> ## Documentation Index
> Fetch the complete documentation index at: https://private-7c7dfe99-detect-table-modification.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.
# ¿Cómo convertir archivos Parquet a CSV o JSON?
> Aprende a usar la herramienta `clickhouse-local` de ClickHouse para convertir fácilmente archivos Parquet a formatos CSV o JSON.
{frontMatter.description}
## Convertir archivos de Parquet a CSV o JSON
Puede usar `clickhouse-local` para convertir archivos entre cualquiera de los [formatos de entrada y salida](/es/reference/formats/index) compatibles con ClickHouse (¡más de 70 formatos distintos!). En este artículo, convertiremos un archivo Parquet en S3 a archivos CSV y JSON.
Empecemos por el principio. ClickHouse tiene un conjunto de [funciones de tabla](/es/reference/functions/table-functions/index) que leen datos de archivos, bases de datos y otros recursos, y los convierten en una tabla. Para demostrarlo, supongamos que tenemos un archivo Parquet en S3. Usaremos la función de tabla `s3` para leerlo (ClickHouse sabe que es un archivo Parquet por el nombre del archivo).
Pero primero, descarguemos el binario `clickhouse`:
```bash theme={null}
curl https://clickhouse.com/ | sh
```
## Acceder a los datos mediante una función de tabla
Verifiquemos que podemos leer el archivo usando `DESCRIBE` sobre la tabla resultante que crea la función de tabla `s3`:
```bash theme={null}
./clickhouse local -q "DESCRIBE s3('https://datasets-documentation.s3.eu-west-3.amazonaws.com/house_parquet/house_0.parquet')"
```
Este archivo en particular contiene los precios de las viviendas vendidas en el Reino Unido. La respuesta tiene este aspecto:
```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)
```
Puedes ejecutar cualquier consulta que quieras sobre los datos. Por ejemplo, veamos qué localidades tienen el precio medio de la vivienda más alto:
```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 respuesta tiene este aspecto:
```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
```
## Convierte el archivo Parquet en un CSV
Puedes enviar el resultado de cualquier consulta SQL a un archivo. Tomemos todas las columnas de nuestro archivo Parquet en S3 y enviemos el resultado a un nuevo archivo CSV. Como el archivo de salida termina en `.csv`, ClickHouse sabe que debe usar el formato de salida `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'"
```
Verifiquemos que haya funcionado:
```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 el archivo Parquet a JSON
Para convertir el archivo Parquet a JSON, basta con cambiar la extensión del nombre del archivo de salida:
```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'"
```
Verifiquemos que haya funcionado:
```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 CSV a Parquet
Funciona en ambos sentidos: podemos leer fácilmente el nuevo archivo CSV y escribirlo como un archivo Parquet. El archivo local `house_prices.csv` puede leerse en ClickHouse mediante la función de tabla `file`, y ClickHouse genera el archivo en formato Parquet según que el nombre del archivo termine en `.parquet` (o podríamos haber añadido la cláusula `FORMAT Parquet`):
```bash theme={null}
./clickhouse local -q "SELECT *
FROM file('house_prices.csv')
INTO OUTFILE 'house_prices.parquet'"
```
Como mencionamos antes, puedes usar cualquiera de los [formatos de entrada y salida](/es/reference/formats/index) de ClickHouse junto con `clickhouse local` para convertir fácilmente archivos a distintos formatos.