Star Schema Benchmark (SSB, 2009)
The Star Schema Benchmark is roughly based on the TPC-H's tables and queries but unlike TPC-H, it uses a star schema layout.
The bulk of the data sits in a gigantic fact table which is surrounded by multiple small dimension tables.
The queries joined the fact table with one or more dimension tables to apply filter criteria, e.g. MONTH = 'JANUARY'
.
References:
- Star Schema Benchmark (O'Neil et. al), 2009
- Variations of the Star Schema Benchmark to Test the Effects of Data Skew on Query Performance (Rabl. et. al.), 2013
First, checkout the star schema benchmark repository and compile the data generator:
git clone https://github.com/vadimtk/ssb-dbgen.git
cd ssb-dbgen
make
Then, generate the data. Parameter -s
specifies the scale factor. For example, with -s 100
, 600 million rows are generated.
./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
Now create tables in ClickHouse:
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;
CREATE TABLE date
(
D_DATEKEY Date,
D_DATE FixedString(18),
D_DAYOFWEEK LowCardinality(String),
D_MONTH LowCardinality(String),
D_YEAR UInt16,
D_YEARMONTHNUM UInt32,
D_YEARMONTH LowCardinality(FixedString(7)),
D_DAYNUMINWEEK UInt8,
D_DAYNUMINMONTH UInt8,
D_DAYNUMINYEAR UInt16,
D_MONTHNUMINYEAR UInt8,
D_WEEKNUMINYEAR UInt8,
D_SELLINGSEASON String,
D_LASTDAYINWEEKFL UInt8,
D_LASTDAYINMONTHFL UInt8,
D_HOLIDAYFL UInt8,
D_WEEKDAYFL UInt8
)
ENGINE = MergeTree ORDER BY D_DATEKEY;
The data can be imported as follows:
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
clickhouse-client --query "INSERT INTO date FORMAT CSV" < date.tbl
In many use cases of ClickHouse, multiple tables are converted into a single denormalized flat table. This step is optional, below queries are listed in their original form and in a format rewritten for the denormalized table.
SET max_memory_usage = 20000000000;
CREATE TABLE lineorder_flat
ENGINE = MergeTree ORDER BY (LO_ORDERDATE, LO_ORDERKEY)
AS SELECT
l.LO_ORDERKEY AS LO_ORDERKEY,
l.LO_LINENUMBER AS LO_LINENUMBER,
l.LO_CUSTKEY AS LO_CUSTKEY,
l.LO_PARTKEY AS LO_PARTKEY,
l.LO_SUPPKEY AS LO_SUPPKEY,
l.LO_ORDERDATE AS LO_ORDERDATE,
l.LO_ORDERPRIORITY AS LO_ORDERPRIORITY,
l.LO_SHIPPRIORITY AS LO_SHIPPRIORITY,
l.LO_QUANTITY AS LO_QUANTITY,
l.LO_EXTENDEDPRICE AS LO_EXTENDEDPRICE,
l.LO_ORDTOTALPRICE AS LO_ORDTOTALPRICE,
l.LO_DISCOUNT AS LO_DISCOUNT,
l.LO_REVENUE AS LO_REVENUE,
l.LO_SUPPLYCOST AS LO_SUPPLYCOST,
l.LO_TAX AS LO_TAX,
l.LO_COMMITDATE AS LO_COMMITDATE,
l.LO_SHIPMODE AS LO_SHIPMODE,
c.C_NAME AS C_NAME,
c.C_ADDRESS AS C_ADDRESS,
c.C_CITY AS C_CITY,
c.C_NATION AS C_NATION,
c.C_REGION AS C_REGION,
c.C_PHONE AS C_PHONE,
c.C_MKTSEGMENT AS C_MKTSEGMENT,
s.S_NAME AS S_NAME,
s.S_ADDRESS AS S_ADDRESS,
s.S_CITY AS S_CITY,
s.S_NATION AS S_NATION,
s.S_REGION AS S_REGION,
s.S_PHONE AS S_PHONE,
p.P_NAME AS P_NAME,
p.P_MFGR AS P_MFGR,
p.P_CATEGORY AS P_CATEGORY,
p.P_BRAND AS P_BRAND,
p.P_COLOR AS P_COLOR,
p.P_TYPE AS P_TYPE,
p.P_SIZE AS P_SIZE,
p.P_CONTAINER AS P_CONTAINER
FROM lineorder AS l
INNER JOIN customer AS c ON c.C_CUSTKEY = l.LO_CUSTKEY
INNER JOIN supplier AS s ON s.S_SUPPKEY = l.LO_SUPPKEY
INNER JOIN part AS p ON p.P_PARTKEY = l.LO_PARTKEY;
The queries are generated by ./qgen -s <scaling_factor>
. Example queries for s = 100
:
Q1.1
SELECT
sum(LO_EXTENDEDPRICE * LO_DISCOUNT) AS REVENUE
FROM
lineorder,
date
WHERE
LO_ORDERDATE = D_DATEKEY
AND D_YEAR = 1993
AND LO_DISCOUNT BETWEEN 1 AND 3
AND LO_QUANTITY < 25;
Denormalized table:
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,
date
WHERE
LO_ORDERDATE = D_DATEKEY
AND D_YEARMONTHNUM = 199401
AND LO_DISCOUNT BETWEEN 4 AND 6
AND LO_QUANTITY BETWEEN 26 AND 35;
Denormalized table:
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,
date
WHERE
LO_ORDERDATE = D_DATEKEY
AND D_WEEKNUMINYEAR = 6
AND D_YEAR = 1994
AND LO_DISCOUNT BETWEEN 5 AND 7
AND LO_QUANTITY BETWEEN 26 AND 35;
Denormalized table:
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),
D_YEAR,
P_BRAND
FROM
lineorder,
date,
part,
supplier
WHERE
LO_ORDERDATE = D_DATEKEY
AND LO_PARTKEY = P_PARTKEY
AND LO_SUPPKEY = S_SUPPKEY
AND P_CATEGORY = 'MFGR#12'
AND S_REGION = 'AMERICA'
GROUP BY
D_YEAR,
P_BRAND
ORDER BY
D_YEAR,
P_BRAND;
Denormalized table:
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),
D_YEAR,
P_BRAND
FROM
lineorder,
date,
part,
supplier
WHERE
LO_ORDERDATE = D_DATEKEY
AND LO_PARTKEY = P_PARTKEY
AND LO_SUPPKEY = S_SUPPKEY
AND P_BRAND BETWEEN
'MFGR#2221' AND 'MFGR#2228'
AND S_REGION = 'ASIA'
GROUP BY
D_YEAR,
P_BRAND
ORDER BY
D_YEAR,
P_BRAND;
Denormalized table:
SELECT
sum(LO_REVENUE),
toYear(LO_ORDERDATE) AS year,
P_BRAND
FROM lineorder_flat
WHERE P_BRAND >= 'MFGR#2221' AND P_BRAND <= 'MFGR#2228' AND S_REGION = 'ASIA'
GROUP BY
year,
P_BRAND
ORDER BY
year,
P_BRAND;
Q2.3
SELECT
sum(LO_REVENUE),
D_YEAR,
P_BRAND
FROM
lineorder,
date,
part,
supplier
WHERE
LO_ORDERDATE = D_DATEKEY
AND LO_PARTKEY = P_PARTKEY
AND LO_SUPPKEY = S_SUPPKEY
AND P_BRAND = 'MFGR#2221'
AND S_REGION = 'EUROPE'
GROUP BY
D_YEAR,
P_BRAND
ORDER BY
D_YEAR,
P_BRAND;
Denormalized table:
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,
D_YEAR,
sum(LO_REVENUE) AS REVENUE
FROM
customer,
lineorder,
supplier,
date
WHERE
LO_CUSTKEY = C_CUSTKEY
AND LO_SUPPKEY = S_SUPPKEY
AND LO_ORDERDATE = D_DATEKEY
AND C_REGION = 'ASIA' AND S_REGION = 'ASIA'
AND D_YEAR >= 1992 AND D_YEAR <= 1997
GROUP BY
C_NATION,
S_NATION,
D_YEAR
ORDER BY
D_YEAR ASC,
REVENUE DESC;
Denormalized table:
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,
D_YEAR,
sum(LO_REVENUE) AS REVENUE
FROM
customer,
lineorder,
supplier,
date
WHERE
LO_CUSTKEY = C_CUSTKEY
AND LO_SUPPKEY = S_SUPPKEY
AND LO_ORDERDATE = D_DATEKEY
AND C_NATION = 'UNITED STATES'
AND S_NATION = 'UNITED STATES'
AND D_YEAR >= 1992 AND D_YEAR <= 1997
GROUP BY
C_CITY,
S_CITY,
D_YEAR
ORDER BY
D_YEAR ASC,
REVENUE DESC;
Denormalized table:
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,
D_YEAR,
sum(LO_REVENUE) AS revenue
FROM
customer,
lineorder,
supplier,
date
WHERE
LO_CUSTKEY = C_CUSTKEY
AND LO_SUPPKEY = S_SUPPKEY
AND LO_ORDERDATE = D_DATEKEY
AND (C_CITY = 'UNITED KI1' OR C_CITY = 'UNITED KI5')
AND (S_CITY = 'UNITED KI1' OR S_CITY = 'UNITED KI5')
AND D_YEAR >= 1992
AND D_YEAR <= 1997
GROUP BY
C_CITY,
S_CITY,
D_YEAR
ORDER BY
D_YEAR ASC,
revenue DESC;
Denormalized table:
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,
D_YEAR,
sum(LO_REVENUE) AS revenue
FROM
customer,
lineorder,
supplier,
date
WHERE
LO_CUSTKEY = C_CUSTKEY
AND LO_SUPPKEY = S_SUPPKEY
AND LO_ORDERDATE = D_DATEKEY
AND (C_CITY='UNITED KI1' OR C_CITY='UNITED KI5')
AND (S_CITY='UNITED KI1' OR S_CITY='UNITED KI5')
AND D_YEARMONTH = 'Dec1997'
GROUP BY
C_CITY,
S_CITY,
D_YEAR
ORDER BY
D_YEAR ASC,
revenue DESC;
Denormalized table:
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
D_YEAR,
C_NATION,
sum(LO_REVENUE - LO_SUPPLYCOST) AS PROFIT
FROM
date,
customer,
supplier,
part,
lineorder
WHERE
LO_CUSTKEY = C_CUSTKEY
AND LO_SUPPKEY = S_SUPPKEY
AND LO_PARTKEY = P_PARTKEY
AND LO_ORDERDATE = D_DATEKEY
AND C_REGION = 'AMERICA'
AND S_REGION = 'AMERICA'
AND (P_MFGR = 'MFGR#1' OR P_MFGR = 'MFGR#2')
GROUP BY
D_YEAR,
C_NATION
ORDER BY
D_YEAR,
C_NATION
Denormalized table:
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 ASC,
C_NATION ASC;
Q4.2
SELECT
D_YEAR,
S_NATION,
P_CATEGORY,
sum(LO_REVENUE - LO_SUPPLYCOST) AS profit
FROM
date,
customer,
supplier,
part,
lineorder
WHERE
LO_CUSTKEY = C_CUSTKEY
AND LO_SUPPKEY = S_SUPPKEY
AND LO_PARTKEY = P_PARTKEY
AND LO_ORDERDATE = D_DATEKEY
AND C_REGION = 'AMERICA'
AND S_REGION = 'AMERICA'
AND (D_YEAR = 1997 OR D_YEAR = 1998)
AND (P_MFGR = 'MFGR#1' OR P_MFGR = 'MFGR#2')
GROUP BY
D_YEAR,
S_NATION,
P_CATEGORY
ORDER BY
D_YEAR,
S_NATION,
P_CATEGORY
Denormalized table:
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 ASC,
S_NATION ASC,
P_CATEGORY ASC;
Q4.3
SELECT
D_YEAR,
S_CITY,
P_BRAND,
sum(LO_REVENUE - LO_SUPPLYCOST) AS profit
FROM
date,
customer,
supplier,
part,
lineorder
WHERE
LO_CUSTKEY = C_CUSTKEY
AND LO_SUPPKEY = S_SUPPKEY
AND LO_PARTKEY = P_PARTKEY
AND LO_ORDERDATE = D_DATEKEY
AND C_REGION = 'AMERICA'
AND S_NATION = 'UNITED STATES'
AND (D_YEAR = 1997 OR D_YEAR = 1998)
AND P_CATEGORY = 'MFGR#14'
GROUP BY
D_YEAR,
S_CITY,
P_BRAND
ORDER BY
D_YEAR,
S_CITY,
P_BRAND
Denormalized table:
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 ASC,
S_CITY ASC,
P_BRAND ASC;