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Как преобразовать файлы из Parquet в CSV или JSON?

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Преобразование файлов из Parquet в CSV или JSON

Вы можете использовать clickhouse-local для преобразования файлов между любыми входными и выходными форматами, которые поддерживает ClickHouse (а это более 70 различных форматов!). В этой статье мы преобразуем файл Parquet из S3 в CSV- и JSON‑файл.

Начнём с самого начала. В ClickHouse есть набор табличных функций, которые читают данные из файлов, баз данных и других ресурсов и представляют их в виде таблицы. Для примера предположим, что у нас есть файл Parquet в S3. Мы будем использовать табличную функцию s3, чтобы прочитать его (ClickHouse определяет, что это файл Parquet, по имени файла).

Но сначала давайте загрузим бинарный файл clickhouse:

curl https://clickhouse.com/ | sh

Доступ к данным с помощью табличной функции

Давайте убедимся, что файл можно прочитать, выполнив DESCRIBE для результирующей таблицы, которую создаёт табличная функция s3:

./clickhouse local -q "DESCRIBE s3('https://datasets-documentation.s3.eu-west-3.amazonaws.com/house_parquet/house_0.parquet')"

Этот файл содержит цены на жильё объектов недвижимости, проданных в Соединённом Королевстве. Ответ выглядит так:

price	Nullable(Int64)
date	Nullable(UInt16)
postcode1	Nullable(String)
postcode2	Nullable(String)
type	Nullable(String)
is_new	Nullable(UInt8)
duration	Nullable(String)
addr1	Nullable(String)
addr2	Nullable(String)
street	Nullable(String)
locality	Nullable(String)
town	Nullable(String)
district	Nullable(String)
county	Nullable(String)

Вы можете выполнить любой запрос к данным. Например, давайте посмотрим, в каких городах самая высокая средняя цена на жилье:

./clickhouse local -q "SELECT
   town,
   avg(price) AS avg_price
FROM s3('https://datasets-documentation.s3.eu-west-3.amazonaws.com/house_parquet/house_0.parquet')
GROUP BY town
ORDER BY avg_price DESC
LIMIT 10"

Ответ будет выглядеть так:

GATWICK	16818750
CHALFONT ST GILES	938090.0985915493
VIRGINIA WATER	789301.1320224719
COBHAM	699874.7111622555
BEACONSFIELD	677247.5483146068
ESHER	616004.6888297872
KESTON	607585.8597560975
GERRARDS CROSS	566330.2959086584
ASCOT	551491.2975753123
WEYBRIDGE	548974.828692494

Преобразование файла Parquet в CSV

Результат любого SQL-запроса можно записать в файл. Давайте извлечём все столбцы из нашего файла Parquet в S3 и запишем результат в новый CSV-файл. Поскольку имя выходного файла оканчивается на .csv, ClickHouse понимает, что нужно использовать выходной формат CSV:

./clickhouse local -q "SELECT *
FROM s3('https://datasets-documentation.s3.eu-west-3.amazonaws.com/house_parquet/house_0.parquet')
INTO OUTFILE 'house_prices.csv'"

Проверим, что всё сработало:

$ tail house_prices.csv
70000,10508,"YO8","9XN","detached",0,"freehold","7","","POPPY CLOSE","SELBY","SELBY","SELBY","NORTH YORKSHIRE"
130000,14274,"YO8","9XP","detached",0,"freehold","10","","HEATHER CLOSE","","SELBY","SELBY","NORTH YORKSHIRE"
150000,18180,"YO8","9XP","detached",0,"freehold","11","","HEATHER CLOSE","","SELBY","SELBY","NORTH YORKSHIRE"
157000,18088,"YO8","9XP","detached",0,"freehold","12","","HEATHER CLOSE","","SELBY","SELBY","NORTH YORKSHIRE"
134000,17333,"YO8","9XP","semi-detached",0,"freehold","16","","HEATHER CLOSE","","SELBY","SELBY","NORTH YORKSHIRE"
250000,13405,"YO8","9YA","detached",0,"freehold","6","","YORKDALE COURT","HAMBLETON","SELBY","SELBY","NORTH YORKSHIRE"
59500,11166,"YO8","9YB","semi-detached",0,"freehold","4","","YORKDALE DRIVE","HAMBLETON","SELBY","SELBY","NORTH YORKSHIRE"
142500,17648,"YO8","9YB","semi-detached",0,"freehold","4A","","YORKDALE DRIVE","HAMBLETON","SELBY","SELBY","NORTH YORKSHIRE"
230000,15125,"YO8","9YD","detached",0,"freehold","1","","ONE ACRE GARTH","HAMBLETON","SELBY","SELBY","NORTH YORKSHIRE"
250000,15950,"YO8","9YD","detached",0,"freehold","3","","ONE ACRE GARTH","HAMBLETON","SELBY","SELBY","NORTH YORKSHIRE"

Преобразуйте файл Parquet в JSON

Чтобы преобразовать файл Parquet в JSON, просто измените расширение выходного файла:

./clickhouse local -q "SELECT *
FROM s3('https://datasets-documentation.s3.eu-west-3.amazonaws.com/house_parquet/house_0.parquet')
INTO OUTFILE 'house_prices.ndjson'"

Давайте проверим, что всё сработало:

 $ tail house_prices.ndjson
{"price":"70000","date":10508,"postcode1":"YO8","postcode2":"9XN","type":"detached","is_new":0,"duration":"freehold","addr1":"7","addr2":"","street":"POPPY CLOSE","locality":"SELBY","town":"SELBY","district":"SELBY","county":"NORTH YORKSHIRE"}
{"price":"130000","date":14274,"postcode1":"YO8","postcode2":"9XP","type":"detached","is_new":0,"duration":"freehold","addr1":"10","addr2":"","street":"HEATHER CLOSE","locality":"","town":"SELBY","district":"SELBY","county":"NORTH YORKSHIRE"}
{"price":"150000","date":18180,"postcode1":"YO8","postcode2":"9XP","type":"detached","is_new":0,"duration":"freehold","addr1":"11","addr2":"","street":"HEATHER CLOSE","locality":"","town":"SELBY","district":"SELBY","county":"NORTH YORKSHIRE"}
{"price":"157000","date":18088,"postcode1":"YO8","postcode2":"9XP","type":"detached","is_new":0,"duration":"freehold","addr1":"12","addr2":"","street":"HEATHER CLOSE","locality":"","town":"SELBY","district":"SELBY","county":"NORTH YORKSHIRE"}
{"price":"134000","date":17333,"postcode1":"YO8","postcode2":"9XP","type":"semi-detached","is_new":0,"duration":"freehold","addr1":"16","addr2":"","street":"HEATHER CLOSE","locality":"","town":"SELBY","district":"SELBY","county":"NORTH YORKSHIRE"}
{"price":"250000","date":13405,"postcode1":"YO8","postcode2":"9YA","type":"detached","is_new":0,"duration":"freehold","addr1":"6","addr2":"","street":"YORKDALE COURT","locality":"HAMBLETON","town":"SELBY","district":"SELBY","county":"NORTH YORKSHIRE"}
{"price":"59500","date":11166,"postcode1":"YO8","postcode2":"9YB","type":"semi-detached","is_new":0,"duration":"freehold","addr1":"4","addr2":"","street":"YORKDALE DRIVE","locality":"HAMBLETON","town":"SELBY","district":"SELBY","county":"NORTH YORKSHIRE"}
{"price":"142500","date":17648,"postcode1":"YO8","postcode2":"9YB","type":"semi-detached","is_new":0,"duration":"freehold","addr1":"4A","addr2":"","street":"YORKDALE DRIVE","locality":"HAMBLETON","town":"SELBY","district":"SELBY","county":"NORTH YORKSHIRE"}
{"price":"230000","date":15125,"postcode1":"YO8","postcode2":"9YD","type":"detached","is_new":0,"duration":"freehold","addr1":"1","addr2":"","street":"ONE ACRE GARTH","locality":"HAMBLETON","town":"SELBY","district":"SELBY","county":"NORTH YORKSHIRE"}
{"price":"250000","date":15950,"postcode1":"YO8","postcode2":"9YD","type":"detached","is_new":0,"duration":"freehold","addr1":"3","addr2":"","street":"ONE ACRE GARTH","locality":"HAMBLETON","town":"SELBY","district":"SELBY","county":"NORTH YORKSHIRE"}

Преобразование CSV в Parquet

Это работает в обе стороны: мы можем без труда прочитать новый CSV-файл и записать его в файл Parquet. Локальный файл house_prices.csv можно прочитать в ClickHouse с помощью табличной функции file, а ClickHouse запишет файл в формате Parquet на основе расширения имени файла .parquet (или можно было бы добавить предложение FORMAT Parquet):

./clickhouse local -q "SELECT *
FROM file('house_prices.csv')
INTO OUTFILE 'house_prices.parquet'"

Как уже упоминалось выше, вы можете использовать любой из форматов ввода и вывода ClickHouse вместе с clickhouse local, чтобы легко преобразовывать файлы в разные форматы.

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