When unique key with MOW table has sequence column, the query result may be wrong with predicates. There are two problems:
The sequence column needs to be removed from primary key index when comparing key.
The sequence column needs to be removed from min/max key.
* [enhancemeng](sql) Remove unused wide common factors to improve scan performance in ExtractCommonFactorsRule
* fix regression test
Co-authored-by: caiconghui1 <caiconghui1@jd.com>
# Proposed changes
- Refactor AggregateFunction
1. AggregateFunction implement ComputeSignature
3. Add a CustomSignature to dynamic compute signature, we can check input type and compute implicit cast type in the `customSignature` method
2. Add PartialAggType to record some type information before disassemble aggregate
4. Refine and create a custom catalog function when translate AggregateFunction, without `finalizeForNereids`
- Support explain plan
1. explain parsed plan select ...
5. explain analyzed plan select ...
6. explain rewritten/logical plan select ...
7. explain optimized/physical plan select ...
8. explain all plan select ...
before:
MySQL [test]> select cast('135.759999999' as DECIMAL(10,3));
+----------------------------------------+
| CAST('135.759999999' AS DECIMAL(10,3)) |
+----------------------------------------+
| 135.759999999 |
+----------------------------------------+
1 row in set (0.00 sec)
now:
MySQL [stage]> select cast('135.759999999' as DECIMAL(10,3));
+----------------------------------------+
| CAST('135.759999999' AS DECIMAL(10,3)) |
+----------------------------------------+
| 135.759 |
+----------------------------------------+
1 row in set (0.01 sec)
When executing create table as select stmt,
the varchar/char/string type of column in created table will be unified to string type.
Because when select from external table (mysql/pg, etc), the length of varchar in external database
is calculated by "char" length, not "byte" length.
So if there is a column with varchar(10) in external table, then there will be a same varchar(10)
in created table. But the byte length of data in external table may be larger than 10, causing failure of CTAS.
Change to string will not impact performance of the capacity of disk storage.
And notice that if a string type column is the first column, it will be changed to varchar(65535),
because we do not allow string type column as sort key column.
When you create the Uniq table, you can specify the mapping of sequence column to other columns.
You no longer need to specify mapping column when importing.
Add regression test for external hive orc table. This PR has generated all basic types support by hive orc, and create a hive external table to touch them in docker environment.
Functions to be tested:
1. Ensure that all types are parsed correctly
2. Ensure that the null map of all types are parsed correctly
3. Ensure that the `SearchArgument` of `OrcReader` works well
4. Only select partition columns
In previous implementation, when doing list partition prune, we need to generation `rangeToId`
every time we doing prune.
But `rangeToId` is actually a static data that should be create-once-use-every-where.
So for hive partition, I created the `rangeToId` and all other necessary data structures for partition prunning
in partition cache, so that we can use it directly.
In my test, the cost of partition prune for 10000 partitions reduce from 8s -> 0.2s.
Aslo add "partition" info in explain string for hive table.
```
| 0:VEXTERNAL_FILE_SCAN_NODE |
| predicates: `nation` = '0024c95b' |
| inputSplitNum=1, totalFileSize=4750, scanRanges=1 |
| partition=1/10000 |
| numNodes=1 |
| limit: 10 |
```
Bug fix:
1. Fix bug that es scan node can not filter data
2. Fix bug that query es with predicate like `where substring(test2,2) = "ext2";` will fail at planner phase.
`Unexpected exception: org.apache.doris.analysis.FunctionCallExpr cannot be cast to org.apache.doris.analysis.SlotRef`
TODO:
1. Some problem when quering es version 8: ` Unexpected exception: Index: 0, Size: 0`, will be fixed later.
Before this pr, if we try to load ORC file with native list(or array) type data, the be will crash.
Because complex types in ORC file include multi real columns, so we need to filter columns by column names.
Otherwise we could not read all columns we need.
Now arrow release-7.0.0 only support create stripe reader by column index, so we patch it to support create stripe reader by column names.
Co-authored-by: cambyzju <zhuxiaoli01@baidu.com>
1. Reduce the configuration options for statistics framework, and add comment for those rest.
2. Move the logic of creation of analysis job to the `StatisticsRepository` which defined all the functions used to interact with internal statistics table
3. Move AnalysisJobScheduler to the statistics package
4. Support display and injections manually for statistics
Create partitions use ：
```
PARTITION BY RANGE(event_day)(
FROM ("2000-11-14") TO ("2021-11-14") INTERVAL 1 YEAR,
FROM ("2021-11-14") TO ("2022-11-14") INTERVAL 1 MONTH,
FROM ("2022-11-14") TO ("2023-01-03") INTERVAL 1 WEEK,
FROM ("2023-01-03") TO ("2023-01-14") INTERVAL 1 DAY,
PARTITION p_20230114 VALUES [('2023-01-14'), ('2023-01-15'))
)
PARTITION BY RANGE(event_time)(
FROM ("2023-01-03 12") TO ("2023-01-14 22") INTERVAL 1 HOUR
)
```
can create a year/month/week/day/hour's date partitions in a batch,
also it is compatible with the single partitioning method.
