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6.7 KiB
6.7 KiB
toc_priority | toc_title |
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16 | Star Schema Benchmark |
Star Schema Benchmark
编译 dbgen:
$ git clone git@github.com:vadimtk/ssb-dbgen.git
$ cd ssb-dbgen
$ make
开始生成数据:
!!! warning "注意"
使用-s 100
dbgen将生成6亿行数据(67GB), 如果使用-s 1000
它会生成60亿行数据(这需要很多时间))
$ ./dbgen -s 1000 -T c
$ ./dbgen -s 1000 -T l
$ ./dbgen -s 1000 -T p
$ ./dbgen -s 1000 -T s
$ ./dbgen -s 1000 -T d
在ClickHouse中创建数据表:
CREATE TABLE 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 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 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 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;
写入数据:
$ 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
将star schema
转换为flat schema
:
SET max_memory_usage = 20000000000, allow_experimental_multiple_joins_emulation = 1;
CREATE TABLE lineorder_flat
ENGINE = MergeTree
PARTITION BY toYear(LO_ORDERDATE)
ORDER BY (LO_ORDERDATE, LO_ORDERKEY) AS
SELECT l.*, c.*, s.*, p.*
FROM lineorder l
ANY INNER JOIN customer c ON (c.C_CUSTKEY = l.LO_CUSTKEY)
ANY INNER JOIN supplier s ON (s.S_SUPPKEY = l.LO_SUPPKEY)
ANY INNER JOIN part p ON (p.P_PARTKEY = l.LO_PARTKEY);
ALTER TABLE lineorder_flat DROP COLUMN C_CUSTKEY, DROP COLUMN S_SUPPKEY, DROP COLUMN P_PARTKEY;
运行查询:
Q1.1
SELECT sum(LO_EXTENDEDPRICE * LO_DISCOUNT) AS revenue FROM lineorder_flat WHERE toYear(LO_ORDERDATE) = 1993 AND LO_DISCOUNT BETWEEN 1 AND 3 AND LO_QUANTITY < 25;
Q1.2
SELECT sum(LO_EXTENDEDPRICE * LO_DISCOUNT) AS revenue FROM lineorder_flat WHERE toYYYYMM(LO_ORDERDATE) = 199401 AND LO_DISCOUNT BETWEEN 4 AND 6 AND LO_QUANTITY BETWEEN 26 AND 35;
Q1.3
SELECT sum(LO_EXTENDEDPRICE * LO_DISCOUNT) AS revenue FROM lineorder_flat WHERE toISOWeek(LO_ORDERDATE) = 6 AND toYear(LO_ORDERDATE) = 1994 AND LO_DISCOUNT BETWEEN 5 AND 7 AND LO_QUANTITY BETWEEN 26 AND 35;
Q2.1
SELECT sum(LO_REVENUE), toYear(LO_ORDERDATE) AS year, P_BRAND FROM lineorder_flat WHERE P_CATEGORY = 'MFGR#12' AND S_REGION = 'AMERICA' GROUP BY year, P_BRAND ORDER BY year, P_BRAND;
Q2.2
SELECT sum(LO_REVENUE), toYear(LO_ORDERDATE) AS year, P_BRAND FROM lineorder_flat WHERE P_BRAND BETWEEN 'MFGR#2221' AND 'MFGR#2228' AND S_REGION = 'ASIA' GROUP BY year, P_BRAND ORDER BY year, P_BRAND;
Q2.3
SELECT sum(LO_REVENUE), toYear(LO_ORDERDATE) AS year, P_BRAND FROM lineorder_flat WHERE P_BRAND = 'MFGR#2239' AND S_REGION = 'EUROPE' GROUP BY year, P_BRAND ORDER BY year, P_BRAND;
Q3.1
SELECT C_NATION, S_NATION, toYear(LO_ORDERDATE) AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE C_REGION = 'ASIA' AND S_REGION = 'ASIA' AND year >= 1992 AND year <= 1997 GROUP BY C_NATION, S_NATION, year ORDER BY year asc, revenue desc;
Q3.2
SELECT C_CITY, S_CITY, toYear(LO_ORDERDATE) AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE C_NATION = 'UNITED STATES' AND S_NATION = 'UNITED STATES' AND year >= 1992 AND year <= 1997 GROUP BY C_CITY, S_CITY, year ORDER BY year asc, revenue desc;
Q3.3
SELECT C_CITY, S_CITY, toYear(LO_ORDERDATE) AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE (C_CITY = 'UNITED KI1' OR C_CITY = 'UNITED KI5') AND (S_CITY = 'UNITED KI1' OR S_CITY = 'UNITED KI5') AND year >= 1992 AND year <= 1997 GROUP BY C_CITY, S_CITY, year ORDER BY year asc, revenue desc;
Q3.4
SELECT C_CITY, S_CITY, toYear(LO_ORDERDATE) AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE (C_CITY = 'UNITED KI1' OR C_CITY = 'UNITED KI5') AND (S_CITY = 'UNITED KI1' OR S_CITY = 'UNITED KI5') AND toYYYYMM(LO_ORDERDATE) = '199712' GROUP BY C_CITY, S_CITY, year ORDER BY year asc, revenue desc;
Q4.1
SELECT toYear(LO_ORDERDATE) AS year, C_NATION, sum(LO_REVENUE - LO_SUPPLYCOST) AS profit FROM lineorder_flat WHERE C_REGION = 'AMERICA' AND S_REGION = 'AMERICA' AND (P_MFGR = 'MFGR#1' OR P_MFGR = 'MFGR#2') GROUP BY year, C_NATION ORDER BY year, C_NATION;
Q4.2
SELECT toYear(LO_ORDERDATE) AS year, S_NATION, P_CATEGORY, sum(LO_REVENUE - LO_SUPPLYCOST) AS profit FROM lineorder_flat WHERE C_REGION = 'AMERICA' AND S_REGION = 'AMERICA' AND (year = 1997 OR year = 1998) AND (P_MFGR = 'MFGR#1' OR P_MFGR = 'MFGR#2') GROUP BY year, S_NATION, P_CATEGORY ORDER BY year, S_NATION, P_CATEGORY;
Q4.3
SELECT toYear(LO_ORDERDATE) AS year, S_CITY, P_BRAND, sum(LO_REVENUE - LO_SUPPLYCOST) AS profit FROM lineorder_flat WHERE S_NATION = 'UNITED STATES' AND (year = 1997 OR year = 1998) AND P_CATEGORY = 'MFGR#14' GROUP BY year, S_CITY, P_BRAND ORDER BY year, S_CITY, P_BRAND;