Add fast path for col like '%%' or col like '%' or regexp '\\.*'
(1) like about 34% speed up when use count() test
support col like '%%' , col like '%', col not like '%%' , col not like '%'
(2) regexp about 37% speed up when use count() test
support col regexp '\\.', col not regexp '\\.'
Q1: select count() From hits where url like '%';
Q2: select count() From hits where url regexp '\\.*';
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.
Result is empty for query select * from person where address like '%\\\\%';, but MySQL can get a line of result.
CREATE TABLE `person` (
`id` int(11) NULL,
`name` text NULL,
`age` int(11) NULL,
`class` int(11) NULL,
`address` text NULL
) ENGINE=OLAP
UNIQUE KEY(`id`)
COMMENT 'OLAP'
DISTRIBUTED BY HASH(`id`) BUCKETS 1
PROPERTIES (
"replication_allocation" = "tag.location.default: 1",
"in_memory" = "false",
"storage_format" = "V2",
"disable_auto_compaction" = "false"
);
insert into person values (10001,'test1',30,2,'test\\\\,xxx');
Adding logs:
select * from person where address like '%\\\\%';
I0323 10:26:15.907760 2387043 like.cpp:558] arg str: %\\%, size: 4, pattern LIKE_ENDS_WITH_RE: (?:%+)(((\\%)|(\\_)|([^%_]))+), size: 30
I0323 10:26:15.907789 2387043 like.cpp:562] match 0: \\%, size: 3
I0323 10:26:15.907801 2387043 like.cpp:562] match 1: \%, size: 2
I0323 10:26:15.907811 2387043 like.cpp:562] match 2: \%, size: 2
I0323 10:26:15.907821 2387043 like.cpp:562] match 3: , size: 0
I0323 10:26:15.907830 2387043 like.cpp:562] match 4: \, size: 1
I0323 10:26:15.907842 2387043 like.cpp:615] search_string : \\%
I0323 10:26:15.907855 2387043 like.cpp:619] search_string escape removed: \%
It matchs against the LIKE_ENDS_WITH_RE which is wrong, the meaning of the sql should be: match strings that have one backslash in any place.
The like predicate process data in block perform better than in row. Currently, only not null column is optimized, nullable column will be handled later.
SELECT COUNT(*) FROM hits WHERE URL LIKE '%google%';
before: ~680ms
after: ~570ms
We have added logical project before, but to actually finish the prune to reduce the data IO, we need to add related supports in translator and BE.
This PR:
- add projections on each ExecNode in BE
- translate PhysicalProject into projections on PlanNode in FE
- do column prune on ScanNode in FE
Co-authored-by: HappenLee <happenlee@hotmail.com>
* add volnitsky substr algorithm
* replace std::search with volnitsky search algorithm in StringSearch
* optimize substring for constant_substring_fn case
use long run length search for performance
# 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>
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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)
