* Revert "[refactor](mysql result format) use new serde framework to tuple convert (#25006)"
This reverts commit e5ef0aa6d439c3f9b1f1fe5bc89c9ea6a71d4019.
* run buildall
* MORE
* FIX
When converting query results into MySQL format, it involves transforming columnar data storage into row-based storage. This process raises the question of choosing between sequential reading and sequential writing. In reality, sequential writing is the better choice for performance optimization.
Test with 9M rows contains more than 20 columns, this patch can reduce the conversion time from 20s to 11s.
Creating a rows buffer for each block can impact non-negligible performance.
So it is necessary to reuse the rows buffer.
Test with a total of 1.7M rows, the AppendBatchTime reduced from 500ms to 280ms.
Dynamic mode used in array type when serialize it to mysql row buffer using dynamic mode, when combine binary row format with dynamic mode,something goes wrong, and lead to invalid binary row format.
Currently, there are some useless includes in the codebase. We can use a tool named include-what-you-use to optimize these includes. By using a strict include-what-you-use policy, we can get lots of benefits from it.
1. support row format using codec of jsonb
2. short path optimize for point query
3. support prepared statement for point query
4. support mysql binary format
```
if (!_dynamic_mode) {
int8store(_len_pos, _pos - _len_pos - 8);
_len_pos = nullptr;
}
```
_len_pos may be pointed to the pos which already deleted in reserve, int8store will asign value to the freed address,
and lead to use after free when build in ASAN.So I changed _len_pos to the offset of _buf
This is beacuse of an const MAX_PHYSICAL_PACKET_LENGTH in fe should be 2^24 -1,
but it is set as 2^24 -2 by mistake.
2. Fix bitmap_to_string may failed when the result is large than 2G
1. replace all boost::shared_ptr to std::shared_ptr
2. replace all boost::scopted_ptr to std::unique_ptr
3. replace all boost::scoped_array to std::unique<T[]>
4. replace all boost:thread to std::thread
This is part of the array type support and has not been fully completed.
The following functions are implemented
1. fe array type support and implementation of array function, support array syntax analysis and planning
2. Support import array type data through insert into
3. Support select array type data
4. Only the array type is supported on the value lie of the duplicate table
this pr merge some code from #4655#4650#4644#4643#4623#2979
