> ## Documentation Index > Fetch the complete documentation index at: https://private-7c7dfe99-fix-nav-issues.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # How do I convert files from Parquet to CSV or JSON? > Learn how to use ClickHouse's `clickhouse-local` tool to easily convert Parquet files to CSV or JSON formats. {frontMatter.description}

Converting Files from Parquet to CSV or JSON

You can use `clickhouse-local` to convert files between any of the [input and output formats](/reference/formats/index) that ClickHouse supports (which is over 70 different formats!). In this article, we are convert a Parquet file in S3 into a CSV and JSON file. Let's start at the beginning. ClickHouse has a collection of [table functions](/reference/functions/table-functions/index) that read from files, databases and other resoures and converts the data to a table. To demonstrate, suppose we have a Parquet file in S3. We will use the `s3` table function to read it (ClickHouse knows it's a Parquet file based on the filename). But first, let's download the `clickhouse` binary: ```bash theme={null} curl https://clickhouse.com/ | sh ```

Accessing the data using a table function

Let's verify we can read the file by using `DESCRIBE` on the resulting table that the `s3` table function creates: ```bash theme={null} ./clickhouse local -q "DESCRIBE s3('https://datasets-documentation.s3.eu-west-3.amazonaws.com/house_parquet/house_0.parquet')" ``` This particular file contains home prices of properties sold in the United Kingdom. The response looks like: ```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) ``` You can run any query you want on the data. For example, let's see which towns have the highest average price of homes: ```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" ``` The response looks like: ```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 ```

Convert the Parquet file to a CSV

You can send the result of any SQL query to a file. Let's grab all the columns from our Parquet file in S3 and send the output to a new CSV file. Because the output file ends in `.csv`, ClickHouse knows to use the `CSV` output format: ```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'" ``` Let's verify it worked: ```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" ```

Convert the Parquet file to a JSON

To convert the Parquet file to JSON, simply change the extension on the output filename: ```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'" ``` Let's verify it worked: ```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"} ```

Convert CSV to Parquet

It works both ways - we can easily read in the new CSV file and output it into a Parquet file. The local file `house_prices.csv` can be read in ClickHouse using the `file` table function, and ClickHouse outputs the file in Parquet format based on the filename ending in `.parquet` (or we could have added the `FORMAT Parquet` clause): ```bash theme={null} ./clickhouse local -q "SELECT * FROM file('house_prices.csv') INTO OUTFILE 'house_prices.parquet'" ``` As we mentioned above, you can use any of the ClickHouse [input and output formats](/reference/formats/index) along with `clickhouse local` to easily convert files into different formats.