Before this PR when encountering null values with some columns which is specified as `NOT NULL`, null values will not be filtered,thi behavior does not match with the original load behavior.
Second column alignment logic has bug :
```
template <typename ColumnInserterFn>
void align_variant_by_name_and_type(ColumnObject& dst, const ColumnObject& src, size_t row_cnt,
ColumnInserterFn inserter) {
CHECK(dst.is_finalized() && src.is_finalized());
// Use rows() here instead of size(), since size() will check_consistency
// but we could not check_consistency since num_rows will be upgraded even
// if src and dst is empty, we just increase the num_rows of dst and fill
// num_rows of default values when meet new data
size_t num_rows = dst.rows();
```
1. introduce a new type `VARIANT` to encapsulate dynamic generated columns for hidding the detail of types and names of newly generated columns
2. introduce a new expression `SchemaChangeExpr` for doing schema change for extensibility
* [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
A const reference member variables as class member stores a temporary object, which cannot be got after the temporary object being destroyed, cause be core dump while enable debug level log
_broker_addr has been destroyed in BrokerFileReader
Issue Number: close#16351
Dynamic schema table is a special type of table, it's schema change with loading procedure.Now we implemented this feature mainly for semi-structure data such as JSON, since JSON is schema self-described we could extract schema info from the original documents and inference the final type infomation.This speical table could reduce manual schema change operation and easily import semi-structure data and extends it's schema automatically.
The performance of ClickBench Q30 is affected by batch_size:
| batch_size | 1024 | 4096 | 20480 |
| -- | -- | -- | -- |
| Q30 query time | 2.27 | 1.08 | 0.62 |
Because aggregation operator will create a new result block for each batch block, and Q30 has 90 columns, which is time-consuming. Larger batch_size will decrease the number of aggregation blocks, so the larger batch_size will improve performance.
Doris internal reader will read at least 4064 rows even if batch_size < 4064, so this PR keep the process of reading external table the same as internal table.
The main purpose of this pr is to import `fileCache` for lakehouse reading remote files.
Use the local disk as the cache for reading remote file, so the next time this file is read,
the data can be obtained directly from the local disk.
In addition, this pr includes a few other minor changes
Import File Cache:
1. The imported `fileCache` is called `block_file_cache`, which uses lru replacement policy.
2. Implement a new FileRereader `CachedRemoteFilereader`, so that the logic of `file cache` is hidden under `CachedRemoteFilereader`.
Other changes:
1. Add a new interface `fs()` for `FileReader`.
2. `IOContext` adds some statistical information to count the situation of `FileCache`
Co-authored-by: Lightman <31928846+Lchangliang@users.noreply.github.com>
Fix three bugs when read iceberg v2 tables:
1. The `delete position` in `delete file` represents the position of delete row in the entire file, but the `read range` in
`RowGroupReader` represents the position in current row group. Therefore, we need to subtract the position of first
row of current row group from `delete position`.
2. When only reading the partition columns, `RowGroupReader` skips processing the `delete position`.
3. If the `delete position` has delete all rows in a row group, the `read range` is empty, but we read the whole row
group in such case.
Optimize four performance issues:
1. We change `delete position` to `delete range`, and then merge `delete range` and `read range` into the final read
ranges. This process is too tedious and time-consuming. . we can merge `delete position` and `read range` directly.
2. `delete position` is ordered in a `delete file`, so we can use merge-sort, instead of ordered-set.
3. Initialize `RowGroupReader` when reading, instead of initialize all row groups when opening a `ParquetReader`, to
save memory usage, and the same as `IcebergReader`.
4. Change the recursive call of `_do_lazy_read` to loop logic.
json reader DCHECK fail because of missing TYPE_STRING
fix bug that if no file is found, the tvf will throw NPE.
The predicate conjuncts can not be pushed down to parquet reader if this is a load task.
Because the predicate should be applied on column of dest table, not on column of source file.
Add a temp property "use_new_load_scan_node" of broker load to make regression test happy.
So that we can use new load scan node for a certain job and avoid setting global FE config.
Issue Number: close#12574
This pr adds `NewJsonReader` which implements GenericReader interface to support read json format file.
TODO:
1. modify `_scann_eof` later.
2. Rename `NewJsonReader` to `JsonReader` when `JsonReader` is deleted.
