https://github.com/ayushverma135/json-to-parquet-parser

Easily convert JSON data into Parquet format for efficient storage and analysis. Simplify data processing and analysis pipelines by converting JSON objects into optimized Parquet files.
https://github.com/ayushverma135/json-to-parquet-parser

json pandas parquet-files python

Last synced: 2 days ago
JSON representation

Easily convert JSON data into Parquet format for efficient storage and analysis. Simplify data processing and analysis pipelines by converting JSON objects into optimized Parquet files.

• Host: GitHub
• URL: https://github.com/ayushverma135/json-to-parquet-parser
• Owner: Ayushverma135
• License: mit
• Created: 2024-05-11T13:02:09.000Z (8 months ago)
• Default Branch: main
• Last Pushed: 2024-05-11T13:12:52.000Z (8 months ago)
• Last Synced: 2024-11-08T13:25:34.938Z (about 2 months ago)
• Topics: json, pandas, parquet-files, python
• Language: Python
• Homepage:
• Size: 8.79 KB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# JSON to Parquet Parser

## Overview

The JSON to Parquet Parser is a Python script designed to streamline the conversion of JSON data into Parquet format. Parquet is a columnar storage format optimized for big data analytics, making it ideal for storing and processing large volumes of structured data efficiently.

## Difference Between Json And Parquet file

JSON (JavaScript Object Notation) and Parquet are both file formats used for storing and exchanging data, but they have different characteristics and are suited for different use cases.

### JSON (JavaScript Object Notation):

- JSON is a human-readable text format for storing and exchanging data.

- It is widely used for data interchange between systems, especially in web applications.

- JSON is easy for humans to read and write, and it is also easy for machines to parse and generate.

- JSON supports a hierarchical structure of data (nested objects and arrays).

- It is not optimized for storage efficiency or query performance, especially for large datasets.

### Parquet:

- Parquet is a columnar storage format optimized for storing and processing large datasets.

- It is well-suited for analytics workloads, especially in Big Data processing frameworks like Apache Spark and Apache Hive.

- Parquet stores data in a compressed, columnar format, which reduces storage space and improves query performance by allowing column-wise operations.

- Parquet files are typically binary files, which are more efficient for storage and processing compared to text-based formats like JSON.

- Parquet supports complex nested data structures, similar to JSON, but its focus is on efficient storage and processing rather than human readability.

## Features

- **Efficient Conversion**: Quickly convert JSON data into Parquet format.

- **Optimized Storage**: Parquet format offers efficient storage and query performance.

- **Simple Integration**: Easy to use within Python projects with minimal setup.

- **Customization**: Supports customization options to fit specific conversion requirements.

- **Streamlined Data Pipelines**: Simplify data processing pipelines by converting JSON objects into Parquet files.

## Usage

1. **Installation**: Clone or download the repository to your local environment.

       git clone https://github.com/Ayushverma135/JSON-to-PARQUET-Parser.git

3. **Integration**: Include the `script.py` script in your Python project directory.

4. **Conversion**: Utilize the script to convert JSON data into Parquet format.