clickhouse簡介
ClickHouse是一個面向列存儲的數(shù)據(jù)庫管理系統(tǒng)，可以使用SQL查詢實時生成分析數(shù)據(jù)報告，主要用于OLAP(在線分析處理查詢)場景。關(guān)于clickhouse原理以及基礎(chǔ)知識在以后學習中慢慢總結(jié)。
1、Docker安裝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、下載SSBM工具
1、git clone https://github.com/vadimtk/ssb-dbgen.git
2、cd ssb-dbgen
3、make
3、生成數(shù)據(jù)
./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
查看下數(shù)據(jù)
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、導入數(shù)據(jù)
準備工作：
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：如果此處報錯，檢查clickhouse的配置（端口是否占用，是否設(shè)置用戶和密碼）
6、測試
| 編號 |
查詢語句SQL |
耗時(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 |
官網(wǎng)參考：
https://clickhouse.tech/docs/zh/getting-started/example-datasets/star-schema/#star-schema-benchmark
以上就是Docker創(chuàng)建ClickHouse 并初始化數(shù)據(jù)測試的詳細內(nèi)容，更多關(guān)于Docker的資料請關(guān)注腳本之家其它相關(guān)文章！
