mirror of
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372 lines
8.1 KiB
Markdown
372 lines
8.1 KiB
Markdown
---
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sidebar_label: Star Schema Benchmark
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description: "Dataset based on the TPC-H dbgen source. The coding style and architecture
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follows the TPCH dbgen."
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---
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# Star Schema Benchmark
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Compiling dbgen:
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``` bash
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$ git clone git@github.com:vadimtk/ssb-dbgen.git
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$ cd ssb-dbgen
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$ make
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```
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Generating data:
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:::warning
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With `-s 100` dbgen generates 600 million rows (67 GB), while while `-s 1000` it generates 6 billion rows (which takes a lot of time)
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:::
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``` bash
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$ ./dbgen -s 1000 -T c
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$ ./dbgen -s 1000 -T l
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$ ./dbgen -s 1000 -T p
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$ ./dbgen -s 1000 -T s
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$ ./dbgen -s 1000 -T d
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```
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Creating tables in ClickHouse:
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``` sql
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CREATE TABLE customer
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(
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C_CUSTKEY UInt32,
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C_NAME String,
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C_ADDRESS String,
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C_CITY LowCardinality(String),
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C_NATION LowCardinality(String),
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C_REGION LowCardinality(String),
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C_PHONE String,
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C_MKTSEGMENT LowCardinality(String)
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)
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ENGINE = MergeTree ORDER BY (C_CUSTKEY);
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CREATE TABLE lineorder
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(
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LO_ORDERKEY UInt32,
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LO_LINENUMBER UInt8,
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LO_CUSTKEY UInt32,
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LO_PARTKEY UInt32,
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LO_SUPPKEY UInt32,
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LO_ORDERDATE Date,
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LO_ORDERPRIORITY LowCardinality(String),
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LO_SHIPPRIORITY UInt8,
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LO_QUANTITY UInt8,
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LO_EXTENDEDPRICE UInt32,
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LO_ORDTOTALPRICE UInt32,
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LO_DISCOUNT UInt8,
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LO_REVENUE UInt32,
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LO_SUPPLYCOST UInt32,
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LO_TAX UInt8,
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LO_COMMITDATE Date,
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LO_SHIPMODE LowCardinality(String)
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)
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ENGINE = MergeTree PARTITION BY toYear(LO_ORDERDATE) ORDER BY (LO_ORDERDATE, LO_ORDERKEY);
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CREATE TABLE part
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(
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P_PARTKEY UInt32,
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P_NAME String,
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P_MFGR LowCardinality(String),
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P_CATEGORY LowCardinality(String),
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P_BRAND LowCardinality(String),
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P_COLOR LowCardinality(String),
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P_TYPE LowCardinality(String),
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P_SIZE UInt8,
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P_CONTAINER LowCardinality(String)
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)
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ENGINE = MergeTree ORDER BY P_PARTKEY;
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CREATE TABLE supplier
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(
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S_SUPPKEY UInt32,
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S_NAME String,
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S_ADDRESS String,
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S_CITY LowCardinality(String),
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S_NATION LowCardinality(String),
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S_REGION LowCardinality(String),
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S_PHONE String
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)
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ENGINE = MergeTree ORDER BY S_SUPPKEY;
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```
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Inserting data:
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``` bash
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$ clickhouse-client --query "INSERT INTO customer FORMAT CSV" < customer.tbl
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$ clickhouse-client --query "INSERT INTO part FORMAT CSV" < part.tbl
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$ clickhouse-client --query "INSERT INTO supplier FORMAT CSV" < supplier.tbl
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$ clickhouse-client --query "INSERT INTO lineorder FORMAT CSV" < lineorder.tbl
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```
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Converting “star schema” to denormalized “flat schema”:
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``` sql
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SET max_memory_usage = 20000000000;
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CREATE TABLE lineorder_flat
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ENGINE = MergeTree
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PARTITION BY toYear(LO_ORDERDATE)
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ORDER BY (LO_ORDERDATE, LO_ORDERKEY) AS
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SELECT
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l.LO_ORDERKEY AS LO_ORDERKEY,
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l.LO_LINENUMBER AS LO_LINENUMBER,
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l.LO_CUSTKEY AS LO_CUSTKEY,
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l.LO_PARTKEY AS LO_PARTKEY,
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l.LO_SUPPKEY AS LO_SUPPKEY,
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l.LO_ORDERDATE AS LO_ORDERDATE,
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l.LO_ORDERPRIORITY AS LO_ORDERPRIORITY,
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l.LO_SHIPPRIORITY AS LO_SHIPPRIORITY,
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l.LO_QUANTITY AS LO_QUANTITY,
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l.LO_EXTENDEDPRICE AS LO_EXTENDEDPRICE,
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l.LO_ORDTOTALPRICE AS LO_ORDTOTALPRICE,
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l.LO_DISCOUNT AS LO_DISCOUNT,
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l.LO_REVENUE AS LO_REVENUE,
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l.LO_SUPPLYCOST AS LO_SUPPLYCOST,
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l.LO_TAX AS LO_TAX,
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l.LO_COMMITDATE AS LO_COMMITDATE,
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l.LO_SHIPMODE AS LO_SHIPMODE,
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c.C_NAME AS C_NAME,
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c.C_ADDRESS AS C_ADDRESS,
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c.C_CITY AS C_CITY,
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c.C_NATION AS C_NATION,
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c.C_REGION AS C_REGION,
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c.C_PHONE AS C_PHONE,
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c.C_MKTSEGMENT AS C_MKTSEGMENT,
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s.S_NAME AS S_NAME,
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s.S_ADDRESS AS S_ADDRESS,
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s.S_CITY AS S_CITY,
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s.S_NATION AS S_NATION,
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s.S_REGION AS S_REGION,
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s.S_PHONE AS S_PHONE,
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p.P_NAME AS P_NAME,
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p.P_MFGR AS P_MFGR,
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p.P_CATEGORY AS P_CATEGORY,
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p.P_BRAND AS P_BRAND,
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p.P_COLOR AS P_COLOR,
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p.P_TYPE AS P_TYPE,
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p.P_SIZE AS P_SIZE,
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p.P_CONTAINER AS P_CONTAINER
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FROM lineorder AS l
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INNER JOIN customer AS c ON c.C_CUSTKEY = l.LO_CUSTKEY
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INNER JOIN supplier AS s ON s.S_SUPPKEY = l.LO_SUPPKEY
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INNER JOIN part AS p ON p.P_PARTKEY = l.LO_PARTKEY;
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```
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Running the queries:
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Q1.1
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``` sql
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SELECT sum(LO_EXTENDEDPRICE * LO_DISCOUNT) AS revenue
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FROM lineorder_flat
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WHERE toYear(LO_ORDERDATE) = 1993 AND LO_DISCOUNT BETWEEN 1 AND 3 AND LO_QUANTITY < 25;
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```
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Q1.2
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``` sql
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SELECT sum(LO_EXTENDEDPRICE * LO_DISCOUNT) AS revenue
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FROM lineorder_flat
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WHERE toYYYYMM(LO_ORDERDATE) = 199401 AND LO_DISCOUNT BETWEEN 4 AND 6 AND LO_QUANTITY BETWEEN 26 AND 35;
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```
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Q1.3
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``` sql
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SELECT sum(LO_EXTENDEDPRICE * LO_DISCOUNT) AS revenue
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FROM lineorder_flat
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WHERE toISOWeek(LO_ORDERDATE) = 6 AND toYear(LO_ORDERDATE) = 1994
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AND LO_DISCOUNT BETWEEN 5 AND 7 AND LO_QUANTITY BETWEEN 26 AND 35;
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```
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Q2.1
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``` sql
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SELECT
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sum(LO_REVENUE),
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toYear(LO_ORDERDATE) AS year,
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P_BRAND
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FROM lineorder_flat
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WHERE P_CATEGORY = 'MFGR#12' AND S_REGION = 'AMERICA'
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GROUP BY
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year,
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P_BRAND
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ORDER BY
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year,
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P_BRAND;
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```
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Q2.2
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``` sql
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SELECT
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sum(LO_REVENUE),
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toYear(LO_ORDERDATE) AS year,
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P_BRAND
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FROM lineorder_flat
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WHERE P_BRAND >= 'MFGR#2221' AND P_BRAND <= 'MFGR#2228' AND S_REGION = 'ASIA'
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GROUP BY
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year,
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P_BRAND
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ORDER BY
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year,
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P_BRAND;
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```
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Q2.3
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``` sql
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SELECT
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sum(LO_REVENUE),
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toYear(LO_ORDERDATE) AS year,
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P_BRAND
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FROM lineorder_flat
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WHERE P_BRAND = 'MFGR#2239' AND S_REGION = 'EUROPE'
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GROUP BY
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year,
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P_BRAND
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ORDER BY
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year,
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P_BRAND;
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```
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Q3.1
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``` sql
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SELECT
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C_NATION,
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S_NATION,
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toYear(LO_ORDERDATE) AS year,
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sum(LO_REVENUE) AS revenue
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FROM lineorder_flat
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WHERE C_REGION = 'ASIA' AND S_REGION = 'ASIA' AND year >= 1992 AND year <= 1997
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GROUP BY
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C_NATION,
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S_NATION,
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year
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ORDER BY
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year ASC,
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revenue DESC;
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```
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Q3.2
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``` sql
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SELECT
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C_CITY,
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S_CITY,
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toYear(LO_ORDERDATE) AS year,
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sum(LO_REVENUE) AS revenue
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FROM lineorder_flat
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WHERE C_NATION = 'UNITED STATES' AND S_NATION = 'UNITED STATES' AND year >= 1992 AND year <= 1997
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GROUP BY
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C_CITY,
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S_CITY,
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year
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ORDER BY
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year ASC,
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revenue DESC;
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```
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Q3.3
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``` sql
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SELECT
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C_CITY,
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S_CITY,
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toYear(LO_ORDERDATE) AS year,
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sum(LO_REVENUE) AS revenue
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FROM lineorder_flat
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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
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GROUP BY
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C_CITY,
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S_CITY,
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year
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ORDER BY
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year ASC,
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revenue DESC;
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```
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Q3.4
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``` sql
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SELECT
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C_CITY,
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S_CITY,
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toYear(LO_ORDERDATE) AS year,
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sum(LO_REVENUE) AS revenue
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FROM lineorder_flat
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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
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GROUP BY
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C_CITY,
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S_CITY,
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year
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ORDER BY
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year ASC,
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revenue DESC;
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```
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Q4.1
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``` sql
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SELECT
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toYear(LO_ORDERDATE) AS year,
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C_NATION,
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sum(LO_REVENUE - LO_SUPPLYCOST) AS profit
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FROM lineorder_flat
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WHERE C_REGION = 'AMERICA' AND S_REGION = 'AMERICA' AND (P_MFGR = 'MFGR#1' OR P_MFGR = 'MFGR#2')
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GROUP BY
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year,
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C_NATION
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ORDER BY
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year ASC,
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C_NATION ASC;
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```
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Q4.2
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``` sql
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SELECT
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toYear(LO_ORDERDATE) AS year,
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S_NATION,
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P_CATEGORY,
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sum(LO_REVENUE - LO_SUPPLYCOST) AS profit
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FROM lineorder_flat
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WHERE C_REGION = 'AMERICA' AND S_REGION = 'AMERICA' AND (year = 1997 OR year = 1998) AND (P_MFGR = 'MFGR#1' OR P_MFGR = 'MFGR#2')
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GROUP BY
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year,
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S_NATION,
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P_CATEGORY
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ORDER BY
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year ASC,
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S_NATION ASC,
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P_CATEGORY ASC;
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```
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Q4.3
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``` sql
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SELECT
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toYear(LO_ORDERDATE) AS year,
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S_CITY,
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P_BRAND,
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sum(LO_REVENUE - LO_SUPPLYCOST) AS profit
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FROM lineorder_flat
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WHERE S_NATION = 'UNITED STATES' AND (year = 1997 OR year = 1998) AND P_CATEGORY = 'MFGR#14'
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GROUP BY
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year,
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S_CITY,
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P_BRAND
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ORDER BY
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year ASC,
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S_CITY ASC,
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P_BRAND ASC;
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```
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[Original article](https://clickhouse.com/docs/en/getting_started/example_datasets/star_schema/) <!--hide-->
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