本篇内容主要讲解“Docker怎么安装ClickHouse并初始化数据测试”,感兴趣的朋友不妨来看看。本文介绍的方法操作简单快捷,实用性强。下面就让小编来带大家学习“Docker怎么安装ClickHouse并初始化数据测试”吧!
clickhouse简介
ClickHouse是一个面向列存储的数据库管理系统,可以使用SQL查询实时生成分析数据报告,主要用于OLAP(在线分析处理查询)场景。关于clickhouse原理以及基础知识在以后学习中慢慢总结。
1、Docker安装ClickHouse
docker run -d --name some-clickhouse-server \ -p 8123:8123 -p 9009:9009 -p 9091:9000 \ --ulimit nofile=262144:262144 \ -v /home/clickhouse:/var/lib/clickhouse \ yandex/clickhouse-server
2、下载SSBM工具
1、git clone https://github.com/vadimtk/ssb-dbgen.git 2、cd ssb-dbgen 3、make
3、生成数据
./dbgen -s 100 -T c ./dbgen -s 100 -T p ./dbgen -s 100 -T s ./dbgen -s 100 -T l ./dbgen -s 100 -T d
查看下数据
4、建表
CREATE TABLE default.customer ( C_CUSTKEY UInt32, C_NAME String, C_ADDRESS String, C_CITY LowCardinality(String), C_NATION LowCardinality(String), C_REGION LowCardinality(String), C_PHONE String, C_MKTSEGMENT LowCardinality(String) ) ENGINE = MergeTree ORDER BY (C_CUSTKEY);
CREATE TABLE default.lineorder ( LO_ORDERKEY UInt32, LO_LINENUMBER UInt8, LO_CUSTKEY UInt32, LO_PARTKEY UInt32, LO_SUPPKEY UInt32, LO_ORDERDATE Date, LO_ORDERPRIORITY LowCardinality(String), LO_SHIPPRIORITY UInt8, LO_QUANTITY UInt8, LO_EXTENDEDPRICE UInt32, LO_ORDTOTALPRICE UInt32, LO_DISCOUNT UInt8, LO_REVENUE UInt32, LO_SUPPLYCOST UInt32, LO_TAX UInt8, LO_COMMITDATE Date, LO_SHIPMODE LowCardinality(String) ) ENGINE = MergeTree PARTITION BY toYear(LO_ORDERDATE) ORDER BY (LO_ORDERDATE, LO_ORDERKEY);
CREATE TABLE default.part ( P_PARTKEY UInt32, P_NAME String, P_MFGR LowCardinality(String), P_CATEGORY LowCardinality(String), P_BRAND LowCardinality(String), P_COLOR LowCardinality(String), P_TYPE LowCardinality(String), P_SIZE UInt8, P_CONTAINER LowCardinality(String) ) ENGINE = MergeTree ORDER BY P_PARTKEY;
CREATE TABLE default.supplier ( S_SUPPKEY UInt32, S_NAME String, S_ADDRESS String, S_CITY LowCardinality(String), S_NATION LowCardinality(String), S_REGION LowCardinality(String), S_PHONE String ) ENGINE = MergeTree ORDER BY S_SUPPKEY;
5、导入数据
准备工作:
先把ssb-dbgen(lineorder.tbl,customer.tbl,part.tbl,supplier.tbl)考到clickhouse-server容器里面
clickhouse-client --query "INSERT INTO customer FORMAT CSV" < customer.tbl clickhouse-client --query "INSERT INTO part FORMAT CSV" < part.tbl clickhouse-client --query "INSERT INTO supplier FORMAT CSV" < supplier.tbl clickhouse-client --query "INSERT INTO lineorder FORMAT CSV" < lineorder.tbl
注意:如果此处报错,检查clickhouse的配置(端口是否占用,是否设置用户和密码)
6、测试
编号 | 查询语句SQL | 耗时(ms) |
---|---|---|
Q1 | SELECT SUM(l.LO_EXTENDEDPRICE * l.LO_DISCOUNT) AS revenue FROM lineorder_flat WHERE toYear(l.LO_ORDERDATE) = 1993 AND l.LO_DISCOUNT BETWEEN 1 AND 3 AND l.LO_QUANTITY < 25; | 36 |
Q2 | SELECT SUM(l.LO_EXTENDEDPRICE * l.LO_DISCOUNT) AS revenue FROM lineorder_flat WHERE toYYYYMM(l.LO_ORDERDATE) = 199401 AND l.LO_DISCOUNT BETWEEN 4 AND 6 AND l.LO_QUANTITYBETWEEN 26 AND 35; | 12 |
Q3 | SELECT SUM(l.LO_EXTENDEDPRICE * l.LO_DISCOUNT) AS revenue FROM lineorder_flat WHERE toISOWeek(l.LO_ORDERDATE) = 6 AND toYear(l.LO_ORDERDATE) = 1994 AND l.LO_DISCOUNT BETWEEN 5 AND 7 AND l.LO_QUANTITY BETWEEN 26 AND 35; | 12 |
Q4 | SELECT SUM(l.LO_REVENUE), toYear(l.LO_ORDERDATE) AS year, p.P_BRAND FROM lineorder_flat WHERE p.P_CATEGORY = ‘MFGR#12' AND s.S_REGION = ‘AMERICA' GROUP BY year, p.P_BRAND ORDER BY year, p.P_BRAND; | 16 |
Q5 | SELECT SUM(l.LO_REVENUE), toYear(l.LO_ORDERDATE) AS year, p.P_BRAND FROM lineorder_flat WHERE p.P_BRAND BETWEEN ‘MFGR#2221' AND ‘MFGR#2228' AND s.S_REGION = ‘ASIA' GROUP BY year, p.P_BRAND ORDER BY year, p.P_BRAND; | 21 |
Q6 | SELECT toYear(l.LO_ORDERDATE) AS year, s.S_CITY, p.P_BRAND, SUM(l.LO_REVENUE -l.LO_SUPPLYCOST) AS profit FROM lineorder_flat WHERE s.S_NATION = ‘UNITED STATES' AND (year = 1997 OR year = 1998) AND p.P_CATEGORY = ‘MFGR#14' GROUP BY year, s.S_CITY, p.P_BRAND ORDER BY year, s.S_CITY, p.P_BRAND; | 19 |
官网参考:
https://clickhouse.tech/docs/zh/getting-started/example-datasets/star-schema/#star-schema-benchmark
到此,相信大家对“Docker怎么安装ClickHouse并初始化数据测试”有了更深的了解,不妨来实际操作一番吧!这里是亿速云网站,更多相关内容可以进入相关频道进行查询,关注我们,继续学习!
免责声明:本站发布的内容(图片、视频和文字)以原创、转载和分享为主,文章观点不代表本网站立场,如果涉及侵权请联系站长邮箱:is@yisu.com进行举报,并提供相关证据,一经查实,将立刻删除涉嫌侵权内容。