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
remove duplicate type definition in function context
remove unused method in function context
not need stale state in vexpr context because vexpr is stateless and function context saves state and they are cloned.
remove useless slot_size in all tuple or slot descriptor.
remove doris_udf namespace, it is useless.
remove some unused macro definitions.
init v_conjuncts in vscanner, not need write the same code in every scanner.
using unique ptr to manage function context since it could only belong to a single expr context.
Issue Number: close #xxx
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Co-authored-by: yiguolei <yiguolei@gmail.com>
1、support stream load with json, csv format for map
2、fix olap convertor when compaction action in map column which has null
3、support select outToFile for map
4、add some regression-test
This commit support:
1、Insert + select for struct/map type
2、Json stream load for struct type
3、m[key] function for map type
How to use:
Set the fe config to create table for struct and map type
1、admin set frontend config("enable_struct_type" = "true");
2、admin set frontend config("enable_map_type" = "true");
#16547
Co-authored-by: xy720 <xuyang25@baidu.com>
Co-authored-by: amory <wangqiannan@selectdb.com>
Co-authored-by: cambyzju <zhuxiaoli01@baidu.com>
Co-authored-by: hucheng01 <hucheng01@baidu.com>
This PR optimize topn query like `SELECT * FROM tableX ORDER BY columnA ASC/DESC LIMIT N`.
TopN is is compose of SortNode and ScanNode, when user table is wide like 100+ columns the order by clause is just a few columns.But ScanNode need to scan all data from storage engine even if the limit is very small.This may lead to lots of read amplification.So In this PR I devide TopN query into two phase:
1. The first phase we just need to read `columnA`'s data from storage engine along with an extra RowId column called `__DORIS_ROWID_COL__`.The other columns are pruned from ScanNode.
2. The second phase I put it in the ExchangeNode beacuase it's the central node for topn nodes in the cluster.The ExchangeNode will spawn a RPC to other nodes using the RowIds(sorted and limited from SortNode) read from the first phase and read row by row from storage engine.
After the second phase read, Block will contain all the data needed for the query
* [feature-wip](inverted index)inverted index api: reader
* [feature-wip](inverted index) Fulltext query syntax with MATCH/MATCH_ALL/MATCH_ALL
* [feature-wip](inverted index) Adapt to index meta
* [enhance] add more metrics
* [enhance] add fulltext match query check for column type and index parser
* [feature-wip](inverted index) Support apply inverted index in compound predicate which except leaf node of and node
Current bitmap index only can apply pushed down predicates which in AND conditions. When predicates in OR conditions and other complex compound conditions, it will not be pushed down to the storage layer, this leads to read more data.
Based on that situation, this pr will do:
1. this pr in order to support bitmap index apply compound predicates, query sql like:
select * from tb where a > 'hello' or b < 100;
select * from tb where a > 'hello' or b < 100 or c > 'ok';
select * from tb where (a > 'hello' or b <100) and (a < 'world' or b > 200);
select * from tb where (not a> 'hello') or b < 100;
...
above sql，column a and b and c has created bitmap_index.
2. this optimization can reduce reading data by index
3. set config enable_index_apply_compound_predicates to use this optimization
The former logic inside aggregate_function_window.cpp would shutdown BE once encountering agg function with complex type like BITMAP. This pr makes it don't crash and would return one more concrete error message which tells the unsupported function signature to user.
1.Support in bitmap syntax, like 'where k1 in (select bitmap_column from tbl)';
2.Support bitmap runtime filter. Generate a bitmap filter using the right table bitmap and push it down to the left table storage layer for filtering.
