[Bug]: Incorrect result in calculating standard deviation.
Is there an existing issue for the same bug?
- [X] I have checked the existing issues.
Branch Name
main
Commit ID
5078085cd5049fa721752637eb402902e48b2656
Other Environment Information
- Hardware parameters:
- OS type:
- Others:
Actual Behavior
job url: https://github.com/matrixorigin/mo-nightly-regression/actions/runs/7709943518/job/21012208316
Expected Behavior
Steps to Reproduce
table schema:
CREATE TABLE `table_basic_for_load_100M` (
`col1` tinyint(4) NULL,
`col2` smallint(6) NULL,
`col3` int(11) NULL,
`col4` bigint(20) NULL,
`col5` smallint(6) NULL,
`col6` int(11) NULL,
`col7` bigint(20) NULL,
`col8` largeint(40) NULL,
`col9` float NULL,
`col10` double NULL,
`col11` varchar(255) NULL,
`col12` date NULL,
`col13` datetime NULL,
`col14` datetime NULL,
`col15` boolean NULL,
`col16` DECIMAL(16, 6) NULL,
`col17` text NULL,
`col18` json NULL,
`col19` text NULL,
`col20` text NULL,
`col21` text NULL,
`col22` text NULL,
`col23` text NULL,
`col24` text NULL,
`col25` text NULL
);
Additional information
No response
decimal的精度问题麻烦同时看下原因: ddl: select sum(abs(col16)) from big_data_test.table_basic_for_load_1B; select sum(ln(col16)) from big_data_test.table_basic_for_load_1B where col16 > 0;
table schema: create table if not exists big_data_test.table_basic_for_load_100M( col1 tinyint, col2 smallint, col3 int, col4 bigint, col5 tinyint unsigned, col6 smallint unsigned, col7 int unsigned, col8 bigint unsigned, col9 float, col10 double, col11 varchar(255), col12 Date, col13 DateTime, col14 timestamp, col15 bool, col16 decimal(16,6), col17 text, col18 json, col19 blob, col20 binary(255), col21 varbinary(255), col22 vecf32(3), col23 vecf32(3), col24 vecf64(3), col25 vecf64(3) );
doris结果:
mo结果:
ddl: select sum(abs(col9)) from big_data_test.table_basic_for_load_100M; select sum(abs(col10)) from big_data_test.table_basic_for_load_100M; select sum(abs(col16)) from big_data_test.table_basic_for_load_100M;
无进展
testing
testing
commit:6b1a10d62ec53a54394120d8c6327c7886c1ce15
以上均为精度问题