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.
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>
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
This PR implement the new bloom filter index: NGram bloom filter index, which was proposed in #10733.
The new index can improve the like query performance greatly, from our some test case , can get order of magnitude improve.
For how to use it you can check the docs in this PR, and the index based on the ```enable_function_pushdown```,
you need set it to ```true```, to make the index work for like query.
Introduce a SQL syntax for creating inverted index and related metadata changes.
```
-- create table with INVERTED index
CREATE TABLE httplogs (
ts datetime,
clientip varchar(20),
request string,
status smallint,
size int,
INDEX idx_size (size) USING INVERTED,
INDEX idx_status (status) USING INVERTED,
INDEX idx_clientip (clientip) USING INVERTED PROPERTIES("parser"="none")
)
DUPLICATE KEY(ts)
DISTRIBUTED BY RANDOM BUCKETS 10
-- add an INVERTED index to a table
CREATE INDEX idx_request ON httplogs(request) USING INVERTED PROPERTIES("parser"="english");
```
# Proposed changes
This PR fixed lots of issues when building from source on macOS with Apple M1 chip.
## ATTENTION
The job for supporting macOS with Apple M1 chip is too big and there are lots of unresolved issues during runtime:
1. Some errors with memory tracker occur when BE (RELEASE) starts.
2. Some UT cases fail.
...
Temporarily, the following changes are made on macOS to start BE successfully.
1. Disable memory tracker.
2. Use tcmalloc instead of jemalloc.
This PR kicks off the job. Guys who are interested in this job can continue to fix these runtime issues.
## Use case
```shell
./build.sh -j 8 --be --clean
cd output/be/bin
ulimit -n 60000
./start_be.sh --daemon
```
## Something else
It takes around _**10+**_ minutes to build BE (with prebuilt third-parties) on macOS with M1 chip. We will improve the development experience on macOS greatly when we finish the adaptation job.
Add `JSON` datatype, following features are implemented by this PR:
1. `CREATE` tables with `JSON` type columns
2. `INSERT` values containing `JSON` type value stored in `String`, which is represented as binary format(AKA `JSONB`) at BE
3. `SELECT` JSON columns
Detail design refers [DSIP-016: Support JSON type](https://cwiki.apache.org/confluence/display/DORIS/DSIP-016%3A+Support+JSON+type)
* add JSONB data storage format type
* fix JsonLiteral resolve bug
* add DataTypeJson case in data_type_factory
* add JSON syntax check in FE
* add operators for jsonb_document, currently not support comparison between any JSON type value
* add ColumnJson and DataTypeJson
* add JsonField to store JsonValue
* add JsonValue to convert String JSON to BINARY JSON and JsonLiteral case for vliteral
* add push_json for MysqlResultWriter
* JSON column need no zone_map_index
* Revert "JSON column need no zone_map_index"
This reverts commit f71d1ce1ded9dbae44a5d58abcec338816b70d79.
* add JSON writer and reader, ignore zone-map for JSON column
* add json_to_string for DataTypeJson
* add olap_data_convertor for JSON type
* add some enum
* add OLAP_FIELD_TYPE_JSON type, FieldTypeTraits for it and corresponding cases or functions
* fix column_json offsets overflow bug, format code
* remove useless TODOs, add CmpType cases for JSON type
* add license header
* format license
* format be codes
* resolve rebase master conflicts
* fix bugs for CREATE and meta related code
* refactor JsonValue constructors, add fe JSON cases and fix some bugs, reformat codes
* modification be codes along code review advice
* fix rebase conflicts with master
* add unit test for json_value and column_json
* fix rebase error
* rename json to jsonb
* fix some data convert bugs, set Mysql type to JSON
Fix _delete_sign_idx and _seq_col_idx when append_column or build_schema when load.
Tablet schema cache support recycle when schema sptr use count equals 1.
Add a http interface for flink-connector to sync ddl.
Improve tablet->tablet_schema() by max_version_schema.
* [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
1. Fix LoadTask, ChunkAllocator, TabletMeta, Brpc, the accuracy of memory track.
2. Modified some MemTracker names, deleted some unnecessary trackers, and improved readability.
3. More powerful MemTracker debugging capabilities.
4. Avoid creating TabletColumn temporary objects and improve BE startup time by 8%.
5. Fix some other details.
## Design:
For now, there are two categories of types in Doris, one is for scalar types (such as int, char and etc.) and the other is for composite types (array and etc.). For the sake of performance, we can cache type info of scalar types globally (unique objects) due to the limited number of scalar types. When we consider the composite types, normally, the type info is generated in runtime (we can also use some cache strategy to speed up). The memory thereby should be reclaimed when we create type info for composite types.
There are a lots of interfaces to get the type info of a specific type. I reorganized those as the following describes.
1. `const TypeInfo* get_scalar_type_info(FieldType field_type)`
The function is used to get the type info of scalar types. Due to the cache, the caller uses the result **WITHOUT** considering the problems about memory reclaim.
2. `const TypeInfo* get_collection_type_info(FieldType sub_type)`
The function is used to get the type info of array types with just **ONE** depth. Due to the cache, the caller uses the result **WITHOUT** considering the problems about memory reclaim.
3. `TypeInfoPtr get_type_info(segment_v2::ColumnMetaPB* column_meta_pb)`
4. `TypeInfoPtr get_type_info(const TabletColumn* col)`
These functions are used to get the type info of **BOTH** scalar types and composite types. The caller should be responsible to manage the resources returned.
#### About the new type `TypeInfoPtr`
`TypeInfoPtr` is an alias type to `unique_ptr` with a custom deleter.
1. For scalar types, the deleter does nothing.
2. For composite types, the deleter reclaim the memory.
By analyzing the callers of `get_type_info`, these classes should hold TypeInfoPtr:
1. `Field`
2. `ColumnReader`
3. `DefaultValueColumnIterator`
Other classes are either constructed by the foregoing classes or hold those, so they can just use the raw pointer of `TypeInfo` directly for the sake of performance.
1. `ScalarColumnWriter` - holds `Field`
1. `ZoneMapIndexWriter` - created by `ScalarColumnWriter`, use `type_info` from the field in `ScalarColumnWriter`
1. `IndexedColumnWriter` - created by `ZoneMapIndexWriter`, only uses scalar types.
2. `BitmapIndexWriter` - created by `ScalarColumnWriter`, uses `type_info` from the field in `ScalarColumnWriter`
1. `IndexedColumnWriter` - created by `BitmapIndexWriter`, uses `type_info` in `BitmapIndexWriter` and `BitmapIndexWriter` doesn't support `ArrayType`.
3. `BloomFilterIndexWriter` - created by `ScalarColumnWriter`, uses `type_info` from the field in `ScalarColumnWriter`
1. `IndexedColumnWriter` - created by `BloomFilterIndexWriter`, only uses scalar types.
2. `IndexedColumnReader` initializes `type_info` by the field type in meta (only scalar types).
3. `ColumnVectorBatch`
1. `ZoneMapIndexReader` creates `ColumnVectorBatch`, `ColumnVectorBatch` uses `type_info` in `IndexedColumnReader`
2. `BitmapIndexReader` supports scalar types only and it creates `ColumnVectorBatch`, `ColumnVectorBatch` uses `type_info` in `BitmapIndexReader`
3. `BloomFilterIndexWriter` supports scalar types only and it creates `ColumnVectorBatch`, `ColumnVectorBatch` uses `type_info` in `BloomFilterIndexWriter`
Add a new column-type to speed up the approximation of quantiles.
1. The new column-type is named `quantile_state` with fixed aggregation function `quantile_union`, which stores the intermediate results of pre-aggregated approximation calculations for quantiles.
2. support pre-aggregation of new column-type and quantile_state related functions.
# Proposed changes
Issue Number: close#6238
Co-authored-by: HappenLee <happenlee@hotmail.com>
Co-authored-by: stdpain <34912776+stdpain@users.noreply.github.com>
Co-authored-by: Zhengguo Yang <yangzhgg@gmail.com>
Co-authored-by: wangbo <506340561@qq.com>
Co-authored-by: emmymiao87 <522274284@qq.com>
Co-authored-by: Pxl <952130278@qq.com>
Co-authored-by: zhangstar333 <87313068+zhangstar333@users.noreply.github.com>
Co-authored-by: thinker <zchw100@qq.com>
Co-authored-by: Zeno Yang <1521564989@qq.com>
Co-authored-by: Wang Shuo <wangshuo128@gmail.com>
Co-authored-by: zhoubintao <35688959+zbtzbtzbt@users.noreply.github.com>
Co-authored-by: Gabriel <gabrielleebuaa@gmail.com>
Co-authored-by: xinghuayu007 <1450306854@qq.com>
Co-authored-by: weizuo93 <weizuo@apache.org>
Co-authored-by: yiguolei <guoleiyi@tencent.com>
Co-authored-by: anneji-dev <85534151+anneji-dev@users.noreply.github.com>
Co-authored-by: awakeljw <993007281@qq.com>
Co-authored-by: taberylyang <95272637+taberylyang@users.noreply.github.com>
Co-authored-by: Cui Kaifeng <48012748+azurenake@users.noreply.github.com>
## Problem Summary:
### 1. Some code from clickhouse
**ClickHouse is an excellent implementation of the vectorized execution engine database,
so here we have referenced and learned a lot from its excellent implementation in terms of
data structure and function implementation.
We are based on ClickHouse v19.16.2.2 and would like to thank the ClickHouse community and developers.**
The following comment has been added to the code from Clickhouse, eg:
// This file is copied from
// https://github.com/ClickHouse/ClickHouse/blob/master/src/Interpreters/AggregationCommon.h
// and modified by Doris
### 2. Support exec node and query:
* vaggregation_node
* vanalytic_eval_node
* vassert_num_rows_node
* vblocking_join_node
* vcross_join_node
* vempty_set_node
* ves_http_scan_node
* vexcept_node
* vexchange_node
* vintersect_node
* vmysql_scan_node
* vodbc_scan_node
* volap_scan_node
* vrepeat_node
* vschema_scan_node
* vselect_node
* vset_operation_node
* vsort_node
* vunion_node
* vhash_join_node
You can run exec engine of SSB/TPCH and 70% TPCDS stand query test set.
### 3. Data Model
Vec Exec Engine Support **Dup/Agg/Unq** table, Support Block Reader Vectorized.
Segment Vec is working in process.
### 4. How to use
1. Set the environment variable `set enable_vectorized_engine = true; `(required)
2. Set the environment variable `set batch_size = 4096; ` (recommended)
### 5. Some diff from origin exec engine
https://github.com/doris-vectorized/doris-vectorized/issues/294
## Checklist(Required)
1. Does it affect the original behavior: (No)
2. Has unit tests been added: (Yes)
3. Has document been added or modified: (No)
4. Does it need to update dependencies: (No)
5. Are there any changes that cannot be rolled back: (Yes)
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
* [Enhance] Make MemTracker more accurate (#5515)
This PR main about:
1. Improve the readability of MemTrackers' name
2. Add the MemTracker of:
* Load
* Compaction
* SchemaChange
* StoragePageCache
* TabletManager
3. Change SchemaChange to a Singleon
* revise some code for Code Review
* change the name of mem_tracker
* keep reader_context have the same lifetime of rowset_reader in schema change.
* change vlog notice to log(warning) in schema change
This CL includes:
* Change the column metadata to a tree structure.
* Refactor the segment_v2.ColumnReader and sgment_v2.ColumnWriter to support complex type.
* Implements the reading and writing of array type.
