> ## Documentation Index
> Fetch the complete documentation index at: https://clickhouse.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# Comment convertir des fichiers Parquet au format CSV ou JSON ?
> Découvrez comment utiliser l’outil `clickhouse-local` de ClickHouse pour convertir facilement des fichiers Parquet au format CSV ou JSON.
{frontMatter.description}
## 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](/docs/fr/reference/formats/index) 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](/docs/fr/reference/functions/table-functions/index) 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` :
```bash theme={null}
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` :
```bash theme={null}
./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 :
```response theme={null}
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 :
```bash theme={null}
./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 :
```bash theme={null}
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` :
```bash theme={null}
./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 :
```response theme={null}
$ 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 :
```bash theme={null}
./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 :
```response theme={null}
$ 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`) :
```bash theme={null}
./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](/docs/fr/reference/formats/index) avec `clickhouse local` pour convertir facilement des fichiers vers différents formats.