Free Online JSON to Parquet Converter - No Installation Required

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How to convert JSON to Parquet

Upload all of the JSON files you want to convert
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Download your converted Parquet files
Process hundreds of files in a single batch
Our converter handles large batches efficiently, saving you time compared to converting files one by one.

Converter Features

Fast conversion

Convert your json files to parquet in seconds, even with large datasets

Batch processing

Upload and convert hundreds of files at once with no file size limitations

Downloadable results

Get all your converted files immediately after conversion

Data integrity

Preserve your data structure and types during conversion with high-fidelity transformations

Format optimization

Automatically optimize output files for size and performance based on the target format

No code required

Convert files without writing a single line of code, perfect for data analysts and business users

How Tab Lab Converts JSON to Tabular Data

Tab Lab converts JSON data into tabular format for easier analysis. Here's how different JSON structures are transformed:

Simple Objects

Basic JSON objects are converted to single-row tables:

JSON Input:

json

{
  "name": "John Smith",
  "age": 30,
  "isStudent": false,
  "gpa": 3.8
}

Table Output:

name	age	isStudent	gpa
John Smith	30	false	3.8

Nested Objects

Nested objects are flattened with dot notation:

JSON Input:

json

{
  "person": {
    "name": "Alice Johnson",
    "contact": {
      "email": "alice@example.com",
      "phone": "123-456-7890"
    }
  }
}

Table Output:

person.name	person.contact.email	person.contact.phone
Alice Johnson	alice@example.com	123-456-7890

Arrays of Objects

Arrays of objects become multiple rows:

JSON Input:

json

{
  "users": [
    {"id": 1, "name": "John", "role": "admin"},
    {"id": 2, "name": "Jane", "role": "user"}
  ]
}

Table Output:

users.id	users.name	users.role
1	John	admin
2	Jane	user

Mixed Types

Different data types are preserved in the conversion:

JSON Input:

json

{
  "string": "Hello World",
  "number": 42,
  "float": 3.14,
  "boolean": true,
  "null": null,
  "array": [1, 2, 3],
  "object": {"key": "value"}
}

Table Output:

string	number	float	boolean	null	array	object.key
Hello World	42	3.14	true	null	[1, 2, 3]	value

How to convert JSON to Parquet in Python

We can convert JSON to Parquet in Python using Pandas, DuckDB, or ClickHouse

How to Convert JSON to Parquet using Pandas

First, we need to install pandas

pip install pandas

Then we can load the json file into a dataframe

df = pd.read_json('path/to/file.json')

Finally, we can export the dataframe to the parquet format

df.to_parquet('path/to/file.parquet', index=False)

How to Convert JSON to Parquet using DuckDB

First, we need to install duckdb for Python

pip install duckdb

The following DuckDB query will read a json file and output a parquet file

duckdb.sql("""COPY (select * from 'path/to/file.json') TO 'path/to/file.parquet' (FORMAT 'parquet')""")

How to Convert JSON to Parquet using ClickHouse

First, we need to install the ClickHouse client for Python

pip install clickhouse-connect

Then we can use ClickHouse to convert from JSON to Parquet

Start by importing the necessary libraries and connecting to ClickHouse:

import clickhouse_connect
import os
# Connect to ClickHouse
client = clickhouse_connect.get_client(host='localhost', port=8123)

Define your input and output file paths:

# Define input and output file paths
input_file = 'path/to/input.json'
output_file = 'path/to/output.parquet'

Now perform the direct conversion from JSON to Parquet:

# Direct conversion from json to parquet
client.command(f'''
INSERT INTO FUNCTION file('{output_file}', 'parquet')
SELECT *
FROM file('{input_file}', 'json')
''')

Confirm the conversion was successful:

print(f'Successfully converted {input_file} to {output_file}')

For more complex conversions or when you need to transform the data during conversion, you can use a table:

First, create a table from the input file:

# Create a table from the input file
client.command(f'''
CREATE TABLE IF NOT EXISTS conversion_data AS
SELECT * FROM file('{input_file}', 'json')
''')

Then, perform any transformations and export to the destination format:

# Now you can perform transformations if needed
client.command(f'''
INSERT INTO FUNCTION file('{output_file}', 'parquet')
SELECT * FROM conversion_data
# Add WHERE, GROUP BY, or other clauses as needed
''')

Finally, clean up by dropping the temporary table:

# Clean up
client.command('DROP TABLE IF EXISTS conversion_data')
print(f'Successfully converted {input_file} to {output_file}')