;
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set histogram_type=@save_histogram_type;
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set histogram_size=@save_histogram_size;
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set histogram_size=@save_histogram_size;
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set optimizer_use_condition_selectivity=@save_optimizer_use_condition_selectivity;
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set optimizer_use_condition_selectivity=@save_optimizer_use_condition_selectivity;
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@ -908,6 +908,22 @@ explain extended select * from t1 where a=-1;
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drop table t0, t1;
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drop table t0, t1;
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--echo #
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--echo # MDEV-4362: Selectivity estimates for IN (...) do not depend on whether the values are in range
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--echo #
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create table t1 (col1 int);
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set @a=-1;
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create table t2 (a int) select (@a:=@a+1) as a from information_schema.session_variables A limit 100;
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insert into t1 select A.a from t2 A, t2 B where A.a < 100 and B.a < 100;
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select min(col1), max(col1), count(*) from t1;
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set histogram_size=100;
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analyze table t1 persistent for all;
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explain extended select * from t1 where col1 in (1,2,3);
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--echo # Must not cause fp division by zero, or produce nonsense numbers:
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explain extended select * from t1 where col1 in (-1,-2,-3);
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explain extended select * from t1 where col1<=-1;
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drop table t1, t2;
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set histogram_type=@save_histogram_type;
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set histogram_type=@save_histogram_type;
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set histogram_size=@save_histogram_size;
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set histogram_size=@save_histogram_size;
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set optimizer_use_condition_selectivity=@save_optimizer_use_condition_selectivity;
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set optimizer_use_condition_selectivity=@save_optimizer_use_condition_selectivity;
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@ -302,16 +302,27 @@ public:
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(max + 1 == get_width() ? 1.0 : (get_value(max) * inv_prec_factor)) -
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(max + 1 == get_width() ? 1.0 : (get_value(max) * inv_prec_factor)) -
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(min == 0 ? 0.0 : (get_value(min-1) * inv_prec_factor));
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(min == 0 ? 0.0 : (get_value(min-1) * inv_prec_factor));
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/*
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if (current_bucket_width < 1e-16)
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So:
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{
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- each bucket has the same #rows
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/*
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- values are unformly distributed across the [min_value,max_value] domain.
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A special case: we are at the first (or the last) bucket in the
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histogram, the bucket's value range is a singlepoint [x,x], and
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pos_value=0 (for the first bucket) or pos_value=1 (for the last).
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*/
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sel= avg_sel;
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}
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else
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{
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/*
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So:
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- each bucket has the same #rows
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- values are unformly distributed across the [min_value,max_value] domain.
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If a bucket has value range that's N times bigger then average, than
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If a bucket has value range that's N times bigger then average, than
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each value will have to have N times fewer rows than average.
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each value will have to have N times fewer rows than average.
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*/
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*/
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DBUG_ASSERT(current_bucket_width);
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sel= avg_sel * avg_bucket_width / current_bucket_width;
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sel= avg_sel * avg_bucket_width / current_bucket_width;
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}
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/*
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/*
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(Q: if we just follow this proportion we may end up in a situation
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(Q: if we just follow this proportion we may end up in a situation
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