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Comment convertir des fichiers Parquet au format CSV ou JSON ?

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Conversion de fichiers Parquet en CSV ou JSON

Vous pouvez utiliser clickhouse-local pour convertir des fichiers entre n’importe lesquels des formats d’entrée et de sortie pris en charge par ClickHouse (soit plus de 70 formats différents !). Dans cet article, nous allons convertir un fichier Parquet dans S3 en fichiers CSV et JSON.

Commençons par le commencement. ClickHouse dispose d’un ensemble de fonctions de table qui lisent des fichiers, des bases de données et d’autres ressources, puis convertissent les données sous forme de table. Pour l’illustrer, supposons que nous ayons un fichier Parquet dans S3. Nous utiliserons la fonction de table s3 pour le lire (ClickHouse sait qu’il s’agit d’un fichier Parquet d’après son nom).

Mais d’abord, téléchargeons le binaire clickhouse :

curl https://clickhouse.com/ | sh

Accéder aux données à l’aide d’une fonction de table

Vérifions que nous pouvons lire le fichier en exécutant DESCRIBE sur la table générée par la fonction de table s3 :

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

Ce fichier contient les prix des biens immobiliers vendus au Royaume-Uni. La réponse ressemble à ceci :

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)

Vous pouvez exécuter n’importe quelle requête sur les données. Par exemple, voyons quelles villes ont le prix moyen des logements le plus élevé :

./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"

La réponse ressemble à ceci :

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

Convertir le fichier Parquet en CSV

Vous pouvez envoyer le résultat de n’importe quelle requête SQL dans un fichier. Récupérons toutes les colonnes de notre fichier Parquet dans S3 et écrivons le résultat dans un nouveau fichier CSV. Comme le fichier de sortie se termine par .csv, ClickHouse sait qu’il doit utiliser le format de sortie 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'"

Vérifions que cela a bien fonctionné :

$ 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"

Convertir le fichier Parquet au format JSON

Pour convertir le fichier Parquet au format JSON, modifiez simplement l’extension du nom du fichier de sortie :

./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'"

Vérifions que cela a bien fonctionné :

 $ 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"}

Convertir un CSV en Parquet

Cela fonctionne dans les deux sens : nous pouvons facilement lire le nouveau fichier CSV et le convertir en fichier Parquet. Le fichier local house_prices.csv peut être lu dans ClickHouse à l’aide de la fonction de table file, et ClickHouse écrit le fichier au format Parquet en se basant sur l’extension .parquet du nom de fichier (ou nous aurions pu ajouter la clause FORMAT Parquet) :

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

Comme nous l’avons vu plus haut, vous pouvez utiliser n’importe lequel des formats d’entrée et de sortie de ClickHouse avec clickhouse local pour convertir facilement des fichiers vers différents formats.

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