1000字范文 > clickhouse 子查询_TPCDS用于Clickhouse和Doris性能测试

clickhouse 子查询_TPCDS用于Clickhouse和Doris性能测试

时间：2022-08-17 01:51:59

大致介绍

TPC-DS采用星型、雪花型等多维数据模式。它包含7张事实表，17张纬度表平均每张表含有18列。其工作负载包含99个SQL查询，覆盖SQL99和的核心部分以及OLAP。这个测试集包含对大数据集的统计、报表生成、联机查询、数据挖掘等复杂应用，测试用的数据和值是有倾斜的，与真实数据一致。可以说TPC-DS是与真实场景非常接近的一个测试集，也是难度较大的一个测试集。

Clickhouse是俄罗斯Yandex公司开源的一个非常快的数据管理系统，性能非常强悍。Apache Doris是百度开源的另一个基于 MPP 的交互式 SQL 数据仓库，主要用于解决报表和多维分析，成熟稳定。

下载编译

下载官方网址

也可以通过Git下载

git clone /gregrahn/tpcds-kit.git

cd tpcds-kit/tools

make OS=LINUX

tpcds.sql是建表SQL

[tools]$ ll *.sql

-rw-r----- 1 prodadmin prodadmin 13875 Mar 12 03:44 tpcds_ri.sql

-rw-r----- 1 prodadmin prodadmin 22153 Mar 12 03:44 tpcds_source.sql

-rw-r----- 1 prodadmin prodadmin 30001 Mar 12 03:44 tpcds.sql

dsdgen是生成数据的工具，dsqgen是生成Query的工具

[tools]$ ll ds*

-rwxr-x--- 1 prodadmin prodadmin 455880 Apr 16 19:15 dsdgen

-rwxr-x--- 1 prodadmin prodadmin 292254 Apr 16 19:15 dsqgen

在query_templates中是query模板

[tools]$ ls ../query_templates/

ansi.tplquery12.tpl query18.tpl query23.tpl query29.tpl query34.tpl query3.tpl query45.tpl query50.tpl query56.tpl query61.tpl query67.tpl query72.tpl query78.tpl query83.tpl query89.tpl query94.tpl query9.tpl

db2.tplquery13.tpl query19.tpl query24.tpl query2.tpl query35.tpl query40.tpl query46.tpl query51.tpl query57.tpl query62.tpl query68.tpl query73.tpl query79.tpl query84.tpl query8.tpl query95.tpl README

netezza.tpl query14.tpl query1.tpl query25.tpl query30.tpl query36.tpl query41.tpl query47.tpl query52.tpl query58.tpl query63.tpl query69.tpl query74.tpl query7.tpl query85.tpl query90.tpl query96.tpl sqlserver.tpl

oracle.tpl query15.tpl query20.tpl query26.tpl query31.tpl query37.tpl query42.tpl query48.tpl query53.tpl query59.tpl query64.tpl query6.tpl query75.tpl query80.tpl query86.tpl query91.tpl query97.tpl templates.lst

query10.tpl query16.tpl query21.tpl query27.tpl query32.tpl query38.tpl query43.tpl query49.tpl query54.tpl query5.tpl query65.tpl query70.tpl query76.tpl query81.tpl query87.tpl query92.tpl query98.tpl

query11.tpl query17.tpl query22.tpl query28.tpl query33.tpl query39.tpl query44.tpl query4.tpl query55.tpl query60.tpl query66.tpl query71.tpl query77.tpl query82.tpl query88.tpl query93.tpl query99.tpl

建表语句

请根据Hive、Doris、Clickhouse等组件特点，修改建表语句，请注意，列是否为空，列的顺序等和后面步骤的导入数据密切相关，请勿轻易修改。

1Clickhouse数据类型

2Doris建表和数据类型

create table dbgen_version

create table customer_address

create table customer_demographics

create table date_dim

create table warehouse

create table ship_mode

create table time_dim

create table reason

create table income_band

create table item

create table store

create table call_center

create table customer

create table web_site

create table store_returns

create table household_demographics

create table web_page

create table promotion

create table catalog_page

create table inventory

create table catalog_returns

create table web_returns

create table web_sales

create table catalog_sales

create table store_sales

数据生成

可以建一个脚本，来生成数据

1 数据分隔符是“|”，空值默认为空。Clickhouse支持的格式，Doris Load格式。

2 scale单位为G，指生成的数据量大小，paralle指分割多少个文件，child指第几个文件

[tools]$ cat build_data_tsv.h

echo $1

mkdir ../../data_tsv/

nohup ./dsdgen -scale 100 -dir ../../data_tsv/ -paralle 10 -child $1 > child$1.log &

数据导入

Clickhouse数据导入，一个例子，我写了一个convert.py的小脚本，处理分隔符、空值、列顺序等问题

if [ ! -f "./data_tsv/dbgen_version_$1_10.done" ]; then

cat ./data_tsv/dbgen_version_$1_10.dat|python convert.py ck|clickhouse-client --query="INSERT INTO default.dbgen_version_dist FORMAT CSV"

touch ./data_tsv/dbgen_version_$1_10.done

fi

Doris数据导入

cat ./data_tsv/dbgen_version_$1_10.dat|python convert.py dr dbgen_version|curl --location-trusted -u root: -H "label:dbgen_version_$1_10_" -H "timeout:1200" -T - http://ip:port/api/testdb/dbgen_version/_stream_load

生成Query

cat build_sql.sh

./dsqgen \

-DIRECTORY ../query_templates \

-INPUT ../query_templates/templates.lst \

-VERBOSE Y \

-QUALIFY Y \

-SCALE 100 \

-DIALECT sqlserver \

-OUTPUT_DIR ../../query/

Query改写

比如如下的SQL，在Doris中是可以正确的执行的，但是在Clickhouse中不行，CK中需要子查询嵌套或者用global inner join来显示指定broadcast的字表。

select

c_last_name,c_first_name,substr(s_city,1,30),ss_ticket_number,amt,profit

from

(select ss_ticket_number

,ss_customer_sk

,store.s_city

,sum(ss_coupon_amt) amt

,sum(ss_net_profit) profit

from store_sales,date_dim,store,household_demographics

where store_sales.ss_sold_date_sk = date_dim.d_date_sk

and store_sales.ss_store_sk = store.s_store_sk

and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk

and (household_demographics.hd_dep_count = 1 or household_demographics.hd_vehicle_count > -1)

and date_dim.d_dow = 1

and date_dim.d_year in (2000,2000+1,2000+2)

and store.s_number_employees between 200 and 295

group by ss_ticket_number,ss_customer_sk,ss_addr_sk,store.s_city) ms,customer

where ss_customer_sk = c_customer_sk

order by c_last_name,c_first_name,substr(s_city,1,30), profit

limit 10;

改写后

select c_last_name, c_first_name, substr(tbl1.s_city,1,30), ss_ticket_number, amt, profit

from customer_dist

global inner join (

select ss_ticket_number, ss_customer_sk, s_city, sum(ss_coupon_amt) as amt, sum(ss_net_profit) as profit

from store_sales_dist

global inner join ( select d_date_sk from date_dim_dist where date_dim_dist.d_dow = 1 and d_year in (2000,2000+1,2000+2) ) on ss_sold_date_sk = d_date_sk

global inner join ( select s_store_sk, s_city from store_dist where s_number_employees between 200 and 295 ) on ss_store_sk = s_store_sk

global inner join ( select hd_demo_sk from household_demographics_dist where hd_dep_count = 1 or hd_vehicle_count > -1 ) on ss_hdemo_sk = hd_demo_sk

group by ss_ticket_number, ss_customer_sk, ss_addr_sk, s_city

) tbl1 on ss_customer_sk = c_customer_sk

order by c_last_name, c_first_name, substr(s_city,1,30), profit

limit 10;