Docker安装ClickHouse并初始化数据测试

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

以上就是Docker创建ClickHouse 并初始化数据测试的详细内容，更多关于Docker的资料请关注免费资源网其它相关文章！