Docker安装ClickHouse并初始化数据测试

时间：2022-03-21 20:46:52

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

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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

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1、git clone https://github.com/vadimtk/ssb-dbgen.git
2、cd ssb-dbgen
3、make

3、生成数据

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./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

Docker安装ClickHouse并初始化数据测试

4、建表

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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);
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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);
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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;
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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

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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的资料请关注服务器之家其它相关文章！

原文链接：https://blog.csdn.net/Joe192/article/details/118159352

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