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ApsaraDB for ClickHouse:效能測試指南

更新時間:Jun 30, 2024

本文以On Time和Star Schema資料集為例,介紹如何將測試資料集匯入雲資料庫ClickHouse並完成效能測試。

準備工作

  • 已建立雲資料庫ClickHouse叢集。如何建立,請參見建立叢集

  • 已建立資料庫帳號。如何建立,請參見建立帳號

  • 已準備一台Linux系統的機器,並將Linux機器的IP地址添加到雲資料庫ClickHouse叢集的白名單中。如何添加,請參見設定白名單

  • 已安裝與雲資料庫ClickHouse叢集版本對應的clickhouse-client工具。下載連結,請參見clickhouse-client

測試說明

本測試中的所有clickhouse-client命令均在clickhouse-client用戶端的安裝目錄下執行。

本測試中使用的On Time和Star Schema資料集均引用自ClickHouse開源網站。更多資訊,請參見樣本資料集

On Time資料集測試

1.串連叢集

在Linux環境中使用clickhouse-client工具串連雲資料庫ClickHouse叢集。

./clickhouse-client --host=<資料庫連接地址> --port=<TCP連接埠號碼> --user=<資料庫帳號> --password=<資料庫帳號的密碼>

2. 建表

請根據云資料庫ClickHouse叢集的規格下載正確的建表語句指令碼並執行。

3.下載On Time資料

說明

On Time資料集覆蓋的時間區間非常大,下載資料時間較長,同時資料下載過程中會遇到一部分資料已丟失的錯誤。

echo https://transtats.bts.gov/PREZIP/On_Time_Reporting_Carrier_On_Time_Performance_1987_present_{1987..2021}_{1..12}.zip | xargs -P10 wget --no-check-certificate --continue

4. 匯入資料至雲資料庫ClickHouse

請根據如下Shell命令,正確配置ck_url、ck_user、ck_pass和ck_port環境變數,再進行資料匯入

export ck_url=<資料庫連接地址>
export ck_user=<資料庫帳號> 
export ck_pass=<資料庫帳號的密碼>
export ck_port=<TCP連接埠號碼> 
for i in *.zip; do echo $i; unzip -cq $i '*.csv' | sed 's/\.00//g' | ./clickhouse-client -h $ck_url -u $ck_user --password $ck_pass --port $ck_port --query="INSERT INTO ontime FORMAT CSVWithNames"; done

5. 測試集

說明

測試集引用自ClickHouse開源網站。更多資訊,請參見On Time資料集

Q0

SELECT avg(c1)
FROM
(
    SELECT Year, Month, count(*) AS c1
    FROM ontime
    GROUP BY Year, Month
);

Q1

SELECT DayOfWeek, count(*) AS c
FROM ontime
WHERE Year>=2000 AND Year<=2008
GROUP BY DayOfWeek
ORDER BY c DESC;

Q2

SELECT DayOfWeek, count(*) AS c
FROM ontime
WHERE DepDelay>10 AND Year>=2000 AND Year<=2008
GROUP BY DayOfWeek
ORDER BY c DESC;

Q3

SELECT Origin, count(*) AS c
FROM ontime
WHERE DepDelay>10 AND Year>=2000 AND Year<=2008
GROUP BY Origin
ORDER BY c DESC
LIMIT 10;

Q4

SELECT Carrier, count(*)
FROM ontime
WHERE DepDelay>10 AND Year=2007
GROUP BY Carrier
ORDER BY count(*) DESC;

Q5

set joined_subquery_requires_alias=0;
set any_join_distinct_right_table_keys=1;
SELECT Carrier, c, c2, c*100/c2 as c3
FROM
(
   SELECT
       Carrier,
       count(*) AS c
   FROM ontime
   WHERE DepDelay>10
       AND Year=2007
   GROUP BY Carrier
)
ANY INNER JOIN
(
   SELECT
       Carrier,
       count(*) AS c2
   FROM ontime
   WHERE Year=2007
   GROUP BY Carrier
) USING Carrier
ORDER BY c3 DESC;

Q6

set joined_subquery_requires_alias=0;
SELECT Carrier, c, c2, c*100/c2 as c3
FROM
(
   SELECT
       Carrier,
       count(*) AS c
   FROM ontime
   WHERE DepDelay>10
       AND Year>=2000 AND Year<=2008
   GROUP BY Carrier
)
ANY INNER JOIN
(
   SELECT
       Carrier,
       count(*) AS c2
   FROM ontime
   WHERE Year>=2000 AND Year<=2008
   GROUP BY Carrier
) USING Carrier
ORDER BY c3 DESC;

Q7

set joined_subquery_requires_alias=0;
SELECT Year, c1/c2
FROM
(
   select
       Year,
       count(*)*100 as c1
   from ontime
   WHERE DepDelay>10
   GROUP BY Year
)
ANY INNER JOIN
(
   select
       Year,
       count(*) as c2
   from ontime
   GROUP BY Year
) USING (Year)
ORDER BY Year;

Q8

SELECT DestCityName, uniqExact(OriginCityName) AS u
FROM ontime
WHERE Year>=2000 and Year<=2010
GROUP BY DestCityName
ORDER BY u DESC
LIMIT 10;

Q9

SELECT Year, count(*) AS c1
FROM ontime
GROUP BY Year;

Q10

SELECT
  min(Year), max(Year), Carrier, count(*) AS cnt,
  sum(ArrDelayMinutes>30) AS flights_delayed,
  round(sum(ArrDelayMinutes>30)/count(*),2) AS rate
FROM ontime
WHERE
  DayOfWeek NOT IN (6,7) AND OriginState NOT IN ('AK', 'HI', 'PR', 'VI')
  AND DestState NOT IN ('AK', 'HI', 'PR', 'VI')
  AND FlightDate < '2010-01-01'
GROUP by Carrier
HAVING cnt>100000 and max(Year)>1990
ORDER by rate DESC
LIMIT 1000;

Star Schema資料集測試

1.串連叢集

在Linux環境中使用clickhouse-client工具串連雲資料庫ClickHouse叢集。

./clickhouse-client --host=<資料庫連接地址> --port=<TCP連接埠號碼> --user=<資料庫帳號> --password=<資料庫帳號的密碼>

2. 建表

請根據云資料庫ClickHouse叢集的規格下載正確的建表語句指令碼並執行。

3. 產生資料檔案

請根據如下Shell命令,首先複製資料產生專案ssb-dbgen,然後通過make編譯,用命令產生資料檔案customer.tbl、lineorder.tbl、part.tbl和supplier.tbl。

說明

樣本中-s 100參數會產生大概6億行的資料(67 GB),您可以根據情況適當調整測試資料量。

git clone https://github.com/vadimtk/ssb-dbgen.git
cd ssb-dbgen
make
./dbgen -s 100 -T c
./dbgen -s 100 -T l
./dbgen -s 100 -T p
./dbgen -s 100 -T s

4. 匯入資料至雲資料庫ClickHouse

請根據如下Shell命令,正確配置ck_url、ck_user、ck_pass和ck_port環境變數,再進行資料匯入

export ck_url=<資料庫連接地址>
export ck_user=<資料庫帳號>
export ck_pass=<資料庫帳號的密碼>
export ck_port=<TCP連接埠號碼> 
./clickhouse-client -h <資料庫連接地址> -u <資料庫帳號> --password <資料庫帳號的密碼> --port <TCP連接埠號碼> --query "INSERT INTO customer FORMAT CSV" < ssb-dbgen/customer.tbl
./clickhouse-client -h <資料庫連接地址> -u <資料庫帳號> --password <資料庫帳號的密碼> --port <TCP連接埠號碼> --query "INSERT INTO part FORMAT CSV" < ssb-dbgen/part.tbl
./clickhouse-client -h <資料庫連接地址> -u <資料庫帳號> --password <資料庫帳號的密碼> --port <TCP連接埠號碼> --query "INSERT INTO supplier FORMAT CSV" < ssb-dbgen/supplier.tbl
./clickhouse-client -h <資料庫連接地址> -u <資料庫帳號> --password <資料庫帳號的密碼> --port <TCP連接埠號碼> --query "INSERT INTO lineorder FORMAT CSV" < ssb-dbgen/lineorder.tbl

5. 測試集

說明

測試集引用自ClickHouse開源網站。更多資訊,請參見Star Schema資料集

Q0

INSERT INTO lineorder_flat
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;

Q1

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;

Q2

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;

Q3

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;

Q4

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;

Q5

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;

Q6

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;

Q7

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;

Q8

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;

Q9

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;

Q10

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;

Q11

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;

Q12

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;

Q13

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;