--- machine_translated: true machine_translated_rev: f865c9653f9df092694258e0ccdd733c339112f5 toc_priority: 20 toc_title: "R\xE9f\xE9rence Du Sch\xE9ma En \xC9toile" --- # Référence Du Schéma En Étoile {#star-schema-benchmark} Compilation de dbgen: ``` bash $ git clone git@github.com:vadimtk/ssb-dbgen.git $ cd ssb-dbgen $ make ``` La production de données: !!! warning "Attention" Avec `-s 100` dbgen génère 600 millions de lignes (67 Go), tandis que while `-s 1000` il génère 6 milliards de lignes (ce qui prend beaucoup de temps) ``` bash $ ./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 ``` Création de tables dans ClickHouse: ``` sql 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; ``` Insertion de données: ``` bash $ 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 ``` Conversion “star schema” pour dénormalisée “flat schema”: ``` sql SET max_memory_usage = 20000000000; CREATE TABLE lineorder_flat ENGINE = MergeTree PARTITION BY toYear(LO_ORDERDATE) 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; ``` Exécution des requêtes: Q1.1 ``` sql 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 ``` sql 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 ``` sql 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 ``` sql 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 ``` sql 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 ``` sql 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 ``` sql 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 ``` sql 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 ``` sql 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 ``` sql 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 ``` sql 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 ``` sql 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 ``` sql 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; ``` [Article Original](https://clickhouse.tech/docs/en/getting_started/example_datasets/star_schema/)