* [feature](planner): push limit to olapscan when meet sort.
* if olap_scan_node's sort_info is set, push sort_limit, read_orderby_key
and read_orderby_key_reverse for olap scanner
* There is a common query pattern to find latest time serials data.
eg. SELECT * from t_log WHERE t>t1 AND t<t2 ORDER BY t DESC LIMIT 100
If the ORDER BY columns is the prefix of the sort key of table, it can
be greatly optimized to read much fewer data instead of read all data
between t1 and t2.
By leveraging the same order of ORDER BY columns and sort key of table,
just read the LIMIT N rows for each related segment and merge N rows.
1. set read_orderby_key to true for read_params and _reader_context
if olap_scan_node's sort info is set.
2. set read_orderby_key_reverse to true for read_params and _reader_context
if is_asc_order is false.
3. rowset reader force merge read segments if read_orderby_key is true.
4. block reader and tablet reader force merge read rowsets if read_orderby_key is true.
5. for ORDER BY DESC, read and compare in reverse order
5.1 segment iterator read backward using a new BackwardBitmapRangeIterator and
reverse the result block before return to caller.
5.2 VCollectIterator::LevelIteratorComparator, VMergeIteratorContext return
opposite result for _is_reverse order in its compare function.
Co-authored-by: jackwener <jakevingoo@gmail.com>
During load process, the same operation are performed on all replicas such as sort and aggregation,
which are resource-intensive.
Concurrent data load would consume much CPU and memory resources.
It's better to perform write process (writing data into MemTable and then data flush) on single replica
and synchronize data files to other replicas before transaction finished.
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>
This is an example of s3 hms_catalog:
```sql
CREATE CATALOG hms_catalog properties(
"type" = "hms",
"hive.metastore.uris"="thrift://localhost:9083",
"AWS_ACCESS_KEY" = "your access key",
"AWS_SECRET_KEY"="your secret key",
"AWS_ENDPOINT"="s3 endpoint",
"AWS_REGION"="s3-region",
"fs.s3a.paging.maximum"="1000");
```
All these params are necessary;
* [Schema Change] support fast add/drop column (#49)
* [feature](schema-change) support fast schema change. coauthor: yixiutt
* [schema change] Using columns desc from fe to read data. coauthor: Lchangliang
* [feature](schema change) schema change optimize for add/drop columns.
1.add uniqueId field for class column.
2.schema change for add/drop columns directly update schema meta
Co-authored-by: yixiutt <yixiu@selectdb.com>
Co-authored-by: SWJTU-ZhangLei <1091517373@qq.com>
[Feature](schema change) fix write and add regression test (#69)
Co-authored-by: yixiutt <yixiu@selectdb.com>
[schema change] be ssupport that delete use newest schema
add delete regression test
fix regression case (#107)
tmp
[feature](schema change) light schema change exclude rollup and agg/uniq/dup key type.
[feature](schema change) fe olapTable maxUniqueId write in disk.
[feature](schema change) add rpc iface for sc add column.
[feature](schema change) add columnsDesc to TPushReq for ligtht sc.
resolve the deadlock when schema change (#124)
fix columns from fe don't has bitmap_index flag (#134)
add update/delete case
construct MATERIALIZED schema from origin schema when insert
fix not vectorized compaction coredump
use segment cache
choose newest schema by schema version when compaction (#182)
[bugfix](schema change) fix ligth schema change problem.
[feature](schema change) light schema change add alter job. (#1)
fix be ut
[bug] (schema change) unique drop key column should not light schema
change
[feature](schema change) add schema change regression-test.
fix regression test
[bugfix](schema change) fix multi alter clauses for light schema change. (#2)
[bugfix](schema change) fix multi clauses calculate column unique id (#3)
modify PushTask process (#217)
[Bugfix](schema change) fix jobId replay cause bdbje exception.
[bug](schema change) fix max col unique id repeatitive. (#232)
[optimize](schema change) modify pendingMaxColUniqueId generate rule.
fix compaction error
* fix be ut
* fix snapshot load core
fix unique_id error (#278)
[refact](fe) remove redundant code for light schema change. (#4)
[refact](fe) remove redundant code for light schema change. (#4)
format fe core
format be core
fix be ut
modify fe meta version
fix rebase error
flush schema into rowset_meta in old table
[refactor](schema change) refact fe light schema change. (#5)
delete the change of schemahash and support get max version schema
* modify for review
* fix be ut
* fix schema change test
* add the array_distinct function
* add the support for decimal and update variable names
* add docs and regression test for array_distinct function
Co-authored-by: hucheng01 <hucheng01@baidu.com>
This PR supports rowset level data upload on the BE side, so that there can be both cold data and hot data in a tablet,
and there is no necessary to prohibit loading new data to cooled tablets.
Each rowset is bound to a `FileSystem`, so that the storage layer can read and write rowsets without
perceiving the underlying filesystem.
The abstracted `RemoteFileSystem` can try local caching strategies with different granularity,
instead of caching segment files as before.
To avoid conflicts with the code in be/src/io, we temporarily put the file system related code in the be/src/io/fs directory.
In the future, `FileReader`s and `FileWriter`s should be unified.
SortInfo is in SortNode. But there are some replicated field in SortNode
Issue Number: close#10616
Remove the redundant field in `TSortNode` which exist in `TSortInfo`.
[API-BREAK] This has changed `Thrift` file.
Define a new file scanner node for hms table in be.
This file scanner node is different from broker scan node as blow:
1. Broker scan node will define src slot and dest slot, there is two memory copy in it: first is from file to src slot
and second from src to dest slot. Otherwise FileScanNode only have one stemp memory copy just from file to dest slot.
2. Broker scan node will read all the filed in the file to src slot and FileScanNode only read the need filed.
3. Broker scan node will convert type into string type for src slot and then use cast to convert to dest slot type,
but FileScanNode will have the final type.
Now FileScanNode is a standalone code, but we will uniform the file scan and broker scan in the feature.
