Star Schema Benchmark (SSB, 2009)

The Star Schema Benchmark is roughly based on the TPC-H 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 (67 GB) 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;

Running the queries:

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;