Hash join node adds three new attributes.
The following will take an SQL as an example to illustrate the meaning of these three attributes
```
select t1. a from t1 left join t2 on t1. a=t2. b;
```
1. vOutputTupleDesc：Tuple2(a'')
2. vIntermediateTupleDescList: Tuple1(a', b'<nullable>)
2. vSrcToOutputSMap: <Tuple1(a'), Tuple2(a'')>
The slot in intermediatetuple corresponds to the slot in output tuple one by one through the expr calculation of the left child in vsrctooutputsmap.
This code mainly merges the contents of two PRs:
1. [fix](vectorized) Support outer join for vectorized exec engine (https://github.com/apache/doris/pull/10323)
2. [Fix](Join) Fix the bug of outer join function under vectorization #9954
The following is the specific description of the first PR
In a vectorized scenario, the query plan will generate a new tuple for the join node.
This tuple mainly describes the output schema of the join node.
Adding this tuple mainly solves the problem that the input schema of the join node is different from the output schema.
For example:
1. The case where the null side column caused by outer join is converted to nullable.
2. The projection of the outer tuple.
The following is the specific description of the second PR
This pr mainly fixes the following problems:
1. Solve the query combined with inline view and outer join. After adding a tuple to the join operator, the position of the `tupleisnull` function is inconsistent with the row storage. Currently the vectorized `tupleisnull` will be calculated in the HashJoinNode.computeOutputTuple() function.
2. Column nullable property error problem. At present, once the outer join occurs, the column on the null-side side will be planned to be nullable in the semantic parsing stage.
For example：
```
select * from (select a as k1 from test) tmp right join b on tmp.k1=b.k1
```
At this time, the nullable property of column k1 in the `tmp` inline view should be true.
In the vectorized code, the virtual `tableRef` of tmp will be used in constructing the output tuple of HashJoinNode (specifically, the function HashJoinNode.computeOutputTuple()). So the **correctness** of the column nullable property of this tableRef is very important.
In the above case, since the tmp table needs to perform a right join with the b table, as a null-side tmp side, it is necessary to change the column attributes involved in the tmp table to nullable.
In non-vectorized code, since the virtual tableRef tmp is not used at all, it uses the `TupleIsNull` function in `outputsmp` to ensure data correctness.
That is to say, the a column of the original table test is still non-null, and it does not affect the correctness of the result.
The vectorized nullable attribute requirements are very strict.
Outer join will change the nullable attribute of the join column, thereby changing the nullable attribute of the column in the upper operator layer by layer.
Since FE has no mechanism to modify the nullable attribute in the upper operator tuple layer by layer after the analyzer.
So at present, we can only preset the attributes before the lower join as nullable in the analyzer stage in advance, so as to avoid the problem.
(At the same time, be also wrote some evasive code in order to deal with the problem of null to non-null.)
Co-authored-by: EmmyMiao87
Co-authored-by: HappenLee
Co-authored-by: morrySnow
Co-authored-by: EmmyMiao87 <522274284@qq.com>
* support like/not like conjuncts push down to storage engine
* vectorized engine support like/not like conjuncts push down to storage engine
* support both evaluate and evaluate_vec method in like predicate
* reuse remove_pushed_conjuncts and prevent logic error during move function conjuncts
* change #ifndef to pragma once as per comments
* change enable_function_pushdown default to false
Co-authored-by: heguangnan <heguangnan@bytedance.com>
In a vectorized scenario, the query plan will generate a new tuple for the join node.
This tuple mainly describes the output schema of the join node.
Adding this tuple mainly solves the problem that the input schema of the join node is different from the output schema.
For example:
1. The case where the null side column caused by outer join is converted to nullable.
2. The projection of the outer tuple.
Now column `Array<T>` contains column `offsets` and `data`, and type of column `offsets` is UInt32 now.
If we call array_union to merge arrays repeatedly, the size of array may overflow.
So we need to extend it before `Array Data Type` release.
Issue Number: close#9555
Make the last value of the dictionary null, when ColumnDict inserts a null value,
add the encoding corresponding to the last value of the dictionary·
SQL with JOIN and columns ARRAY, will call function ColumnArray::replicate. At this pr,
we implement replicate for ARRAY type, to support SQL like this:
`SELECT count(lo_array),count(d_array),SUM(lo_extendedprice*lo_discount) AS REVENUE FROM lineorder, date WHERE lo_orderdate = d_datekey AND d_year = 1993 AND lo_discount BETWEEN 1 AND 3 AND lo_quantity < 25;`
1.Member functions defined in a class are inline by default (implicitly), and do not need to be added
2.inline is a keyword used for implementation, which has no effect when placed before the function declaration
recurrent:
When `enable_low_cardinality_optimize = true`, for the TPCH dataset, using the following SQL query will Core
```sql
select count(*) from lineitem where l_comment = 'ously even exc';
```
This SQL will trigger the execution of `ColumnDictionary::convert_to_predicate_column_if_dictionary`, and `res->reserve(_codes.size())` is problematic because the current `_codes.size()` is smaller than its reserve value, so inserting a value into `PredicateColumn` will Core.
Fix a bug when query bitmap return wrong result, even the simplest query.
Such as
```
CREATE TABLE `pv_bitmap_fix2` (
`dt` int(11) NULL COMMENT "",
`page` varchar(10) NULL COMMENT "",
`user_id_bitmap` bitmap BITMAP_UNION NULL COMMENT ""
) ENGINE=OLAP
AGGREGATE KEY(`dt`, `page`)
COMMENT "OLAP" DISTRIBUTED BY HASH(`dt`) BUCKETS 2
PROPERTIES (
"replication_allocation" = "tag.location.default: 1",
"in_memory" = "false",
"storage_format" = "V2"
)
Insert any hundreds of rows of data
select count(distinct user_id_bitmap) from pv_bitmap_fix2
the result is wrong
```
This is a bug of vectorization of storage layer.
