Make database, table, column and other names support unicode by changing LABEL_REGEX COMMON_NAME_REGIEX COMMON_TABLE_NAME_REGEX COLUMN_NAME_REGEX regular expressions in class FeNameFormat.
P.S. @SharpRay has transfered PR #13467 to me, and I‘m responsible for the task now. There will be some modifications during the review period, so I create a new PR and the original #13467 could be closed. Thanks.
This pr refactor the rewrite framework from memo to plan tree, and speed up the analyze/rewrite stage.
Changes:
- abandoned memo in the analysis/rewrite stage, so that we can skip some actions, like new GroupExpression, distinct GroupExpression in the memo(high cost), update children to GroupPlan
- change the most of rules to static rule, so that we can skip initialize lots of rules in Analyzer/Rewriter at every query. but some rules need context, like visitor rule, create rule at the runtime make it is easy to use, so make `custom` rule can help us to create it.
- remove the `logger` field in the Job, Job are generated in large quantities at runtime, we don't need to use logger so save huge time to initialize logger.
- skip some rule as far as possible, e.g. `SelectMaterializedIndexWithoutAggregate`, skip select mv if the table not exist rullup.
- add some caches for frequent operation, like get Job.getDisableRules, Plan.getUnboundExpression
- new bottom up rewrite rule, it can keep traverse multiple new plan which return by rules, this feature depends on `Plan.mutableState`, it is necessary to add this variable field for plan. if the plan is fully immutable, we must use withXxx to renew the plan and set the state for it, this take more runtime overhead and developing workload. another reason is we need multiple mutable state, e.g. whether is applied the rule, whether this plan is manage by the rewrite framework. the good side of mutable state is efficient, but I suggest we don't direct use mutable state in the rule as far as possible, if we need use it, please wrap the mutable state in the framework to update and release it correctly. a good example is `AppliedAwareRuleCondition`, it can update and get the state: whether this plan is applied to a rule before.
- merge some rules, invoke multiple rules in one traverse
- refactor the `EliminateUnnecessaryProject` by CustomRewritor, fix the problem which eliminate some Project which decided the query output order, the case is limit(project), sort(project).
TODO: add trace for new rewrite framework
benchmark:
legacy optimizer:
```
+-----------+---------------+---------------+---------------+
| SQL ID | avg | min | max |
+-----------+---------------+---------------+---------------+
| SQL 1 | 1.39 ms | 0 ms | 9 ms |
| SQL 2 | 1.38 ms | 0 ms | 10 ms |
| SQL 3 | 2.05 ms | 1 ms | 18 ms |
| SQL 4 | 0.89 ms | 0 ms | 9 ms |
| SQL 5 | 1.74 ms | 1 ms | 11 ms |
| SQL 6 | 2.00 ms | 1 ms | 13 ms |
| SQL 7 | 1.83 ms | 1 ms | 15 ms |
| SQL 8 | 0.92 ms | 0 ms | 7 ms |
| SQL 9 | 2.60 ms | 1 ms | 19 ms |
| SQL 10 | 3.54 ms | 2 ms | 28 ms |
| SQL 11 | 3.04 ms | 1 ms | 18 ms |
| SQL 12 | 3.26 ms | 2 ms | 16 ms |
| SQL 13 | 1.10 ms | 0 ms | 10 ms |
| SQL 14 | 2.90 ms | 1 ms | 13 ms |
| SQL 15 | 1.18 ms | 0 ms | 9 ms |
| SQL 16 | 1.05 ms | 0 ms | 13 ms |
| SQL 17 | 1.03 ms | 0 ms | 7 ms |
| SQL 18 | 0.94 ms | 0 ms | 7 ms |
| SQL 19 | 1.47 ms | 0 ms | 13 ms |
| SQL 20 | 0.47 ms | 0 ms | 4 ms |
| SQL 21 | 0.54 ms | 0 ms | 5 ms |
| SQL 22 | 3.34 ms | 1 ms | 19 ms |
| SQL 23 | 7.97 ms | 4 ms | 44 ms |
| SQL 24 | 11.11 ms | 7 ms | 28 ms |
| SQL 25 | 0.98 ms | 0 ms | 8 ms |
| SQL 26 | 0.83 ms | 0 ms | 7 ms |
| SQL 27 | 0.93 ms | 0 ms | 16 ms |
| SQL 28 | 2.19 ms | 1 ms | 18 ms |
| SQL 29 | 3.23 ms | 1 ms | 20 ms |
| SQL 30 | 59.99 ms | 51 ms | 81 ms |
| SQL 31 | 2.65 ms | 1 ms | 18 ms |
| SQL 32 | 2.47 ms | 1 ms | 17 ms |
| SQL 33 | 2.30 ms | 1 ms | 16 ms |
| SQL 34 | 0.66 ms | 0 ms | 8 ms |
| SQL 35 | 0.63 ms | 0 ms | 6 ms |
| SQL 36 | 2.25 ms | 1 ms | 15 ms |
| SQL 37 | 5.97 ms | 3 ms | 20 ms |
| SQL 38 | 5.73 ms | 3 ms | 21 ms |
| SQL 39 | 6.32 ms | 4 ms | 23 ms |
| SQL 40 | 8.61 ms | 5 ms | 35 ms |
| SQL 41 | 6.29 ms | 4 ms | 28 ms |
| SQL 42 | 6.04 ms | 4 ms | 15 ms |
| SQL 43 | 5.81 ms | 3 ms | 16 ms |
+-----------+---------------+---------------+---------------+
| TOTAL AVG | 4.22 ms | 2.47 ms | 17.05 ms |
| TOTAL SUM | 181.62 ms | 106 ms | 733 ms |
+-----------+---------------+---------------+---------------+
```
nereids with memo rewrite framework(old):
```
+-----------+---------------+---------------+---------------+
| SQL ID | avg | min | max |
+-----------+---------------+---------------+---------------+
| SQL 1 | 3.61 ms | 1 ms | 20 ms |
| SQL 2 | 3.47 ms | 2 ms | 16 ms |
| SQL 3 | 3.27 ms | 1 ms | 18 ms |
| SQL 4 | 2.23 ms | 1 ms | 12 ms |
| SQL 5 | 3.60 ms | 1 ms | 20 ms |
| SQL 6 | 2.73 ms | 1 ms | 17 ms |
| SQL 7 | 3.04 ms | 1 ms | 23 ms |
| SQL 8 | 3.53 ms | 2 ms | 20 ms |
| SQL 9 | 3.74 ms | 2 ms | 22 ms |
| SQL 10 | 3.66 ms | 2 ms | 18 ms |
| SQL 11 | 3.93 ms | 2 ms | 15 ms |
| SQL 12 | 4.85 ms | 2 ms | 27 ms |
| SQL 13 | 4.41 ms | 2 ms | 28 ms |
| SQL 14 | 5.16 ms | 2 ms | 41 ms |
| SQL 15 | 4.33 ms | 2 ms | 33 ms |
| SQL 16 | 4.94 ms | 2 ms | 51 ms |
| SQL 17 | 3.27 ms | 1 ms | 25 ms |
| SQL 18 | 2.78 ms | 1 ms | 22 ms |
| SQL 19 | 3.51 ms | 1 ms | 42 ms |
| SQL 20 | 1.84 ms | 1 ms | 13 ms |
| SQL 21 | 3.47 ms | 1 ms | 66 ms |
| SQL 22 | 5.21 ms | 2 ms | 29 ms |
| SQL 23 | 5.55 ms | 3 ms | 25 ms |
| SQL 24 | 4.21 ms | 2 ms | 28 ms |
| SQL 25 | 3.47 ms | 1 ms | 23 ms |
| SQL 26 | 3.03 ms | 2 ms | 21 ms |
| SQL 27 | 3.07 ms | 1 ms | 17 ms |
| SQL 28 | 4.51 ms | 3 ms | 22 ms |
| SQL 29 | 4.97 ms | 3 ms | 21 ms |
| SQL 30 | 11.95 ms | 8 ms | 33 ms |
| SQL 31 | 3.92 ms | 2 ms | 23 ms |
| SQL 32 | 3.74 ms | 2 ms | 15 ms |
| SQL 33 | 3.62 ms | 2 ms | 22 ms |
| SQL 34 | 4.60 ms | 1 ms | 55 ms |
| SQL 35 | 3.47 ms | 2 ms | 25 ms |
| SQL 36 | 3.34 ms | 2 ms | 18 ms |
| SQL 37 | 4.77 ms | 2 ms | 23 ms |
| SQL 38 | 4.44 ms | 2 ms | 39 ms |
| SQL 39 | 4.52 ms | 2 ms | 23 ms |
| SQL 40 | 5.50 ms | 3 ms | 30 ms |
| SQL 41 | 5.01 ms | 2 ms | 24 ms |
| SQL 42 | 4.32 ms | 2 ms | 24 ms |
| SQL 43 | 4.29 ms | 2 ms | 42 ms |
+-----------+---------------+---------------+---------------+
| TOTAL AVG | 4.11 ms | 1.91 ms | 26.30 ms |
| TOTAL SUM | 176.88 ms | 82 ms | 1131 ms |
+-----------+---------------+---------------+---------------+
```
nereids with plan tree rewrite framework(new):
```
+-----------+---------------+---------------+---------------+
| SQL ID | avg | min | max |
+-----------+---------------+---------------+---------------+
| SQL 1 | 3.21 ms | 1 ms | 18 ms |
| SQL 2 | 3.99 ms | 1 ms | 76 ms |
| SQL 3 | 2.93 ms | 1 ms | 21 ms |
| SQL 4 | 2.13 ms | 1 ms | 21 ms |
| SQL 5 | 2.43 ms | 1 ms | 30 ms |
| SQL 6 | 2.08 ms | 1 ms | 11 ms |
| SQL 7 | 2.03 ms | 1 ms | 11 ms |
| SQL 8 | 2.27 ms | 1 ms | 22 ms |
| SQL 9 | 2.42 ms | 1 ms | 16 ms |
| SQL 10 | 2.65 ms | 1 ms | 14 ms |
| SQL 11 | 2.78 ms | 1 ms | 14 ms |
| SQL 12 | 3.09 ms | 1 ms | 19 ms |
| SQL 13 | 2.33 ms | 1 ms | 13 ms |
| SQL 14 | 2.66 ms | 1 ms | 16 ms |
| SQL 15 | 2.34 ms | 1 ms | 15 ms |
| SQL 16 | 2.04 ms | 1 ms | 30 ms |
| SQL 17 | 2.09 ms | 1 ms | 17 ms |
| SQL 18 | 1.87 ms | 1 ms | 15 ms |
| SQL 19 | 2.21 ms | 1 ms | 50 ms |
| SQL 20 | 1.32 ms | 0 ms | 12 ms |
| SQL 21 | 1.63 ms | 1 ms | 11 ms |
| SQL 22 | 2.75 ms | 1 ms | 30 ms |
| SQL 23 | 3.44 ms | 2 ms | 17 ms |
| SQL 24 | 2.01 ms | 1 ms | 14 ms |
| SQL 25 | 1.58 ms | 1 ms | 11 ms |
| SQL 26 | 1.53 ms | 0 ms | 13 ms |
| SQL 27 | 1.62 ms | 1 ms | 12 ms |
| SQL 28 | 2.90 ms | 1 ms | 21 ms |
| SQL 29 | 3.04 ms | 2 ms | 17 ms |
| SQL 30 | 10.54 ms | 7 ms | 49 ms |
| SQL 31 | 2.61 ms | 1 ms | 21 ms |
| SQL 32 | 2.42 ms | 1 ms | 14 ms |
| SQL 33 | 2.13 ms | 1 ms | 14 ms |
| SQL 34 | 1.69 ms | 1 ms | 14 ms |
| SQL 35 | 1.87 ms | 1 ms | 15 ms |
| SQL 36 | 2.37 ms | 1 ms | 21 ms |
| SQL 37 | 3.06 ms | 1 ms | 15 ms |
| SQL 38 | 4.09 ms | 1 ms | 31 ms |
| SQL 39 | 5.81 ms | 2 ms | 43 ms |
| SQL 40 | 4.55 ms | 2 ms | 34 ms |
| SQL 41 | 3.49 ms | 1 ms | 20 ms |
| SQL 42 | 2.75 ms | 1 ms | 26 ms |
| SQL 43 | 2.81 ms | 1 ms | 14 ms |
+-----------+---------------+---------------+---------------+
| TOTAL AVG | 2.78 ms | 1.19 ms | 21.35 ms |
| TOTAL SUM | 119.56 ms | 51 ms | 918 ms |
+-----------+---------------+---------------+---------------+
```
bug: some chinese word not sort by pinyin in GBK coding
CREATE TABLE `test_convert` (
`a` varchar(100) NULL
) ENGINE=OLAP
DUPLICATE KEY(`a`)
DISTRIBUTED BY HASH(`a`) BUCKETS 3
PROPERTIES (
"replication_allocation" = "tag.location.default: 1"
);
insert into test_convert values("b"), ("a"), ("c"), ("睿"), ("多"), ("丝");
Query OK, 6 rows affected (0.03 sec)
{'label':'insert_ca73a6acc2194d5b_888218a3949355a6', 'status':'VISIBLE', 'txnId':'18068'}
mysql [test]>select * from test_convert;
+------+
| a |
+------+
| a |
| c |
| 丝 |
| b |
| 多 |
| 睿 |
+------+
6 rows in set (0.01 sec)
mysql [test]>select * from test_convert order by convert(a using gbk);
+------+
| a |
+------+
| a |
| b |
| c |
| 多 |
| 丝 |
| 睿 |
+------+
6 rows in set (0.01 sec)
1. Make sure all sub types which STRUCT supported work correctly;
2. remove unused variable `_need_validate_data`;
3. lazy init min or max decimal to support nested DecimalV2 column validate;
Co-authored-by: cambyzju <zhuxiaoli01@baidu.com>
For Unique Key MoW table, if there are duplicate keys in one single load job and there's multiple segments, we need to calculate delete bitmap to mark these duplicate keys deleted.
Add a check here to detect any bugs that might cause duplicate keys.
Hive store all the data without partition columns to a default partition named __HIVE_DEFAULT_PARTITION__.
Doris will fail to get the this partition when the partition column type is INT or something else that
__HIVE_DEFAULT_PARTITION__ couldn't convert to.
This pr is to support hive default partition, set the column value to NULL for the missing partition columns.
Loading a big local file will cause `INTERNAL_ERROR]too many filtered rows` issue since the bytebuffer from mysql client always use the same byte array.
And the later bytes will overwrite the previous one and make wrong bytes order among the network.
Copy the byte array and then fill it into network.
* disable setting storage policy on MoW table
* fix error in regression test
* make the name of test table unique
* use Strings.isNullOrEmpty to replace equals
* fix error in if statement
Different version numbers are used to calculate the delete bitmap between segments and rowsets, resulting in the failure of the last update of the delete bitmap.
* Support mapping es date format, default/yyyy-MM-dd HH:mm:ss/yyyy-MM-dd/epoch_millis
* Replace simple json with jackson, resolve column order random problem
* Add es array doc version
Enhance aggregate function `collect_set` and `collect_list` to support optional `max_size` param,
which enables to limit the number of elements in result array.
Demo:
```
# HELP doris_fe_mtmv_job Total job number of mtmv.
# TYPE doris_fe_mtmv_job gauge
doris_fe_mtmv_job{type="TOTAL-JOB"} 1
doris_fe_mtmv_job{type="ACTIVE-JOB"} 1
# HELP doris_fe_mtmv_task Running task number of mtmv.
# TYPE doris_fe_mtmv_task gauge
doris_fe_mtmv_task{type="RUNNING-TASK"} 0
doris_fe_mtmv_task{type="PENDING-TASK"} 0
doris_fe_mtmv_task{type="FAILED-TASK"} 0
doris_fe_mtmv_task{type="TOTAL-TASK"} 1
```
decode method is only used for big int and other decode method is only used in unit test.
I remove the useless method and we can remove mempool parameter from decode method.
---------
Co-authored-by: yiguolei <yiguolei@gmail.com>
The logic of topn and full sort is wrong when there are both offsets and limits, the offset is not considered when doing the max heap optimization, which will lead to wrong result.
* [Optimize](simd json reader) Cached search results for previous row (keyed as index in JSON object) - used as a hint.
`_simdjson_set_column_value` could become a hot spot while parsing json in simdjson mode,
introduce `_prev_positions` to cache results for previous row (keyed as index in JSON object) due to the json name field order,
should be quite the same between each lines
* fix case
