The changes of this PR for JdbcOracleClient are as follows:
#### bug fixes:
1. Fix the problem that if there is an approximate table name for Schema synchronization with a table name with `/` characters, the synchronization Column will be confused
2. Fix the NPE problem of metadata synchronization after enabling lower_case_table_names configuration
#### improvement:
1. Modify the method of synchronizing Oracle User to Doris Database mapping, use `metadata.getSchemas` instead of `SELECT DISTINCT OWNER FROM all_tables`
2. When synchronizing metadata, change `null` at the catalog level to `conn.getcatalog`
A row of complex type may be stored across two(or more) pages, and the parameter `align_rows` indicates that whether the reader should read the remaining value of the last row in previous page.
`ParquetReader` confuses logical/physical/slot id of columns. If only reading the scalar types, there's nothing wrong, but when reading complex types, `RowGroup` and `PageIndex` will get wrong statistics. Therefore, if the query contains complex types and pushed-down predicates, the probability of the result set is incorrect.
FEATURE:
1. enable array type in Nereids
2. support generice on function signature
3. support array and map type in type coercion and type check
4. add element_at and element_slice syntax in Nereids parser
REFACTOR:
1. remove AbstractDataType
BUG FIX:
1. remove FROM from nonReserved keyword list
TODO:
1. support lambda expression
2. use Nereids' way do function type coercion
3. use castIfnotSame when do implict cast on BoundFunction
4. let AnyDataType type coercion do same thing as function type coercion
5. add below array function
- array_apply
- array_concat
- array_filter
- array_sortby
- array_exists
- array_first_index
- array_last_index
- array_count
- array_shuffle shuffle
- array_pushfront
- array_pushback
- array_repeat
- array_zip
- reverse
- concat_ws
- split_by_string
- explode
- bitmap_from_array
- bitmap_to_array
- multi_search_all_positions
- multi_match_any
- tokenize
if we write sql with : `select cast(array() as array<varchar(10)>)`
castexpr in fe will call analyze() with `Type.matchExactType(childType, type, true);`
here array type only check contains_null , but should check inner type to make array matchExactType right
if we write sql with : select array(1.0,2.0,null, null,2.0)
here will pass arg type with uint8 to be which does not match array() func sign with deicmal, and make be core. so here should cast from be and make null tag to cast decimal type
[Fix](orc-reader) Fix filling partition or missing column used incorrect row count.
`_row_reader->nextBatch` returns number of read rows. When orc lazy materialization is turned on, the number of read rows includes filtered rows, so caller must look at `numElements` in the row batch to determine how
many rows were not filtered which will to fill to the block.
In this case, filling partition or missing column used incorrect row count which will cause be crash by `filter.size() != offsets.size()` in filter column step.
When orc lazy materialization is turned off, add `_convert_dict_cols_to_string_cols(block, nullptr)` if `(block->rows() == 0)`.
Previously, delete statement with conditions on value columns are only supported on duplicate tables. After we introduce delete sign mechanism to do batch delete, a delete statement with conditions on value columns on unique tables will be transformed into the corresponding insert into ..., __DELETE_SIGN__ select ... statement. However, for unique table with merge-on-write enabled, the overhead of inserting these data can be eliminated. So this PR add the ability to allow delete predicate on value columns for merge-on-write unique tables.
## Proposed changes
Refactor thoughts: close#22383
Descriptions about `enclose` and `escape`: #22385
## Further comments
2023-08-09:
It's a pity that experiment shows that the original way for parsing plain CSV is faster. Therefor, the refactor is only applied on enclose related code. The plain CSV parser use the original logic.
Fallback of performance is unavoidable anyway. From the `CSV reader`'s perspective, the real weak point may be the write column behavior, proved by the flame graph.
Trimming escape will be enable after fix: #22411 is merged
Cases should be discussed:
1. When an incomplete enclose appears in the beginning of a large scale data, the line delimiter will be unreachable till the EOF, will the buffer become extremely large?
2. What if an infinite line occurs in the case? Essentially, `1.` is equivalent to this.
Only support stream load as trial in this PR, avoid too many unrelated changes. Docs will be added when `enclose` and `escape` is available for all kinds of load.
