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* replace exit with assert in test_single_page * improve save_raw_single_page docs option * More grammar fixes * "Built from" link in new tab * fix mistype * Example of include in docs * add anchor to meeting form * Draft of translation helper * WIP on translation helper * Replace some fa docs content with machine translation * add normalize-en-markdown.sh * normalize some en markdown * normalize some en markdown * admonition support * normalize * normalize * normalize * support wide tables * normalize * normalize * normalize * normalize * normalize * normalize * normalize * normalize * normalize * normalize * normalize * normalize * normalize * lightly edited machine translation of introdpection.md * lightly edited machhine translation of lazy.md * WIP on translation utils * Normalize ru docs * Normalize other languages * some fixes * WIP on normalize/translate tools * add requirements.txt * [experimental] add es docs language as machine translated draft * remove duplicate script * Back to wider tab-stop (narrow renders not so well) * Links to nowhere check at least for English * use f string * More complete es translation
8.4 KiB
8.4 KiB
Estrella Schema Benchmark
Compilación de dbgen:
$ git clone git@github.com:vadimtk/ssb-dbgen.git
$ cd ssb-dbgen
$ make
Generación de datos:
!!! warning "Atención"
Desventaja -s 100
dbgen genera 600 millones de filas (67 GB), mientras que -s 1000
genera 6 mil millones de filas (lo que lleva mucho tiempo)
$ ./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
Creación de tablas en 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;
Inserte datos:
$ 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
Conversión “star schema” a desnormalizado “flat schema”:
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;
Las consultas:
Número de teléfono
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;
¿Qué puedes encontrar en Neodigit
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;
¿Qué puedes encontrar en Neodigit
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;
Preguntas frecuentes
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;
Preguntas frecuentes
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;
Preguntas más frecuentes
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;
¿Qué puedes encontrar en Neodigit
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;
¿Qué puedes encontrar en Neodigit
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;
¿Qué puedes encontrar en Neodigit
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;
¿Qué puedes encontrar en Neodigit
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;
Preguntas más frecuentes
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;
Preguntas más frecuentes
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;
Preguntas más frecuentes
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;