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Star Schema Benchmark

Star Schema Benchmark

Star Schema Benchmark(SSB) is a lightweight performance test set in the data warehouse scenario. SSB provides a simplified star schema data based on TPC-H, which is mainly used to test the performance of multi-table JOIN query under star schema. In addition, the industry usually flattens SSB into a wide table model (Referred as: SSB flat) to test the performance of the query engine, refer to Clickhouse.

This document mainly introduces the performance of Doris on the SSB 1000G test set.

We tested 13 queries on the SSB standard test dataset based on Apache Doris version 2.0.6.

1. Hardware Environment​

HardwareConfiguration Instructions
Number of mMachines4 Tencent Cloud Virtual Machine(1FE,3BEs)
CPUAMD EPYC™ Milan(2.55GHz/3.5GHz) 48C
Memory192G
Network21Gbps
DiskESSD Cloud Hard Disk

2. Software Environment​

  • Doris Deployed 3BEs and 1FE
  • Kernel Version: Linux version 5.4.0-96-generic (buildd@lgw01-amd64-051)
  • OS version: Ubuntu 20.04 LTS (Focal Fossa)
  • Doris software version: Apache Doris 2.0.6.
  • JDK: openjdk version "1.8.0_131"

3. Test Data Volume​

SSB Table NameRowsAnnotation
lineorder5,999,989,709Commodity Order Details
customer30,000,000Customer Information
part2,000,000Parts Information
supplier2,000,000Supplier Information
dates2,556Date
lineorder_flat5,999,989,709Wide Table after Data Flattening

4. SSB Flat Test Results​

Here we use Apache Doris 2.0.6 for comparative testing. In the test, we use Query Time(ms) as the main performance indicator. The test results are as follows:

QueryDoris 2.0.6 (ms)
q1.186
q1.231
q1.387
q2.11046
q2.2569
q2.3480
q3.11339
q3.2957
q3.3215
q3.434
q4.11569
q4.2174
q4.3109
Total6696

5. Standard SSB Test Results​

Here we use Apache Doris 2.0.6 for comparative testing. In the test, we use Query Time(ms) as the main performance indicator. The test results are as follows:

QueryDoris 2.0.6 (ms)
q1.1332
q1.286
q1.380
q2.1985
q2.2844
q2.3768
q3.12924
q3.2944
q3.3766
q3.4146
q4.13451
q4.2829
q4.3325
Total12480

6. Environment Preparation​

Please first refer to the [official documentation](. /install/install-deploy.md) to install and deploy Apache Doris first to obtain a Doris cluster which is working well(including at least 1 FE 1 BE, 1 FE 3 BEs is recommended).

7. Data Preparation​

7.1 Download and Install the SSB Data Generation Tool.​

Execute the following script to download and compile the ssb-tools tool.

sh bin/build-ssb-dbgen.sh

After successful installation, the dbgen binary will be generated under the ssb-dbgen/ directory.

7.2 Generate SSB Test Set​

Execute the following script to generate the SSB dataset:

sh bin/gen-ssb-data.sh -s 1000

Note 1: Check the script help via sh gen-ssb-data.sh -h.

Note 2: The data will be generated under the ssb-data/ directory with the suffix .tbl. The total file size is about 600GB and may need a few minutes to an hour to generate.

Note 3: A standard test data set of 100G is generated by default.

7.3 Create Table​

7.3.1 Prepare the doris-cluster.conf File.​

Before import the script, you need to write the FE’s ip port and other information in the doris-cluster.conf file.

The file is located under ${DORIS_HOME}/tools/ssb-tools/conf/.

The content of the file includes FE's ip, HTTP port, user name, password and the DB name of the data to be imported:

# Any of FE host
export FE_HOST='127.0.0.1'
# http_port in fe.conf
export FE_HTTP_PORT=8030
# query_port in fe.conf
export FE_QUERY_PORT=9030
# Doris username
export USER='root'
# Doris password
export PASSWORD=''
# The database where SSB tables located
export DB='ssb'

7.3.2 Execute the Following Script to Generate and Create the SSB Table:​

sh bin/create-ssb-tables.sh -s 1000

Or copy the table creation statements in create-ssb-tables.sql and create-ssb-flat-table.sql and then execute them in the MySQL client.

7.4 Import data​

We use the following command to complete all data import of SSB test set and SSB FLAT wide table data synthesis and then import into the table.

 sh bin/load-ssb-data.sh

7.5 Checking Imported data​

select count(*) from part;
select count(*) from customer;
select count(*) from supplier;
select count(*) from dates;
select count(*) from lineorder;
select count(*) from lineorder_flat;

7.6 Query Test​

7.6.1 SSB FLAT Test for SQL​

--Q1.1
SELECT SUM(LO_EXTENDEDPRICE * LO_DISCOUNT) AS revenue
FROM lineorder_flat
WHERE
LO_ORDERDATE >= 19930101
AND LO_ORDERDATE <= 19931231
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
LO_ORDERDATE >= 19940101
AND LO_ORDERDATE <= 19940131
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
weekofyear(LO_ORDERDATE) = 6
AND LO_ORDERDATE >= 19940101
AND LO_ORDERDATE <= 19941231
AND LO_DISCOUNT BETWEEN 5 AND 7
AND LO_QUANTITY BETWEEN 26 AND 35;

--Q2.1
SELECT
SUM(LO_REVENUE), (LO_ORDERDATE DIV 10000) 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), (LO_ORDERDATE DIV 10000) 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), (LO_ORDERDATE DIV 10000) 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, (LO_ORDERDATE DIV 10000) AS YEAR,
SUM(LO_REVENUE) AS revenue
FROM lineorder_flat
WHERE
C_REGION = 'ASIA'
AND S_REGION = 'ASIA'
AND LO_ORDERDATE >= 19920101
AND LO_ORDERDATE <= 19971231
GROUP BY C_NATION, S_NATION, YEAR
ORDER BY YEAR ASC, revenue DESC;

--Q3.2
SELECT
C_CITY,
S_CITY, (LO_ORDERDATE DIV 10000) AS YEAR,
SUM(LO_REVENUE) AS revenue
FROM lineorder_flat
WHERE
C_NATION = 'UNITED STATES'
AND S_NATION = 'UNITED STATES'
AND LO_ORDERDATE >= 19920101
AND LO_ORDERDATE <= 19971231
GROUP BY C_CITY, S_CITY, YEAR
ORDER BY YEAR ASC, revenue DESC;

--Q3.3
SELECT
C_CITY,
S_CITY, (LO_ORDERDATE DIV 10000) AS YEAR,
SUM(LO_REVENUE) AS revenue
FROM lineorder_flat
WHERE
C_CITY IN ('UNITED KI1', 'UNITED KI5')
AND S_CITY IN ('UNITED KI1', 'UNITED KI5')
AND LO_ORDERDATE >= 19920101
AND LO_ORDERDATE <= 19971231
GROUP BY C_CITY, S_CITY, YEAR
ORDER BY YEAR ASC, revenue DESC;

--Q3.4
SELECT
C_CITY,
S_CITY, (LO_ORDERDATE DIV 10000) AS YEAR,
SUM(LO_REVENUE) AS revenue
FROM lineorder_flat
WHERE
C_CITY IN ('UNITED KI1', 'UNITED KI5')
AND S_CITY IN ('UNITED KI1', 'UNITED KI5')
AND LO_ORDERDATE >= 19971201
AND LO_ORDERDATE <= 19971231
GROUP BY C_CITY, S_CITY, YEAR
ORDER BY YEAR ASC, revenue DESC;

--Q4.1
SELECT (LO_ORDERDATE DIV 10000) 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 IN ('MFGR#1', 'MFGR#2')
GROUP BY YEAR, C_NATION
ORDER BY YEAR ASC, C_NATION ASC;

--Q4.2
SELECT (LO_ORDERDATE DIV 10000) 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 LO_ORDERDATE >= 19970101
AND LO_ORDERDATE <= 19981231
AND P_MFGR IN ('MFGR#1', 'MFGR#2')
GROUP BY YEAR, S_NATION, P_CATEGORY
ORDER BY
YEAR ASC,
S_NATION ASC,
P_CATEGORY ASC;

--Q4.3
SELECT (LO_ORDERDATE DIV 10000) AS YEAR,
S_CITY,
P_BRAND,
SUM(LO_REVENUE - LO_SUPPLYCOST) AS profit
FROM lineorder_flat
WHERE
S_NATION = 'UNITED STATES'
AND LO_ORDERDATE >= 19970101
AND LO_ORDERDATE <= 19981231
AND P_CATEGORY = 'MFGR#14'
GROUP BY YEAR, S_CITY, P_BRAND
ORDER BY YEAR ASC, S_CITY ASC, P_BRAND ASC;

7.6.2 SSB Standard Test for SQL​

--Q1.1
SELECT SUM(lo_extendedprice * lo_discount) AS REVENUE
FROM lineorder, dates
WHERE
lo_orderdate = d_datekey
AND d_year = 1993
AND lo_discount BETWEEN 1 AND 3
AND lo_quantity < 25;

--Q1.2
SELECT SUM(lo_extendedprice * lo_discount) AS REVENUE
FROM lineorder, dates
WHERE
lo_orderdate = d_datekey
AND d_yearmonth = 'Jan1994'
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, dates
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;

--Q2.1
SELECT SUM(lo_revenue), d_year, p_brand
FROM lineorder, dates, 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 p_brand;

--Q2.2
SELECT SUM(lo_revenue), d_year, p_brand
FROM lineorder, dates, 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;

--Q2.3
SELECT SUM(lo_revenue), d_year, p_brand
FROM lineorder, dates, part, supplier
WHERE
lo_orderdate = d_datekey
AND lo_partkey = p_partkey
AND lo_suppkey = s_suppkey
AND p_brand = 'MFGR#2239'
AND s_region = 'EUROPE'
GROUP BY d_year, p_brand
ORDER BY d_year, p_brand;

--Q3.1
SELECT
c_nation,
s_nation,
d_year,
SUM(lo_revenue) AS REVENUE
FROM customer, lineorder, supplier, dates
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;

--Q3.2
SELECT
c_city,
s_city,
d_year,
SUM(lo_revenue) AS REVENUE
FROM customer, lineorder, supplier, dates
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;

--Q3.3
SELECT
c_city,
s_city,
d_year,
SUM(lo_revenue) AS REVENUE
FROM customer, lineorder, supplier, dates
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;

--Q3.4
SELECT
c_city,
s_city,
d_year,
SUM(lo_revenue) AS REVENUE
FROM customer, lineorder, supplier, dates
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;

--Q4.1
SELECT
d_year,
c_nation,
SUM(lo_revenue - lo_supplycost) AS PROFIT
FROM dates, 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;

--Q4.2
SELECT
d_year,
s_nation,
p_category,
SUM(lo_revenue - lo_supplycost) AS PROFIT
FROM dates, 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;

--Q4.3
SELECT
d_year,
s_city,
p_brand,
SUM(lo_revenue - lo_supplycost) AS PROFIT
FROM dates, 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 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;